Underinsurance of PhilHealth's MCP by Jemar Mapili

A Cross-Sectional Study on the Factors affecting Underinsurance among Women who have availed of the Philippine Health Insurance Corporationâ&#x20AC;&#x2122;s Maternity Care Package in Pasig City, Philippines

A Thesis Proposal Submitted to the Faculty of Health Sciences Program School of Science and Engineering Ateneo de Manila University

In Partial Fulfillment for the Requirements for the Degree Bachelor of Science in Health Sciences

Cabalquinto, Alvin S. Estanislao, Rafael Deo F. Ku, Kimberly L. Mapili, Jerahmeel Aleson M. Tang, Vincent Anthony S. Zaldarriaga, Jose Ma. H.

March 2, 2013

The Faculty of Health Sciences Program of Ateneo de Manila University accepts the undergraduate thesis proposal entitled:

On March 2, 2013 from Cabalquinto, Alvin S. Estanislao, Rafael Deo F. Ku, Kimberly L. Mapili, Jerahmeel Aleson M. Tang, Vincent Anthony S. Zaldarriaga, Jose Ma. H.

in partial fulfillment for the requirements for the degree of Bachelor of Science in Health Sciences

_____________________________ John Q. Wong, MD, MSc Faculty, Health Sciences Program

_____________________________ Anne Remonte, MD MDG Team Head, Health Finance Policy Sector, PhilHealth

____________________________ Mary Joy Aguilar Manager, Liza-Aguilar Racuya Lying-in Clinic

______________________________________ Genejane M. Adarlo, MD Thesis Adviser ______________________________________ NORMAN DENNIS E. MARQUEZ, MD Director Health Sciences Program Ateneo de Manila University

Abbreviations ANOVA- Analysis of Variance CBHI- Community-Based Health Insurance CHDMM- Center for Health Development-Metro Manila CSHN- Children with Special Healthcare Needs DOH- Department of Health DSWD- Department of Social Welfare and Development FHSIS- Field Health Service Information System GDP- Gross Domestic Product GSIS- Government Service Insurance System INGID- International Nursing Group for Immunodeficiencies ISQSH- Irish Society for Quality and Safety in Healthcare IPM- Individually Paying Member LGU- Local Government Unit LFS- Labor Force Survery MDG- Millennium Development Goal MCP- Maternity Care Package MMR- Maternal Mortality Ratio NCR- National Capital Region NEDA- National Economic and Development Authority NHIP- National Health Insurance Program NHTS-PR- National Household Targeting System for Poverty Reduction NSCB- National Statistical Coordination Board NSO- National Statistics Office OFW- Overseas Filipino Worker OWWA- Overseas Workers Welfare Administration PhilHealth- Philippine Health Insurance Corporation PMA- Philippine Medical Association PMCC- Philippine Medical Care Commission PMT- Proxy Means Test PSS- Patient Satisfaction Score PSQ- Patient Satisfaction Questionnaire SES- Socioeconomic Status SF-12- Short-Form-12 Health Survey SF-36- Short-Form-36 Health Survey SHI- Social Health Insurance SOU- Statement of Understanding SPSS- Statistical Product and Service Solutions SSS- Social Security System UN- United Nations UNDP- United Nations Development Program UNICEF- United Nations Childrens Fund WB- World Bank WHO- World Health Organization

Table of Contents

List of Tables List of Figures Abstract Chapter I – Introduction Statement of the Problem Objectives of the Study Hypotheses Significance of the Study Delimitations and Limitations of the Study Chapter II – Review of Related Literature Chapter III – Methodology Participants and Setting Data Collection Data Analysis Time Schedule Research Personnel Research Facilities Budget Requirements References Appendices Appendix A Means Test Appendix B Short-Form-12 Health Status Survey Appendix C Patient Satisfaction Questionnaire Appendix D Letter for Maternity Clinics Appendix E Statement of Understanding Appendix F Map of Pasig City showing the 17 PhilHealth-accredited birthing and lying-in clinics offering the MCP

i ii iii 1 1 1 3 7 8 9 33 34 36 44 48 49 50 51 55 61 61 62 65 73 74 75

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP List of Tables Table 1. Hypotheses for Bivariate Data Analysis

Table 2. Hypotheses for Multivariate Data Analysis

Table 3. PhilHealth-accredited birthing and lying-in clinics offering the MCP in Pasig City, Philippines

Table 4. Bivariate data analysis and encoding

Table 5. Multiple linear regression data encoding

Table 6. Time schedule for Jan to Mar 2013

Table 7. Time schedule for Apr to Jun 2013

Table 8. Time schedule for Jul to Sept 2013

Table 9. Time schedule for Oct to Dec 2013

Table 10. Time schedule for Jan to Mar 2014

Table 11. The 17 PhilHealth-accredited birthing and lying-in clinics offering the MCP in Pasig City, Philippines

Table 12. Breakdown of budget for thesis work

Table 13. Budget for personnel training and incentives

Table 14. Budget for materials and equipment

Table 15. Budget for gasoline consumption

Table 16. Budget for tricycle rides

Underinsurance among Women who have availed of PhilHealth’s MCP List of Figures Figure 1. The three dimensions in achieving and evaluating universal coverage

Figure 2. Bashshur, Smith, and Stiles’ three conceptual definitions for underinsurance (Ward, 2006)

Figure 3. Alternative framework to Bashshur, Smith, and Stiles’ classification scheme for underinsurance

Figure 4. Conceptual Framework

Figure 5. Research Design of the Study

Figure 6. Methodological Flow of Pre-Testing the Survey Tool

Figure 7. Methodological Flow of Implementation of Revised Survey Tool

Underinsurance among Women who have availed of PhilHealth’s MCP ABSTRACT Objective: This study will seek to identify the prevalence and the factors that can affect underinsurance among women who have availed of the Philippine Health Insurance Corporation’s (PhilHealth) Maternity Care Package (MCP) from April to November of 2013 in Pasig City, Philippines. Design: A Cross-sectional design is used. Both Benefits and Economic dimensions of underinsurance are studied and varied combinations of Underinsured and Adequately insured claimants according to the two dimensions are considered. Setting: PhilHealth-accredited maternity clinics offering the MCP in Pasig City, an urban municipality located in the Philippines’ National Capital Region (NCR), comprise the study’s setting. Participants: All women who will be filing their claims for the MCP from May to November of 2013 in PhilHealth-accredited maternity clinics in Pasig City are eligible to be study participants. The minimum sample size calculated is 118. Observations: A survey tool will be administered to women once they availed of the MCP in the PhilHealth-accredited maternity clinics of Pasig City to measure their patient satisfaction and collect information on certain demographics. Outcome Measures: The study’s outcome measure is patient satisfaction which will be the basis for categorizing the MCP claimant as underinsured or adequately insured. Data Analysis: The study’s minimum sample size was calculated by factoring in the following input variables: (1) number of predictor variables, (2) anticipated effect size (f2), (3) desired statistical power level (1-β), and (4) probability level. Both descriptive and analytical tests will be used. With the number of predictors set at 10, the anticipated effect size (f2) set at 0.15, the desired statistical power level (1-β) set at 0.80, and the probability level set at 0.05, the software Statistics Calculators: A Priori Sample Size Calculator for Multiple Regression Studies calculated the minimum sample size of this study to be 118. Descriptive statistics such as frequency tables, distribution graphs, mean, median, and mode will be generated to have an overview of the data. To dig deeper, the Pearson correlation, one-way ANOVA, and two independent samples t-test will be used to test for significance of each of the independent variables. In addition, a multiple linear regression model will be used to show the relationship of the independent variables to the dependent variable after accounting for all the other independent variables. Conclusions: Women who are unsatisfied with the MCP are to be considered underinsured. Depending on the results of the study, the independent variables found to have a significant association and/or are found to be significant predictors of underinsurance will be reported.

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Underinsurance among Women who have availed of PhilHealth’s MCP CHAPTER I INTRODUCTION Two years ago, 221 out of 100, 000 mothers in the Philippines died from childbirth complications – the highest it has been since ten years prior. This is a step away – indeed, a reversal of gains – from the Millennium Development Goal (MDG) of reducing the maternal mortality ratio to a quarter of what it was in 2000. The country still struggles to achieve that goal, even as the deadline – 2015 – draws near. The Philippine Health Insurance Corporation (PhilHealth) is one of those struggling to achieve the MDG. This government-owned and controlled corporation provides Social Health Insurance (SHI) to help give mothers access to quality health care. One of PhilHealth’s benefit packages is the Maternity Care Package (MCP) which covers costs for delivery, prenatal and postpartum care, newborn care, and family planning counselling. The MCP is one way through which PhilHealth pushes the country toward attainment of the MDG. PhilHealth is mandated to achieve universal health coverage and, in so doing, can provide mothers access to services and facilities that will ensure their health. Mere enrolment, however, is insufficient. It is possible that a mother may be insured but the services covered by the insurance are insufficient, forcing the mother to pay for some. This situation is called underinsurance. However, the opposite- all services for free – is likewise undesirable and can lead to inequity. Adequate, not excessive nor inadequate, coverage is needed to ensure that there is no underinsurance, and consequently, less loss of life. How the MCP is to be made adequate depends a great deal on patient satisfaction, which in this case is the mother’s satisfaction. Thus, this study aims to determine the prevalence of underinsurance as well as the factors that could affect underinsurance among PhilHealth members who avail of the MCP. An analysis of patient satisfaction with the package will identify this prevalence and these factors that could serve as significant predictors of underinsurance. This will, hence, lead ultimately to a redesigned MCP – a better tool towards the attainment of the MDG. Statement of the Problem What can affect underinsurance among women who have availed the Philippine Health Insurance Corporation’s (PhilHealth) Maternity Care Package (MCP) from April to November of 2013 in Pasig City, Philippines? Objectives of the Study General Objective To determine what can affect underinsurance among women who have availed the Philippine Health Insurance Corporation’s (PhilHealth) Maternity Care Package (MCP) from April to November of 2013 in Pasig City, Philippines

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP

Specific Objectives 1. To determine the prevalence of underinsurance as measured through patient satisfaction among women who have availed the MCP from April to November of 2013 in Pasig City, Philippines 2. To determine whether a significant association exists between the following factors and underinsurance among women who have availed the MCP from April to November of 2013 in Pasig City, Philippines: a. Predisposing Factors i. Age ii. Educational Attainment iii. Civil status b. Enabling Factors i. Income ii. Length of membership in health insurance firm iii. Beneficiary type iv. Familiarity with benefits v. Membership Type c. Perceived Health Status i. Physical health status ii. Mental health status 3. To determine whether the following factors are significant predictors of underinsurance among women who have availed the MCP from April to November of 2013 in Pasig City, Philippines: a. Predisposing Factors i. Age ii. Educational Attainment iii. Civil status b. Enabling Factors i. Income ii. Length of membership in health insurance firm iii. Beneficiary type iv. Familiarity with benefits v. Membership Type c. Perceived Health Status i. Physical health status ii. Mental health status

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP Research Hypotheses Table 1. Hypotheses for Bivariate Data Analysis HYPOTHESES FOR BIVARIATE DATA ANALYSIS Dependent Independent Null Hypothesis Alternative Variable Variable Hypothesis Age There is no There is a significant significant association association between Age and between Age and Patient Patient Satisfaction Score Satisfaction Score (PSS) (PSS) Educational Attainment

