DesIGnInG a health system for comorBIDIty

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.

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

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)

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).

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

% of population

70%

60%

50%

40%

30%

20%

10%

0% 62%

57%

53%

33% 35%

30% Total Male Female

10%

7% 12%

1% 0% 1% 0.01% 0% 0.01%

0 1 2 3 4 Number of chronic illnesses

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%

4.0%

3.5%

3.0%

2.5%

2.0%

1.5%

1.0%

0.5%

0.0% 3.53% 4.09%

1.21%

0.22%

2011 2012 2013 2014

Two simultaneous CDLs Three simultaneous CDLs

1.81%

0.42%

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

Diabetes Hypertension Cardiovascular incident Coronary disease Mental disorders Asthma Arthritis Any NCD PERCENTAGE OF THOSE wITH THE NCD THAT HAvE ONE OR MORE OTHER NCDS

85% 55% 92% 89% 66% 53% 85% 44%

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:

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).

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.

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.

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