BHF 2021 Southern African Health Journal by Board Of Healthcare Funders

SOUTHERN AFRICAN

HEALTH

JOURNAL

2021 Pushing Beyond. Solutions for Change.

Exploring the expected, unexpected and everything in between

SOUTHERN AFRICAN

HEALTH

JOURNAL

PRODUCTION Editor in Chief: Charlton Murove Copy Editor: Peter Wagenaar Project Co-ordinator: Camille Shamburg Layout & Design: Mariette du Plessis

/ 2021

Published by the Board of Healthcare Funders Tel: +27 11 537-0200 Fax: +27 11 880-8798 Client Services: 0861 30 20 10 Web: www.bhfglobal.com Email: zolam@bhfglobal.com

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From the

Editor's DESK The BHF is pleased to present the third edition of the Southern African Health Journal.

he devastating impact of COVID-19 on our lives is

and multimorbidity in health systems. It highlights the

still felt by individuals, businesses and economies.

growing disease burden, with patients having multiple

This publication includes papers that discuss its impact

chronic conditions that are more complex to manage.

on the healthcare funding environment and on beneficiaries. One paper looks at changes in utilisation of

Customer-centricity is a concept widely used across

health services during the pandemic. The authors argue

many industries, but it is unfortunately not seen in

that it is important to understand these changes as the

many health systems, according to Dr Anuschka Coova-

observed decrease in utilisation may suggest delayed

dia. In her paper, we are challenged with regard to the

access to much needed health services, with adverse

importance of patient-centricity in the health system,

impacts over the long term.

particularly from a funder perspective. The author then provides an overview of how a patient-centric system

Another paper provides a legislative overview of how to

was implemented on behalf of Key Health, a medical

deal with COVID-19 protocols in the workplace. It looks

scheme in South Africa.

at the South African legislative framework from the perspective of health and workplace safety and is very help-

The last paper is a systematic review of the reimburse-

ful for navigating associated pitfalls. It also delves into

ment models used in sub-Saharan Africa. Reimburse-

the complex discussions around vaccine mandates.

ment methods are critical for the sustainability of a health system, as they speak to both cost and quality

Some publications note the increase in mental disease,

of care and how best to achieve balance between these

partly attributed to COVID-19, and the social impacts

objectives. The paper notes that most systems use a

of its management. A paper unpacks mental health is-

fee-for-service model although there are also some in-

sues in detail and how they can best be managed. The

stances of capitation models, particularly in primary

authors note that mental diseases are the third largest

care settings.

contributor to the burden of disease in South Africa and that they are often associated with other non-communi-

The BHF would like to thank all the authors and peer re-

cable diseases.

viewers for their, time, expertise, dedication and effort, which have made the publication of the third edition of

The impact of non-communicable diseases has not

the SAHJ possible.

abated during the pandemic; instead evidence suggests that it has grown and that COVID-19 has only made the management of these conditions more difficult. The authors of a paper on this subject illustrate the

Charlton Murove

burden of and challenges associated with comorbidity

Head of Research, Board of Healthcare Funders

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SOUTHERN AFRICAN

HEALTH

JOURNAL

/ 2021

Table of Contents Impact of COVID-19 on private sector healthcare

The COVID-19 pandemic has affected the utilisation of healthcare services by shifting resources from routine care to pandemic management. This paper analyses changes in the utilisation of private healthcare services in South Africa using medical scheme claims data.

the Difference Between Vaccine Mandate & Mandatory Vaccination

The South African COVID-19 vaccine mandate is a government policy to provide vaccinations for COVID-19. It does not necessarily imply that everyone is legally obliged to be vaccinated.

Mind the Gap: South Africa’s mental health burden

Mental health conditions are becoming increasingly large contributors towards disease and disability burdens worldwide. In South Africa, mental disorders are ranked as the third-largest contributor to the burden of disease. The aim of this paper is to explore this burden and to inform a potential investment case for the funding or delivery of mental health services.

Designing a health system for comorbidity

As the country moves towards implementation of National Health Insurance (NHI), integrated approaches to tackling chronic disease should be prioritised so as to manage the burden of comorbidity most effectively. The aim of this paper is to illustrate the burden and challenge of comorbidity and multimorbidity in health systems.

Enhancing the provision of Patient-Centred Care in the Medical Scheme Sector in South Africa

This paper aims to explore a set of common customer-centric innovations that other sectors have adopted to improve the customer experience, as well as discuss key challenges with customer-centricity in the medical scheme environment.

Capitation models in sub-Saharan Africa

This systematic review aims to review various reimbursement models, especially capitation models, in subSaharan Africa within the published literature and summarise potential learnings and strategies for ensuring their success.

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THE IMPACT OF COVID-19

on private sector healthcare utilisation AUTHORS Craig Getz, Insight Actuaries and Consultants Daniel Shapiro, Insight Actuaries and Consultants Gareth Kantor, Insight Actuaries and Consultants Karyna Pierce, Government Employees Medical Scheme Mabatlo Semenya, Government Employees Medical Scheme Phumla Tsematse, Insight Actuaries and Consultants Selaelo Mametja, Government Employees Medical Scheme

PEER REVIEWER: Martin Coxon

ABSTRACT Background: The COVID-19 pandemic has affected the utilisation of healthcare services by shifting resources from routine care to pandemic management. This paper analyses changes in the utilisation of private healthcare services in South Africa using medical scheme claims data. METHOD: We used claims and membership data from the Government Employees Medical Scheme to evaluate changes in healthcare utilisation. We used descriptive methods to describe changes in utilisation levels by age, by chronic conditions and by member income level. RESULTS: There were substantial decreases in utilisation of healthcare services at the start of the pandemic, differing among healthcare services and beneficiary characteristics. Decreases in utilisation were substantial for acute medication, out-of-hospital visits and hospital admissions and among the 0-10 age group in quarter 2 of 2020. Both surgical and medical hospital admissions declined, but the former to a greater extent. Primary care and certain preventative screening declined at the start of the pandemic but subsequently recovered. Preventative mammograms and pap smears had the largest drops and are still far off their original levels. CONCLUSION: The reduction in healthcare utilisation suggests significant unmet needs among medical scheme members for essential healthcare. The large drop in certain types of utilisation may also suggest elements of unnecessary healthcare utilisation in the private sector before the pandemic.

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Introduction The COVID-19 pandemic has been characterised by delayed or foregone utilisation of healthcare services. Fearing infection, individuals made decisions to avoid hospitals and other healthcare facilities. Healthcare systems have shut down or reduced services to ensure capacity for COVID-19 patients at hospitals. Capacity has also been reduced by modifications to service delivery and access to facilities, workforce and supplyrelated disruptions (Harling et al., 2020; Wani, Rather, & Ahmad, 2020). These decreases have been observed worldwide and for many types of healthcare services (WHO, 2021; Moynihan et al., 2021). The magnitude of the decreases globally were most intense during the second and third quarters of 2020 and moderated in 2021 (WHO, op. cit.). Decreases in utilisation of healthcare services occurred in the South African public health system. The initial lockdown period saw dramatic declines in primary healthcare utilisation, including immunisations, antenatal care, HIV testing, TB testing, use of HIV and TB medication (Burger et al., 2021; Pillay et al., 2021) and hospital admissions (McIntosh et al., 2021). Primary healthcare and immunisations were still below their prepandemic levels in most areas by August 2020 (Siedner et al., 2020). Decreases in healthcare utilisation have also been noted in the medical schemes environment (Insight Actuaries and Consultants, 2021; Discovery Health, 2021), but there is no formal published work that shows this. As a result of decreased utilisation of healthcare services, individuals have missed needed or essential care (Harling, op. cit.; Wani, Rather & Ahmad, op. cit.; Whaley et al., 2020). Care that has been missed includes essential healthcare services such as health promotion and disease prevention, diagnostics, treatment, rehabilitation and palliation, and life-saving emergency services across all major disease categories (WHO, op. cit.; Moynihan et al., op. cit.; McIntosh et al., op. cit.). Unmet need for acute healthcare services may result in near-term impacts on healthcare outcomes. Disruptions in elective care may result in consequences that accumulate over time (WHO, op. cit.). Alternatively, foregone utilisation may indicate the avoidance of less important or unnecessary care (Salerno et al., 2020). Over-servicing, i.e. the provision of healthcare services deemed unnecessary or inappropriate, has been identified as a driver of high costs in the South African private healthcare system (HPCSA, 2016; Competition Commission, 2019). This paper reports on a retrospective cohort study of changes in healthcare utilisation during the pandemic using data from the Government Employees Medical Scheme (GEMS). The paper’s aim is to describe changes in a range of healthcare services, for different beneficiary characteristics. GEMS is the second-largest medical scheme in South Africa with about 2.1 million beneficiaries. GEMS data offer detailed claims information for a range of healthcare services, demographic information of beneficiaries, information on chronic conditions of beneficiaries, as well as income levels of members from the government Personal and Salary System (PERSAL).

Literature review Studies of outpatient visits at the start of the pandemic showed decreases of between 30% and 50% (Moynihan el al., op. cit.). Primary care services were affected, including non-communicable diseases, cancer, infectious diseases including HIV and TB, and newborn, child and maternal care (Siedner et al., op. cit.); there were also fewer newly diagnosed cases of chronic conditions (Pillay et al.,op, cit.). In one study, dental care was the most common type of day-to-day care that was delayed or foregone, followed by GP/specialist consultations, preventive health screenings and medical tests (Urban Institute, 2021). Several studies showed that screening services for cancer also saw large reductions ( Jones et al., 2020; Collado-Mesa et al., 2020; Cox, Amin & Kamal, 2021).

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There were significant reductions in immunisation services during the pandemic in many countries (WHO, op. cit.; Heneghan, Brassey & Jefferson, 2021). This included vaccine uptake for diphtheria/tetanus/pertussis, TB, measles and polio. The reductions were most significant among countries that had existing low rates of vaccination and for young children and children from disadvantaged communities (Heneghan, Brassey & Jefferson, op. cit.). Reductions in vaccinations occurred in many countries in Africa, with some countries seeing rates decline by more than 10% (Masresha et al., 2020). Reductions in many, but not all, countries reversed once restrictions were lifted (WHO, op.cit). Utilisation did not necessarily decline in respect of medicines. A study from the USA showed that spending on prescription medicines in the US increased over the pandemic period, despite large decreases in other healthcare spending (Cox et al., op. cit.). Decreases in in-hospital utilisation were found to be greater than decreases in outpatient visits (Ahn, Kim & Koh, 2020). The extent of the decreases varied among studies of medical admissions (Discovery, op. cit.) and ranged from 20% to 87%. Decreases may have been lower for pregnancy and childbirth, as shown in a study of gynaecological hospitalisation, which showed a relatively low decrease (Athiel et al., 2020). Decreases in admissions for surgical cases also varied considerably among studies. Admissions for general surgery typically showed large declines of 60-70% (Cano-Valderrama et al., 2020; Mazzatenta et al., 2020). Scope procedures, which are typically elective, showed large decreases of 70-80% (Bozovich et al., 2020; Gawron, Kaltenbach & Dominitz, 2020). Urgent procedures (Santana et al., 2020; Bernstein & Stead Sellers, 2020) and procedures related to trauma (Giuntoli et al., 2020) showed smaller declines of 20-30%. Emergency room visits showed large declines in some studies, with reductions of 64% in paediatric emergency room visits in Germany and a 73-88% drop in Italy (Cox et al., op. cit.). Reductions were experienced in routine care as well as more critical care (Giuntoli et al., op. cit.). The South African public sector saw decreases in primary healthcare visits and HIV and TB testing. Antenatal care saw decreases (Burger et al., op. cit.; Pillay et al., op. cit.), but recovered after the initial lockdown (Burger et al., op. cit.). In the South African public sector, childhood immunisation rates dropped (Burger et al., op. cit.; Pillay et al., op. cit.) and were at their lowest during the waves of the pandemic (Siedner et al., op. cit.). Immunisation had recovered, but not to pre-pandemic levels, by August 2020 (Pillay et al., op. cit.). The South African public sector also saw reduced admissions, with an expectation that there will be substantial pent-up demand for surgeries after the pandemic (Burger et al., op. cit.). A study of a public hospital complex in South Africa found a 44% reduction in non-trauma admissions and 53% reduction in trauma admissions (Moustakis, Piperidis & Ogunrombi, 2020). Findings on characteristics of the population that experienced the largest reduction in healthcare services were mixed. Some studies found that unmet care during the pandemic was associated with various factors, including women, younger individuals, less educated individuals and lower-income occupations (Czeisler et al., 2020). By contrast a study found that hospital admissions remained higher for females (Callison & Ward, 2021), which may be due to admission for childbirth. Avoidance of emergency care was greatest for caregivers, individuals with healthcare conditions, non-white racial groups, young adults and individuals with disabilities (Czeisler et al., op. cit.), as well as individuals in specific regions (Callison & Ward, op. cit.). Paediatric care and emergency cases saw large declines (Dopfer et al., 2020). Other studies found that the reduction in utilisation was larger for older ages and for those with more education (Smolić, Čipin & Međimurec, 2021; Masroor, 2020). In one study, admissions for older patients were at 53-63% of predicted levels compared to 68-75% for younger patients (Rosenbaum, 2020). Among the elderly, lower access to healthcare during the pandemic was greater among actively employed individuals, more educated individuals and individuals in urban areas (Smolić, Čipin & Međimurec, op. cit.). About 76% of adults who delayed or forewent healthcare presented with at least one chronic condition (Harling et al., op. cit.), suggesting that chronic conditions are associated with decreases in healthcare utilisation.

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Unmet needs in respect of healthcare services can result in near-term impacts on healthcare outcomes, and disruptions in elective care may result in consequences that accumulate over time (WHO, op. cit.). Delays in treatment during the pandemic have led to significant complications, with consequent increased morbidity and mortality (Masroor, op. cit.). During the pandemic oncologists revisited chemotherapy protocols to minimise the frequency of chemotherapy visits. There is uncertainty about these treatment modifications and how they will affect overall survival (Rosenbaum, op. cit.). Among adults reporting delayed or foregone healthcare, 33% reported that one or more of their health conditions worsened or that the foregone healthcare limited their abilities to work or perform other daily activities (Cox et al.,op. cit.). It is projected that reductions in routine vaccinations during the pandemic period will result in child deaths (Abbas et al., 2020), and mortality data suggest that there have been excess deaths from conditions such as diabetes, dementia, hypertension, heart disease and stroke, as well as drug overdoses (Woolf et al., 2020). In South Africa reductions in antenatal visits have already resulted in maternal and neonatal mortality (Pillay et al., op. cit.). An investigation in South Africa found that among cancer registrations, the first recorded stage had slightly higher proportions between stages 2 and 4 and fewer in stage 1 in 2020 and 2021 (Discovery Health, op. cit.). This may be due to individuals at lower stages not seeking care during the pandemic, as well as a consequence of foregone screening. Conversely, reductions in healthcare utilisation during the pandemic may help healthcare systems identify and reduce unnecessary and low-value care (Moynihan et al., op. cit.; Oakes & Segal, 2020; Hughes-Cromwick, Miller & Beaudin-Seiler, 2020; Moynihan et al., 2020; Born & Levinson, 2021; Elshaug & Duckett, 2020). Overservicing was a problem in the system before the pandemic and the fall in healthcare utilisation can be a natural experiment to assess the necessity of some healthcare services (Moynihan et al., op. cit.). There is a need for rigorous studies that test the effects of reduced utilisation on outcomes and costs arising from the pandemic (Born & Levinson,, op. cit.). The large drop in healthcare utilisation among children may indicate unnecessary care as children are known to experience overdiagnosis and overtreatment (Coon et al., 2014). A study of the utilisation of radiological examination during the pandemic identified a list of potential low-value examinations for which utilisation decreased and it was suggested that the use of these be assessed to improve quality (Hofmann, Andersen & Kjelle, 2021). Decreases in childhood tonsillectomies, which have been identified as procedures that are performed without a sound clinical basis and often have low efficacy (Šumilo, 2019; Marshall, 2020), have been identified as an example where the pandemic can be used to indicate procedures that are performed when not indicated (Sutherland et al., 2020).

Methods The analysis used claims, hospital authorisations, chronic authorisations and membership data from GEMS for 2019, 2020 and 2021. The authors received ethics clearance for use of these data in research from Pharma-Ethics (Reference No: 210824214) and the ethics clearance covers this study. The data were used to assess utilisation for five categories of healthcare services: out-of-hospital medication use, out-of-hospital visits, hospital admissions, preventative screening and immunisations. Utilisation was measured as rates, which were calculated as counts of utilisation divided by the exposure of the eligible population who can make use of the healthcare service. Table 1 sets out the categories, measures that were used within each category, definitions of the counts of utilisation and definitions of the exposures of the eligible population. The counts excluded visits and admissions for COVID-19 and thus reflect non-COVID-19 utilisation.

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Table 1. Definitions of measures used in the analysis Category

Measure

Count

Exposure

Medicines

Acute medication

Number of medicines

All beneficiaries

dispensed Chronic medication

Number of medicines

Beneficiaries registered

dispensed

for at least one chronic condition

Out-of-hospital

HIV antiretroviral

Number of medicines

Beneficiaries registered for

medication

dispensed

HIV medication

GP consultations

Service at a GP on a day All beneficiaries

Specialist consultations

Service at any specialist

visits All beneficiaries

discipline on a day Dentist visits

Service at a dentist on

All beneficiaries

a day Optometry visits

Service at an optome-

All beneficiaries

trist on a day Hospital

All admissions

All hospital authorisa-

admissions

All beneficiaries

tions Surgical admissions

Hospital admissions

All beneficiaries

with relevant DRGs Medical admissions

Hospital admissions

All beneficiaries

with relevant DRGs

Screening tests

Pregnancy and childbirth

Hospital admissions

Female beneficiaries

admissions

with relevant DRGs

between ages of 20 and 40

Examples of medical scheme

Hospital admissions

All beneficiaries

surgical admissions

with relevant DRGs

HIV testing

Number tests

All beneficiaries

HbA1c test

Number tests

Beneficiaries above age 30

Cholesterol test

Number tests

Beneficiaries above age 30

Mammogram

Number tests

Female beneficiaries above age 20

Pap smear

Number tests

Female beneficiaries above age 20

PSA test

Number tests

DTP vaccine

Number of vaccines

Male beneficiaries above age 40

Immunisations

Beneficiaries between 0 and 5 years old

Measles vaccine

Number of vaccines

Beneficiaries between 0 and 5 years old

Pneumococcal vaccine

Number of vaccines

Beneficiaries between 0 and 5 years old

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Rates of utilisation were calculated for each quarter from quarter 1 of 2019 to quarter 2 of 2021. The percentage changes in rates for quarters in 2020 and 2021 were calculated relative to the corresponding quarters of 2019. Thus utilisation rates in 2019 were used as a benchmark for both 2020 and 2021. It should be noted that utilisation statistics in the four quarters of 2019 may provide a low or high base with which to compare 2020 and 2021, depending on utilisation experience in 2019. Results were described overall, as well as by characteristics of age, chronic status and income. Age was defined in 10-year age bands; chronic status was defined by whether a beneficiary had been taking medication for any chronic condition; and income was defined as the salary of the principal member for each beneficiary, split into six groups numbered in increasing order. The overall results may be affected by changes in the percentages of beneficiaries in different age bands and with different conditions in the years of the analysis. These percentages are shown below in Table 2. The percentages did not change significantly in the years of the analysis, which indicates that the changes should not affect the results.