There is no There is a significant significant difference between difference between the mean PSS the mean PSS between mothers between mothers of different of different educational educational attainment attainment

Civil Status

There is no There is a significant significant difference between difference between the mean PSS the mean PSS between mothers between mothers of different civil of different civil status status

Patient Satisfaction

Income

Perceived Familiarity with Benefits

Perceived Physical Health Status

There is no significant association between income and PSS

There is a significant association between income and PSS

There is no There is a significant significant difference between difference between the mean PSS the mean PSS between mothers between mothers of different of different perceived perceived familiarity with familiarity with benefits benefits There is no There is a significant significant association association 3

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP between perceived physical health status and PSS

between perceived physical health status and PSS

Length of Membership

There is no significant association between length of membership and PSS

There is a significant association between length of membership and PSS

Membership Type

There is no There is a significant significant difference between difference between the mean PSS the mean PSS between mothers between mothers of different of different membership types membership types There is no There is no significant significant difference between difference between the mean PSS the mean PSS between mothers between mothers of different of different beneficiary type beneficiary type There is no There is a significant significant association association between perceived between perceived mental health mental health status and PSS status and PSS

Dependency or Primary Beneficiary

Perceived Mental Health Status

Table 2. Hypotheses for Multivariate Data Analysis HYPOTHESES FOR MULTIVARIATE DATA ANALYSIS Dependent Independent Null Hypothesis Alternative Variable Variable Hypothesis Age Age is not a Age is a significant significant predictor of predictor of patient satisfaction patient satisfaction after accounting after accounting for the effects of for the effects of the other the other independent independent variables in the variables in the model model Educational Educational Educational Patient Attainment Attainment is not Attainment is a 4

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP Satisfaction

a significant predictor of patient satisfaction after accounting for the effects of the other independent variables in the model Civil Status Civil Status is not a significant predictor of patient satisfaction after accounting for the effects of the other independent variables in the model Income Income is not a significant predictor of patient satisfaction after accounting for the effects of the other independent variables in the model Perceived Perceived Familiarity with Familiarity with Benefits Benefits is not a significant predictor of patient satisfaction after accounting for the effects of the other independent variables in the model Perceived Physical Perceived Physical Health Status Health Status is not a significant predictor of patient satisfaction after accounting for the effects of the other independent 5

significant predictor of patient satisfaction after accounting for the effects of the other independent variables in the model Civil Status is a significant predictor of patient satisfaction after accounting for the effects of the other independent variables in the model Income is a significant predictor of patient satisfaction after accounting for the effects of the other independent variables in the model Perceived Familiarity with Benefits is a significant predictor of patient satisfaction after accounting for the effects of the other independent variables in the model Perceived Physical Health Status is a significant predictor of patient satisfaction after accounting for the effects of the other independent

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP variables in the model Perceived Mental Health Status is not a significant predictor of patient satisfaction after accounting for the effects of the other independent variables in the model Membership Type is not a significant predictor of patient satisfaction after accounting for the effects of the other independent variables in the model Beneficiary Type is not a significant predictor of patient satisfaction after accounting for the effects of the other independent variables in the model Length of Membership is not a significant predictor of patient satisfaction after accounting for the effects of the other independent variables in the model

Length of Membership

Membership Type

Beneficiary Type

Perceived Mental Health Status

variables in the model Perceived Mental Health Status is a significant predictor of patient satisfaction after accounting for the effects of the other independent variables in the model Membership Type is a significant predictor of patient satisfaction after accounting for the effects of the other independent variables in the model Beneficiary Type is a significant predictor of patient satisfaction after accounting for the effects of the other independent variables in the model Length of Membership is a significant predictor of patient satisfaction after accounting for the effects of the other independent variables in the model

Underinsurance among Women who have availed of PhilHealth’s MCP Significance of the Study According to the United Nations Children’s Fund (UNICEF), women in the world’s developing countries are 300 times more likely to die in childbirth or from pregnancy-related complications than women in developed nations (UNICEF, 2009). Everyday, it is estimated that there are 11 maternal deaths in the Philippines (NSO, 2008). The maternal mortality ratio (MMR) of the country has never been close to the targeted MDG reduction of 52 deaths per 100,000 live births by 2015. Currently, the country has a national MMR of 221 maternal deaths per 100,000 live births (FHSIS, 2011), more than four times the targeted reduction. Access to maternal health care services could significantly reduce the risk for maternal deaths (Cook, 2001; de Bernis et al., 2003; DOH, 2007; Gupta et al., 2009; Ziyo et al., 2009). PhilHealth’s MCP, which helps provide access for maternal health services, is a crucial step towards improving the maternal health situation of the Philippines. Covering prenatal care, delivery, postpartum care, and family planning and reproductive health counseling services, the MCP can be availed by any PhilHealth member belonging to any membership type, with a few exceptions (Casimiro, 2007; PhilHealth, 2009). Social health insurance (SHI) in the country in the form of PhilHealth has achieved great strides in population coverage. By 2010, it has reportedly covered 86% of the entire Filipino population (Obermann et al., 2006). Population coverage, however, is just one of the three dimensions by which universal health coverage is achieved. As the World Health Organization (WHO) states, the proportion of healthcare costs covered by the insurance program and the range of services it offers must also be considered if true universal coverage is to be achieved (2008; 2010). Despite PhilHealh’s high population coverage, problems remain with the financial risk protection and service coverage it offers its members. A review by Tangcharoensathien et al. (2011) has found that “the design of PhilHealth does not provide adequate financial protection for its members.” (Tangcharoensathien et al., 2011, p. 8). Except for indigent beneficiaries, inpatient care is reimbursed only to a limit and patients have to pay for bills beyond the level of reimbursement. It has been found that reimbursement pays for only roughly a third of the total medical bill paid by enrolled patients in (DOH, 2010). There is also much that needs to be improved with PhilHealth’s service coverage (Tangcharoensathien et al., 2011). Outpatient consultation and routine diagnostic services are covered only for members enrolled in the Overseas Workers Program and the Sponsored Program (Tangcharoensathien et al., 2011). The services covered by PhilHealth favor admission or in-patient services (Manasan, 2011). Also, drugs and medicines, accounting for roughly 50% of total out-of-pocket health expenditures of households, are not covered in the outpatient benefit package (Manasan, 2011). This study determines the prevalence of underinsurance, defined in this study as inadequate insurance coverage based on patient satisfaction with the benefit package design, among women who have availed of PhilHealth’s MCP. Measuring underinsurance is critical to finding out if the benefit packages are adequate. Unfortunately, very few studies have been conducted on it. This study is one of the first to explore underinsurance in the Philippines; a topic which should have warranted attention but which has been overlooked and neglected. 7

Underinsurance among Women who have availed of PhilHealth’s MCP By studying underinsurance among women who availed of the MCP, this study will aid PhilHealth in identifying inadequacies in financial risk protection and service coverage, if there are any, in the design of the MCP. It is PhilHealth’s goal to provide universal health care to all Filipinos regardless of economic and social background (PhilHealth, 2012). The benefit packages it provides – the MCP in particular – could minimize financial burden on the patient and make adequate the health services it covers. The MCP targets one of the country’s most important public health concerns, and no mother who has availed of it should be deemed underinsured. In tackling underinsurance among those who availed of this benefit package, this study contributes significantly to the advancement of the Philippines’ maternal health situation. Delimitations and Limitations of the Study The study will determine the prevalence of underinsurance as well as the factors associated with underinsurance among women who have availed of the MCP. It will be done through their satisfaction with the scope of the benefits and the financial risk protection provided for by the MCP. The study will measure only satisfaction with provisions of the MCP and not the service delivery and quality of care. Survey forms will be distributed to different PhilHealth-accredited birthing clinics and lying-in clinics in Pasig City. The study will cover the months from April to November of 2013. The study has a cross-sectional design which can only provide significant associations between predictor variables and the outcome. It cannot establish causation. Given the study design, biases may occur. Recall bias may arise due to the mothers relying on their memory to answer a survey on their experience of the MCP. To minimize this, the surveys will be given right after they file their claim for the MCP. Non-response bias may also arise if the respondents do not complete the survey. To minimize non-response bias, the survey questionnaire will be made it such a way that the questions are stated in a clear, concise, short, highly objective and close-ended manner. In light of this, the researchers will be using the Likert scale to make more respondents willing to answer. In addition to that, the study personnel will be trained to follow a certain protocol as to how the survey form will be handed out. However, closed ended questions also have their limitations as it will not fully express what the respondent is really feeling or thinking because of the limited options set in the questionnaire. The study will adapt a non-probability convenience sampling. Disadvantages of this method are that the sample may not be representative of the population and therefore its external validity will be questionable. External validity will only be limited to similar populations.

Underinsurance among Women who have availed of PhilHealth’s MCP CHAPTER II REVIEW OF RELATED LITERATURE The Review of Related Literature surveys the research already done on concepts relevant to this study and serves as the foundation on which this study will build on. This review will begin with a discussion of the maternal health situation of the Philippines as a whole. It will then zoom in to present the maternal health situation of Pasig City, the study’s primary setting. A discussion on health financing, insurance, and an insurance provider in the Philippines follows. The benefit package this study focuses on will then be described and discussed. The next sections deal with insurance coverage and underinsurance, followed by patient satisfaction. These sections are concluded by a discussion on how underinsurance and patient satisfaction play into the design of a health insurance benefit package. The last is a discussion on some factors that may affect underinsurance in a patient. Maternal Health Situation of the Philippines The WHO defines a maternal death as “the death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the duration or site of the pregnancy, from any cause related to or aggravated by the pregnancy or management, but nor from accidental causes.” (WHO, 2009, p. 156). Up to 358, 000 maternal deaths occur worldwide, most of which occur in the developing world. To address this, one of the aims of the fifth Millennium Development Goal (MDG) is to reduce maternal deaths between 1990 and 2015. (UN, 2010) This is done by addressing the Maternal Mortality Ratio (MMR), which is defined as the number of maternal deaths per 100, 000 live births. The MDG aims to reduce the MMR by three quarters. The Philippine MMR is at 221 maternal deaths per 100, 000 live births, as of 2011 (FHSIS, 2011). This is more than four times the country’s target of 52 per 100, 000 by 2015. The 2011 ratio is the highest the country has had since 2001. Reducing the MMR is the least likely of the MDGs that the country is likely to attain (NEDA, 2007). Within the country, the National Capital Region (NCR) consistently has one of the highest MMRs in the country. It is also responsible for one of the largest proportion of live births in the Philippines (FHSIS, 2008; FHSIS, 2009; FHSIS, 2010; FHSIS, 2011). According to the United Nations Development Program (UNDP), the NCR has only a medium probability of reaching their target MMR. Within the NCR, Pateros has the highest MMR, with 248, followed by Pasig with 194 (FHSIS, 2011). Pasig had rates higher than Pateros prior to 2011, with 371 in 2008, 218 in 2009, and 266 in 2010 (FHSIS, 2010). The leading cause of maternal mortality in the Philippines is pregnancyrelated complications, 47% of which occur during labor, delivery, and puerperium (DOH, 2008). These complications are related to the delivery attendant and the place of delivery. Other main causes of maternal mortality include postpartum hemorrhage, unsafe abortion, and hypertension (DOH, 2008). Maternal Health Situation of Pasig City In 2010, Pasig City had a total of 11, 639 live births, 65.9% of which were 9

Underinsurance among Women who have availed of PhilHealth’s MCP delivered by a medical doctor and 28.2% by midwife. Of these deliveries, 63.47% were made in a health facility while 34.94% were made at home or elsewhere (FHSIS, 2010). Nearly two thirds of all pregnant women have had four or more prenatal check-ups while almost three fourths of all mothers received one post-natal care service (CHDMM, 2008). Pasig City has relatively accessible maternal healthcare facilities, with two public hospitals, fifteen private hospitals, and forty three health centers (CHDMM, 2008). According to the Pasig City Health Department, there are a total of 17 PhilHealth-accredited maternal healthcare facilities offering the MCP in Pasig City (Pasig City Health Department, 2012). These facilities, comprising maternity clinics, birthing clinics, and lying-in clinics, are located across the different barangays of the municipality. In 2012, PhilHealth recorded a total of 1,486 MCP claims in Pasig City (PhilHealth, 2012). Surprisingly, Pasig City has consistently had one of the highest MMRs in NCR and in the entire country. The municipality, in fact, has a rising MMR in the past few years. Pasig City’s MMR reached 371 in 2008 (FHSIS, 2008), 218 in 2009 (FHSIS, 2009), and 266 in 2010 (FHSIS, 2010). Pasig City also has the 2nd highest number of high-risk pregnancy deliveries, with an 8.7 percentage. In addition, at least 14% of all births in the municipality were still delivered by a traditional hilot (FHSIS, 2008). Health Financing Health financing provides the money needed to achieve health system goals (Normand and Weber, 2009). The WHO states that health financing is concerned with how finances are generated, allocated, and consumed in and for health systems with the goal of attaining universal health coverage that is both efficient and equitable (WHO, 2002). The WHO states six widely used health financing mechanisms. The first is general revenue financing. This mechanism uses government revenue – mostly from taxes – to provide health care for the population (World Bank, 2011). The second is social health insurance (SHI). In SHI, finances are generated from the compulsory payment of premiums or contributions from individuals in an eligible group. These premiums are linked to a specific benefit package that can be used within a selected period of time. Wage-earners make mandatory contributions based on their wages (Wagstaff, 2009). In cases where the individuals cannot pay for health insurance, the government can use general revenues to pay for social health insurance premiums especially for the unemployed, the poor, and informal sector workers (World Bank, 2011). Third is private health insurance financing. This is similar to SHI with generating money except that individuals get their own health insurance. They can choose their own health care plan from a wide range of plans, and they can choose according to their propensity to spend for health care insurance and their ability to pay (World Bank, 2011). Fourth is community-based health insurance (CBHI). In CBHI, communities control and operate their finances for health through prepayment. It involves community membership. The community is empowered to manage its own system (World Bank, 2011). 10

Underinsurance among Women who have availed of PhilHealth’s MCP Fifth is the out-of-pocket expenditure scheme. Patients’ payments are made directly to the doctors, nurses, hospitals, and other health institutions and professionals (World Bank, 2011). The last of these mechanisms is external financing sources. When a state, especially the poorest ones, cannot accommodate for health expenditures, they rely on foreign aid to fund their health initiatives and projects (World Bank, 2011). Social Health Insurance Social Health Insurance (SHI) is one way to gather finances for health insurance. SHI is government-legislated, its members are required to pay according to their ability to pay, and benefit packages are standardized (Doherty et al., 2001). Although there is no one definition for SHI, Dixon et al. (2002) states that “social health insurance funding occurs when it is legally mandatory to obtain health insurance with a designated third-party payer through contributions or premiums not related to risk that are kept separate from other legally mandated taxes or contributions.” (Dixon et al., 2002, p. 59). There are problems that hinder full implementation of SHI. For one, it may be difficult to explain to individuals how the system works. This could affect their acceptance of SHI as a mechanism for healthcare (Normand and Weber, 2009). Another is that SHI is difficult to manage, as it needs to manage the contributions, and the administration of the health-care providers and the government (Normand and Weber, 2009). SHI also has its advantages. SHI allows for a more equitable health financing system than one relying on out-of-pocket spending. It is a more stable source of funding than other schemes. This is especially true when poor people are concerned. SHI prevents individuals from being pushed below the poverty line by out-of-pocket health care expenditures (Normand and Weber, 2009). The Beginnings of Social Health Insurance in the Philippines SHI started in the Philippines roughly 35 years ago with the MARIA Project of the 1960s. The MARIA project was introduced by the Philippine Medical Association (PMA). It prioritized aid to communities needing medical assistance. The project was a precursor to the Medicare program. The Medicare program was signed into law in 1969 through Republic Act 6111 or the Philippine Medical Care Act of 1969. It was implemented two years later, in August 1971. The Philippine Medical Care Commission (PMCC) was tasked with overseeing the implementation of the program. Medicare is composed of two programs: Phase I targeted those in formal employment while Phase II reached for the informal sector and most especially the poor. Phase I was more successful than Phase II in enrolling members. Medicare benefits were focused on hospital care. Medicare covered expenses up to a limit if patients were confined in a private hospital. If expenses went beyond that provided by Medicare, the patient was supposed to be transferred to a government hospital. This is the reimbursement concept and it is a concept still in use (Gamboa, Bautista, and Beringuela, 1993). Cory Aquino’s administration saw a chance to overhaul SHI, which had 11

Underinsurance among Women who have availed of PhilHealth’s MCP failed to provide coverage for the poor during Marcos’s reign. The Health Financing Development Project did intensive research on the experiences of other countries with SHI. A major finding was that SHI did not need a stronger economy (La Forgia and Griffin, 1993). The Philippine Health Insurance Corporation (PhilHealth) The National Health Insurance Act of 1995 (R.A. 7875), signed by former President Fidel V. Ramos, signified the birth of what is now known as the Philippine Health Insurance Corporation (PhilHealth), a government-owned and controlled corporation. It served as a response to the call for a better, more responsive, and more comprehensive government health care program (PhilHealth, 2012). PhilHealth is mandated to have achieved universal coverage by the year 2010. Its funding comes from national and local government unites for the annual premiums of enrolled sponsored members, and from the contribution of members into the program (PhilHealth, 2012). PhilHealth assumed the responsibility of administering the former Medicare program from government and private sector employees from the Government Service Insurance System (GSIS) in 1997, from the Social Security System (SSS) in 1998, and from the Overseas Workers Welfare Administration (OWWA) in 2005 (Obermann et al., 2006). Together with the transfers was the turnover of the health insurance funds, totalling PhP 105 million from GSIS and PhP 14 billion from SSS. Contributions from local government units (LGUs) totalled PhP 53,200 for premium contributions of indigent members were also entrusted to the agency in the years 1997 to 1998. The approval from the national Department for Budget and Management for the creation of 995 regular plantilla positions paved the way for the full implementation and response of the NHIP to the needs of its members in 1998 (PhilHealth, 2012). PhilHealth Membership Types Currently, PhilHealth offers insurance programs under the National Health Insurance Program (NHIP). To be part of the NHIP, one must be a Filipino citizen. The type of membership depends on two criteria: one’s capacity to pay and one’s employment. A Filipino who is below 21 years old is considered as a dependent rather than a primary member. Five membership types/programs are offered under the NHIP. These are the Sponsored Program, Individually Paying Program, Employed Sector Program, Overseas Workers Program, and Lifetime Member Program. Each of these programs caters to specific groups on the basis of the two aforementioned criteria (PhilHealth, 2012). The Sponsored Program of PhilHealth focuses on addressing the health needs of indigents identified to be part of the lowest 40% or Quintiles 1 and 2 of the Philippine population. PhilHealth uses the National Household Targeting System for Poverty Reduction (NHTS – PR) of the Department of Social Welfare and Development (DSWD). PhilHealth also uses the sponsor LGU unit's list of indigents. The coverage of members of the Sponsored Program is jointly shouldered by the national government and a partner, whether LGUs, private 12

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP individuals and companies, members of Congress, and other sponsors (PhilHealth, 2012). The Employed Sector Program enrolls employees from both the government sector and private sector. Employers partner with PhilHealth for their employees to be enrolled. Members of this program handle transactions through their employers. For those working in government, PhilHealth determines if the person is appointed or elected. For the private sector, those who can avail are: those employed in Philippine-based organizations, foreign organizations based in the Philippines, foreign organizations based abroad but which agreed with PhilHealth to cover their Filipino employees, sea-based Overseas Filipino Workers (OFWs), and household employees (PhilHealth, 2012). The Individually Paying Program is the insurance program catering to various groups considered by PhilHealth. These include: self-employed individuals, individuals separated from employment, employees of international organizations and foreign governments based in the Philippines but which have no agreement with PhilHealth on insurance coverage, and unemployed individuals not qualified as indigents. PhilHealth classifies self-employed individuals as individuals who work for him/herself. Such people range from self-earning professionals (e.g. physicians and lawyers) to workers in the informal sector (e.g. ambulant vendors, watch-your-car boys, hospitality girls, and tricycle drivers) (PhilHealth, 2012). PhilHealth also offers an Overseas Workers Program for Philippine Overseas Employment Agency-registered land-based OFWs and OFWs abroad but are not yet registered with PhilHealth. As with the other programs, the OWP can also be used by dependents currently residing in the country (PhilHealth, 2012). Last, the Lifetime Member Program is offered to old-age retirees and pensioners of the GSIS, SSS, and other government agencies who have made at least 120 monthly contributions to PhilHealth. Members of the Lifetime Member Program are entitled to lifetime coverage. As with the other programs, dependents of these members are also entitled to enjoy the same benefits (PhilHealth, 2012). PhilHealth Benefit Packages PhilHealth members can avail of many different benefit packages. Benefit packages are collections of health services designed to address a specific health issue. The main reason for having benefit packages is to provide access to necessary services of adequate quality while covering financial risks and containing costs (Normand and Weber, 2012). PhilHealth offers nine benefit packages, namely, the Maternity Care Package (MCP), Neonatal Care Package, TB-DOTS Package, Malaria Package, Animal Bite Package, Primary Care Package, Outpatient HIV/AIDS Package, and Z Benefit Package (DOH, 2009; PhilHealth, 2012). Maternity Care Package (MCP) To improve maternal health outcomes in the Philippines, PhilHealth introduced the MCP in 2001 (Casimiro, 2007). The package covered the first two normal deliveries, prenatal and postpartum care, newborn care, and family planning counselling. In 2009, PhilHealth extended their coverage to the first four 13