Table 2. Age profile and chronic prevalence over the years of the analysis Age band

Chronic prevalence

2019

2020

2021

00 - 10

19.5%

19.3%

18.9%

10 - 20

20.6%

20.7%

20 - 30

8.9%

9.1%

9.2%

30 - 40

11.4%

11.3%

11.4%

40 - 50

14.5%

14.1%

13.8%

50 - 60

13.8%

14.0%

14.1%

60 - 70

7.1%

7.3%

7.5%

70 - 80

3.0%

3.1%

3.2%

80 +

1.3%

Hypertension

14.9%

14.4%

13.6%

HIV

7.5%

7.7%

7.6%

Diabetes

6.2%

6.1%

5.8%

Hyperlipidaemia

6.4%

6.2%

5.6%

Asthma

3.2%

3.1%

Results Overall results The results section first considers the overall percentage changes in utilisation in 2020 and 2021 compared to 2019. Results are presented in tables, accompanied by figures that graphically depict the tables

Medication The change in medication usage is shown in Table 3 and Figure 1. Medication usage showed an increase in quarter 1 of 2020, which may have been due to members stockpiling medicines in advance of the lockdown. There was a decrease of about 28% in acute medicines in quarter 2 as the pandemic started but this recovered and reached previous levels by quarter 4. Chronic medicines and antiretrovirals for treatment of HIV showed slight increases. This indicates effective management and distribution of chronic medication during

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the pandemic. GEMS makes use of courier pharmacies, which contributed to chronic medicines usage for beneficiaries who avoided visiting pharmacies during the period. Additionally, the increases may be due to greater numbers registered for chronic medication and antiretroviral medication for HIV in 2020 and 2021.

Table 3. Change from 2019 in medicines dispensed

2020

2021

Acute medicines

Chronic medicines

Antiretrovirals for HIV

10.1%

10.6%

6.0%

-27.8%

9.2%

7.5%

-9.2%

7.2%

1.7%

8.1%

6.1%

4.7%

0.2%

5.9%

4.3%

-5.3%

3.6%

4.8%

Figure 1. Change from 2019 in medicines dispensed 15% 10%

Change compared to 2019

5% 0%

-5%

2020

Q2 2021

-10% -15% -20% -25% -30%

Acute medicines

Chronic medicines

Antiretrovirals for HIV

Out-of-hospital visits Out-of-hospital visits decreased by about 25-30% in quarter 2 of 2020 but recovered in quarter 3, shown in Table 4 and Figure 2. Decreases occurred for all categories of providers. Specialist consultations saw the slowest recovery after quarter 2 in 2020. Optometrist visits decreased by the largest percentage in quarter 2 in 2020, but experienced the largest recovery.

Table 4. Change from 2019 in out-of-hospital visits

2020

2021

GP consultations

Specialist consultations

Dentist visits

Optometrist visits

3.3%

-3.0%

-4.0%

1.6%

-26.7%

-27.5%

-28.2%

-31.6%

-8.5%

-15.3%

-7.9%

-2.4%

1.6%

-1.8%

-2.9%

4.7%

-5.8%

-15.4%

-6.1%

-1.0%

-10.3%

-13.7%

-5.4%

2.6%

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Figure 2. Change from 2019 in out-of-hospital visits 10% 5%

Change compared to 2019

-5%

2020

Q2 2021

-10% -15% -20% -25% -30% -35%

GP consultations

Specialist consultations

Dentist visits

Optometrist visits

Hospital admissions Hospital admission rates saw decreases of around 40% in quarter 2 for medical and surgical admissions, shown in Table 5 and Figure 3. This is similar to the reduction reported for admissions in the South African public sector. The decrease was slightly greater for surgical admissions. Admissions for pregnancy and childbirth did not decrease dramatically. Admissions partially recovered in quarters 3 and 4 of 2020, relative to the decreases in quarter 2 of 2020, but decreased again in quarter 1 of 2021. Two examples of medical and surgical admission were investigated, shown in Table 6 and Figure 4: tonsillectomies and cataracts for surgical admissions; and respiratory conditions (excluding COVID-19 admissions) and oesophagitis and gastroenteritis for medical admissions. Admissions for tonsillectomies and cataracts are likely to include elective admissions. Admission for tonsillectomies and cataracts had large declines in quarter 2 of 2020, but recovered from quarter 3. The recovery was slightly faster for cataracts. Admissions for respiratory conditions and oesophagitis and gastroenteritis showed large drops in quarter 2 of 2020. Admissions for oesophagitis and gastroenteritis had a slower recovery compared to respiratory admissions.

Table 5. Change from 2019 in hospital admissions

2020

2021

All admissions

Medical

Surgical

Pregnancy and childbirth

0.5%

2.4%

-3.6%

6.8%

-41.3%

-42.4%

-46.9%

-6.6%

-29.7%

-26.8%

-37.6%

-11.8%

-10.2%

-14.6%

-11.2%

-23.9%

-20.9%

-30.9%

-12.1%

-20.4%

-20.3%

-23.3%

-8.5%

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Table 6. Change from 2019 for examples of surgical and medical admissions Surgical examples

2020

2021

Medical examples

Tonsillectomies

Cataracts

Respiratory conditions

Oesophagitis and gastroenteritis

-14.35%

22.40%

-1.21%

6.61%

-42.90%

-39.90%

-44.80%

-52.24%

-32.20%

-23.90%

-35.20%

-59.09%

-12.60%

-7.00%

-11.50%

-29.42%

-22.60%

-15.40%

-26.10%

-45.91%

-18.30%

-17.50%

-16.60%

-25.67%

Figure 3. Change from 2019 in hospital admissions

Change compared to 2019

10%

2020

-10%

Q2 2021

-20%

-30%

-40%

-50%

All admissions

Medical

Surgical

Pregnancy and childbirth

Figure 4. Change from 2019 for examples of surgical and medical admissions

Change compared to 2019

30% 20% 10% 0% -10%

2020

Q2 2021

-20% -30% -40% -50% -60% -70%

Tonsillectomies

Cataracts

Respiratory conditions

Oesophagitis and gastroenteritis

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Screening Changes in screening varied for different types of tests, as shown in Table 7 and Figure 5. HIV testing decreased by about 9% in quarter 2 of 2020 and remained lower than in 2019 up to quarter 1 of 2021. The use of HbA1c tests showed little decline during the pandemic. Cholesterol screening decreased upon the initial lockdown but recovered thereafter. Mammograms, pap smears and PSA tests showed large declines, which had not recovered by quarter 2 of 2021.

Table 7. Change from 2019 in preventative screening

2020

2021

HIV testing

HbA1c test

Cholesterol test

Mammogram

Pap smear

PSA test

6.2%

6.9%

7.2%

11.6%

-1.9%

2.8%

-8.8%

-2.3%

-13.0%

-47.9%

-34.6%

-19.8%

-4.7%

5.3%

-6.8%

-35.0%

-27.8%

-22.7%

-1.8%

15.0%

4.9%

-9.2%

-7.5%

-4.7%

-4.8%

6.7%

0.7%

-27.9%

-21.6%

-8.6%

0.2%

24.0%

15.0%

-20.1%

-8.8%

-3.8%

Figure 5. Change from 2019 in preventative screening

Change compared to 2019

30% 20% 10% 0% -10%

Q3 2020

Q2 2021

-20% -30% -40% -50% -60%

HIV testing

HbA1c test

Cholesterol test Pap

Mammogram

Pap smear

PSA test

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Immunisation Childhood vaccination rates did not decline during the pandemic, which is seen in Table 8 and Figure 6. This is in contrast to the reductions seen in the South African public sector. It can be noted that vaccination rates in 2021 were affected by GEMS’ benefit enhancements. It is also possible that GEMS may only see a proportion of childhood vaccinations, as GEMS beneficiaries may go to public facilities for vaccinations and billing is often not forthcoming from these facilities.

Table 8. Change from 2019 in immunisations DTP vaccine 2020

2021

Measles vaccine

Pneumococcal vaccine

3.8%

6.1%

6.6%

20.9%

4.4%

24.9%

28.6%

24.9%

17.0%

13.8%

21.5%

16.2%

28.1%

19.8%

17.1%

9.3%

9.6%

2.5%

Figure 6. Change from 2019 in immunisations

Change compared to 2019

40%

30%

20%

10%

Q3 2020

DTP vaccine

Measles vaccine

Q2 2021

Pneumococcal vaccine

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Results by sociodemographic characteristics The results for population sociodemographic characteristics are shown below. The effects of age, the presence of a chronic condition and income level are considered in turn. The results for this section are presented as graphs. Because of the large number of graphs, they are consolidated in Appendix A.

Age The changes in medication use by age are shown in Figure 7. The decrease in claims for acute medication was very large for children and did not recover fully up to the end of quarter 2 of 2021. The decrease for older ages was lower and was above 2019 levels from quarter 4 of 2020. Chronic medication and antiretroviral medication for HIV showed increases for older ages but no increases for younger ages. The changes in out-of-hospital visits by age are shown in Figure 8. The decrease in GP consultations was very large below age 20, especially below age 10. The decrease was smaller for ages older than 20. Decreases below age 20 remained larger by the end of quarter 2 in 2021. Decreases in specialist consultations were the largest for individuals below age 10 and above age 70. The decreases below age 10 recovered strongly from quarter 4 in 2020. Dentist and optometry visits had large decreases for older beneficiaries, but less so for younger ages. The changes in hospital admissions by age are shown in Figure 9. Hospital admissions decreased significantly for young individuals, especially between 0 and 10 years. Older beneficiaries had lower decreases and recovered to 2019 levels in quarter 4 of 2020. This was especially the case for medical admissions, which saw relatively low decreases in quarter 2 of 2020 and quick recoveries in the number of admissions to levels before the pandemic. Surgical admissions showed the same pattern by age but the differences in decreases in admissions between young and old were smaller. After the recovery in quarter 4 in 2020, admission rates decreased for all ages in quarter 1 of 2021, although to a lesser degree than in 2020. The changes in screening by age are shown in Figure 10. The decrease in HIV testing occurred among young members. By contrast the decrease in HbA1c testing and cholesterol testing occurred in older ages. The decreases in mammograms and pap smears did not show a clear pattern by age.

Chronic disease status The change in acute medication use by chronic status is shown in Figure 11. Use of acute medicines decreased for both chronic and non-chronic individuals in quarter 2 of 2020, but the extent was larger for non-chronic individuals. The changes in out-of-hospital visits by chronic status are shown in Figure 12. The decrease in GP visits was large for non-chronic individuals, which is consistent with the decrease seen for children. There was only a small decrease for chronic individuals in quarter 2 of 2020. This indicates that chronic disease patients continued to consult GPs. By contrast the decrease in specialist consultations, dentist visits and optometrist visits were the same for chronic and non-chronic individuals in all quarters. The changes in hospital admissions by chronic status are shown in Figure 13. The decrease in hospital admissions was larger for non-chronic individuals. As with age, this was particularly the case for medical admissions. The changes in screening by chronic status are shown in Figure 14. There was not much difference in the changes for screening tests between chronic and non-chronic individuals. An exception was HIV testing, for which chronic patients saw a much smaller decrease. However there were stronger recoveries in screening tests for chronic individuals for some of the screening tests after quarter 2 of 2020.

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Income The changes in medication use, out-of-hospital visits, hospital admissions, screening and childhood immunisations by chronic status are shown in Figures 15-19, respectively. Decreases in utilisation for GP consultations were largest for highest-income groups, while decreases in hospital admissions were lowest for the lowest-income group. However the differences were relatively small and may not be conclusive. Differences among incomes for other healthcare services did not show a pattern and were relatively small.

Discussion The results of this study provide a view of changes in healthcare utilisation during the pandemic in the South African private sector. The following findings and interpretations were made for the categories of healthcare services investigated. The decreases in out-of-hospital visits and acute medication usage were followed by recoveries, especially for specialist consultations and optometry visits, which were higher than in 2019. This may indicate pent-up demand following the decreases. In contrast with the state sector (Burger et al., op. cit.; Pillay et al., op. cit.), access to chronic medication and antiretroviral medication was not affected by the pandemic. This could be as a result of access to courier pharmacy services, and delivery and pick-up services implemented by pharmacies that provide services to GEMS. The largest decreases in utilisation occurred in respect of hospital admissions, slightly more so for surgical admissions than medical admissions. Surgical admissions include procedures that are elective and are more likely to be deferred. Medical admissions, despite not being elective, showed large decreases. Decreases in medical admissions may be the result of restricted bed availability at hospitals to ensure capacity during the pandemic, individuals avoiding hospitals due to fear of infection, decreased access to facilities and workforce and supply-related disruptions. Pregnancy and childbirth had lower decreases, although a decrease was still present. The decreases were due to illness-related admissions during pregnancy and abortions, rather than deliveries. Decreases in HIV testing for young members are of concern and match what has been seen in the South African public sector (Burger et al, op. cit.; Pillay et al.,op. cit.) The decrease in HIV testing creates the risk that individuals do not detect their HIV status until a later stage in its progression. The decrease in HbA1c testing and cholesterol testing occurred for older ages and may be the result of older beneficiaries avoiding healthcare services. Foregone HbA1c testing may result in uncontrolled diabetes and the complications associated with it. Mammograms, pap smears and PSA tests showed large declines, which had not recovered by quarter 2 of 2021. These declines are in line with decreases in specialist consultations and may be a consequence of fewer specialist consultations. Poor uptake of these screening benefits may result in delayed diagnosis of these cancers, with unintended risk of death and costs of care. The continuation of childhood immunisation during the pandemic contrasts with the decreases seen in the public sector. Reasons for the difference, such as different populations or different ways in which immunisations are delivered, can be investigated further. Additionally, the following findings and interpretations were made with regard to the effects of sociodemographic characteristics on healthcare utilisation.

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Individuals below age 10 and those without chronic conditions experienced large decreases in out-of-hospital visits, acute medicine use and hospital admissions. The decreases in utilisation in children could be due to a reduction in the burden of infectious diseases consequent on stringent COVID-19 hygiene measures. Alternatively, the large decreases in admission for children and non-chronic individuals may be due to unnecessary admissions that could be foregone. As described in the literature review, childhood tonsillectomies are often not based on evidence and the drop may suggest unnecessary procedures before the pandemic period. Smaller decreases and faster recoveries in admissions for medical admissions among older ages and individuals with chronic conditions may indicate that these admissions were essential and could not be foregone. Some out-of-hospital visits, especially for optometrists and dentists, may reflect the ability to defer visits on the part of those most at risk of infection. The decrease in specialist consultations also included older ages, which can be investigated further. Increased utilisation of chronic medication and HIV medication among older individuals may be due to fear of COVID-19 infection. Older ages and individuals with chronic conditions are at high risk of severe COVID19. Individuals may try to alleviate severe COVID-19 infections by managing their chronic conditions better. Literature on changes in utilisation by income was mixed and, similarly, this study had mixed results by income. Larger decreases in GP consultations among the highest-income groups may indicate foregoing of unnecessary consultations. By contrast, smaller decreases in admissions for the lowest-income groups may reflect low existing admission rates and less potential to forego admissions. However, all differences between income groups were small and further work is needed to test the significance of these differences and the precise reasons for them.

Recommendation Further work is needed to assess whether decreases in utilisation constitute foregone care that will have adverse health consequences, or alternatively may indicate unnecessary care pre-pandemic. It may not yet be possible to perform this work due to the short time period in which to assess healthcare outcomes. More time is needed to assess whether foregone care will have adverse consequences, as well as to assess whether there will be pent-up demand for care following the pandemic period.

“ 16

Further work is needed to assess whether decreases in utilisation constitute foregone care that will have adverse health consequences, or alternatively may indicate unnecessary care pre-pandemic.

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Appendix A Figure 7. Change from 2019 in medicines dispensed by age CHRONIC MEDICINES

ACUTE MEDICINES 25% Change compared to 2019

30%

Change compared to 2019

20% 10% 0% -10%

2020

2021

-20%

20% 15% 10% 5%

-30% 0%

-40% -50%

2020

-5%

Q2 2021

-60%

00 - 10

10 - 20

20 - 30

30 - 40

40 - 50

50 - 60

60 - 70

70 - 80

30 - 40

80 +

40 - 50

50 - 60

60 - 70

70 - 80

80 +

ANTIRETROVIRALS FOR HIV

Change compared to 2019

50% 40% 30% 20% 10% 0%

2020

-10%

Q2 2021

-20% 20 - 30

30 - 40

40 - 50

50 - 60

60 - 70

Figure 8. Change from 2019 in out-of-hospital visits by age GP CONSULTATIONS

SPECIALIST CONSULTATIONS 40%

20%

2020

-20%

Change compared to 2019

30% 0%

Q2 2021

-40%

-60%

20% 10% 0% -10%

2020

-20%

Q2 2021

-30% -40% -50%

-80%

00 - 10

-60% 10 - 20

20 - 30

30 - 40

40 - 50

50 - 60

60 - 70

70 - 80

00 - 10

80 +

10 - 20

20 - 30

20%

30%

10%

20%

2020

-10%

Q2 2021

-20% -30% -40%

50 - 60

60 - 70

70 - 80

80 +

10% 0%

-10%

2020

Q2 2021

-20% -30% -40%

-50% 00 - 10

40 - 50

OPTOMETRY VISITS

Change compared to 2019

DENTIST VISITS

30 - 40

-50% 10 - 20

20 - 30

30 - 40

40 - 50

50 - 60

60 - 70

70 - 80

80 +

00 - 10

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10 - 20

20 - 30

30 - 40

40 - 50

50 - 60

60 - 70

70 - 80

80 +

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Appendix A (continued) Figure 9. Change in hospital admissions by age MEDICAL ADMISSIONS

ALL HOSPITAL ADMISSIONS

20%

2020

-20%

Change compared to 2019

20%

2021

-40%

-60%

-80% 00 - 10

2020

-20%

Q2 2021

-40%

-60%

-80%

10 - 20

20 - 30

30 - 40

40 - 50

50 - 60

60 - 70

70 - 80

80 +

00 - 10

10 - 20

20 - 30

30 - 40

40 - 50

50 - 60

60 - 70

70 - 80

80 +

SURGICAL ADMISSIONS 20%

Change compared to 2019

2020

-20%

Q2 2021

-40%

-60%

-80% 00 - 10

10 - 20

20 - 30

30 - 40

40 - 50

50 - 60

60 - 70

70 - 80

80 +

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[ 1 ] i m p a c t o f CO V I D - 1 9 o n p r i v a t e s e c t o r h e a l t h c a r e u t i l i s a t i o n

Appendix A (continued) Figure 10. Change from 2019 in preventative screening by age HbA1c TEST 40%

30%

2020

-5%

Q2 2021

-10%

Change compared to 2019

HIV TEST 10%

-15%

20% 10% 0%

30 - 40

40 - 50

20 - 30

30 - 40

Q2 2021

30%

-10%

2020

Q2 2021

-20%

Change compared to 2019

10%

60 - 70

70 - 80

80 +

40% 20% 0%

2020

-20%

Q2 2021

-40%

-30%

-60%

-40%

-80%

-50% 20 - 30

30 - 40

40 - 50

50 - 60

60 - 70

70 - 80

20 - 30

80 +

30 - 40

40 - 50

PAP SMEAR

10%

2020

-10%

Q2 2021

-20% -30%

Change compared to 2019

20%

50 - 60

60 - 70

70 - 80

80 +

PSA TEST

20%

50 - 60

60%

20%

40 - 50

MAMMOGRAM

CHOLESTEROL TEST

Change compared to 2019

-30%

20 - 30

2020

-10%

Q2 2021

-20% -30% -40%

-40%

-50%

-50% 20 - 30

30 - 40

40 - 50

50 - 60

60 - 70

70 - 80

80 +

20 - 30

30 - 40

40 - 50

Childhood immunisations are not shown as these apply only to the 0-10 age band.