Underinsurance among Women who have availed of PhilHealth’s MCP normal births. The provision for newborn care was later removed upon creation of the PhilHealth Newborn Care Package. Payment for claims for the MCP is now at PhP 6500 in all accredited lying-in clinics, birthing clinics, and midwife-managed clinics. According to PhilHealth Circular No. 39, s-2009, of the PhP 6500, MCP allots PhP 5000 for the following services: delivery, postpartum care and family planning which already includes counselling on reproductive health, breast feeding, newborn screening, payment for rooms, laboratory services, medicines, and supplies. Delivery should be attended by a skilled and accredited health professional and should include use of a partograph. The postpartum care includes a visit within 72 hours and a visit on the 7th day postpartum. This also includes vitamin A supplements, maternal nutrition and lactation counselling. The remaining PhP 1500 is allotted for prenatal care expenses incurred prior to confinement and covers the basics of prenatal care which include iron, iodine, and folate supplementation, drugs, laboratory tests and ancillary procedures, 2 tetanus toxoid immunization, and consultation fees. In addition to the services, PhilHealth Circular No. 30, s-2009 states that an MCP provider should have the following resources, among others: general infrastructure, consultation and delivery room equipment, standard supplies, records, an available emergency transport vehicle, and accredited human resources. The MCP can be availed of by any PhilHealth member of any membership type, as well as by the member’s dependents. For all membership types, the mother’s first prenatal visit must be made prior to the 16th week of gestation. For the MCP to be availed, there should be at least 4 prenatal visits done prior to delivery. Different membership types have varied rules for being eligible to avail of the MCP. For the Individually Paying Members (IPMs) and their dependents, including IPMs under the Group Enrolment Scheme, they are required 9 months of premium payment within the immediate 12 months prior to the month of benefit availment. Employed members and IPMs enrolled by organized groups through KASAPI must have paid at least three months contribution within the immediate six months prior to the month of availment. Sponsored and Overseas Workers Program Members are entitled to the package if the date of availment falls within the validity period of their membership as stated in their PhilHealth ID card. Nonpaying members and dependents are entitled to avail of the MCP upon presentation of a valid PhilHealth ID. PhilHealth lists exclusions for availment of the MCP. The availing member should not have: maternal age of less than 19 years old, age of 35 years or older during first pregnancy, multiple pregnancies, abnormalities in the ovary, urinary tract and placenta, abnormal fetal presentations or breech, undergone three or more miscarriages or abortions, history of one still birth, history of a major obstetric or gynecologic procedure, history of medical conditions, and other risk factors. These guidelines were developed to protect high-risk pregnant women from any complications and to ensure that they be brought to a more specialized facility for the procedures (Casimiro, 2007). Universal Health Coverage The World Health Organization (WHO) states that universal coverage may be defined as “physical and financial access by all persons in society to the full 14

Underinsurance among Women who have availed of PhilHealth’s MCP range of personal and non-personal health services that they need at affordable cost.” (WHO, 2005, p. 1). To achieve universal coverage, pre-paid contributions are pooled and the funds used “to ensure that services are available, accessible, and produce quality care for those who need them, without exposing them to the risk of catastrophic expenditures.” (WHO, 2010, p. 187). Achieving and evaluating universal coverage requires a framework for understanding universal coverage. The framework chosen includes three dimensions (WHO, 2008; WHO, 2010): 1. Breadth of coverage or population coverage refers to the proportion of the population that enjoys social health protection. 2. Height of coverage or financial risk protection refers to the portion of health-care costs that are covered under the social health insurance program. 3. Depth of coverage or service coverage refers to the range of services that are available from the system. The following diagram summarizes the three dimensions that should be considered when understanding universal coverage:

Figure 1. The three dimensions in achieving and evaluating universal coverage (WHO, 2010) Health Insurance Coverage Situation in the Philippines The Philippine Health Insurance Corporation (PhilHealth) is mandated to provide universal health coverage to give Filipinos financial access to health services (Manasan, 2011). PhilHealth strives to provide adequate and affordable social health insurance coverage for all Filipinos (PhilHealth, 2012). In 2010, there were 70 million beneficiaries, 22.4 million of which were principal members and the rest, dependents. The ratio of PhilHealth beneficiaries to the total population had gone up from 59% in 2007 to 79% in 2010. This data presents the progress that PhilHealth has made in ensuring that more Filipinos have health insurance coverage (Manasan, 2011). Coverage rate for the different membership types remains unequal. The coverage rate is the ratio of the number of registered principal members with the 15

Underinsurance among Women who have availed of PhilHealth’s MCP number of potential principal members. These are based on the Labor Force Survey (LFS). The Employed Sector Program continues to have the highest coverage rate, while the Individually Paying Program and Overseas Workers Program have the lowest combined coverage rate among the membership types. On financial risk protection, PhilHealth members continue to have high out-of-pocket expenditures. A study by Tangcharoensathien et al. (2011) states that “the design of PhilHealth does not provide adequate financial protection for its members.” (Tangcharoensathien et al., 2011, p. 7). The researchers point out that, except for indigent beneficiaries, reimbursement for inpatient care is limited; patients must pay for costs beyond the reimbursement limit PhilHealth sets. This reimbursement was roughly only one third of the total medical bill paid by enrolled patients in 2008 (DOH, 2010). The result is that the insured patient pays almost as much as the uninsured patient. (Gertler and Solon, 2002; Jowett et al., 2007). Obermann et al. (2006) recognized this, stating that “for the patient, there is considerable uncertainty about the extent of out-of-pocket payments [for healthcare] and he/she effectively bears the risk of uncontrolled pricing.” (Obermann et al., 2006, p. 3179). Filipinos’ out-of-pocket expenses for healthcare has increased from 45% in 1998 to 53% in 2010 (NSCB, 2002; NSCB, 2010; Acuin et al., 2010). Several issues also concern PhilHealth’s service coverage, the scope of benefits covered by a benefit package. According to Obermann et al. (2005), several of PhilHealth’s decisions on which services to cover appear to have been based on political lobbying rather than a clear needs analysis or health technology assessment. Another study by Almario and Weber (2002) claims that one of the main reasons PhilHealth enrolled only 80,000 indigent families - just 15% of the target group by late 2001 - was that the initial benefit package “only provided for inpatient hospital care, which was not the highest priority for many poor families.” (Almario and Weber, 2002, p. 47). Manasan (2011) notes that PhilHealth supports mostly inpatient services. Outpatient consultation and routine diagnostic services are covered only for members enrolled in the Overseas Workers Program and the Sponsored Program (Tangcharoensathien et al., 2011). As such, most insured members pay for their own outpatient services (Tangcharoensathien et al., 2011). The Concept of Underinsurance Underinsurance is a widely used though ill-defined term. Many different definitions exist. Some of these include: the experience of gaps in coverage, the actuarial value of the benefits provided in a plan, and the out-of-pocket healthcare costs that exceed what families consider appropriate or burdensome (Oswald et al., 2005). Although there is no universally accepted definition, “underinsurance” is generally used to refer to “healthcare insurance whose depth and height of coverage is in some way inadequate” (Ward, 2006, p. 500). A more specific version is given by Oswald et al (2005), with underinsurance as “health insurance that requires excessive out-of-pocket expenditures, that has significant limits with respect to what health care services are covered, or that fails to cover health care expenses that are perceived by the insured person to be essential for his or her health.” (Oswald et al., 2005, p. 68). The concept of underinsurance is fast gaining relevance, significance, and recognition as an appropriate framework in evaluating health insurance. Most 16

Underinsurance among Women who have availed of PhilHealth’s MCP policy makers see only a dichotomy for health insurance: a person is either insured or uninsured. Health services researchers are now finding that the dichotomy is inadequate. Implications of Underinsurance Underinsurance may be at least as common as absence of insurance and may even be more prevalent, depending on how underinsurance is defined. Underinsurance can hurt both the health insurance provider and the insured individuals. As Ward (2006) states, “Regardless of the cause of the increase in the number of underinsured people, underinsured individuals are more likely to delay or to forgo seeking healthcare. This failure to receive healthcare can have detrimental physical, psychological, and financial impacts on individuals and families.” (Ward, 2006, p. 511). A study by Oswald et al. (2005) states that “limited coverage and inadequate reimbursement can result in significant gaps in services and an increased probability of compromised health outcomes.” (Oswald et al., 2005, p. 68). The researchers add that “underinsurance in childhood may lead to deterioration of health or exacerbation of illnesses and to more costly medical care in later life due to emergency or chronic health care needs.” (Oswald et al., 2005, p. 69). Schoene et al. (2008) state that underinsured persons experience the same access and financial difficulties as do the uninsured. 53% of the underinsured and 68% of the uninsured did not receive the healthcare they needed. This included not seeing a doctor when sick, not filling prescriptions, and not following up or adhering to recommended treatments. The study adds that “the sharp increase in the number of underinsured adults is partly due to design changes in insurance benefits that leave individuals financially vulnerable. Underinsured adults were more likely than those with adequate insurance to report benefit limits—for example, restrictions on the total amount a plan would pay for medical care or on the number of physicians’ visits allowed.” (Schoen et al., 2008, p. 301). The researchers conclude that “benefit design matters” and that the “the goal [of the health insurance’s benefit package] is high-quality care and improved outcomes— not just population coverage.” (Schoen et al., 2008, p. 309). Similar findings were discovered in a study by Kogan et al. (2005) on the impact of underinsurance on access to needed healthcare. The study laments that while policy discussions on insurance often focus on ways to extend insurance coverage for the uninsured, “such discussions are incomplete and ignore a large segment of children who are underinsured. In many respects, these children experience access problems that are similar in magnitude to the uninsured.” (Kogan et al., 2005, p. 1163). Implications of Underinsurance to Women of Birthing Age Underinsurance hurts insured mothers and women of birthing age. In general, being underinsured restricts financial access to healthcare, compromising one’s health and producing adverse health outcomes (Davis, 2007; Rosenbaum, 2008). A survey by Link and McKinlay (2010) on the sociodemographic and health characteristics associated with underinsurance states that the latter is as much a problem as uninsurance. The absence of health insurance has been linked 17

Underinsurance among Women who have availed of PhilHealth’s MCP to adverse health outcomes (Aquilante et al., 2007; Hadley, 2007; Halpern et al., 2008; Markovitz and Andresen, 2006; Rahimi et al., 2007; Ward et al., 2008). Underinsurance is also linked to the same. Several studies have been conducted on the effects of underinsurance on women of birthing age. A study by Rosenbaum (2008) found that underinsurance severely prevents “[putting] acute treatments within financial reach”. (Rosenbaum, 2008, p. 221). This deters “financial interventions that can help to achieve population-wide preventive results.” (Rosenbaum, 2008, p. 221). The study adds that underinsurance could, therefore, hinder long-term improvement of the health of both women and children. Similar conclusions were found in a study by Wong et al. (2005) on financial disparities of maternal and children’s healthcare. The researchers report that being underinsured could impede access to health services for maternal and child care, leading to the non-attainment of desired health outcomes. The same study by Wong et al. (2005) and that of Thompson et al. (2009) found that underinsurance is closely linked and tied to patient satisfaction. Adequate Coverage Since underinsurance is understood as the inadequacy of health insurance coverage, it is important to first understand what “adequate” insurance is. Bashshur. Smith, and Stiles (1993) classified the coverage offered by the benefit package into three kinds: excessive coverage, full coverage, and adequate coverage. Excessive coverage means services are covered more than once, which gives no financial advantage over a service covered only once. Full coverage means services are covered only once (Bashshur, Smith, and Stiles, 1993). Ward (2006) points out a similarity: “Both classifications refer to comprehensive benefit packages that provide complete protection against out- of-pocket expenses outside of premiums.” (Ward, 2006, p. 502). Benefit packages of both kinds include service coverage scope (benefits) and protection from out-of-pocket expenses (economic). Benefit packages that offer either excessive or full coverage give the insured member complete protection from out-of-pocket expenditures. Insured members may also avail of any service any number of times, whether the service is needed or merely desired (Ward, 2006). Both kinds of coverage provide complete protection from out-of-pocket expenses associated with all needed healthcare services as well as providing complete protection for out-of-pocket expenses associated with desired health care services (Ward, 2006). In contrast to full or excessive coverage, adequate coverage limits both the protection from out-of-pocket expenses and the scope of services covered (Ward, 2006). Bashshur, Smith and Stiles (1993) define adequate coverage as referring to “a less comprehensive set of benefits, wherein the beneficiaries are liable for designated amounts of out-of-pocket expenditures in the form of deductibles, copayments, exclusions, limits-of-coverage, and other forms of cost sharing outside of premiums.” (Bashshur, Smith, and Stiles, 1993, p. 202). Rationale for Limiting Coverage Ward (2006) cites two reasons why an excessive or full coverage benefit 18

Underinsurance among Women who have availed of PhilHealth’s MCP package should not be made a benchmark. The first reason deals with the concept of “moral hazard”. Both excessive and full coverage may encourage excessive and inappropriate use of healthcare services. Since both guarantee complete protection from out-of-pocket expenses, the insured member has no incentive to limit his use of insurance. Two things result. First, the insured person may avail of unnecessary services, raising the costs of healthcare services. Second, non-users will pay for majority of the healthcare costs incurred by the users (Ward, 2006). The second reason why an excessive or full coverage of a benefit package is not an ideal benchmark is that premium costs are not included in characterizing a benefit package as excessive or full. Packages with very expensive premiums may still be considered full or excessive. Bashshur, Smith, and Stiles (1993) suggest that the outlay for premiums necessary to provide either excessive or full coverage could be too expensive for much of the insured. This could increase the number of uninsured (Ward, 2006). For these two reasons, it is ideal to have “less-than-full” or adequate coverage. Ward (2006) states that it is not only socially and economically acceptable but is in fact necessary. Adequate coverage limits out-of-pocket expenditures and services, but too many limitations could turn it into underinsurance. The challenge is to find balance between scope of service coverage and protection from out-of-pocket expenses. Defining Underinsurance Underinsurance is a state where an insured member has inadequate health insurance coverage. This inadequacy is associated with two things: limited scope of benefits covered by the benefit package and insufficient protection from out-ofpocket expenses. Determining how and when these limitations become excessive depends on the definition of underinsurance that is adopted. Specifics of underinsurance were laid out by Bashshur, Smith, and Stiles (1993) as referring to one or more of the following conditions: 1. too few services are covered or the coverage is inadequate 2. amounts of out-of-pocket expenditures, with or without regard to family  income, are excessive 3. insurance is perceived to be inadequate; or 4. some combination of the three is present From these four, Bashshur, Smith, and Stiles (1993) developed three definitions of underinsurance (Oswald et al, 2005). They are: Structural Definition Structural definitions of underinsurance consider the type of benefits offered by the program and the range of providers whose services are covered under the plan. A Structural approach to defining underinsurance uses a benchmark benefits package. Underinsurance is identified when at least one benefit in the benchmark package is not covered by the individual’s health insurance plan (Oswald et al., 2005). Economic Definition

Underinsurance among Women who have availed of PhilHealth’s MCP Economic definitions focus on a person’s ability to pay for health care, which includes the cost of the insurance premiums, co-pays, and deductibles. An Economic definition of underinsurance defines a limit above which the expense of health care coverage becomes a burden and interferes with access to care. Using this definition, underinsurance is identified when out-of-pocket expenses for necessary medical care exceed a specified percent of the person’s income within a given time frame, or when a person delays health care due to out-of-pocket costs associated with the services (Oswald et al., 2005). Attitudinal Definition Attitudinal definitions emphasize consumer perceptions and satisfaction as they relate to health care. Underinsurance is identified when at least one health benefit the person would prefer to receive is not covered by insurance, when there is at least one symptom that the person believed required treatment for which insurance coverage treatment was not provided, or when a person is dissatisfied with their insurance plan (Oswald et al., 2005). Ward (2006) summarizes the underinsurance in the diagram below:

three

conceptual

definitions

Figure 2. Bashshur, Smith, and Stiles’ three conceptual definitions for underinsurance (Ward, 2006) Ward (2006), however, offered an alternate and more comprehensive conceptual framework for which to define and measure underinsurance. He argued that the perceptual/attitudinal dimension is a way of counting the number of people who are underinsured. This measurement is done through a “subjective assessment” of the adequacy of two components: the benefits the benefit package covers and the adequacy of the protection from out-of-pocket cost. Ward (2006) illustrates his argument:

Figure 3. Alternative framework to Bashshur, Smith, and Stiles’ classification scheme for underinsurance (Ward, 2006) Ward (2006) explains: “In this classification schema, the solid ‘arrowed’ lines refer to dimensions of underinsurance, and the broken ‘arrowed’ lines refer to ways of 20

Underinsurance among Women who have availed of PhilHealth’s MCP measuring (counting) the number of underinsured people relative to one or more features of a dimension of underinsurance. The important difference is that economic and benefits dimensions provide definitions of ‘underinsurance’ and can, but need not provide numbers of people who are underinsured, whereas attitudinal measurements provide information about the number of people who are underinsured based upon an accepted definition of underinsurance.” (Ward, 2006, p. 527). There are two dimensions of underinsurance (benefits and economic) which are measured by individuals’ perception and therefore two ways a health insurance benefits package can be inadequate. As Ward (2006) states in his study: “It follows from this that a person may believe that his or her health insurance benefits package coverage is inadequate in either of two ways. On the one hand, a person may believe that his or her health insurance benefits package coverage is inadequate from the perspective of the benefits dimension of underinsurance. On the other hand, a person may believe that his or her health insurance benefits package coverage is inadequate from the perspective of the economics dimension of underinsurance.” (Ward, 2006, p. 529). Therefore, the satisfaction of individuals towards the benefits and economic dimensions of the benefit packages can be used to measure the adequacy of coverage offered by a specific benefit package. The framework proposed may be used as a means to determine whether a benefit package provides adequate coverage. Defining Patient Satisfaction To date, patient satisfaction is still ill-defined. Patient satisfaction can be defined as “an attitude - a person’s general orientation towards a total experience of healthcare. [It] comprises both cognitive and emotional facets and is related to previous experiences, expectations, and social networks.” (Keegan and McGee, 2003, p. 178). This supports an idea where the patient’s overall satisfaction with the healthcare he/she received is affected by both what he thinks (cognitive aspect) and what he feels (affective aspect) about it (INGID, 2006). Another definition of patient satisfaction was presented in the study of Finley (2001). Patient satisfaction is “how patients value and regard their care.” (Finley, 2001, p. 5). Last, the following definition of patient satisfaction is adopted by the Irish Society for Quality and Safety in Healthcare (ISQSH): “Patient satisfaction is achieved when the patient’s perception of the quality of care and services that [he/she] received in healthcare setting has been positive, satisfying, and meets [his/her] expectations." (ISQSH, 2003, p. 21). Patient satisfaction could pertain to four aspects of healthcare: “the settings and amenities of care; technical management and operations; features of interpersonal care; and the physiological, physical, psychological, or social consequences of [health] care.” (Donabedian, 1990, p. 33). This implies that patient satisfaction can be measured either by looking into the patient’s overall 21

Underinsurance among Women who have availed of PhilHealth’s MCP experience with the healthcare he/she received in general or by looking into his/her experience with only a specific aspect of healthcare. Patient satisfaction can also be measured either by looking into the overall experience of the patient with the benefit package or by looking into the experiences of the patient with specific parts of the package. The Role of Patient Satisfaction in the Design of a Benefit Package Underinsurance is tied to the insured individual’s satisfaction with the design of the benefit package. Several studies report that incorporating the insured member’s satisfaction with the benefit package will lead to, among other things, greater enrollment and willingness to co-pay. Considering patient satisfaction is indispensable and crucial in designing benefit packages (Dror et al., 2006) The numerous advantages and benefits of considering and evaluating patient satisfaction in benefit package design have been reported by a number of studies. Liu (2002), in her analysis of the advantages and challenges of implementing reforms for China’s urban health insurance system, states “the design of the benefit package, particularly the benefit ceiling/coverage ceiling, drastically affects satisfaction for health insurance systems.” (Liu, 2002, p. 139). Clients’ decision to enroll in a health insurance scheme is affected by their satisfaction over benefit package design, as well as specifics of the insurance scheme. These specifics include the unit of enrolment, premium level, payment modalities, health service provider network, and managerial structure of the insurance scheme (DeAllegri et al., 2006). A study found that clients who were satisfied with the benefit package design generally had higher participation rates. It concludes that the incorporation of clients’ preferences or patient satisfaction “in the design of a [health insurance] scheme may result in increased participation rates, ensuring that poor populations gain better access to health services and enjoy greater protection against the cost of illness.” (DeAllegri et al., 2006, p. 154). These findings are also supported by other studies stating that willingness to join health insurance schemes may increase when prospective clients are satisfied with the benefit package and identify with it (Fleck, 1994; Schone and Cooper, 2001). Dror et al. (2006) reports that if people have to pay to avail of a benefit package of a health insurance scheme, they will be more willing to pay if they are more satisfied with the benefit package. Weisman and Koch (1989) also found that higher patient satisfaction with the benefit package leads to higher willingness to follow treatment recommendations set by the health practitioner. On employer-sponsored health insurance plans, Reeves et al. (2012) found that “economic pressures are driving employer sponsors of health plans to seek improved value from their investments in healthcare coverage. As such, they pursue lower medical cost trend and better care quality with higher patient satisfaction ratings.” (Reeves et al., 2012, p. 76). For health insurance plans sponsored by employers, patient satisfaction ratings for the benefit packages offered affect the employers’ choice of a health plan. The literature on the role of patient satisfaction in the design of benefit packages continues to grow. This is unsurprising since the studies that have already been conducted on this subject clearly points out that both the healthcare provider and the healthcare recipient stand to gain benefits by incorporating and 22

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP constantly evaluating patient satisfaction in benefit packages. Factors affecting Patient Satisfaction / Underinsurance Several factors affect patient satisfaction over the services of a health insurance company. Inconvenience Tessler and Mechanic (1975) linked dissatisfaction with inconvenience and scheduling difficulties. Inconvenience may come in the form of long lines, difficulty in acquiring required documents, and patient-provider psychosocial interaction. The satisfaction of care is commonly perceived to be reflected in the nature of the care alone but Ward (1990) reports that satisfaction may also reflect self-selected characteristics (i.e. specifications or actions that are selected by the patient). He suggests that self-selection results in congruence between the provided health care and the values and expectations of members, and that selfselection is crucial for the stability of patient-provider relationship and psychosocial care. Lack of Familiarity and Length of Membership Lack of familiarity is suggested to also contribute to dissatisfaction because poorly-informed or unrealistic expectations tend toor disorient the patient. Ward reports that insurance familiarity and length of membership affects health insurance service satisfaction towards the positive direction. As familiarity and length of membership increases, so does health insurance service satisfaction. Formal Education In a study by Oswald et al. (2005) wherein the prevalence of underinsurance among Children with Special Healthcare Needs (CSHN) was investigated, it was shown post-High School education of the parent uniquely contributed to the likelihood of the child being underinsured. In a study by Spears et al. (2011) wherein the prevalence and correlates of childrenâ&#x20AC;&#x2122;s underinsurance within a primary-care based practice, the underinsurance of the children were significantly associated with whether the parents had a college degree or not, with the trend showing that having lower educational attainment came with a higher risk of underinsurance. In a study by Ebetino (2012) wherein the prevalence and predictors for underinsurance in the state of Ohio was determined, those with less than a high school education or some college education were about 60% more likely to be underinsured than a college graduate. Socioeconomic Status In a study by Oswald et al. (2005) wherein the prevalence of underinsurance among Children with Special Healthcare Needs (CSHN) was