-20%

Change compared to 2019

Q3 2020

-10%

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50 - 60

60 - 70

70 - 80

80 +

i m p a c t o f CO V I D - 1 9 o n p r i v a t e s e c t o r h e a l t h c a r e u t i l i s a t i o n [ 1 ]

Appendix A (continued) Figure 11. Change from 2019 in medicines dispensed by chronic status ACUTE MEDICINES 20% 15%

Change compared to 2019

10% 5% 0% -5%

2020

-10%

Q2 2021

-15% -20% -25% -30% -35% N

Chronic medicines and antiretrovirals for HIV are not shown as these apply only to chronic

Figure 12. Change from 2019 in out-of-hospital visits by chronic status GP CONSULTATIONS

SPECIALIST CONSULTATIONS

20%

20% 15%

2020

-10%

Q2 2021

-20%

Change compared to 2019

10%

10% 5% 0%

-5%

2020

Q2 2021

-10% -15%

-30%

-20% -25%

-40% N

DENTIST VISITS

OPTOMETRY VISITS 20%

-5%

15%

2020

Q2 2021

-10% -15% -20% -25%

10%

Change compared to 2019

5% 0% -5% -10%

2020

Q2 2021

-15% -20% -25%

-30%

-30% -35%

-35% N

20 2 1 S O UT H E R N A FR IC A N H E A LT H JO UR N A L P U B L I S H E D B Y T H E B O A R D O F H E A LT H C A R E F U N D E R S

[ 1 ] i m p a c t o f CO V I D - 1 9 o n p r i v a t e s e c t o r h e a l t h c a r e u t i l i s a t i o n

Appendix A (continued) Figure 13. Change from 2019 in hospital admissions by chronic status MEDICAL ADMISSIONS

ALL HOSPITAL ADMISSIONS 10%

2020

-10%

Q2 Change compared to 2019

Change compared to 2019

10%

2021

-20%

-30%

-10%

2020

Q2 2021

-20% -30% -40% -50% -60% N

2 0 2 1 SOU T H ERN AFRICAN H E A LT H JO UR N A L P U B L I S H E D B Y T H E B O A R D O F H E A LT H C A R E F U N D E R S

Q2 2021

-30%

SURGICAL ADMISSIONS

Change compared to 2019

-20%

10%

Q3 2020

-50%

-40%

-10%

i m p a c t o f CO V I D - 1 9 o n p r i v a t e s e c t o r h e a l t h c a r e u t i l i s a t i o n [ 1 ]

Appendix A (continued) Figure 14. Change from 2019 in preventative screening by chronic status HIV TEST

HbA1c TEST 30% 25%

5% 0%

2020

-5%

Change compared to 2019

10%

Q2 2021

-10% -15%

20% 15% 10% 5% 0%

-20%

-25%

2020

-5%

Q2 2021

-10% N

CHOLESTEROL TEST

MAMMOGRAM

25%

20%

Change in compared to 2019

Change compared to 2019

20% 15% 10% 5% 0%

-5%

2020

Q2 2021

10% 0%

-10%

-40% -50%

Q2 2021

-60%

-20% N

PAP SMEAR Q2

PSA TEST Q4

2020

Q2 2021

-15% -20% -25%

15% 10%

Change compared to 2019

-10%

Change compared to 2019

-30%

-15%

-5%

-20%

-10%

Q3 2020

5% 0% -5%

2020

Q2 2021

-10%

-30%

-15%

-35%

-20% -25%

-40% N

Childhood immunisations are not shown as these apply only to children for whom chronic status is not relevant

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[ 1 ] i m p a c t o f CO V I D - 1 9 o n p r i v a t e s e c t o r h e a l t h c a r e u t i l i s a t i o n

Appendix A (continued) Figure 15. Change from 2019 in medicines dispensed by income CHRONIC MEDICINES

ACUTE MEDICINES 25% 30%

20%

Change compared to 2019

20% 10% 0%

2020

-10%

2021

-20%

15% 10% 5% 0%

-40%

2020

-5%

-30%

2021

-10%

Income 1

Income 2

Income 3

Income 4

Income 5

Income 6

Pensioners

Income 1

Income 2

Income 3

Income 4

Income 5

Income 6

Pensioners

ANTIRETROVIRALS FOR HIV

Change compared to 2019

50%

40%

30%

20%

10%

2020

-10%

-20% Income 1

Income 2

2021

Income 3

Income 4

Income 5

Income 6

Pensioners

Figure 16. Change from 2019 in out-of-hospital visits by income SPECIALIST CONSULTATIONS

GP CONSULTATIONS 30%

20%

2020

-10%

Q2 2021

-20%

Change compared to 2019

10%

10% 0%

2020

-10%

Q2 2021

-20%

-30% -30%

-40% Income 1

Income 2

Income 3

Income 4

Income 5

Income 6

Income 1

Pensioners

Income 2

Income 3

DENTIST VISITS

2020

-10%

Q2 2021

-20%

Change compared to 2019

-30%

Pensioners

20% 10% 0%

2020

-10%

Q2 2021

-20% -30%

-40%

Income 6

30%

10%

Income 1

Income 5

OPTOMETRY VISITS

20%

Income 4

-40% Income 2

Income 3

Income 4

Income 5

Income 6

Pensioners

Income 1

2 0 2 1 SOU T H ERN AFRICAN H E A LT H JO UR N A L P U B L I S H E D B Y T H E B O A R D O F H E A LT H C A R E F U N D E R S

Income 2

Income 3

Income 4

Income 5

Income 6

Pensioners

i m p a c t o f CO V I D - 1 9 o n p r i v a t e s e c t o r h e a l t h c a r e u t i l i s a t i o n [ 1 ]

Appendix A (continued) Figure 17. Change from 2019 in hospital admissions by income ALL HOSPITAL ADMISSIONS

MEDICAL ADMISSIONS 20%

10%

-10%

2020

Change compared to 2019

10%

Q2 2021

-20% -30% -40%

2020

-10%

Q2 2021

-20%

-30%

-40%

-50% -50%

-60% Income 1

Income 2

Income 3

Income 4

Income 5

Income 6

Pensioners

Income 1

Income 2

Income 3

Income 4

Income 5

Income 6

Pensioners

SURGICAL ADMISSIONS 10%

Change compared to 2019

2020

-10%

Q2 2021

-20% -30% -40% -50% -60% Income 1

Income 2

Income 3

Income 4

Income 5

Income 6

Pensioners

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[ 1 ] i m p a c t o f CO V I D - 1 9 o n p r i v a t e s e c t o r h e a l t h c a r e u t i l i s a t i o n

Appendix A (continued) Figure 18. Change from 2019 in preventative screening by income HIV TEST

HbA1c TEST

30%

Change compared to 2019

20%

10%

40%

2020

30%

20%

10%

Q2 2021

-10%

Income 2

Income 3

Income 4

Income 5

Income 6

Pensioners

Income 1

Income 2

Income 3

CHOLESTEROL TEST

Q2 2021

Income 4

Income 5

Income 6

Pensioners

MAMMOGRAM

10%

20%

10%

2020

-10%

Q2 2021

Change compared to 2019

20%

30%

Q3 2020

-20%

-20% Income 1

-10%

2020

Q2 2021

-20% -30% -40%

-20%

-50% -30%

Income 1

-60% Income 2

Income 3

Income 4

Income 5

Income 6

Income 1

Pensioners

Income 2

Income 3

2020

-10%

Q2 2021

-15% -20%

Change compared to 2019

Pensioners

20% 10% 0%

Q3 2020

-10%

Q2 2021

-25% -20%

-30% -35%

-30%

-40% -45% Income 1

Income 6

30%

10%

-5%

Income 5

PSA TEST

PAP SMEAR

Income 4

-40%

Income 2

Income 3

Income 4

Income 5

Income 6

Pensioners

Income 1

2 0 2 1 SOU T H ERN AFRICAN H E A LT H JO UR N A L P U B L I S H E D B Y T H E B O A R D O F H E A LT H C A R E F U N D E R S

Income 2

Income 3

Income 4

Income 5

Income 6

Pensioners

i m p a c t o f CO V I D - 1 9 o n p r i v a t e s e c t o r h e a l t h c a r e u t i l i s a t i o n [ 1 ]

Appendix A (continued) Figure 19. Change from 2019 in immunisations by income DTP VACCINE 70%

120%

60%

Change compared to 2019

PNEUMOCOCCAL VACCINE 140%

100% 80% 60% 40% 20% 0%

-20%

2020

50% 40% 30% 20% 10% 0% -10%

2021

-40%

2020

Q2 2021

-20%

Income 1

Income 2

Income 3

Income 4

Income 5

Income 6

Income 1

Income 2

Income 3

Income 4

Income 5

Income 6

MEASLES VACCINE 40% 35%

Change compared to 2019

30% 25% 20% 15% 10% 5% 0% -5%

2020

Q2 2021

-10% Income 1

Income 2

Income 3

Income 4

Income 5

Income 6

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The Difference Between a vaccine mandate and mandatory vaccination AUTHOR Deborah Pearmain

PEER REVIEWER: Rajesh Patel

Executive summary In South Africa, the term ‘vaccine mandate’ refers to national health policy determined by the National Executive or the Minister of Health in terms of the Constitution and other legislation to provide vaccinations for COVID-19 or other diseases as prophylaxis. Mandatory vaccination is vaccination required in terms of a law or a contract or both, refusal of which may have legal consequences for the person required to be vaccinated. The constitutional rights to privacy and bodily and psychological integrity are not absolute and may be limited in terms of section 36 of the Constitution.

Introduction According to the dictionary, a mandate is an official order or commission to do something. It implies the authority to carry out a policy or act in a certain way described in the terms of the mandate. The South African Constitution states in section 85 that the executive authority of the Republic is vested in the President. The President exercises the executive authority, together with the other members of Cabinet, by developing and implementing national policy and by implementing national legislation except where the Constitution or an Act of Parliament provides otherwise. The President together with Cabinet can decide that it is national policy to provide COVID-19 vaccinations to people. The Minister of Health is a member of Cabinet and can make decisions on national health policy. The Director-General of the National Department of Health is responsible for implementing national health policy in terms of section 21 of the National Health Act No 61 of 2003. The South African Constitution confers on everyone the right to bodily and psychological integrity. This right includes the right to security in and control over one’s own body and the right not to be subjected to medical or scientific experiments without informed consent.

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THE D i ff e r e n c e B e t w e e n V a c cine Mandate & Mandatory Vaccinati on [2 ]

One of the legally mandated roles of the Director-General is to identify national health goals and priorities and monitor the progress of their implementation. The Director-General is also required to co-ordinate health and medical services during national disasters and facilitate and promote the provision of health services for the management, prevention and control of communicable and non-communicable diseases. COVID-19 is a communicable disease because it can be passed from one person to another. On 15 March 2020, the Minister of Cooperative Governance and Traditional Affairs exercised her powers in terms of the Disaster Management Act No 57 of 2002 to declare a national state of disaster with regard to the outbreak of COVID-19. The Disaster Management Act is South African legislation that sets out the powers of the Minister to make regulations or issue directions or to authorise the issue of directions to the extent necessary for the purpose of (a) assisting and protecting the public; (b) providing relief to the public; (c) protecting property; (d) preventing or combatting disruption; or (e) dealing with the destructive and other effects of the disaster.

COVID-19 Vaccine Mandate The South African COVID-19 vaccine mandate is a government policy to provide vaccinations for COVID-19. It does not necessarily imply that everyone is legally obliged to be vaccinated against COVID-19. Mandates are an important aspect of responsible, constitutional government because they must be funded (Malherbe 2002). COVID-19 is classified as a Category 1 Notifiable Medical Condition in the Regulations Relating to the Surveillance and the Control of Notifiable Medical Conditions (2017). A notifiable medical condition is defined in these regulations as a medical condition, disease or infection of public health importance that is classified as a notifiable medical condition in terms of regulation 12. Regulation 12(2) allows the Minister of Health to declare a medical condition as notifiable if in his or her opinion the medical condition (a) poses a public health risk to a population of a particular community, district, municipality, province or the country; (b) may be regarded as a public health risk or has a potential for regional or international spread; and (c) may require immediate, appropriate and specific action to be taken by the national department, one or more provincial departments or one or more municipalities. Regulation 12(1) also declares the medical conditions listed in Annexure A to the regulations to be notifiable medical conditions. Under Category 1 of Annexure A, respiratory diseases caused by a novel respiratory pathogen are listed. The explanatory note states that examples of novel respiratory pathogens include novel influenza A virus and MERS coronavirus. COVID-19 fits into this category because it is a novel coronavirus that first emerged in or around 2020 and is a respiratory pathogen. Other examples of Category 1 diseases include cholera, rabies, measles, anthrax and viral haemorrhagic fevers such as Ebola and Marburg. The regulations set out the responsibilities of the national department of health, provincial departments of health, health districts, health establishments, health laboratories and medical schemes with regard to notifiable medical conditions. Regulation 14(1) states that the disease-specific guidelines on how to diagnose,

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[2 ] THE D i ffe r e n c e B e t w e e n Vaccine Mandate & Mandatory Vaccinati on

manage and prevent the spread of notifiable medical conditions issued by the national department must be followed in implementing the appropriate medical examination, prophylaxis, counselling, treatment, isolation or quarantine measures. Persons involved in the provision of health care who diagnose a notifiable medical condition are legally obliged to report it to the National Institute of Communicable Diseases. Medical schemes are also obliged to report notifiable medical conditions. It is a criminal offence not to do so. The South African government has not enacted specific legislation to make COVID-19 vaccination mandatory. However, there are existing regulations it could use to do so that are discussed below. They are somewhat cumbersome and expensive to implement as they require court orders. At the time of writing, the government’s approach is to encourage the vaccination of as many people as possible against COVID-19 in the hope of achieving herd immunity and preventing serious illness in the event that people do contract the virus.

Mandatory Vaccination For COVID-19 When something is mandatory, it is required by law or is compulsory in terms of a lawful agreement. If a person does not comply with something that is mandatory, there can be legal consequences. Regulation 15 of the Regulations Relating to the Surveillance and the Control of Notifiable Medical Conditions stipulates that the required mandatory medical examination, prophylaxis, treatment, isolation or quarantine procedures must be determined on a case-by-case basis and tailored depending on the public health risk and individual circumstances of the person in question. The regulation stipulates that the head of a provincial department of health must apply for an appropriate court order, if a person who is a clinical or laboratory confirmed case, carrier or contact of a notifiable medical condition listed in Annexure A to the regulations refuses to consent to (a) a medical examination, including the taking of a biological specimen; (b) being admitted at a health establishment; or (c) mandatory prophylaxis, treatment, isolation of quarantine in order to prevent transmission, Regulation 15 (3) states that the health care provider, with the assistance of law enforcement agencies, should subject a person who is a clinical or laboratory confirmed case, carrier or contact of a notifiable medical condition to prophylaxis, treatment or implement isolation or quarantine procedures whilst awaiting the court order to prevent transmission. The regulations require that certain conditions are fulfilled before mandatory prophylaxis, treatment, isolation or quarantine may be taken. To date the government has not used the regulations on notifiable medical conditions to enforce COVID-19 vaccination. The Minister of Cooperative Governance and Traditional Affairs made various regulations in terms of section 27(2) of the Disaster Management Act relating to COVID-19. Regulation 4(1) of these regulations states that No person who has been confirmed as a clinical case or as a laboratory confirmed case as having contracted COVID-19, or who is suspected of having contracted COVID-19, or who has been in contact with a person who is a carrier of COVID 19, may refuse to consent to – (a) submission of that person to a medical examination, including but not limited to the taking of any bodily sample by a person authorised in law to do so; (b) admission of that person to a health establishment of a quarantine or isolation site; or

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THE D i ff e r e n c e B e t w e e n V a c cine Mandate & Mandatory Vaccinati on [2 ]

(c) submission of that person to mandatory prophylaxis, treatment, isolation or quarantine, or isolation in order to prevent transmission. Provided that if a person does not comply with the instruction or order of the enforcement officer, that person must be placed in isolation or quarantine for a period of 48 hours, as the case may be, pending a warrant being issued by a competent court, on the application by an enforcement officer for the medical examination contemplated in paragraph (a). In terms of these regulations, or the regulations on notifiable medical conditions, a person could be compelled to be vaccinated by a court order because a vaccination constitutes prophylaxis. However, as at the time of writing, the government has chosen the route of incentivising people to obtain the vaccine voluntarily.

Mandatory Vaccinations Required By Employers Section 9 of the Occupational Health and Safety Act No 85 of 1993 imposes a legal obligation on employers to conduct their undertaking in such a manner as to ensure as far as reasonably practicable that persons other than those in their employment who may be directly affected by the employer’s activities are not exposed to hazards to their health or safety. Section 8 of the Act requires every employer to provide and maintain, as far as is reasonably practicable, a working environment that is safe and without risk to the health of its employees. The Minister of Employment and Labour issued a Direction with regard to COVID-19 in the workplace on 11 June 2021. It required every employer to undertake a risk assessment, taking into account various factors, including whether it intends to make vaccinations mandatory and if so, to identify those employees who by virtue of the risk of transmission through their work or their risk for severe COVID-19 disease or death due to their age or comorbidities that must be vaccinated. The employer has to develop a plan based on the risk assessment, or amend an existing plan, and consult on the risk assessment and plan with various parties referred to in the directions. If the employer decides that vaccination is mandatory in respect of employees, the vaccination plan must comply with any applicable collective agreement and take into account the guidelines set out in Annexure C to the Direction. Annexure C of the Direction stresses that employers and employees should treat each other with mutual respect and says that employees must be notified of the obligation to be vaccinated as and when a vaccine becomes available for that employee. The employee must also be notified of his or her right to refuse to be vaccinated on constitutional grounds and the opportunity to consult a health and safety representative or a worker representative or trade union official upon request. If the employee refuses to be vaccinated on any constitutional or medical ground the employer must counsel the employee and if requested, allow the employee to seek guidance from those same individuals. The employer must refer the employee for further medical evaluation should there be a medical contraindication for vaccination. The employer must also, if necessary, take steps to reasonably accommodate the employee in a position that does not require the employee to be vaccinated. While some people believe that if employers require employees to receive COVID-19 vaccinations it would violate their constitutional rights, the constitutional court has stated that none of these rights is absolute (Gaertner v Minister of Finance, 2014). The constitutional rights of one individual cannot trump the constitutional rights of others. There are many different constitutional rights that must be balanced against each other and the constitution itself provides in section 36 for the limitation of constitutional rights in terms of a law of general application in certain circumstances.

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[2 ] THE D i ffe r e n c e B e t w e e n Vaccine Mandate & Mandatory Vaccinati on

Constitutional law and labour law expert, Halton Cheadle (‘Mandatory vaccine policies will survive a constitutional challenge’ 2021) expressed the view in a webinar held by the South African Medical Research Council that a challenge to the constitutionality of a mandatory vaccination policy of an employer would probably withstand the scrutiny of the constitutional court. He also stated that it would be legally possible to dismiss an employee who refused to receive the vaccine provided that the employer followed the correct procedures. Examples of past cases where a court has compelled a person to undergo medical treatment without consent are Minister of Safety and Security v Gaqa (2002) and Minister of Health, Western Cape v Goliath and Others (2009). In Gaqa, the high court compelled a person to undergo surgery to remove a bullet from his leg, taking into account the public interest in law enforcement and criminal prosecution. In Goliath, the high court compelled two people with XDR (drug resistant) tuberculosis to be admitted to a hospital and abide by the rules of behaviour for XDR tuberculosis patients at the hospital. The court held that isolation of patients with infectious diseases was universally recognised in open and democratic societies as justifiable to protect and preserve the health of citizens.

Conclusions A vaccine mandate is generally a reference to government policy on providing vaccinations to people in order to promote and protect public health and prevent the spread of certain diseases. Mandatory vaccinations may be required by legislation or an employment contract, read with relevant labour law, or a court order. The refusal of a mandatory COVID-19 vaccine may have legal consequences for the refuser. Mandatory vaccinations are not necessarily a violation of the constitutional rights of the individuals required to be vaccinated. In an open and democratic society, the limitation of constitutional rights is, at times, justifiable in the public interest.

“ 34

Mandatory vaccinations are not necessarily a violation of the constitutional rights of the individuals required to be vaccinated. In an open and democratic society, the limitation of constitutional rights is, at times, justifiable in the public interest.

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THE D i ff e r e n c e B e t w e e n V a c cine Mandate & Mandatory Vaccinati on [2 ]

ReferenceS Constitution of the Republic of South Africa, 1996 Consolidated Direction on Occupational Health and Safety Measures in Certain Workplaces, Government Gazette No 44700 Notice No R.499 11 June 2021 Declaration of a National State of Disaster, Government Gazette No 43096, Notice No 313, 15 March 2020 Disaster Management Act No 57 of 2002 Disaster Management Act, 2002: Amendment of Regulations Issued in terms of Section 27(2) Government Gazette No 43148, Notice No 398, 25 March 2020 Ellis, E. (2021) ‘Mandatory vaccine policies will survive a constitutional challenge’ Daily Maverick, 10 Nov 2021 https://www.dailymaverick.co.za/article/2021-11-10-mandatory-vaccine-policies-will-survive-a-constitutionalchallenge-legal-expert-halton-cheadle/ accessed on 16 November 2021 Gaertner and Others v Minister of Finance and Others 2014 (1) SA 442 (CC) Malherbe R, ‘The Unconstitutionality Of Unfunded Mandates Imposed By One Sphere Of Government On Another’ 2002 TSAR 541 Minister of Health, Western Cape v Goliath and Others 2009 (2) SA 248 (C) Minister of Safety and Security and Another v Gaqa 2002 (1) SACR 654 (C) National Health Act No 61 of 2003 Regulations Relating to the Surveillance and the Control of Notifiable Medical Conditions under the National Health Act

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MIND THE GAP

South Africa’s mental health burden AUTHORS Emma Finestone Jodi Wishnia Shivani Ranchod

PEER REVIEWER: Charles Hongoro

ABSTRACT Background: Mental health conditions are becoming increasingly large contributors towards disease and disability burdens worldwide. In South Africa, mental disorders are ranked as the third largest contributor to the burden of disease. The aim of this paper is to explore this burden and to inform a potential investment case for the funding or delivery of mental health services. METHODS: This paper draws on multiple data sources to form a picture of the extent of the South African mental health burden and to create empirical data for an investment case. Household survey data and medical scheme data were used for the quantitative analysis. Household survey data include the 2018 General Household Survey (GHS) and the 2017 National Income Dynamics Study (NiDS). Medical scheme data were provided by a large medical scheme administrator and managed care service provider. These included mental health hospital admission data, between 2014 and 2018, and chronic-benefit registration data for 2020. We also used qualitative data derived from primary data collected in one region of South Africa. RESULTS: Self-reported measures of prevalence of mental disorders were far lower (~2%) than objective measures of depression prevalence (one such mental health disorder) (~12%). The medical scheme data illustrated high levels of comorbidity between mental disorders and other non-communicable diseases (NCDs) in the South African medical scheme population, three in five beneficiaries aged 20+ who are registered for chronic benefits for depression were also registered for hypertension benefits, while one in four was also registered for diabetes benefits. CONCLUSION: The high levels of comorbidity between mental and physical illness strengthen the mental health investment case in South Africa. By creating an investment case, policy-makers will be able to prioritise high-impact activities to improve diagnosis, treatment and management of mental health disorders. This investment is likely to avert downstream costs from both the comorbidities and complications that create pressure on the (already constrained) health system and negatively impact the economy.

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M i n d t h e g a p : S o u t h Af r i c a ’ s m e n t a l h e a l t h b u r d e n [ 3 ]

Introduction The aim of this paper is to explore the burden of mental health in South Africa, to inform a potential future investment case for the funding and delivery of mental health services. As per the World Health Organization’s (WHO) Special Initiative for Mental Health: 2019-2023, there is no health without mental health (World Health Organization 2019). In recent years, there has been an acknowledgement of the need to increase investment in mental healthcare to avoid the negative health consequences of poor prevention, screening, management and treatment of these conditions (World Health Organization 2019). Mental health conditions are becoming increasingly large contributors towards disease and disability burdens worldwide. In South Africa, mental disorders are ranked as the third largest contributor to the burden of disease (Hamdulay 2013). This high burden can largely be explained by socioeconomic factors such as the high levels of poverty and inequality, urbanisation (Srivastava 2009), violence, substance abuse and intergenerational trauma stemming from a long history of oppression (Adonis 2016). All of these are prominent risk factors for the onset of mental disorders (Nguse and Wassenaar 2021). Despite the high prevalence of mental disorders, access to adequate mental health services is lacking. Only 28% of individuals suffering from mental disorders receive the relevant care (Lund et al. 2010) and 50% of health facilities do not meet required quality standards (South African Depression & Anxiety Group n.d.). In line with best practice for mental healthcare, new national policies are progressively moving away from the historic hospital-centric approach. The intention behind this shift to mental health services in primary healthcare settings is to integrate mental healthcare into community-based care, to improve health outcomes most cost-efficiently (Lund et al. 2010). However, the development of any such community-based services in South Africa has been slow and mental healthcare remains largely centred around hospitals (Docrat et al. 2019). Mental ill-health also has major implications for physical well-being. Individuals suffering from mental illness experience higher morbidity, disability and mortality (Grandón et al. 2019). For example, those with severe mental disorders can be up to 60% more likely to have a premature death related to a physical health condition, particularly another NCD (Vigo, Thornicroft, and Atun 2016). Comorbidity is also associated with poorer adherence to treatment (for both the mental and physical conditions) because of the mental disorder’s symptoms. For example, low motivation and other symptoms of depression can make it more difficult for patients to maintain a healthy diet and remain physically active to manage metabolic diseases such as diabetes or can lead to missing healthcare appointments. Furthermore, the relationship between mental and physical health is bidirectional: those with mental disorders are more likely to suffer from physical disorders and those with physical disorders are also more likely to suffer from mental disorders (Stein et al. 2019). Mental-physical comorbidity becomes the rule as opposed to the exception: the majority of those with either a mental disorder or another NCD have both (Wille, Bettge, and Ravens-Sieberer 2008). The impacts of mental ill-health are therefore wide-reaching and felt far beyond symptoms and costs directly attributable to mental disorders alone; this demonstrates that overall wellbeing and health cannot be achieved without mental health.

Methods This paper draws on multiple data sources to form a picture of the extent of the South African mental health burden, to create empirical data for a future investment case. There is a striking absence of accurate data to fully estimate the mental health burden of disease – in part because mental health conditions show up in mortality data to a limited degree, and in part because of widespread underdiagnosis and misdiagnosis, stigma (which contributes to poor health seeking) and low levels of screening.

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[ 3 ] M i n d t h e g a p : S o u t h Af r i c a ’ s m e n t a l h e a l t h b u r d e n

Two broad quantitative data sets were analysed for this research: household survey data and medical scheme data. Household survey data include the 2018 GHS (Statistics South Africa 2019) and the 2017 NiDS (Southern Africa Labour and Development Research Unit 2018). Prevalence from the GHS dataset is estimated using self-reported data around previously diagnosed mental disorders. Prevalence of depression from the NiDS dataset is estimated based on the results of a standardised diagnostic tool (CES-D 10 scale) which is included as a part of the NiDS questionnaire. Participants with a CES-D 10 score of 15 or greater are considered to have symptoms of depression. Medical scheme data were provided by a large medical scheme administrator and managed care service provider. These included mental health hospital admission data, between 2014 and 2018, and chronic benefit registration data for 2020. Only those schemes that offer benefits for mental disorders beyond the required prescribed minimum benefits were included in the dataset. Prevalence of mental disorders in the medical scheme population is estimated by ascertaining the proportion of beneficiaries registered for chronic disease benefits for the relevant disorder. Relative prevalence ratios indicate the ratio of prevalence in one subgroup of the medical scheme population compared to another. Asterisks are used to denote the statistical significance of the findings of the household survey and medical scheme data analysis: * = p<0.1: statistically marginally significant ** = p<0.05: statistically significant *** = p<0.01: statistically highly significant Where results have been age standardised, the standardisation is based on the Statistics South Africa midyear population estimates for 2018. We also use qualitative data (carried out by one qualitative researcher, Dr Beth Vale) in this article, based on primary data collected in one pocket of South Africa, to marry the quantitative findings to the reality on the ground. The qualitative and quantitative data collection and use were approved by Stellenbosch University’s Human Research Ethics Council (N20/01/002).

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Results Household survey analysis The GHS’ self-reported prevalence of mental illness is extremely low (under 2%) at all ages. The results of the CES-D 10 scale, which was included as part of the NiDS questionnaire in the health module, show that more than six times as many South Africans (12.5% of females and 12.3% of males) had symptoms of depression alone. 14%

12.5%

12.3%

12%

Prevalence

10% 8% 6% 4% 2% 0%

Female

Male

Symptomatic of depression by CES-D 10 Scale (NiDS 2017)

0.3%

0.5%

Female

Male

Self-reported mental illness (GHS 2018)

Figure 1. Prevalence of self-reported mental disorders is far lower than prevalence based on objective measures of depression (one such mental health disorder), on an age-adjusted basis. It is clear that South Africa has a large undiagnosed burden of mental ill-health, and that stigma around mental health persists as a problem in the country.

Medical scheme data Medical scheme utilisation data, particularly for schemes that offer extensive mental health benefits, provide useful insights into the prevalence of mental ill-health in South Africa. However, these figures are also likely to reflect underdiagnosis due to stigma and reluctant health-seeking behaviour. The close associations between poverty/socio-economic status and mental health would suggest that there is an even higher prevalence of mental disorders in those who are unable to afford medical scheme cover. Therefore, medical scheme data are limited in their applicability to the rest of the South African population but provide a good baseline estimate in the absence of detailed public sector data. The prevalence of mental disorders in the South African medical scheme population is estimated by finding the proportion of beneficiaries who are registered for chronic disease benefits for the relevant disorder. Unsurprisingly, due to better access to care, the medical scheme data show a higher prevalence of mental illness than the self-reported data in household surveys (Table 1).

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Table 1. Proportion of beneficiaries registered for chronic benefits for mental disorders in 2020*** (Own analysis) Mental disorder

Proportion of beneficiaries registered for chronic mental health benefits

Anxiety and panic disorders

0.2%

Bipolar

1.1%

Depression

5.8%

Schizophrenia

0.2%

PTSD

0.2%

Psychosis

0.02%

When disaggregated by age and sex, the data show that females are almost twice as likely to be registered for a chronic depression benefit as men, and that the risk of depression increases with age (Figure 2).

18%

Prevalence of chronic registration for depression

16% 14% 12% 10% 8% 6% 4% 2% 0%

0-9

10-19

20-29

30-39

40-49

Women

50-59

60-69

70-79

80+

All ages

Men

Figure 2. Proportion of beneficiaries registered for chronic benefits for depression in 2020, by age and sex*** (Medical scheme data 2020: own analysis) The age- and sex-standardised prevalence rate of depression in the medical scheme population (4%) is lower than the prevalence of having depression symptoms, as per the NiDS (12%). The medical scheme chronic registration data likely under-estimate true prevalence, given that not all those with depression are necessarily diagnosed and/or actively receiving (pharmaceutical) treatment (which they would need to be in order to be registered for the chronic benefit). The lower prevalence in the medical scheme population could also reflect the higher incidence of mental disorders in populations with lower socio-economic status (owing to the associations between socio-economic status, depression and other mental disorders). The medical scheme data also show an increase in the utilisation of mental healthcare services over time. Data from 2014-2018 show a clear increase in the proportion of beneficiaries admitted to hospital because of mental health disorders over the period (the Council for Medical Schemes reports on admissions to psychiatric facilities, but this excludes psychiatric admissions to acute hospitals and is not disaggregated by age and sex). The proportion of beneficiaries claiming for mental health hospital admissions increased by 10.3% between 2014 and 2018 (from 1.5% to 1.7%) (Figure 3). The highest increases in mental health hospital admissions occurred at younger ages, with a 38% increase in admissions in those aged between 15 and 20. Women were 51% and 47% more likely to be admitted for depressive and bipolar disorders, respectively, compared

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to men. Substance use disorders were more common in men, who were found to be 403% more likely to be admitted for such disorders compared to women. An increase in hospitalisation on the grounds of mental illness likely equates to increased prevalence of mental illness. However, the increases in mental health hospitalisation in the medical scheme population could also indicate increases in severity of mental disorders, given that hospitalisation occurs only in severe cases. (It could also be a reflection of the way benefits are designed, as these are more likely to fully cover in-hospital care than outpatient care). Supporting the severity argument is the fact that the average length of stay in hospital for any mental illness admission increased by 0.5 days from 10.6 days in 2014 to 11.1 days in 2018.

Prevalence of mental health hospital admission

2.5%

2.0%

1.5%

1.0%

0.5%

0.0%

15-20

20-25

25-30

2014 Women

30-35

35-40

2014 Men

40-45

2018 Women

45-50

50-55

55-60

60-65

2018 Men

Figure 3. Proportion of beneficiaries with mental health hospital admissions in 2014 and 2018, by age and gender*** (Medical scheme data: own analysis)

The burden of comorbidity Data analysis confirms high levels of comorbidity between mental disorders and other NCDs in the South African medical scheme population. The analysis showed that three in five beneficiaries aged 20+ who are registered for chronic benefits for depression were also registered for chronic benefits for hypertension, while one in four was also registered for chronic benefits for diabetes. Table 2 depicts the relative prevalence ratios (for beneficiaries over 20 years) of being registered for chronic benefits for an NCD in those registered for chronic benefits for depression compared to those who are not; this demonstrates the close association between depression and NCDs.

Table 2. Increased risk of chronic benefit registration for NCDs in beneficiaries aged 20+ who are registered for chronic benefits for depression*** (Medical scheme data 2020: own analysis) NCD

Ratio of prevalence of chronic benefit registration for NCDs in beneficiaries aged 20+ who are registered for chronic benefits for depression compared to those who are not

Arthritis

3.42

Asthma

2.76

Diabetes

1.69

Heart problems

2.49

Hypertension

1.84

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Qualitative insights on mental health in South Africa The ‘invisibility’ of mental disorders, owing to their lack of physical symptoms, means that mental health issues are framed and described in a variety of ways. In South Africa, a common framing of mental ill-health is ‘stress.’ Box 1 provides some insight into how the idea of ‘stress’ is also understood to be an explanation for the connection between mental and physical disorders.

Box 1. Stress

Reflections from the field, by Dr Beth Vale In my observations in Karoo clinics, ‘stress’ was the primary language through which patients reported their psychological dis-ease. Social workers and caregivers also spoke regularly of their clients’ stresses. Reported sources of stress included debt, childcare, sickly relatives and work. A social worker described to me her elderly clients, supporting large families off their pensions, including adult children who were unable to find work. For the few with jobs, there was also immense pressure to support wider families. ‘This is also compounding stress in the town,’ she said. ‘Add to this the level of debt and anxieties over repayment and you have a recipe for disaster.’ Trepiline, a mild antidepressant, was regularly prescribed throughout the clinics in which I observed, often as a chronic treatment – for sleeplessness, pain and anxiety. Indeed, many described ‘stress’ as related to physical pain. Both within and outside clinics, those living with chronic illness often related ‘stress’ both to the emergence and management of their condition. On one farm, an insulindependent diabetic described the emergence of her diabetes as an outcome consequent on the ‘stress’ of taking care of her grandchildren. Others, in an attempt to explain to clinicians their poor treatment adherence, spoke of being under ‘stress’. While some in this region had received mental health diagnoses – with bipolar disorder, schizophrenia and depression seemingly the most common – others were experiencing psychological distress that was either undiagnosed, a precursor to a later diagnosis, or a reflection of everyday stressors that could nevertheless have a severe effect on physical health. Conversely, physical ill-health can also cause serious psychological distress. As Karoo residents, carers and clinicians grapple with rising rates of NCDs, they are also grappling with language and how best to describe complex webs of psychological and physical distress. Emily Mendenhall and Shane Norris’ study (Mendenhall and Norris 2015) of a cohort of diabetic women in Soweto, South Africa, showed similar findings: descriptions of ‘stress’ were widespread among the participants, who also believed stress to be a cause of sickness and physical pain. Many participants also attributed their ‘stress’ to social problems, particularly problems in the family and histories of grief.