Underinsurance among Women who have availed of PhilHealth’s MCP investigated, it was shown that poverty level significantly predicted underinsurance for the child. In a study by Kogan et al. (2005) wherein the impact of underinsurance on access to care among children with special health care needs (CSHCN) in the United States was examined, it was found that poverty figured as a significant correlate of underinsurance, with those in most poverty having the significantly highest odds of being underinsured. In a study by Link and McKinlay (2010) wherein the socio-demographic and health characteristics of the underinsured were examined, it was shown that those of lower and middle SES were more likely to be underinsured than those of upper SES. Income In a study by Spears et al. (2012) wherein the prevalence and correlates of children’s underinsurance within a primary-care based practice, the income level of the parents had a significant association with the underinsurance of the child. It was shown that the risk of underinsurance was highest for those who belonged to the highest socioeconomic subgroup. In a study by Voorhees et al. (2008) wherein the prevalence of underinsurance was determined among patients in primary-care practice networks, higher proportions of those with reported low income levels were characterized as underinsured. More precisely, patients reporting an annual income of less than $50,000 had higher odds of being underinsured than being adequately insured. Schoen et al. (2008) has demonstrated the proportion of underinsurance in higher income groups since 2003 has increased significantly, which has resulted from the increase cost of health care relative to inflation. Moreover, adults belonging to the income group with an annual income of $20,000-$39,999 were at high risk of underinsurance Age Voorhees et al. (2008) showed that the adult underinsured group is more likely to be between 18 and 39 years of age. However, Schoen et al. (2008) demonstrated that being 50 to 64 years old increases one’s risk of being underinsured. The discrepancy in findings may be a result of the different definitions and measurements between the studies. In a study by Ebetino (2012) wherein the prevalence and predictors for underinsurance in the state of Ohio was determined, it was shown that respondents aged 25-64 years old had the highest risk of underinsurance as opposed to respondents aged 18-24 years old who had the lowest risk of underinsurance. Health Status In a study by Spears et al. (2012) wherein the prevalence and correlates of children’s underinsurance within a primary-care based practice, it was shown that underinsurance was significantly associated with the child’s health status being reported as less than excellent. In a study by Kogan et al. (2005) wherein the impact of underinsurance on access to care among children with special health care needs (CSHCN) in the 24

Underinsurance among Women who have availed of PhilHealth’s MCP United States was examined, families in which the child was most limited in their activities of daily living had higher odds of being underinsured, as were families in which the child needed physical, occupational, or speech therapy or the child was treated for an emotional, developmental, or behavioral condition. In a study by Voorhees et al. (2008) wherein the prevalence of underinsurance was determined among patients in primary-care practice networks, underinsured patients were characterized as reporting higher proportions of fair or poor health status or that their health has suffered in some way. Moreover, patients who reported their general health as fair to poor and who believe their health suffered because they were unable to afford the cost of necessary care also had higher odds of being underinsured. In a study by Link and McKinlay (2010) wherein the socio-demographic and health characteristics of the underinsured were examined, those who were underinsured were characterized as having a higher prevalence of co-morbidities such as depression. Moreover, in terms of health-related quality of life, people who were underinsured were more likely to report poor or fair health, and they report lower physical and mental health component scores. In a study by Oswald et al. (2005) wherein the prevalence of underinsurance among Children with Special Healthcare Needs (CSHN) was investigated, it was shown that the pervasiveness of the child’s special healthcare needs significantly predicted underinsurance status. Short-Form-12 Health Survey There are several ways to measure an individual’s health status, one of which is through the Short-Form-12 Health Survey (SF-12). The SF-12 is an abbreviated version of the Short-Form-36 Health Survey (SF-36). Like its unabridged predecessor, the SF- 12 was designed as a generic indicator of health status “for use in population surveys and evaluative studies of health policy.” (McDowell, 2006, p. 649). Nonetheless, the SF-12 can also be used alongside disease-specific measures as an outcome measure in clinical practice and research. The SF-12 traces its roots to the RAND Corporation of Santa Monica during the 1970s. The company’s Health Insurance Experiment compared the impact of alternative health insurance systems on health status and insurance utilization (Lohr et al., 1986; Ware, Kosinki, and Gandek, 2002). The outcome measures created for this study were widely used and subsequently refined in RAND’s Medical Outcomes Study (MOS), a study which examined more specifically the care for chronic medical and psychiatric conditions (Stewart et al., 1989; Tarlov et al., 1989). The MOS surveys covered 40 physical and mental health concepts. Due to their length, several abbreviated forms were developed. An 18-item survey was created in 1984, followed by the 20-item short-form (SF20) in 1986. In response to criticisms about the limitations of the SF-20, the SF-36 which covered the eight most important concepts of the original 40 was constructed (Ware, Kosinki, and Gandek, 2002). Although the SF-36 has eight dimensions, the physical and mental summary scores account for 80 to 85% of reliable variance in the eight scores. Hence, reducing the number of health dimensions does not significantly affect validity. Ware et al. (1994) argued that an abbreviated version of the SF-36 that covers only the physical and mental dimensions of health would be very practical for general use while still being valid at the same time. The SF-12, thus, was 25

Underinsurance among Women who have availed of PhilHealth’s MCP developed by Ware et al. in 1994 with the following goals: to account for at least 90% of the variance in the SF-36 physical and mental summary scores, to provide summary scores that would coincide with the average scores on the SF-36, and to be brief enough to be printed on a single page and administered in less than two minutes (McDowell, 2012; Ware et al., 1994) The principal scores of the SF-12 are the physical health composite score (PCS-12) and the mental health composite score (MCS-12). In a revised version developed in 1998, an eight-domain profile can be produced, providing scores for Physical Functioning, Role Physical, Bodily Pain, General Health, Vitality, Social Functioning, Role Emotional, and Mental Health (Ware, Kosinki, and Gandek, 2002). The scoring for the SF-12 was changed between its first and second versions. The latter may be scored in a conventional manner involving three steps. First, out-of-range values are treated as missing. Second, scores for some items are reversed while some are recalibrated, and the total scores for each domain are calculated. Lastly, these total scores are transformed into a 0 to 100 scale. Alternatively, norm-based scoring makes use of regression weights to standardize each of the eight scale scores to a mean of 50 and standard deviation of 10 using weights based on the general population of a particular country. (Maddigan, Feeny, and Johnson, 2004). PCS and MCS scores are also based on factor score weights for combining the eight scale scores (Ware et al., 2002). This norm-based method of scoring has been shown to provide a significantly stronger correlation with SF-36 scores than a simpler equal-interval scoring approach (Ware, Kosinski, and Keller, 1996). The researcher using the SF-12 can also opt to have the scoring performed online at the website of QualityMetric, Incorporated, a company founded by John Ware and associates in 1997 that develops and tests health surveys which coordinates the development and use of the SF-12 globally. According to Ware’s original description of the SF-12, test-retest reliability of the PCS-12 was 0.89 in the US and 0.86 in the UK. Coefficients of the MCS were 0.76 and 0.77 (Ware, Kosinki, and Gandek, 2002). The second version of the SF-12 has theta reliability estimates ranging from 0.73 to 0.87 across the eight scales. The value for the PCS-12 was 0.89 whereas that for the MCS-12 was 0.86 (Ware et al., 2002). In a sample of patients with arthritis, the SF-12 was compared with the SF36 (Ware, Kosinki, and Gandek, 2002). For the SF-12, intraclass reliability correlations were 0.75 compared with 0.81 for the SF-36. Furthermore, the correlation between the two scales was found to be 0.94 (Hurst, Ruta, and Kind, 1998). In another study, the correlation between the PCS scores on the two instruments was 0.95. The correlation for the MCS was 0.97 (Ware, Kosinki, and Gandek, 2002). For the PCS items, Cronbach’s alpha was 0.81 whereas it was 0.84 for the MCS items (Lim and Fisher, 1999). As for the validity of the SF-12, the PCS scores had an R2 of 0.91 while that for the MCS was 0.92. (Ware, Kosinki, and Gandek, 2002). Ware et al. (2002) also compared SF-12 scores with those of the SF-36 derived from the same data set. It was found that the correlation between the SF-12 and SF-36 PCS was 0.95 while the correlation between the SF-12 and SF-36 MCS was 0.97 (Ware, Kosinki, and Gandek, 2002). The researchers also reported that in several

Underinsurance among Women who have availed of PhilHealth’s MCP international studies, the PCS correlations ranged from 0.94 to 0.96 while those for the MCS ranged from 0.94 to 0.97 (Ware, Kosinki, and Gandek, 2002). The agreement between scores was likewise high. On average, scores differed by less than one point. The percentile values also agreed within less than one point (McDowell, 2006). The standard deviations for the SF-12 were generally lower than those for the SF-36 (Ware, Kosinski, and Keller, 1996). The SF-12 showed neither ceiling nor floor effects in a study of patients with heart failure. On the other hand, two disease-specific instruments- the congestive heart failure questionnaire and the Minnesota Living with Heart Failure questionnaire- did (Bennett et al., 2002). The overall, general impression is that the SF-12 “performs remarkably well compared with the SF-36” (McDowell, 2006, p. 669). The SF-12 substantially reproduces the PCS and MCS scale values of the SF-36 while imposing only one third of the respondent burden. Should it be used for large samples, the loss of precision is likely to be insignificant. The SF-12, hence, is “remarkably effective as a brief but broad-ranging instrument, certainly suitable for survey use and also sensitive to change as an evaluative instrument.” (McDowell, 2006, p. 670). The SF-12 has been translated and adapted for use in 36 countries globally through the International Quality of Life Assessment project (Ware, Kosinski, and Keller, 1996). A version of the SF-12 written in the Filipino language and applicable for use in the Philippine health setting has been developed by QualityMetric and can be accessed through their website, http://www.qualitymetric.com/products/SFSurveys.shtml. This version of the SF12 will be used by this study for data collection. Proxy Means Test An important aspect of any social welfare program is being able to identify the target population for whom the benefits are intended for. Moreover, the adoption of an accurate and precise identification process/procedure allows for greater resource efficiency and maximum impact for the intended beneficiaries. In order to provide benefits to the poor, it is important to devise an appropriate and precise definition of the target group. Once the target group has been properly defined, a methodology must be found for identifying individuals or households that are in that group and for excluding those who are not. In the case of the poor as the target group for a specific social program/project, the process of identification adopted to include and exclude individuals one must involve precise judgment about the level of welfare or the means of the recipient. Conducting a means test that correctly measures the earnings of a household is the best way to determine eligibility when the poor are the target group (Narayan and Yoshida, 2005). However, a straightforward means test is hard to implement and carry out in developing countries primarily because applicants have an incentive to understate their welfare level, and verifying that information is difficult in developing countries where reliable records typically do not exist. In addition, income is also considered as an imperfect measure of welfare in developing countries, since it is unlikely to measure the accurately inputted value of ownproduced goods, gifts and transfers, or owner-occupied housing. Lastly, incomes of the poor in developing countries are also often subject to high volatility due to 27

Underinsurance among Women who have availed of PhilHealth’s MCP factors ranging from seasonality of agriculture and sporadic nature of employment in the informal sector. Since adjustments for such volatility are hard to make in practice, actual welfare from income measures are likely to be highly distorted. Given the administrative difficulties associated with sophisticated means tests and the inaccuracy of simple means tests, the idea of using proxy means tests that avoid the problems involved in relying on reported income is appealing. Proxy Means Test (PMT) involves using information on household or individual characteristics correlated with welfare levels in a formal algorithm to proxy household income or welfare. These instruments are selected based on their ability to predict welfare as measured by, for example, consumption expenditure of households. The obvious advantage of proxy means testing is that good predictors of welfare – like demographic data, characteristics of dwelling units and ownership of durable assets – are likely easier to collect and verify than are direct measures like consumption or income. PMTs tend to produce the best incidence outcomes in developing countries (Narayan and Yoshida, 2005). PMTs have been and continue to be used for various functions and purposes in the Philippines. One of their applications lies in the PhilHealth Indigent Program. The PhilHealth Indigent Program aims to provide health insurance privileges to the marginalized sector of Philippine society. Beneficiaries are identified through a survey called CBIS-MBN using the Family Data Survey Form (FDSF) which is conducted by the local Social Welfare Development Office. There is currently a two stage screening process to identify eligible beneficiaries to the PhilHealth Indigent Program. This screening process may lead to significant exclusion and, consequently, undercoverage. The current process entails first identifying poor barangays from which poor families in these poor barangays are selected. Poor barangays are identified by the Municipal/City Social Worker. Next, primary data collection is undertaken in all families in these “poor barangays”. Families whose reported incomes fall below a certain threshold are then classified as eligible. In this scheme, hence, poor families in “non-poor” barangays are automatically excluded from the program. In a study by Reyes (2006), the objective of which was to provide proxy means testing options to PhilHealth’s current practice in identifying beneficiaries for the Indigent Program, three alternative means testing options were considered: income, ownership of assets and socio-economic characteristics, and electricity consumption. A household is classified as poor or non-poor based on these three criteria. If the household is classified as non-eligible based on any of the categories, then that household is deemed not eligible for the PhilHealth Indigent Program (Reyes, 2006). Relying on income as the sole indicator of welfare/poverty has proven to be largely unreliable as the means for classifying households as poor or non-poor because of two primary reasons. First, if income tax returns or pay slips are to be the basis of confirming a household’s income, it is likely that, for low-income households which are often employed in the informal sector, they may not have pay slips. Also, low-income households are exempt from paying taxes and are not required to file income tax returns. In light of this, it is likely that the poor would not have verifiable income documents and so the other two criteria, socioeconomic index and electricity consumption, will be used.

Underinsurance among Women who have availed of PhilHealth’s MCP It has been established in many previous studies that income is highly correlated with ownership of assets, access to basic amenities and housing structure and tenure. In the study by Reyes (2006), the following variables were considered in determining the poverty status of the household: Television  VCD/VHS/DVD  Computer  Refrigerator  Washing Machine  Microwave oven  Telephone  Airconditioner  Car/Jeep/Motor Vehicle  Sanitary toilet facilities  Electricity  Safe water supply  Makeshift housing  Informal settlers  Household head not engaged in agriculture. To get an indication of the performance of the model, we can see how well it does in terms of classifying the families. Various cut-offs are tried in classifying whether a family is poor or non- poor. If a family has a probability of being nonpoor greater than or equal to the specified cut-off, then that family is classified as non-poor. Sensitivity is a measure of the probability of the family being classified as non-poor given that the family is actually non-poor. Specificity is a measure of the probability of the family being classified as poor given that the family is actually poor. The higher the probability cut-off, the lower is the sensitivity and the higher is the specificity of the model. Using the higher cut-off will result to a higher leakage rate but lower exclusion rate. It is recommended that cut-off of 0.8 be used since at this cut-off the poor are correctly classified as poor more than 90 percent of the time. Using a cut-off of 0.8 puts the specificity to 91.33% but reduces the sensitivity to 59.45%. The overall predictive accuracy is 68.95%. This implies that the exclusion will be less than 10%. This leakage can then be reduced by the other criteria that will be used such as income and electricity consumption. Electricity consumption, the last of the three alternative means testing options, has been used as a good indicator of the economic status of the household. The idea is that a poor household will have very few electrical appliances and light bulbs. Thus, electricity consumption will be closely correlated with poverty status. The key is to find that threshold of electricity consumption that can serve as the cut-off between the poor and the non-poor. In conclusion, the study by Reyes (2006) recommended a two-stage proxy means test which can be used to prioritize the eligible beneficiaries of the PhilHealth Indigent Program. First, it is recommended that the socioeconomic index using a probability cut-off of 0.8 be used at the first stage. The electricity consumption is used as the second filer. It is recommended that a cut-off of PhP 100 monthly electricity bill be used to identify the poor and therefore are eligible for the PhilHealth for the Indigent Program.

Underinsurance among Women who have availed of PhilHealth’s MCP Conceptual Framework Independent Variable

FACTORS

Socio-demographic Factors - Age - Education - Civil Status

Enabling Factors - Income - Length of membership in health insurance firm - Familiarity with benefits - Membership type

Perceived Health Status - Physical Health - Mental Health

SATISFACTION

Cost coverage

SATISFACTION

Services

SATISFACTION

Availment Prerequisites

SATISFACTION

Economic Dimension UNDERINSURANCE Benefits Dimension

Dependent Variable

Claims Process

Dependent Variable (Dummy Variable)

Figure 4. Conceptual Framework

A goal of the study is to determine factors that may serve as predictors of underinsurance. These factors were selected and based from the Review of Related Literature. Specifically, these factors can be grouped into three categories: sociodemographic factors, enabling factors, and perceived health status. This study’s definitions for socio-demographic and enabling factors were patterned after those in a study by Preskitt (2010), “Underinsurance in Children with Special Health Care Needs”. Socio-demographic factors are factors inherent to the study respondent as well as social and educational influences (Preskitt, 2010). Enabling factors are factors that may support or increase access to healthcare and health services (Preskitt, 2010). Perceived health status, as defined in this study, refers to 30

Underinsurance among Women who have availed of PhilHealth’s MCP the respondent’s perception of his general state of health. Specifically, it is broken down into physical health status and mental health status. Under enabling factors, the study will focus only on income, length of membership in a health insurance firm, membership type, and familiarity with benefits. All factors, being enabling factors, have been shown to be associated with and linked to access to healthcare and health services. Higher income is associated with increased access to health care (Dror et al., 2006; Freeman et al., 1987; Newacheck et al., 1996; Preskitt, 2010). A positive correlation also exists between length of membership and access to healthcare (Fincham and Wetheimer, 1985; Raebel et al., 2008; Weiss and Senf, 1990). The same is true for familiarity with benefits (Gordon, 1995; Morgan et al., 2008; Weiss and Senf, 1990). To date, a patient’s membership type has not been explored as an enabling factor and/or as a factor that may be associated with or linked to underinsurance. The researchers of this study, however, believe that the inclusion of this factor is nonetheless important especially in the context of PhilHealth which has 5 membership types. These three groups or categories of factors- socio-demographic factors, enabling factors, and perceived health status - are interrelated. In a general sense, socio-demographic factors are associated and have correlations with enabling factors (Clark and Oswald, 1996; Ferrer-i-Carbonell, 2005; Kawachi et al., 1999; Preskitt, 2010) and with perceived health status (Cockerham et al., 1983; Goldstein et al., 1984; Hunt et al., 1984; Kaplan and Camacho, 1982; Preskitt, 2010). Enabling factors also have correlations with perceived health status (Goldstein et al., 1984; Kaplan and Camacho, 1982; Preskitt, 2010; Soobader et al., 1999). Collectively, these factors represent the study’s independent variable. These factors have been found to affect and/or influence patient satisfaction. Specifically, they affect and/or influence patient satisfaction over four dimensions of the MCP- cost coverage, service coverage, availment prerequisites, and claims process. Patient dissatisfaction in and among these four dimensions subsequently leads to underinsurance. Hence, it becomes evident here that while patient satisfaction is a dependent variable in itself, it is more aptly described as a dummy variable- a variable that is to be directly measured but which only serves as a means to measuring another outcome variable. Measuring patient satisfaction is only the means of determining whether those who availed the MCP are underinsured or not. Underinsurance, therefore, is the final outcome variable being measured through patient satisfaction.

Operational Definition of Terms For a better understanding of the succeeding discussions, the following terms are defined as used in the study. Perceived Health Status – patient’s perceived health status as measured by the Short Form-12 version 2. It is broken down to perceived mental and physical health status. Perceived Familiarity with Benefits – the perceived familiarity of the patient with the benefits included in the Maternity Care Package of PhilHealth

Underinsurance among Women who have availed of PhilHealth’s MCP Membership Type – the membership category under which a claimant of the MCP is enrolled in Beneficiary Type – the category of a claimant which is divided into two types: dependent and primary beneficiary Dependent – an individual who was declared as a dependent of a member under the PhilHealth Primary Beneficiary – an individual who is identified by PhilHealth as the enrolled member Income – gross monthly income of the entire family of the claimant Underinsurance – condition of a claimant of being inadequately insured based on the satisfaction with the scope of benefits and financial risk protection provided by the MCP Benefits Underinsurance – condition of a claimant of being adequately insured based on the satisfaction with the scope of benefits provided by the MCP Economic Underinsurance – condition of a claimant of being adequately insured based on the satisfaction with the financial risk protoection provided by the MCP Scope of Benefits – all health services and interventions covered by the package, including the non-economic characteristics associated with their delivery. This includes provisions regarding service coverage, availment prerequisites, and claims process in the MCP. Service Coverage – the provisions regarding the services included in the benefit package. It is broken down to 4 categories provided in the MCP: pre-natal care, delivery proper, postpartum care and reproductive health education. Availment pre-requisites – a set of conditions provided for under the MCP which much be fulfilled by the claimant before they can avail of the Maternity Care Package. These include 4 required prenatal visits, that the first prenatal visit should not exceed 16 weeks AOG, and required premium contribution. Claims Process in the MCP – a set of conditions the provided for under the MCP that must be fulfilled by the claimant in order to receive the financial benefits of the MCP. This includes the requirements for filing an MCP claim, separate forms for the MCP, and the number of days allotted to file an MCP claim. Patient Satisfaction – patient’s perception of the adequacy of the scope of benefits and financial risk protection afforded to her by the MCP Prevalence of Underinsurance- number of dissatisfied women who have availed of the MCP who were included in this study in proportion to the total number of women who have availed of the MCP who were included in this study