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Discussion According to the Council for Medical Schemes’ (CMS) annual reports, mental health spending by medical schemes has increased dramatically. Payments to psychologists increased by ~300% from 2010 to 2020 in real terms. From 2015 to 2020 admissions to mental health institutions increased by 137%. These changes are indicative of dramatic changes in resource allocation and are, at least in part, driven by an increase in the prevalence and severity of mental disorders in the South African medical scheme population. The increased expenditure may also reflect changes to benefits and the supply of mental health services. In addition to the negative health impact and subsequent burden to the health system, mental illness can lead to decreased productivity, decreased quality of work, increased absenteeism and safety risks at work (South African Depression & Anxiety Group n.d.); all of these come at a cost to the workplace and thus an economic cost/burden to the country. It is estimated that the total loss of earnings in South Africa owing to mental illness amounts to R40 billion annually, approximately 2.2% of the country’s gross domestic product (Bateman 2014). There are also severe social costs related to mental illness: not only are high levels of mental illness a result of poverty, but mental illness can lead to poverty itself. Individuals suffering from mental illness may be subject to stigma and discrimination, which can in turn act as a barrier to education, employment and other basic human rights (National Department of Health: South Africa n.d.). The burden of caregiving (which predominantly falls on women in South Africa) translates into higher risk for mental illness, which in turn leads to the caregiver being at higher risk of developing another NCD. The findings also point to a severe increase in mental disorders in the youth. The highest increase in mental health hospital admissions occurs in those aged 15-20. These results could indicate an increase in risk factors for mental disorders in adolescents, including the impact of intergenerational trauma and the effects of violence. In the Western Cape, 17% of children under the age of 16 are suffering from the effects of violence, with 8% experiencing post-traumatic stress disorder and 11% experiencing generalised anxiety disorder (Swingler 2019). In recent years the increased use of social media, which is associated with increases in low self-esteem and poor body image in adolescents, could help to explain the large increases in prevalence of depression at young ages (Kelly et al. 2018). The large differential in self-reported mental ill-health and objective measures of depression in the NiDS demonstrate that stigma around mental health persists as a national challenge. Stigma can lead to unfair treatment, abuse, rejection, neglect and isolation of mentally ill individuals. As a result, stigma can have major social costs (Docrat et al. 2019). Stigma also has negative impacts on access to, availability of and use of mental healthcare, thus worsening the country’s state of mental health (Docrat et al. 2019). The South African Stress and Health (SASH) study of 2003/2004 (Herman et al. 2009), is the most recent survey investigating the prevalence of mental disorders at a national level; the most recent review of mental health services in the country dates from more than two decades ago (1997) (Lund et al. 2010). The severe lack of recent and reliable data on mental health in the country poses a major challenge to estimating the true burden of disease. Additionally, it hinders the ability to understand the true extent of the impact of mental-physical comorbidity. The high health-related, economic and social costs of mental ill-health highlight the importance of quantifying and understanding the burden thereof, so that resources can be allocated and interventions designed accordingly.

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Conclusion Routine data collection on mental health and mental health service provision should be prioritised, including enhanced survey data. The data described here provide evidence of a high burden of mental disorders in South Africa. However, the true burden of mental illness is difficult to estimate, owing to a lack of reliable and recent data, as well as underdiagnosis and poor access to treatment. Late diagnosis can make treatment more complex and can even lead to inappropriate treatment for physical conditions, given that the clinical history is incomplete (Stein et al. 2019). An integrated approach to mental health services should be adopted. The high levels of comorbidity between mental and physical illness highlight the value of an integrated approach to tackling the mental health burden in the country (for example, the inclusion of social workers and psychologists in multidisciplinary teams), as opposed to considering mental health in isolation or as only the ambit of psychiatrists. Addressing the burden of mental health should be prioritised as a high-impact intervention. High levels of mental-physical comorbidity also provide evidence of the need for a mental health investment case in South Africa. By creating an investment case, policy-makers will be able to prioritise high-impact activities to improve diagnosis, treatment and management of mental health disorders. It would also create impetus for better routine data collection. This investment is likely to avert downstream costs from the comorbidities and complications that create pressure on the (already constrained) health system and negatively impact on the economy.

References Adonis, Cyril Kenneth. 2016. “Exploring the Salience of Intergenerational Trauma among Children and Grandchildren of Victims of Apartheid-Era Gross Human Rights Violations.” Indo-Pacific Journal of Phenomenology 16 (2): 1–17. https://doi.org/10.1080/20797222.2016.1184838. Bateman, Chris. 2014. “Mental Health Under-Budgeting Undermining SA’s Economy.” South African Medical Journal 105 (1): 7–8. https://doi.org/10.7196/SAMJ.9166. Docrat, Sumaiyah, Donela Besada, Susan Cleary, Emmanuelle Daviaud, and Crick Lund. 2019. “Mental Health System Costs, Resources and Constraints in South Africa: A National Survey.” Health Policy and Planning 34 (9): 706–19. https://doi.org/10.1093/heapol/czz085. Grandón, Pamela, Sandra Saldivia, Pamela Vaccari, Raul Ramirez-Vielma, Víctor Victoriano, Carlos Zambrano, Camila Ortiz, and Felix Cova. 2019. “An Integrative Program to Reduce Stigma in Primary Healthcare Workers Toward People With Diagnosis of Severe Mental Disorders: A Protocol for a Randomized Controlled Trial.” Frontiers in Psychiatry 10: 110. https://doi.org/10.3389/fpsyt.2019.00110. Hamdulay, Ali. 2014. “Proactive Management Is the Best Medicine for Mental Health in the Workplace.” 2014. http://www.optimabloem.co.za/manage-mental-illness-in-the-workplace/. Herman, Allen A, Dan J Stein, Soraya Seedat, Steven G Heeringa, Hashim Moomal, and David R Williams. 2009. “The South African Stress and Health (SASH) Study: 12-Month and Lifetime Prevalence of Common Mental Disorders.” South African Medical Journal = Suid-Afrikaanse Tydskrif Vir Geneeskunde 99 (5 Pt 2): 339–44. Kelly, Yvonne, Afshin Zilanawala, Cara Booker, and Amanda Sacker. 2018. “Social Media Use and Adolescent Mental Health: Findings From the UK Millennium Cohort Study.” EClinicalMedicine 6 (December): 59–68. https://doi.org/10.1016/j.eclinm.2018.12.005.

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Lund, Crick, Sharon Kleintjes, Ritsuko Kakuma, Alan J. Flisher, and MHaPP Research Programme Consortium. 2010. “Public Sector Mental Health Systems in South Africa: Inter-Provincial Comparisons and Policy Implications.” Social Psychiatry and Psychiatric Epidemiology 45 (3): 393–404. https://doi.org/10.1007/s00127009-0078-5. Mendenhall, Emily, and Shane A. Norris. 2015. “When HIV Is Ordinary and Diabetes New: Remaking Suffering in a South African Township.” Global Public Health 10 (4): 449–62. https://doi.org/10.1080/17441692.2014.998698. National Department of Health: South Africa. n.d. “National Mental Health Policy Framework and Strategic Plan 2013-2020.” Pretoria, South Africa. Accessed December 31, 2021. https://www.mindbank.info/item/4018. Nguse, Siphelele, and Douglas Wassenaar. 2021. “Mental Health and COVID-19 in South Africa.” South African Journal of Psychology 51 (2): 304–13. South African Depression & Anxiety Group. n.d. “Mental Health Fact Sheet.” Accessed December 31, 2021. https://www.sadag.org/index.php?option=com_content&view=article&id=2988:mental-health-fact-sheet2012&catid=153&Itemid=132. Southern Africa Labour and Development Research Unit. 2018. “National Income Dynamics Study 2017.” Wave 5, Version 1. SALDRU. Srivastava, Kalpana. 2009. “Urbanization and Mental Health.” Industrial Psychiatry Journal 18 (2): 75–76. https://doi.org/10.4103/0972-6748.64028. Statistics South Africa. 2019. “General Household Survey 2018.” Version 1. Statistics South Africa. https://www. datafirst.uct.ac.za/dataportal/index.php/catalog/801. Stein, Dan J., Corina Benjet, Oye Gureje, Crick Lund, Kate M. Scott, Vladimir Poznyak, and Mark van Ommeren. 2019. “Integrating Mental Health with Other Non-Communicable Diseases.” BMJ 364 (January): l295. https://doi. org/10.1136/bmj.l295. Swingler, Helen. 2019. “Conflict Leaves Children Traumatised, Anxious – for Life.” August 26, 2019. http://www. news.uct.ac.za/article/-2019-08-26-conflict-leaves-children-traumatised-anxious-for-life. Vigo, Daniel, Graham Thornicroft, and Rifat Atun. 2016. “Estimating the True Global Burden of Mental Illness.” The Lancet. Psychiatry 3 (2): 171–78. https://doi.org/10.1016/S2215-0366(15)00505-2. Wille, Nora, Susanne Bettge, and Ulrike Ravens-Sieberer. 2008. “Risk and Protective Factors for Children’s and Adolescents’ Mental Health: Results of the BELLA Study.” European Child & Adolescent Psychiatry 17 (Supplement 1): 133–47. World Health Organization. 2019. “Special Initiative for Mental Health (2019–2023).” Geneva: World Health Organization. https://www.who.int/publications-detail-redirect/special-initiative-for-mental-health-(2019-2023).

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Compounding the complexity: Designing a health system for comorbidity AUTHORS Emma Finestone Jodi Wishnia Shivani Ranchod

PEER REVIEWER: Shan Naidoo

Abstract BACKGROUND: As the leading cause of death worldwide, non-communicable diseases (NCDs) have been recognised as a major public health concern. The prevalence of NCDs, and so too comorbidity and multimorbidity, is high and increasing in South Africa. As the country moves towards implementation of National Health Insurance (NHI), integrated approaches to tackling chronic disease should be prioritised so as to manage the burden of comorbidity most effectively. The aim of this paper is to illustrate the burden and challenge of comorbidity and multimorbidity in health systems. METHODS: Two quantitative data sets were analysed for this research: household survey data (2016 South African Demographic and Health Survey) and medical scheme data (2020). Four chronic illnesses are included in the analysis: diabetes, hypertension, HIV and cancer. We also use qualitative data in this article, based on primary data collected in one pocket of South Africa, to marry the quantitative findings to the reality on the ground. RESULTS: Costs of comorbidity and multimorbidity are super-additive. Targeting prevention efforts on disease combinations can be substantially more effective than looking through a single-disease prevention lens. Forty-four percent of medical scheme members registered for a chronic condition were registered for two or more such conditions. Eighty-five percent with diabetes also had one or more other chronic conditions. Given the relationship between socioeconomic status and health, the prevalence of chronic disease and multimorbidity is likely to be higher in the uninsured population. CONCLUSION: This paper highlights both the interconnectedness of different chronic conditions and the care that these complex clients require. To provide quality care, the South African health system needs to adapt, allowing for better record-keeping, easier sharing of data and comprehensive clinical care.

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Designing a health system for comorbidity [4]

Introduction As the leading cause of death worldwide, NCDs have been recognised as a major public health concern (Biswas et al. 2019). The impact of these conditions on health systems across the globe is compounded by the fact that they are often associated with high levels of comorbidity and multimorbidity (Mendenhall et al. 2017) (with other NCDs as well as other conditions, such as HIV and tuberculosis (Lalkhen and Mash 2015)). The term ‘chronic conditions’, rather than NCDs, is used to include diseases that are chronic but communicable, such as HIV. In this paper, comorbidity is defined as two co-existing chronic conditions and multimorbidity as more than two co-existing chronic conditions (Valderas et al. 2009). Therefore, comorbidity and multimorbidity refer to long-term, chronic conditions that need to be managed using medical, behavioural and/or social interventions for the remainder of a person’s life. Chronic diseases, in particular non-communicable chronic diseases, share many biological risk factors (such as age and sex) and social and environmental risk factors (such as gender and socio-economic status); these play a prominent role in the onset of disease. As such, some chronic conditions are inherently linked to each other owing to the crossover of the factors that first give rise to them (causative factors). Examples of conditions with overlapping risk factors are heart disease, hyperlipidaemia and hypertension (Zulman et al. 2014). If a person displays the risk factors for these conditions, they are also likely to experience all three conditions simultaneously. Relationships also exist between infectious diseases and NCDs. For example, antiretroviral therapy, used to treat HIV, has been linked to increased cardiovascular disease, and the human papillomavirus, a sexually transmitted infection (STI), can cause cervical cancer (Gouda et al. 2019). Both these conditions are particularly relevant to South Africa, given the high prevalence of HIV and STIs. Therefore, a person’s experience of infectious diseases can also contribute to their susceptibility to NCDs. This linkage goes in both directions. For example, diabetes makes people more susceptible to tuberculosis and pneumonia, both of which are infectious diseases (Zulman et al. 2014). Diabetes has also been shown to increase the severity of infectious disease, as is the case with COVID-19 (Rawshani et al. 2021). Therefore, comorbidity and multimorbidity can be a result of overlapping risk factors, as well as causal associations across diseases. Additionally, comorbidity is associated with poorer adherence to treatment, particularly in the case of mental-physical comorbidity (Antol et al. 2018; Saadat et al. 2015). Symptoms of mental disorders can make adhering to the behavioural changes necessary for managing chronic diseases more difficult (Stein et al. 2019). For example, individuals suffering from mental illnesses like anxiety and depression may be less inclined to seek healthcare or attend appointments with healthcare providers, as a direct result of associated symptoms, such as low motivation and hopelessness (Nel and Kagee 2013). Individuals experiencing depressive symptoms may also find engaging in regular physical activity and eating a healthy diet more difficult to adhere to (Stein et al. 2019). Furthermore, mental health conditions, particularly depression and anxiety, often arise after diagnosis with diabetes, hypertension or HIV (Nel and Kagee 2013; Madavanakadu Devassy et al. 2020). Comorbidity and multimorbidity generally equate to higher health expenditure (Stein et al. 2019). Many combinations of chronic conditions exhibit what is referred to as super-additive costs of treatment (when the combined cost of treatment is greater than the additive sum of treatment for each condition on its own) (Cortaredona and Ventelou 2017). However, not all chronic conditions are super-additive. One study found that in 10 selected chronic conditions (which resulted in 45 combinations of comorbidities that were analysed), 41 combinations were found to be super-additive (Cortaredona and Ventelou 2017). Diabetes was found to be a particularly significant driver of super-additive costs when co-occurring with another chronic

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[4] Designing a health system for comorbidity

condition; it was found to significantly increase the aggregate cost of treating chronic kidney disease, heart disease, respiratory illnesses and stroke (Cortaredona and Ventelou 2017). A study of health system costs for individual and comorbid NCDs in New Zealand found that 23.8% of total health expenditure on NCDs could be attributed to the super-additive nature of certain combinations of comorbid chronic conditions (Blakely et al. 2019). The prevalence of NCDs, and so too comorbidity and multimorbidity, is high and increasing in South Africa. As the country moves towards implementation of NHI, integrated approaches to tackling chronic disease should be prioritised so as to manage the burden of comorbidity most effectively. The aim of this paper is to illustrate the burden and challenge of comorbidity and multimorbidity in health systems. A conceptual framework is used to inform health funders’ risk management strategies such as benefit design, managed care interventions, service delivery design and strategic purchasing. The limitations of viewing diseases in a siloed manner are illustrated both from a conceptual and a data-driven perspective.

Conceptual framework Comorbidity and multimorbidity are associated with higher levels of mortality, disability and morbidity (Grandón et al. 2019). Moreover, the impact on the health system is super-additive given that comorbidity increases the clinical complexity of care a client would require from the health system and makes quality care more difficult to render (Zulman et al. 2014). This can be attributed to the specific characteristics of these conditions independently, as well as how they interact with one another. Figure 1 provides a conceptual framework illustrating the influence of comorbidity on the complexity and quality of care.

Figure 1. Conceptual framework of the influence of comorbidities on clinical complexity and quality of care for patients (Zulman et al. 2014)

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Designing a health system for comorbidity [4]

Methods The study employed a mixed methods design including use of secondary quantitative data from various sources along with qualitative data.

Data Two quantitative data sets were analysed for this research: household survey data and medical scheme data. The household survey data comes from the 2016 South African Demographic and Health Survey (SADHS). Four chronic illnesses were included in the results, namely: diabetes, hypertension, HIV and cancer. The 2016 SADHS uses objective measures for HbA1C, blood pressure and HIV tests to ascertain the prevalence of diabetes, hypertension and HIV status, respectively, while cancer is self-reported (National Department of Health: South Africa 2019). Respondents who stated that they were receiving cancer treatment or had been treated for cancer in the past are included. Medical scheme data were obtained from the reports published by the Council for Medical Schemes (CMS) (2017-2020). In addition to this, data were provided by a large healthcare administrator and managed care services provider (2020). The data include chronic benefit registration data for 2020. Prevalence of chronic disease in the medical scheme population is estimated by ascertaining the proportion of beneficiaries registered for chronic disease benefits for the relevant health condition. Relative prevalence ratios indicate the ratio of prevalence in one subgroup of the medical scheme population compared to another. Qualitative data were collected in one pocket of South Africa by Dr Beth Vale. She used an ethnographic research design, collecting data through observation, in-depth semi-structured interviewing (with patients and caregivers) and focus group discussions (with caregivers). The data were analysed using thematic analysis. The study protocol was approved by Stellenbosch University’s Human Research Ethics Council (N20/01/002).

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Results Household survey analysis The results of the 2016 SADHS show high levels of comorbidity and multimorbidity in the South African population; 57% of respondents were found to have none of the four chronic conditions of interest, 33% had at least one, 10% had two, while only 1% had three chronic conditions (Figure 2). Women had a higher prevalence of co-occurrence than men, with 13% having two or three chronic illnesses, while 9% of men in the sample were found to have two or three chronic illnesses. Only one respondent in the SADHS dataset had all four chronic conditions. Of all the respondents that had chronic conditions, 22.3% had one other condition and 1.6% had two or more other conditions. An analysis of SADHS respondents with either diabetes, cancer, HIV or hypertension who have at least one other chronic illness showed that 76% of diabetics, 57% of people being treated for cancer or have had cancer in the past, 46% of people living with HIV and 29% of people with hypertension have at least one other chronic illness.

Figure 2. Prevalence of comorbidity across four conditions, SADHS 2016 70% 62% 60%

57% 53%

Total

Male

Female

% of population

50%

40% 33% 30%

35% 30%

20% 10%

10%

12% 7%

2 Number of chronic illnesses

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1% 0% 1%

0.01% 0% 0.01%

Designing a health system for comorbidity [4]

Medical scheme data In 2019, the CMS published a report on chronic conditions and their co-occurrence with one another, which has shed light on the prevalence of comorbidity and multimorbidity in the insured population (Cairncross and Govuzela 2019). Figure 3 shows the prevalence rates of two, three and four or more chronic conditions in the medical scheme environment. The data show an increasing trend between 2011 and 2017 for all numbers of co-occurrence. Individuals with four or more chronic conditions have increased by 91% since 2011 (0.22% to 0.42% in 2017), albeit off a low base. Individuals with three or more chronic conditions have shown a 50% increase between 2011 and 2017 – a substantial jump in just six years. The medical scheme population shows an overall prevalence of 6% of people (556,160 individuals) living with more than one chronic condition. This is lower than the 11% estimated for the general population using the SADHS survey data.

Figure 3. Comorbidity burden in the medical scheme population (Cairncross and Govuzela 2019) 4.5%

4.09%

4.0%

3.53% 3.5% 3.0% 2.5%

1.81%

2.0% 1.5%

1.21%

1.0% 0.5% 0.0%

0.42%

0.22% 2011

2012

Two simultaneous CDLs

2013

2014

Three simultaneous CDLs

2015

2016

2017

Four or more simultaneous CDLs

Overall, 44% of members who were registered for a chronic condition were registered for two or more chronic conditions; 85% of medical scheme members with diabetes also had one or more other chronic conditions (Table 1).

Table 1. Comorbidity according to chronic registration for NCDs in medical schemes NCD

Percentage of those with the NCD that have one or more other NCDs

Diabetes

85%

Hypertension

55%

Cardiovascular incident

92%

Coronary disease

89%

Mental disorders

66%

Asthma

53%

Arthritis

85%

Any NCD

44%

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[4] Designing a health system for comorbidity

Medical scheme chronic benefit registration data also show high prevalence of mental-physical comorbidity. Individuals registered for chronic benefits for depression are more likely to be registered for chronic benefits for arthritis (probability ratio (PR): 3.4), asthma (PR: 2.8), diabetes (PR: 1.7), heart disease (PR: 2.5) and hypertension (PR: 1.8) compared to those who are not. This indicates that individuals who have depression are more likely to have other chronic conditions than those who do not have depression.

Qualitative insights on managing comorbidities When a clinician is not actively managing a patient’s medication load and assisting them with ways to simplify the mental burden associated with taking medication, adherence is likely to suffer. Poor adherence leads to worse health outcomes. Box 1 illustrates the impact of poor management from the patient’s perspective.

Box 1. Medication overwhelm

Insights from qualitative research by Dr Beth Vale The ‘medication overwhelm’ for patients with multimorbidity was illustrated most powerfully in one consultation I observed – between a dietician (D) and a woman in her late fifties (W). D: Why have you come to see me today? W: It’s my kidneys and my heart. I was short of breath. So, I went to see the doctor and found out that my heart and my kidneys aren’t working. They said I must speak with you about my diet. The patient paused for a moment and then pulled out a shopping packet, full of medication: W: I don’t know which pills are for my kidneys and which are for my heart. There’s such a pile of pills, I don’t know what’s what. D: Bring them, I’ll try. [She looked closely at the packets, boxes, and blister packs] Okay, this one is for cholesterol, take it in the evening. W: [The woman nodded] In the evening. D: Do you know what cholesterol is? W: [The woman shook her head] No. D: We’ll speak about that later. What about this pill? Do you know it? This one is for blood pressure. W: Okay, so I know the ones in the boxes, but I don’t know the ones in these packets.’ D: [The dietician scanned the labels] Okay, this one is for heartburn [holding up a packet]. Can I write that on the label? Take it in the evening... Okay, next one: this one is also for high blood pressure. You take it at lunchtime. So, you have two…no three for blood pressure. By now, the dietician had stopped telling the patient when to take each pill. Even she was becoming overwhelmed. Nevertheless, she kept going:

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Designing a health system for comorbidity [4]

D: Okay, this is iron. That could be because your kidneys don’t work so well, so you have too little iron.’ W: [Now, it was the patient’s turn to point at a box] And this one, I know this one is for the heart. D: Okay. And where’s your water pill? Oh, here it is. I’ll write it on the package…. And this one, I think if I had to guess, this one is for the heart that doesn’t work very well. Yes, this is for the heart. [Slowly, the dietician returned the medicines back to the shopping packet] It’s good to ask the nurses at the pharmacy to explain to you. It’s important that you ask. It’s your body. But even she seemed to acknowledge that what was being asked of her patient – a caregiver of three grandchildren – was near impossible.

Discussion The findings of this paper show that the South African medical scheme population experiences high levels of comorbidity and multimorbidity: 44% of individuals with an NCD have at least two NCDs. In addition to this, the prevalence of co-occurrence of conditions is increasing over time, at a rapid rate. These findings are in line with previous research (Lalkhen and Mash 2015; Sheik et al. 2016; Hoare, Mendelson, and Frenkel 2021). A study conducted in a primary healthcare setting in South Africa found a 48% prevalence of co-occurrence (Lalkhen and Mash 2015). The high prevalence of comorbidity and multimorbidity highlights the need to target prevention efforts on disease combinations; this can be substantially more effective than looking through a single-disease prevention lens (Cortaredona and Ventelou 2017). For example, given the high co-occurrence of physical and mental health conditions, awareness and screening for mental conditions in those with other chronic conditions should form part of the basic standard of care. Understanding how diseases cluster together is important for designing appropriate clinical disease management guidelines for certain chronic conditions that tend to co-occur (Schäfer et al. 2014). In addition, the importance of addressing the high levels of comorbidity in South Africa is accentuated by the super-additivity of healthcare costs associated with comorbidity and multimorbidity. Further research on the cost of combinations of comorbid chronic diseases is therefore recommended. This study does not analyse cost data, and therefore does not focus on the cost of comorbidity. The findings of the qualitative research in this study demonstrate the complexity of disease management where comorbidities exist. This is supported by existing literature. For example, a study of patient and healthcare provider experiences with the care and management of comorbid chronic diseases at public healthcare facilities providing HIV care across Cape Town, South Africa, found that people living with HIV stated that they were inconvenienced by having to collect ARVs and other chronic medications at different facilities (Peer et al. 2020). They also complained of a lack of continuity of care as they were treated by different clinicians at every visit. Healthcare providers also stated that patients often struggled with the high pill burden (Peer et al. 2020).

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This highlights the importance of managing multiple conditions using a holistic person-centred approach, as opposed to simply treating single diseases in isolation. To do this, more integrated care approaches are needed. These should allow patients to receive treatment in ways that enable continuity of care and track which medications have been prescribed to minimise polypharmacy where possible. Tools such as STOPP (screening tool of older people’s prescriptions) and START (screening tool to alert providers of the right treatment) can be used to assist with decision-making (Halli-Tierney, Scarbrough, and Carroll 2019). The risk that comes with multiple medications is lessened when someone is in the care of a team of clinicians who are aware of that individual’s clinical history. In the private sector, it is possible for someone to have a designated general practitioner (GP) who supports them. However, GPs mostly work alone, and data are not shared freely between clinicians if a person needs to change GPs or expand their care to a broader care team. In the public sector, while healthcare workers demonstrate better teamwork, a client cannot ‘book’ with a particular healthcare worker. Therefore, clinicians are reliant on the robustness and depth of clinical notes left by other clinicians, usually documented in paper-based folders. This method of documentation makes patient record-keeping more cumbersome and notes are often less comprehensive than required for streamlined care. Therefore, both the public and private systems currently do not lend themselves to quality care for either chronic or comorbid clients. Patients’ experience of care and the absolute level of quality of care provided would improve if the South African health system (private and public sectors) rolled out a single electronic health record (EHR). An EHR allows the health system and providers to track individuals using a unique patient identifier. This supports a flow of information between different providers with regard to whether a patient has been screened and what the result was and whether they are on a medication/treatment regimen. As more conditions arise, an EHR would allow the health system to alert healthcare workers that a person is a high-risk individual requiring more intensive care. EHRs ideally need to belong to the patient so that the information moves with them, regardless of the provider team or funder of care.

Limitations The findings of the quantitative analysis from both household survey and medical scheme data probably underestimate the true burden of comorbidity in South Africa. The household survey data analysis relies predominantly on objective measures of disease and although objective measures are obtained through tests, they are voluntary and therefore do not necessarily represent the population prevalence of these chronic conditions, but rather only the prevalence among the population who volunteered to be tested. People may have refused to be tested because they perceived themselves to be in good health, or they may have feared disclosing their health status. In addition to this, only four chronic conditions are included in this analysis; many others have no easy-to-administer objective measures, therefore they have not been included. Estimates based on chronic registration (medical scheme) data are also likely to underestimate the true prevalence of comorbidities in this population. Firstly, not all medical scheme beneficiaries will have been screened for chronic illnesses, particularly on options with limited day-to-day benefits, so they may be unaware of their conditions. Additionally, not all medical scheme beneficiaries claim from their medical schemes when purchasing chronic medication or care for chronic illnesses; many simply pay out of pocket. This is often because of the administrative processes associated with accessing benefits, which act as a barrier.

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Designing a health system for comorbidity [4]

Conclusion This study highlighted both the interconnectedness of different chronic conditions and the care that these complex clients require. To provide quality care, the South African health system needs to adapt, allowing for better record-keeping, easier sharing of data and comprehensive clinical care. Certain chronic conditions are predictors of others and therefore, by targeting one or two of the most prevalent conditions, we could bring down the number of comorbidities at the individual and collective level.

References Antol, DD, AW Casebeer, R Khoury, T Michael, A Renda, S Hopson, et al. 2018. “The Relationship between Comorbidity Medication Adherence and Health Related Quality of Life among Patients with Cancer.” Journal of Patient Reported Outcomes 2: 29. https://pubmed.ncbi.nlm.nih.gov/30294709/. Biswas, Tuhin, Nick Townsend, Md Saimul Islam, Md Rajibul Islam, Rajat Das Gupta, Sumon Kumar Das, and Abdullah Al Mamun. 2019. “Association between Socioeconomic Status and Prevalence of Non-Communicable Diseases Risk Factors and Comorbidities in Bangladesh: Findings from a Nationwide Cross-Sectional Survey.” BMJ Open 9 (3). https://doi.org/10.1136/bmjopen-2018-025538. Blakely, Tony, Giorgi Kvizhinadze, June Atkinson, Joseph Dieleman, and Philip Clarke. 2019. “Health System Costs for Individual and Comorbid Noncommunicable Diseases: An Analysis of Publicly Funded Health Events from New Zealand.” PLoS Medicine 16 (1): e1002716. https://doi.org/10.1371/journal.pmed.1002716. Cairncross, Carrie-Anne, and Mondi Govuzela. 2019. “Prevalence of Chronic Diseases in the Population Covered by Medical Aid Schemes in South Africa.” Research and Monitoring Unit: Council for Medical Schemes. Cortaredona, Sébastien, and Bruno Ventelou. 2017. “The Extra Cost of Comorbidity: Multiple Illnesses and the Economic Burden of Non-Communicable Diseases.” BMC Medicine 15 (1): 216. https://doi.org/10.1186/s12916017-0978-2. Gouda, Hebe N., Fiona Charlson, Katherine Sorsdahl, Sanam Ahmadzada, Alize J. Ferrari, Holly Erskine, Janni Leung, et al. 2019. “Burden of Non-Communicable Diseases in Sub-Saharan Africa, 1990-2017: Results from the Global Burden of Disease Study 2017.” The Lancet. Global Health 7 (10): e1375–87. https://doi.org/10.1016/ S2214-109X(19)30374-2. Grandón, Pamela, Sandra Saldivia, Pamela Vaccari, Raul Ramirez-Vielma, Víctor Victoriano, Carlos Zambrano, Camila Ortiz, and Felix Cova. 2019. “An Integrative Program to Reduce Stigma in Primary Healthcare Workers Toward People With Diagnosis of Severe Mental Disorders: A Protocol for a Randomized Controlled Trial.” Frontiers in Psychiatry 10: 110. https://doi.org/10.3389/fpsyt.2019.00110. Halli-Tierney, Anne D., Catherine Scarbrough, and Dana Carroll. 2019. “Polypharmacy: Evaluating Risks and Deprescribing.” American Family Physician 100 (1): 32–38. Hoare, J., M. Mendelson, and L. Frenkel. 2021. “COVID-19 Vaccine Hesitancy and Anti-Vaxxers – Supporting Healthcare Workers to Navigate the Unvaccinated: Reflections from Clinical Practice.” South African Medical Journal 112 (1). http://www.samj.org.za/index.php/samj/article/view/13482. Lalkhen, Hoosain, and Robert Mash. 2015. “Multimorbidity in Non-Communicable Diseases in South African Primary Healthcare.” South African Medical Journal = Suid-Afrikaanse Tydskrif Vir Geneeskunde 105 (2): 134–38. https://doi.org/10.7196/samj.8696. Madavanakadu Devassy, Saju, Anuja Maria Benny, Lorane Scaria, Anjana Nannatt, Meredith Fendt-Newlin, Jacques Joubert, Lynette Joubert, and Martin Webber. 2020. “Social Factors Associated with Chronic Non-Communicable Disease and Comorbidity with Mental Health Problems in India: A Scoping Review.” BMJ Open 10 (6): e035590. https://doi.org/10.1136/bmjopen-2019-035590.

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Mendenhall, Emily, Brandon A. Kohrt, Shane A. Norris, David Ndetei, and Dorairaj Prabhakaran. 2017. “Non-Communicable Disease Syndemics: Poverty, Depression, and Diabetes among Low-Income Populations.” Lancet (London, England) 389 (10072): 951–63. https://doi.org/10.1016/S0140-6736(17)30402-6. National Department of Health: South Africa. 2019. “South African Demographic and Health Survey 2016.” Nel, Adriaan, and Ashraf Kagee. 2013. “The Relationship between Depression, Anxiety and Medication Adherence among Patients Receiving Antiretroviral Treatment in South Africa.” AIDS Care 25 (8): 948–55. https:// doi.org/10.1080/09540121.2012.748867. Peer, Nasheeta, Anniza de Villiers, Deborah Jonathan, Cathy Kalombo, and Andre-Pascal Kengne. 2020. “Care and Management of a Double Burden of Chronic Diseases: Experiences of Patients and Perceptions of Their Healthcare Providers.” PloS One 15 (7): e0235710. https://doi.org/10.1371/journal.pone.0235710. Rawshani, Aidin, Elin Allansson Kjölhede, Araz Rawshani, Naveed Sattar, Katarina Eeg-Olofsson, Martin Adiels, Johnny Ludvigsson, et al. 2021. “Severe COVID-19 in People with Type 1 and Type 2 Diabetes in Sweden: A Nationwide Retrospective Cohort Study.” The Lancet Regional Health – Europe 4 (May). https://doi.org/10.1016/j. lanepe.2021.100105. Saadat, Zahra, Farahnaz Nikdoust, Hossein Aerab-Sheibani, Mostafa Bahremand, Elham Shobeiri, Habibollah Saadat, Yashar Moharramzad, and Donald E. Morisky. 2015. “Adherence to Antihypertensives in Patients With Comorbid Condition.” Nephro-Urology Monthly 7 (4): e29863. https://doi.org/10.5812/numonthly.29863. Schäfer, Ingmar, Hanna Kaduszkiewicz, Hans-Otto Wagner, Gerhard Schön, Martin Scherer, and Hendrik van den Bussche. 2014. “Reducing Complexity: A Visualisation of Multimorbidity by Combining Disease Clusters and Triads.” BMC Public Health 14 (December): 1285. https://doi.org/10.1186/1471-2458-14-1285. Sheik, Sadiyya, Juliet Evans, Erna Morden, and David Coetzee. 2016. “Non-Communicable Diseases in the Western Cape.” https://www.westerncape.gov.za/assets/departments/health/burden_of_disease_update_ ncds_.pdf. Stein, Dan J., Corina Benjet, Oye Gureje, Crick Lund, Kate M. Scott, Vladimir Poznyak, and Mark van Ommeren. 2019. “Integrating Mental Health with Other Non-Communicable Diseases.” BMJ 364 (January): l295. https://doi. org/10.1136/bmj.l295. Valderas, Jose M., Barbara Starfield, Bonnie Sibbald, Chris Salisbury, and Martin Roland. 2009. “Defining Comorbidity: Implications for Understanding Health and Health Services.” Annals of Family Medicine 7 (4): 357–63. https://doi.org/10.1370/afm.983. Zulman, Donna M., Steven M. Asch, Susana B. Martins, Eve A. Kerr, Brian B. Hoffman, and Mary K. Goldstein. 2014. “Quality of Care for Patients with Multiple Chronic Conditions: The Role of Comorbidity Interrelatedness.” Journal of General Internal Medicine 29 (3): 529–37. https://doi.org/10.1007/s11606-013-2616-9.

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Enhancing the provision

of patient-centred care in the medical scheme sector in South Africa AUTHOR Anuschka Coovadia

PEER REVIEWER: Buddy Modi

Executive summary In an ecosystem where the core products and services are deeply intertwined with the very essence of being human, the lack of humanness in the processes, engagements and systems in healthcare is often stark and apparent. Unlike other sectors, such as telecommunications, hospitality and retail, the healthcare industry has failed to evolve and noticeably lacks critical aspects of customer-centricity. The system does not place the customer or patient at the centre of everything it does. In South Africa, specifically, patient-centricity is deeply compromised by the nature and structure of the healthcare system, which is highly fragmented, specialist-driven and hospital-centric. Care is most often acute, reactive or episodic, rather than proactive, multidisciplinary and continuous. Communication is poor and the provision of timeous, coordinated and relevant treatment is often lacking, difficult to access or provided ‘too little too late’. In this paper on patient-centricity in the medical scheme sector, I aim to: Explore a set of common customer-centric innovations that other sectors have adopted to improve the customer experience Discuss the key challenges with customer-centricity in the medical scheme environment, with a focus on scheme member satisfaction and patient care Explore a set of enhancements that PPS Healthcare Administrators (PPSHA) have developed for their client KeyHealth that they believe could improve the provision of more responsive, sensitive, potent engagements with patients and their families, which should ultimately lead to improved quality of care.

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[ 5 ] E n h a n c i n g t h e p r o v i s i o n o f pat i e n t- c e n t r e d c a r e . . .

The ultimate outcome of patient care is highly dependent on patients’ experience and interactions with the systems, processes and people throughout the continuum. In the absence of a single, holistic, integrated provider system, we have to discover ways of working across and between places, payers and providers to improve the journey for patients across their lifetime needs, during times of both sickness and health. It is my hope that this paper will provide examples of patient-centric innovations and ideas, which will give the reader food for thought and further the medical scheme industry’s views on the role that it can play in advancing these objectives.

Customer-centricity is more than it is Customer-centricity is a manner in which an organisation delivers products, services and experiences to customers, in order to create satisfaction and loyalty (Frankenfield, 2021). It has become a ‘hot topic’ in many sectors, as the world starts to stand up again and recover from the onslaught of the pandemic. Never before has it been more important to chase every sale, keep every customer happy and go the extra mile to build strong relationships and trust. Customer-centricity is more than a style of engagement; it has become a core organisational strategy, which is directly related to the brand, performance, profitability and sustainability of the organisation.

Starbucks is customer obsessed A great example of an iconic brand that lives these values is the coffee chain, Starbucks. They have professed to be customer obsessed. They actively listen to their customers and have gone to great lengths to make them feel comfortable, through the use of lighting and furniture. Their training has ensured that customers are constantly greeted in a warm manner throughout their 32,000 stores across the world. They offer incentives to encourage loyalty and boldly give back to their communities, defining themselves as a global force for social change. They have streamlined their processes to ensure every customer receives a premium cup of coffee with an average of three minutes’ waiting time (Morgan, 2020).

Amazon, from a bookstore to the world’s largest online e-commerce platform Amazon is another highly recognised organisation, which attributes its phenomenal success to its ability to harness its customers’ needs and wants and focus on mass customisation (Yu, 2017), while keeping costs low through the use of artificial intelligence, digitisation and aggressive target segmentation. Amazon’s mission is to be Earth’s most customer-centric company. Their core belief is: “Leaders start with the customer and work backwards. They work vigorously to earn and keep customer trust. Although leaders pay attention to competitors, they obsess over customers.” With over 2.45 billion visitors to their site per month, Amazon creates a personal ‘feel’ through the use of artificial intelligence and deep learning techniques, used to provide: A homepage that seems to be especially designed for each user Product recommendations using the ‘Customers who bought’ widget Purchase options based on products that have been viewed, bought, rated or reviewed in the past ‘Discovery’ - showing people items they are most likely to buy and may be unlikely to discover on their own. Amazon’s intense focus has led to their becoming the world’s leading online retailer, with growth of 15% in revenue over the last year.

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E n h a n c i n g t h e p r o v i s i o n o f pat i e n t- c e n t r e d c a r e . . . [ 5 ]

The Mayo Clinic, redefining and elevating the concept and delivery of care Another noteworthy example of a customer-centric organisation is the Mayo Clinic, which has consistently been ranked as one of the best hospitals in the world (Farrugia, 2021). It has built its reputation on its ability to deliver healthcare services in a patient-centric manner. According to its president, Dr Anton Decker, “The entire organisation is laser-focused on patients’ wellbeing and their experience, from the cleaners, to the administrators, to the CFO, to the physicians, everyone." (KPMG, 2021). The group has intentionally created a system that fosters collaboration between different components of the organisation, to ensure that the patient has a seamless experience. They have developed their processes and systems, and selected and trained their people, with this single goal in mind. Patient care is organised around the patient’s needs rather than the clinician's or hospital’s. They have embedded this culture into the organisation through a cleverly designed system of visual and experiential clues, which reinforces the message that the ‘patient comes first’. The combination of these various initiatives has resulted in very high levels of brand recognition, patient satisfaction and customer loyalty (Berry and Bendapudi, 2003).

Customer-centricity based on convenience, customisation and care As can be seen from above, leading companies in different sectors across the world have converged on three common aspects of customer-centricity – convenience, customisation and care: Convenience is related to how, where and when products and services are accessed by the consumer: instantly or at a time that suits the consumer face-to-face, virtually or hybrid through multi-channels with ease, speed and minimal effort Customisation makes a generic offering more specific to the preferences and needs of the individual: messaging adjusted to age, gender, profession or other defining characteristics tailoring a product or service to the individual’s preferences providing ‘soft’ features or services, such as personal attention, thanking your clients and engaging frequently, which creates a feeling of 'being unique or special’ for a customer Care is the deliberate act and overt demonstration of empathy in every interaction and touch-point that the customer has with the business: actively and openly listening to the customer’s needs addressing their concerns as a priority investing time and effort to build relationships. In the delivery of healthcare services and products, the ‘customer’ is the patient and their family. In the medical scheme environment, the principal member and their dependents are the clients. The three attributes, convenience, customisation and care, are deeply relevant and critically linked to their experience and the eventual outcome of care. While pockets of clinical and service excellence do exist, these attributes are not embedded across the healthcare system and are not provided consistently between the different components of care (Maphumulo and Bhengu, 2019).

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[ 5 ] E n h a n c i n g t h e p r o v i s i o n o f pat i e n t- c e n t r e d c a r e . . .

A medical condition is now understood to be far more than just a biological challenge – sickness has a deep impact on the psychological, behavioural, economic and social state of a person, and often their family too (World Health Organization, 1948). Patients with complex diseases, multiple comorbidities or conditions that have a social stigma are particularly vulnerable to a lack of patient-centricity in the access and delivery of their care.

Patient-centricity in the medical scheme sector in South Africa South Africa spends more on private health insurance, as a percentage of total health expenditure, than almost any other developing country (NDoH, 2011), but this covers fewer than nine million beneficiaries or approximately 16% of the population (CMS, 2021). Despite this high level of expenditure on a relatively small population base, the level of privately insured member satisfaction is performing ‘below par (SAcsi-Consulta, 2020). Patient value = (quality * service) / affordability In an industry that sells a product that is often considered a grudge purchase (Bateman, 2012), the member’s perception of value is a direct function of quality and service, and indirectly related to affordability: Quality depends on the product design, access to benefits, network management, and the effectiveness, efficiency, equity, responsiveness and safety of care Service depends on the ability to manage the membership’s needs, respond to queries, streamline authorisation and claims processes, provide additional value, and extract optimal service from healthcare provider networks Affordability is critically dependent on the management of both healthcare and non-healthcare expenditures. Fraud, waste and abuse also need to be managed carefully. These key elements of patient value do not come together spontaneously – intervention is required. A structural framework is required to put the patient at the centre of their own care, create meaningful channels of communication and collaboration, and optimise the delivery of care.

Common medical scheme member concerns The 2019 South African Customer Satisfaction Index (Geldenhuys, 2020) showed that members have high expectations of their schemes and their overall levels of satisfaction and price tolerance are decreasing. Of note, the satisfaction levels for medical schemes are lower than for other financial services. It was found that individuals are struggling with the complexity of industry jargon, scheme rules and benefit options. Members think that premiums are too high for the quality of cover offered and their key complaints are related to account fees and charges, issues with claims or cover, inadequate feedback and long waiting times.

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E n h a n c i n g t h e p r o v i s i o n o f pat i e n t- c e n t r e d c a r e . . . [ 5 ]

Common consumer complaints are related to (Hellopeter, no date): Healthcare benefits Out-of-pocket payments Communication Customer service Response to queries Claims processes Affordability and value. The Ask Africa Orange Index 2020, looking at the customer experience within the medical scheme industry, identified that First Call Resolution (FCR), trust, customer effort, fairness, reputation and emotional satisfaction are critical drivers of customer-centricity and customer satisfaction (De Beer and Richards, 2021).

The COVID-19 pandemic has amplified existing fault lines The pandemic has significantly impacted the member experience and levels of satisfaction. Affordability concerns have been intensified, amidst other challenges, with an increased burden of disease due to mental health and other concomitant conditions. Delays in access to treatment, fears about utilising healthcare services, the move to the virtual and hybrid environments, and bereavements or prolonged suffering due to COVID-19 are all contributing to members’ lowered perception of value (SAcsi-Consulta, 2020). Patients often see their medical schemes and providers as faceless, uncaring and inaccessible. Never before has it been more important for the medical scheme sector to pause and hold up the mirror. Patient-centricity needs to be defined, unpacked and embedded in every instance and interaction throughout the funding environment, from the discussions that are held by the leadership and boards of schemes to the strategy designed by the executives of funder organisations, and finally to the delivery of service by the frontline teams in the administrative services.

Enhancing the provision of patient-centred care PPSHA have developed a bespoke programme for their client KeyHealth, which has been designed to enhance the provision of patient-centred care to their members. The model is based on the understanding that medical scheme members are a specific subset of consumers and that patients are a specific subset of the members (PPSHA, 2021). They have noted that while there may be many similarities between their needs and preferences, patients have a heightened need for confidence, communication, information, education and support throughout their engagements with the system. Medical schemes need to purposefully provide or contract with their administrators and healthcare service providers to embed patient-centricity into the delivery of services. Based on the PPSHA model, it is noted that the ethos of 'putting the patient first’ needs to permeate every aspect of the organisation from the strategy to the structure to the operations. The full set of interventions per component of the organisation are demonstrated in the Table 1, on the next page.

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[ 5 ] E n h a n c i n g t h e p r o v i s i o n o f pat i e n t- c e n t r e d c a r e . . .

Table 1. Organisation-wide interventions: Component

Intervention

Strategy

Develop and implement a strategy that makes patient-centricity a core organisational goal, which is cascaded down into the key performance indicators for each team and every employee

Structure

Design the organisational structure to facilitate cross-divisional engagements, remove the ‘silo’ effect and create accountability across and between teams, with a joint focus on improving the member and patient experience

Oversight

Manage the oversight structures related to governance, risk and compliance to ensure that the rights of the member and patient are recognised, monitored and evaluated

Products

Intentional benefit and product design to optimise benefits, service delivery and care coordination, including preventative healthcare

Processes

Enhance core process such as membership management, query resolution and claims processing to allow for ease of interactions, timeous feedback and improved member satisfaction

Providers

Network management and value-based contracting to align incentives with providers, encourage integrated care and the practice of evidence-based medicine

Services

Focus pharmaceutical, disease and hospital case management to be accessible and responsive to patient and family needs

Technology

Provide engaging member app and web interfaces with rich content and multi-purpose functionality

Communications

Simplify information and communication, remove jargon and use language, imagery and content that are relevant to a diversified audience

Innovation

Partner with other market-leading companies to leverage core capabilities to enable more potent engagements with members, e.g. InQuba and Brandmed

People

Recruitment, training and performance management of staff designed to build a workforce that lives and breeds patient-centricity as part of its DNA

From the preceding table, it is clear that the PPSHA/KeyHealth patient-centricity model is an organisational mindset, which places members and patients at the core of the ecosystem. The member’s experience is intentionally designed and driven from the leadership of the scheme to the frontline of the administrator. Every person understands their role, how they interface with the member and how they need to prioritise the patient experience to deliver excellence.

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E n h a n c i n g t h e p r o v i s i o n o f pat i e n t- c e n t r e d c a r e . . . [ 5 ]

Embedding patient-centricity in the care economy ‘Convenience, customisation and care’ are the three critical pillars of delivering patient-centric care and services to medical scheme members. They improve the perception of value by driving better quality, greater levels of service and more affordable medical scheme cover. Patients are so much more than ICD10 and CPT codes. Everyone who has the privilege to work in healthcare must identify with the nobleness of the profession and adhere to the highest standing in their individual and joint commitments, to enhancing the delivery of patient-centricity in their daily duties, their team’s function and their organisation’s mandate.

“

Everyone who has the privilege to work in healthcare must identify with the nobleness of the profession and adhere to the highest standing in their individual and joint commitments, to enhancing the delivery of patient-centricity in their daily duties, their team’s function and their organisation’s mandate.

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[ 5 ] E n h a n c i n g t h e p r o v i s i o n o f pat i e n t- c e n t r e d c a r e . . .

References Bateman K. 2012. Medical aid system: Change way overdue. South African Medical Journal; 102(3). Available at: http://www.samj.org.za/index.php/samj/article/view/5693/3905 Council for Medical Schemes. 2021. Annual Report 2020/21: Regulating through a pandemic. Available at: https://www.medicalschemes.co.za/cmsannual-report-2020-21/ De Beer S, Richards, A. 2021. Customer experience within the medical aid industry. Available at: https://www. askafrika.co.za/customer-experience-within-the-medical-aid-industry/ Berry L, Bendapudi N. 2003. Clueing In customers, Harvard Business Review; February: 1646-1660. Available at: https://hbr.org/2003/02/clueing-in-customers Farrugia G. 2021. Quality and Mayo Clinic, Mayo Clinic. Mayo Clinic. Available at: https://www.mayoclinic.org/ about-mayo-clinic/quality/rankings#:~:text=Mayo Clinic has always ranked,%22Best Hospitals Honor Roll.%22 (Accessed: 16 February 2022). Frankenfield J. 2021. Client-Centric, Investopedia. Available at: https://www.investopedia.com/terms/c/clientcentric.asp (Accessed: 16 February 2022). Geldenhuys J. 2020. South African Customer Satisfaction Index – Who got the most “likes” in the life industry? Moonstone. Available at: https://www.moonstone.co.za/south-african-customer-satisfaction-index-who-gotthe-most-likes-in-the-life-industry/. (Accessed: 16 February 2022). Hellopeter. No date. Compare medical aid companies on Hellopeter. Available at: https://www.hellopeter.com/ industries/medical-aid (Accessed: 26 February 2022). KPMG. 2021. Patience for patient-centricity. Available at: https://home.kpmg/xx/en/home/insights/2021/06/ patience-for-patient-centricity.html (Accessed: 16 February 2022). Maphumulo WT, Bhengu BR. 2019. Challenges of quality improvement in the healthcare of South Africa postapartheid: A critical review. Curationis: 42(1): 1-9. doi: 10.4102/curationis.v42i1.1901. Morgan B. 2020. 25 of the most customer-centric companies from 2020. Forbes. Available at: https://www. forbes.com/sites/blakemorgan/2020/12/21/25-most-customer-centric-companies-2020/?sh=65ffbdfa884b (Accessed: 16 February 2022). National Department of Health (South Africa). 2011. National Health Insurance in South Africa: Policy paper. Department of Health. Available at: https://www.gov.za/sites/default/files/nationalhealthinsurance.pdf PPSHA. 2021. Patient-centric approach model; South Africa; Available at: https://ppsha.co.za/ SAcsi-Consulta 2020. Covid-19 ups the customer satisfaction stakes and expectations from medical schemes. Available at: https://blog.consulta.co.za/covid-19-ups-the-customer-satisfaction-stakes-and-expectations-frommedical-schemes/ (Accessed: 16 February 2022). World Health Organization. 1948. Constitution of the World Health Organization. (Online). Available at: https:// apps.who.int/gb/bd/PDF/bd47/EN/constitution-en.pdf?ua=1 (Accessed: 16 February 2022). Yu Y. 2017. Amazon: From a book store, to the everything store, to running the Internet. Harvard Business School. Available at: https://digital.hbs.edu/platform-digit/submission/amazon-from-a-book-store-to-theeverything-store-to-running-the-internet/ (Accessed: 17 February 2022).

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Capitation models in sub-Saharan Africa: A systematic review AUTHOR Moyo Roland

PEER REVIEWER: Jodi Wishnia

ABSTRACT Access to quality healthcare, whether preventative or curative, remains a prerequisite for a population to attain health and achieve wellbeing. Despite all global agreements on arresting the continuous rise in healthcare costs, access to essential health services still depends on fee-for-service models and/or out-of-pocket payments (OOPs) in some lower- and middle-income countries. Such access barriers work against the 2030 Agenda for Sustainable Development, which requires that all have access to healthcare services without suffering any financial hardships. Healthcare costs are constantly increasing in sub-Saharan Africa (SSA), making it difficult for individuals and communities to access quality healthcare without suffering financial hardship. Healthcare costs need to be contained to promote equity in access. Cost-containment remains a major challenge to the viability and sustainability of private healthcare funders. Within current global debates on strategic purchasing, the capitation model is promoted as a preferred provider payment mechanism that can contain costs and is set to replace the fee-for-service reimbursement models, with shared accountability for patients' healthcare outcomes. This systematic review aims to review various reimbursement models, especially capitation models, in SSA within the published literature and summarise potential learnings and strategies for ensuring their success. A systematic review was conducted aligned with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines. PubMed, Web of Science, Global Health Database, the Cochrane Library and Scopus were searched for literature published. Evidence was synthesised in the form of a table and thematic analysis. The results indicate that most healthcare funding models in SSA are based on direct OOPs, but there is some evidence of the use of capitation models in primary healthcare.

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[ 6 ] C a p i t a t i o n m o d e l s i n s u b - S a h a r a n Af r i c a

Introduction Value-based reimbursement models are key in moving towards universal healthcare coverage (UHC) in SSA. UHC is firmly grounded on the 1948 World Health Organization (WHO) constitution, which declares that health is a fundamental human right and commits to ensuring the highest attainable level of health for all. The disease burden in SSA is growing, in respect of both infectious and non-communicable diseases, which is putting a strain on the region’s healthcare spending. The WHO (2020) reported that between 2000 and 2018 global health expenditure reached USD8.3 trillion or 10% of global gross domestic product (GDP). McIntyre et al (2018) proffered in their review article that SSA relies heavily on OOPs, approximately 36% of current health expenditure. This is higher than in all other regions in the world, where OOPs account for 22% of current health expenditure (WHO, 2014). Protection against financial hardships that can arise due to accessing health is generally low; citizens pay for health services from their own household income (Asante, Wasike & Ataguba, 2020). The situation is made worse by low government spend on healthcare, which results in poor quality outcomes. Where a private sector exists, access is limited to those who can afford to pay for healthcare (Beogo et al, 2016). The authors further postulate that health spending per capita in lowincome countries averaged USD110 in 2015 compared with USD5,551 in high-income countries. Patients in low-income and lower-middle-income countries are less protected against high OOPs than those in highermiddle-income countries (WHO, 2010; Chang et al, 2019). In SSA, OOPs increased from USD15 per capita in 1995 to USD38 in 2014 (International Monetary Fund, 2016). It is estimated that 11 million Africans are falling into poverty and do not access quality health services due to poor-quality public health systems and/or high OOPs (World Bank, 2016).

Definitions The UHC concept has gained prominence in the health systems agenda in SSA in response to the 2030 Agenda for Sustainable Development goal of access to healthcare services by all without suffering any financial hardship. In this discussion, the capitation payment method has been highlighted as a key lever in costcontainment and quality healthcare outcomes (Rajkumar, 2014; James & Poulsen, 2016). Capitation is a prospective provider payment mechanism in which a flat payment per person is predetermined and paid to a provider to cover a defined benefit package of services for all persons registered under the provider over a given period of time (Atuoye et al, 2016; Obadha, 2019; Abiiro, Alatinga & Yamey, 2021). The capitation model is a potential cost-containment tool for providing services to high-risk populations like those within SSA with a high disease burden. Scholars hold the view that a capitation approach provides a motivation for healthcare service providers to deliver care in a cost-effective manner. New Zealand has made a strategic shift towards a capitation payment model and this has brought a fundamental change to the country’s primary healthcare reforms (Volmink et al, 2014). Blomqvist & Busby (2012) opine that this reimbursement model works best if there is already a working relationship between the service provider and the patient and that the model is geared mainly to primary care service providers rather than specialists. Unlike a fee-for-service payment model, capitation creates incentives for healthcare providers to control costs and improve efficiency but may result in the under-provision of services if quality is not actively monitored (Brocklehurst et al, 2013; Cashin, 2015).

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C a p i t a t i o n m o d e l s i n s u b - S a h a r a n Af r i c a [ 6 ]

Methods and search strategy The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines were used in this study. PubMed, Web of Science, Global Health Database, the Cochrane Library and Scopus were searched for literature published between 2012 and 2021. The focus on this period was motivated by key global developments in the healthcare agenda, although the debates on the concepts themselves date back to the 18th century. In 2012 the United Nations General Assembly endorsed a resolution on global health and foreign policy aimed at ensuring that everyone everywhere has access to quality and affordable healthcare. Furthermore, the period is important as the 2030 Agenda for Sustainable Development adopted the target of UHC by 2030, including financial risk protection and access to quality essential healthcare services.

Study selection and eligibility Only papers written in English were considered because of cost and language resource constraints. The targeted publications were mainly those originating from Africa, although reimbursement payment models used on other continents were also scrutinised. The key terms used in the search were fee-for-service, OOPs, healthcare, capitation, access and reimbursement. The titles and abstracts were reviewed. Studies included are those that address provider payment methods, particularly capitation methods. Articles focused on a particular area of healthcare like dentistry only were excluded. Comprehensive articles were chosen; those that were inaccessible were removed.

Data extraction Data extraction was performed using a literature summary table. Peer-reviewed articles, non-peer reviewed articles and conference papers written in English were considered.

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2021

Abiiro, Alatinga &

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P U B L I S H E D B Y T H E B O A R D O F H E A LT H C A R E F U N D E R S

service

ing in outpatient

evaluation

resource setting:

payment mechanisms

ences of health

care providers

ees in their capitation pool

mechanisms

not because providers did not have information on the number of enrol-

Insurance Fund (NHIF)

and fee-for-service

capitation funds from NHIF were

insurers were predictable, while

amounts from NHIF and private

expected fee-for-service payment

perceived as inadequate. The

Capitation payment rates were

these policies

that threatens the sustainability of

increase in medical expenditures

these elements may generate an

and cost-control measures because

to the provider payment method

tries; greater attention must be paid

Cost-reduction policies in SSA coun-

evidence

uncertain due to very low‐certainty

methods on health outcomes are

The effects of changes in payment

torates

provider payment

accredited by the National Hospital

members in six health providers

interviews with 29 management team

were collected using semi-structured

study in two counties in Kenya. Data

The authors conducted a qualitative

facilities (CSPS, MCs and hospitals)

the strata were the types of health

fied sampling was conducted, where

Experimental study, multistage strati-

Systematic literature review

with capitation

service; provider

Kenya: Experi-

capitation; fee-for-

Barasa E

Health care

study Attributes; Kenya;

health policy; policy

ditures in a low-

a paired pre-post

evaluation; exemption mechanisms;

oping countries;

method for health

medical expen-

ing; costs; devel-

tive payment

facilities on direct

Health financ-

Effect of a prospec-

GA, Beck MJ,

2019

Obadha M, Chuma

outpatient, fee-for-

providers work-

purchasing in

2020

Meda et al

payment method,

ods for healthcare

healthcare settings

Capitation,

nity-level policy beneficiaries

policy analysis

Payment meth-

focus group discussions with commu- providers and opposition party elec-

A regional level

as a strategy to punish fraudulent

cally negative reframing of the policy

health benefits resulted in a politi-

less attention on portraying its

district level policy actors and four

2019 in the Ashanti region through

collecting field data in December 18 interviews with regional and

level, Ghana

tation payment

a cost-containment strategy with

Technically framing capitation as

Key Findings

policy agenda?

analysis, regional

insurance capi-

tive qualitative policy analysis by

The authors conducted a retrospec-

Methodology

model fall off the

capitation, policy

Provider payment,

Key Words

national health

Why did Ghana’s

Title

J, Kazungu J, Abiiro

2021

Jia et al

Yamey

Year

Author (s)

[ 6 ] C a p i t a t i o n m o d e l s i n s u b - S a h a r a n Af r i c a

2016

Atuoye et al

2018

Andoh-Adjei et al

2017

2019

Obadha et al

Yuan et al

Year

Author (s) choice experiment; provider payment mechanism; strategic purchasing

ers for capitation

payment in Kenya:

a discrete choice

where both the intervention and control groups are selected without random assignment

Scheme: a cross-

sectional study of

three regions in

policy; health; health insurance

access and qual-

ity in a challenged

scheme in Ghana

debate in Ghana

lenges facing the health insurance

which reflect broader systemic chal-

insurance claims payment systems,

implementation of earlier health

debate stems from challenges in

capitation policy

literature

making and health insurance

situate the debate within policy-

mentary proceedings; the authors

The ongoing capitation payment

examination of the

health system: an

analysis; Ghana;

ability versus

(very low-certainty evidence) Content analysis of public and parlia-

mixed systems Capitation; content

fee for service;

facilities

Financial sustain-

and costs of services were uncertain

mance; capitation;

for outpatient care

to fee-for-service on the utilisation

Pay for perfor-

The effects of capitation compared

control costs in healthcare delivery

for primary outpatient care to

tion a key provider payment method

therefore, want to consider capita-

Payment methods

Systematic literature review

lar approach to quasi-experiments

Ghana

according to Creswell, is a popu-

Health Insurance

and post-test control group design

used a non-equivalent pre-test

under National

health insurance

utilisation and

can be used to configure UHC

used in the analysis

Health policymakers in Ghana may,

authors conclude that capitation

logit and latent class models were The study was cross-sectional and

health services were preferred. The

those that paid for a limited set of

rates per individual per year and

lier disbursements, higher payment

counties. Panel mixed multinomial

health facilities in seven Kenyan

health facility managers across 98

data were collected from 233 senior

(before and after study) which,

care services;

tion payment on

Capitation arrangements with

Key Findings

cient experimental design, and choice frequent payment schedules, time-

The authors used a Bayesian effi-

Methodology

claims expenditure

Capitation; health-

Effects of capita-

experiment

Capitation; discrete

healthcare provid-

Key Words

Preferences of

Title

C a p i t a t i o n m o d e l s i n s u b - S a h a r a n Af r i c a [ 6 ]

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P U B L I S H E D B Y T H E B O A R D O F H E A LT H C A R E F U N D E R S

2013

insurance

type 2 diabetes in

Chirwa,

national health

management of

2013

diabetes mellitus;

tion model to the

Robyn et al

effectiveness;

sector capitaintervention and a usual prac-

P U B L I S H E D B Y T H E B O A R D O F H E A LT H C A R E F U N D E R S

2 0 2 1 SOU T H ERN AFRICAN H E A LT H JO UR N A L the research questions and was conducted in five CHAM health facilities. National and district level decision-makers were interviewed while provid-

facilities to expand

access-lessons

learned from

Malawi

surveyed on their experiences

with the health facilities were

ers and clients associated

research methods to address

faith-based health

Thomas

sal healthcare

tion: contracting

Faedo &

qualitative and quantitative

sal financial protec- agreement, univer-

The study employed both

to January 2010

Kazanga,

Promoting univer-

review

Equity, service level

systematic review

developing counoping countries published up

methods used by CBI in devel-

tries: a systematic

ature on provider payment

oping country,

systematic review of the liter-

The authors conducted a

tice model as the comparator

ance schemes in

ance, third-party

in community-

intervention to be cost-effective, with an ICER of

Probabilistic modelling found the capitation

Key Findings

and material resources

parency, poor communication, inadequate human

revised prices, late payment of bills, lack of trans-

factors including lack of clear guidelines, non-

mance of SLAs in Malawi were affected by various

tions. However, the findings show that the perfor-

particularly for vulnerable and underserved popula-

SLAs have the potential to improve health and UHC,

provided and provider and patient retention

faction with CBI, quantity and quality of services

for CBI, population enrolment and patient satis-

mance through provider participation and support

suggests that provider payment impacts CBI perfor-

tation and 6 applied a co-insurance. The evidence

salaries, 9 applied a coverage ceiling, 7 used capi-

the CBI schemes: 17 used fee-for-service, 12 used

Various types of provider payment were applied by

sector model of the DMP as the ZAR8,356 (USD1,018) per LYG

was undertaken with a public

Cost-effectiveness analysis

Methodology

based health insur- payments, devel-

Health insur-

Provider payment

analysis

cost-effectiveness

public sector: a

the South African

Capitation; cost-

2014

Volmink et al

Key Words

Applying a private

Year Title

Author (s)

[ 6 ] C a p i t a t i o n m o d e l s i n s u b - S a h a r a n Af r i c a

C a p i t a t i o n m o d e l s i n s u b - S a h a r a n Af r i c a [ 6 ]

Equity, service level agreement, universal healthcare The study employed both qualitative and quantitative research methods to address the research questions and was conducted in five CHAM health facilities. National and district level decision-makers were interviewed while providers and clients associated with the health facilities were surveyed on their experiences. SLAs have the potential to improve health and UHC, particularly for vulnerable and underserved populations. However, the findings show that the performance of SLAs in Malawi were affected by various factors including lack of clear guidelines, non-revised prices, late payment of bills, lack of transparency, poor communication, inadequate human and material resources

Assessment of study quality The study quality assessment tool utilised was adopted from Hawker et al (2002). It contains nine questions (e.g. Is the abstract clear?, Does the background state the aims of the study well?, Is the method clearly explained?, Are the findings transferrable to a wider population?), each of which can be answered ‘good’, ‘fair’, ‘poor’ or ‘very poor’.

Results A total of 1,660 records were identified from the databases. Fifty duplicates were removed, and the remainder assessed based on their titles and abstracts. The exclusion criteria were publications older than 2012, topics not relevant to the aim of the paper, and articles without sufficient information regarding methodology source. This resulted in 1,022 selected with a further 746 removed after the papers in question had been read in full. Data were extracted from the 15 references and three reports (WHO, World Bank and IMF) as shown below:

Figure 1. PRISMA 2020 flow diagram for new systematic review which included searches of databases, registers and other sources

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[ 6 ] C a p i t a t i o n m o d e l s i n s u b - S a h a r a n Af r i c a

Key findings Cost-containment The review established that the capitation payment model is a cost-containment mechanism (Andoh-Adjei et al, 2016; Etiaba et al, 2018). In Ghana, an earlier study by Carrin & Hanvoravongchai (2003) stated that there is no direct link between capitation and cost-containment. Moreover, the authors recommended that health policymakers in Ghana may, therefore, consider capitation a key provider payment method for primary outpatient care to control costs in healthcare delivery. Ochieng (2019) concluded that a capitation payment model is a cheaper form of insurance than fee-for-service in Kenya. The findings also corroborate those of a study on capitation payments for primary outpatient services in China, which found a positive effect in controlling costs of healthcare services (Sun et al, 2016).

Quality of care Divergent views emerged in respect of whether a capitation payment method improves healthcare equality. Capitation was found to encourage better standardisation of care and improvement in clinical outcomes alongside cost reduction (Atuoye et al, 2016). It was noted that physicians receiving capitation payments administered fewer medications to chronic patients and used less expensive health personnel, such as generalists to manage specialist conditions and nurse-aides rather than nurses to provide care for capitated insured clients (Abiiro, Alatinga & Yamey, 2021).

Capitation vs fee-for-service Capitation and fee-for-service are two contrasting systems for paying healthcare providers. Studies comparing them suggest that capitation has a natural advantage in invoking selection and ensuring the superior health of patients through risk profiling and lower costs (Robyn et al, 2013). A review in primary care demonstrated that fee-for-service was associated with more patient visits, specialist referrals and increased use of diagnostic and curative services (Ochieng, 2019). Capitation models have been shown to be cheaper than fee-for-service in providing all-inclusive healthcare. Most evidence in this regard originates from Ghana and applies to its National Health Insurance Fund programme, where services to most service providers are now paid on a capitated basis. There is also evidence from a few smaller capitated providers in Nigeria. Compared to fee-for-service payments, capitated schemes were associated with prescription of more essential medicines (Slattery et al, 2013).

Discussion In SSA, the challenge of UHC is critical most especially to ensuring financial protection and access to healthcare. In this systematic review analysis, there are some examples of countries that use capitation for primary healthcare providers in SSA (Andoh-Adjei et al, 2018). Moreover, capitation is a cost-containment mechanism (Barasa et al, 2018). This is in line with the view of Volmink et al (2013), who posited that a capitation payment model proved to be cost-effective in their probabilistic modelling study. However, other scholars suggest that the capitation model does not translate to quality health outcomes (Abiiro et al, 2021). It only contains costs. Atuoye (2016) argues that that the implementation of a capitation model poses a lot of risk. It looks very good on paper, but there are challenges related to its application. Obadha et al (2019) proffered that capitation arrangements can be used in configuring UHC. Debates are evident in the literature, but there is a sense that this model offers value in primary healthcare service provision. More can still be done with regard to specialist services and hospitals. Fee-for-service is deterring access and there is thus a need for alternative value-based reimbursement models like capitation.

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Conclusion Most healthcare funding models in SSA involve direct OOPs and this limits access to healthcare services. Capitation models are used in primary healthcare services. The review affirms that capitation contains healthcare costs better than a fee-for-service payment model. Balance between quantity and quality is still an issue. UHC is the focus of many health systems but how services can be accessed equitably is still being debated. Studies have focused more on primary healthcare services; further studies are needed, particularly with regard to specialist services (e.g. physician and dental services) where the fees charged are higher.

References Abiiro, Gilbert & Alatinga, Kennedy & Yamey, Gavin. (2021). Why did Ghana's national health insurance capitation payment model fall off the policy agenda? A regional level policy analysis. Health Policy and Panning; 36(6): 869-880. Andoh-Adjei, F., Boudewijns, B., & Nsiah-Boateng, E., et al (2018a). Effects of capitation payment on utilization and claims expenditure under National Health Insurance Scheme: a cross-sectional study of three regions in Ghana. Health Economics Review; 8: 17. Asante, A., Wasike, W.S.K., & Ataguba, J.E. (2020). Health financing in Sub-Saharan Africa: From analytical frameworks to empirical evaluation. Appl Health Econ Health Policy; 18: 743-746. Atuoye, Kilian & Vercillo, Siera & Antabe, Roger & Galaa, Sylvester & Luginaah, Isaac. (2016). Financial sustainability versus access and quality in a challenged health system: An examination of the capitation policy debate in Ghana. Health Policy and Planning; 31(9): 1240-9. Barasa, E., Rogo,K., Mwaura,N., & Chuma, J. (2018). Kenya National Hospital Insurance Fund Reforms: Implications and Lessons for Universal Health Coverage. Health Systems & Reform, 4:4, 346-361. Beogo, I., Huang, N., & Gagnon, M.P., et al (2016). Out-of-pocket expenditure and its determinants in the context of private healthcare sector expansion in sub-Saharan Africa urban cities: evidence from household survey in Ouagadougou, Burkina Faso. BMC Research Notes; 9: 34. Blomqvist, A., & Busby, C. (2012). How to pay family doctors: Why ‘pay per patient’ is better than fee for service. CD Howe Institute Commentary. No. 365. Brocklehurst, P., Price, J., & Glenny, A.M., et al (2013). The effect of different methods of remuneration on the behaviour of primary care dentists. Cochrane Database of Systematic Reviews; 11: CD009853. Cashin, C. (2015). Assessing Health Provider Payment Systems: A Practical Guide for Countries Working Toward Universal Health Coverage. Joint Learning Network for Universal Health. Carrin, G., Hanvoravongchai, P. (2003). Provider payments and patient charges as policy tools for costcontainment: How successful are they in high-income countries? Hum Resour Health; 1(1): 6. Chang, A.Y., Cowling, K., & Micah, A.E. (2019). Past, present, and future of global health financing: a review of development assistance, government, out-of-pocket, and other private spending on health for 195 countries, 1995-2050. Lancet; 393(10187): 2233-2260. Chirwa, M.L., Kazanga, I., Faedo, G. et al . (2013). Promoting universal financial protection: contracting faithbased health facilities to expand access – lessons learned from Malawi. Health Res Policy Sys; 11: 27. Etiaba, E., Onwujekwe, O., Honda, A., Ibe, O., Uzochukwu, B., & Hanson, K. (2018). Strategic purchasing for universal health coverage: Examining the purchaser–provider relationship within a social health insurance scheme in Nigeria. BMJ Global Health; 3(5): e000917. Hawker, S., Payne, S., Kerr, C., Hardey, M., & Powell, J. (2002). Appraising the Evidence: Reviewing Disparate Data Systematically. Qualitative Health Research; 12(9): 1284-1299.

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[ 6 ] C a p i t a t i o n m o d e l s i n s u b - S a h a r a n Af r i c a

International Monetary Fund (IMF). (2014). “Macroeconomic Developments and Prospects in Low-Income Developing Countries: 2014.” IMF Policy Paper, Washington. International Monetary Fund (IMF). (2016). “Macroeconomic Developments and Prospects in Low-Income Developing Countries: 2016.” IMF Policy Paper, Washington. James,B., & Poulsen, G. (2016).The Case for Capitation. Harv Bus Rev; 94(7-8): 102-111, 134. Jia, L., Meng, Q., Scott A., Yuan, B., & Zhang L. (2021) Payment methods for healthcare providers working in outpatient healthcare settings. Cochrane Database System Review; 20: 1(1). McIntyre, D., Obse, A., Barasa, E., & Ataguba, J.E. (2018) Challenges in financing universal health coverage in sub-Saharan Africa. Oxf Rese Encycl Econ Finance. Meda, I., Kouanda, S., Dumont, A., & Ridde, V. (2020). Effect of a prospective payment method for health facilities on direct medical expenditures in a low-resource setting: a paired pre-post study, Health Policy and Planning; 35(7): 775-783. Obadha, M., Chuma, J., Kazungu, J., Abiiro, J., Beck, M., & Barasa, B. (2020). Preferences of healthcare providers for capitation payment in Kenya: a discrete choice experiment. Health Policy and Planning; 35(7): 842-854. Ochieng, T. B. (2019). A Comparison of capitation and fee for service provider payment mechanisms and their effects on cost of healthcare: A case study of the Avenue Hospital, Nairobi (Thesis, Strathmore University). Robyn, P.J., Sauerborn, R., & Bärnighausen, T. (2013). Provider payment in community-based health insurance schemes in developing countries: a systematic review. Health Policy Plan; 28(2): 111-122. Slattery, E., Clancy, K.X., Harewood, G.C., Murray, F.E., & Patchett, S. (2013). Does the cost of care differ for patients with fee-for-service vs. capitation of payment? A case-control study in gastroenterology. Ir J Med Sci; 182(4): 669-72. Volmink, H.C., Bertram, M.Y., Jina, R., Wade, A.N., & Hofman, K.J. (2014). Applying a private sector capitation model to the management of type 2 diabetes in the South African public sector: a cost-effectiveness analysis. BMC Health Serv Res; 14: 444. World Health Organization (2018). Public spending on health: a closer look at global trends. Geneva:WHO World Health Organization (2020). World health statistics 2020: monitoring health for the sustainable development goals. Geneva: WHO. Yuan, B., He, L., Meng, Q., & Jia, L. (2017). Payment methods for outpatient care facilities. Cochrane Database System Rev; 3: 3(3).

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AUTHOR INDEX A-Z Anuschka Coovadia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 KeyHealth administered by Professional Provident Society Healthcare Administrators (PPSHA), 2021 (5)

Craig Getz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Insight Actuaries and Consultants

Daniel Shapiro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Insight Actuaries and Consultants

Emma Finestone. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36, 46 Percept Actuaries and Consultants

Gareth Kantor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Insight Actuaries and Consultants (1)

Jodi Wishnia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36, 46 Percept Actuaries and Consultants

Karyna Pierce . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Government Employees Medical Scheme

Mabatlo Semenya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Government Employees Medical Scheme

Moyo Roland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 School of Finance and Professional Studies, Botswana Accountancy College, Gaborone, Botswana

Shivani Ranchod . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36, 46 Percept Actuaries and Consultants

Phumla Tsematse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Insight Actuaries and Consultants

Selaelo Mametja . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Government Employees Medical Scheme

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NOTES

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