Underinsurance among Women who have availed of PhilHealth’s MCP CHAPTER III METHODOLOGY This study will seek to identify the factors that can affect underinsurance among women who have availed of PhilHealth’s MCP from May to November of 2013 in Pasig City, Philippines. To find answers to the research problem, the cross-sectional study design is deemed the most appropriate design for this study. A cross-sectional design is a study where exposures and outcomes are measured simultaneously at one point in time; it is a snapshot of a current situation of interest (Coggon, Rose, and Barker, 1997). The researchers will be measuring patient satisfaction with the MCP and the predictors of patient satisfaction simultaneously, specifically at the time when a woman files her MCP PhilHealth claim in the respective MCP-accredited facilities in Pasig City. The researchers opted to use the cross-sectional design because it will be quicker to gather data, it requires no follow up, and it requires less resources and financing compared to other study designs. Although descriptive study designs such as the cross-sectional design cannot establish a cause-and-effect relationship between the variables being measured in the study, it will be able to suggest if there are significant associations between and among variables. This study design is also an excellent way to determine prevalence of underinsurance over the MCP among the study’s respondents. The following diagram illustrates the research design of this study. Benefit-dimension Underinsured and Economic-dimension Adequately Insured

Sample Population

PhilHealth Accredited Lying-in Clinics

Economic-dimension Underinsured and Benefitdimension Adequately Insured

Underinsured

Benefit-dimension Underinsured and Economic-dimension Underinsured Economic-dimension Adequately Insured and Benefit-dimension Adequately Insured Figure 5. Research design of the study

Adequately Insured

Underinsurance among Women who have availed of PhilHealth’s MCP Participants and Setting This study’s setting is Pasig City, an urban municipality located in the 2 nd district of the National Capital Region (NCR) of the Philippines. It is bordered on the west by Quezon City and Mandaluyong City, on the east by Antipolo City, on the north by Marikina City, and on the south by Makati City, Pateros, and Taguig City. Pasig is primarily residential, though it has become increasingly commercial in the past few years (Pasig City Government, 2010). It is a first class municipality based on income classification, with an annual GDP of $12, 032. Still, 65.4% of Pasig is classified as urban poor. As of 2010, Pasig City had a population of 617, 301 (NSCB, 2010), which is the fourth highest in the region. It has an average household size of 4.66. There are 30 barangays, all of which are classified asurban. In the same year, the municipality recorded a total of 11,639 live births. Since 2008, Pasig City has consistently had one of the highest MMRs in both NCR and the entire Philippines. Its MMR has in fact been on the rise. Pasig City’s MMR reached 371 in 2008 (FHSIS, 2008), 218 in 2009 (FHSIS, 2009), and 266 in 2010 (FHSIS, 2010). All these MMRs are off-target from the MDG of 52 maternal deaths per 100, 000 live births by 2015. Pasig City was chosen as the study’s setting primarily because of its consistently high MMR in both NCR and the Philippines. As was established in this study’s Review of Related Literature, underinsurance can lead to compromised health status. And if women of birthing age are particularly affected, this compromised health status may subsequently lead to maternal deaths. Given that Pasig City has consistently had very high MMRs in the past few years, this study posits that there is a high probability that underinsurance among women availing of the MCP in this municipality is likewise high. Underinsurance, in fact, may be one of the primary factors aggravating the municipality’s maternal health situation. Second, Pasig City was chosen as the setting also because of the feasibility and convenience it affords the researchers. Given this study’s time constraints and budget limitations, Pasig City is one of the most physically accessible municipalities to the researchers. Visiting each of the partnered birthing and lyingin clinics across the different barangays of Pasig City would not demand too much time and resources on the part of the researchers who will be doing it on a regular and periodic basis. According to the Pasig City Health Department, Pasig City has a total of 66 maternity clinics which comprise birthing and lying-in clinics located across the 30 barangays of the municipality (Pasig City Health Department, 2012). Of these 66 maternal health facilities, 17 are PhilHealth-accredited. Hence, 17 birthing and lying-in clinics offer PhilHealth’s MCP. The following table enumerates the names of these facilities and their addresses. Appendix F shows a map of Pasig City depicting the locations of these facilities by means of their corresponding number codes.

Underinsurance among Women who have availed of PhilHealth’s MCP Table 3. PhilHealth-accredited birthing and lying-in clinics offering the MCP in Pasig City, Philippines Number Code 1 2 3 4 5

Name of Birthing Clinic/ Lying-in Clinic Che Midwife LIC Clinica Paiso-Ramos Maternity LIC Well Care Maternity, Medical, and Pediatric Clinic Inc. Well Care LIC

St. Christiana Maternity Hospital F.B. Ancheta Childrens Maternity and LIC Pasig Medical and Maternity Hospital Foundation Gertrudes Luderico Well Family Clinic T/V’s Medical Clinic

10 11 12 13 14

MCLC Maternity Clinic L. Salonga Birthing Home Divine Grace Maternity Clinic Abelido’s Birthing Center Immaculate Concepcion LIC

15 16

Catapang-Combate OB-Gyne Clinic Liza Aguilar-Racuya LIC

God Gift LIC Services

6 7 8

Address 109 C2 Paseo de Animales St., Bgy. Santolan 102 Amang Rodriguez Ave., Bgy. Santolan 3223 Kaimito St., Napico, Bgy. Manggahan 1596 Ma. Bldg., Magsaysay, Bgy. Manggahan Lot 2 Blk. 1 3238, KV, Magsaysay, Bgy. Manggahan Lot 4 Blk. 36, Kaginhawahan, Karangalan, Bgy. Manggahan 101 London St., PGPV, Bgy. Manggahan Blk 2 Lot 17 West Bank Road, Bgy. Santa. Lucia Blk 1 Lot 26 Bliss East Bank Road, Barangay Sta. Lucia 111 Dr. Pilapil, Bgy. Sagad 106 R. Valdez St., Bgy. Bagong Ilog Blk 1 Lot 15, Bgy. San Nicolas 41 Villa Antonio, Bgy. Bambang Immaculate Concepcion St., Bgy. San Miguel 318 Willa Rey Hi-way, Urbano Velasco Ave., Bgy. Pinagbuhatan Noah Rd., Dreamville, Centennial II-B, Nagpayong, Bgy. Pinagbuhatan Aries St., Maryland, Centennial II-A, Bgy. Pinagbuhatan

The study’s minimum sample size was calculated by factoring in the following input variables: (1) number of predictor variables, (2) anticipated effect size (f2), (3) desired statistical power level (1-β), and (4) probability level. These four variables were inputted into a software which calculates sample size for multiple regression analysis, the Statistics Calculators: A Priori Sample Size Calculator for Multiple Regression Studies. This study has 10 predictors corresponding to the 10 factors being determined as significant predictors of underinsurance, namely: age, educational attainment, civil status, income, perceived familiarity with benefits, perceived physical health status, perceived mental health status, length of membership, membership type, and dependency or primary beneficiary. A study’s anticipated effect size is a measure of the strength of the relationship between two variables in a statistical population or a sample-based 35

Underinsurance among Women who have availed of PhilHealth’s MCP estimate of that quantity (Kelley and Preacher, 2012). For this study, the anticipated effect size (f2) was set at 0.15. This value is what is commonly set by similar studies which also employ multiple regression analysis. Desired statistical power level refers to the probability that a statistical test will reject the null hypothesis when it is false. Hence, it is a measure of the probability of not committing a Type II error or a false negative. As the statistical power level increases, the probability of committing a Type II error decreases. Because the probability of committing a Type II error is called the false negative rate (β), statistical power level is equal to 1- β. This study has set its statistical power level at 0.80 which is the statistical power level commonly set by similar studies employing multiple regression analysis. Lastly, a study’s probability level is the probability of obtaining a test statistic at least as extreme as the one actually observed, assuming that the null hypothesis is true (Goodman, 1999). If the probability level is less than the predetermined significance level α, the null hypothesis is rejected. The commonly set probability level for similar studies employing multiple regression analysis is 0.05 which is the value which this study has also used. With the number of predictors set at 10, the anticipated effect size (f2) set at 0.15, the desired statistical power level (1-β) set at 0.80, and the probability level set at 0.05, the software Statistics Calculators: A Priori Sample Size Calculator for Multiple Regression Studies calculated the minimum sample size of this study to be 118. Despite this minimum sample size, this study will set a target sample size of 145 in order to account for non-responsiveness on the part of MCP claimants who may not be willing to answer the survey as well as MCP claimants who submit incompletely answered surveys. The target sample size of 145 is the calculated sample size inflated by 20%. This study’s sampling algorithm is discussed in Appendix. This study will make use of non-probability convenience sampling in including study participants. Non-probability convenience sampling is a sampling technique in which the probability of obtaining a particular sample cannot be calculated (Lucas, 2012). In other words, it does not involve random selection of study participants. Non-probability convenience sampling will be used in the study because all patients who will go to one of the PhilHealth-accredited birthing or lying-in clinics in Pasig City to file their MCP claims within the allotted time period for data collection and are willing to answer the survey will be participants of this study. Non-probability convenience sampling was deemed the most appropriate sampling technique for this study because the characteristics of the respondents who need to be included in the study would make it hard to reach the required sample size had a randomized sampling been used. This sampling method runs the risk of over representing or under representing certain group of individuals included in the study. Data Collection In order to quantify the proportion of underinsured women, the researchers will use patient satisfaction as a measurable outcome. The researchers will be using this method because low patient satisfaction has been proven to be associated to underinsurance as discussed in the Review of Related Literature. 36

Underinsurance among Women who have availed of PhilHealth’s MCP Underinsurance, though, has two dimensions – the economic dimension and benefits dimension. As such, the researchers will measure patient satisfaction for both aforementioned dimensions of underinsurance. In order to measure patient satisfaction, the researchers will administer a survey tool that will be answered by women who will file their MCP claims from May to November of 2013 in PhilHealh-accredited maternity clinics in Pasig City, Philippines. The survey will contain questions to measure each of the independent variables in the study. The researchers’ main outcome variable, patient satisfaction, will be measured for cost coverage, service coverage, pre-requisites for filing MCP claims, and the claims process associated with the use of the MCP. The benefits dimension of underinsurance will be measured using the satisfaction for service coverage, pre-requisites for filing MCP claims, and the claims process. Consequently, the economic dimension of underinsurance will be measured using the satisfaction for the cost covered. Each survey question for satisfaction will be answered using a 4-point Likert scale using the options “Strongly Agree”, “Agree”, “Disagree” and “Strongly Disagree”. Each option will correspond to a score. This study has two phases for data collection. The first phase is pre-testing the survey tool while the second phase is using the revised survey tool to obtain data from all women who gave consent to be part of the study and who have claimed of the MCP in the PhilHealth-accredited maternity clinics in Pasig City. Pre-Testing of Survey Tool

Phase 1.1 Identification of Variables and Factors

Phase 1.2 Drafting of Survey Tool

Phase 1.3:

Phase 1.4

Pre-Testing of Patient Satisfaction Questionnaires

Revision of Patient Satisfaction Questionnaire

Figure 6. Methodological Flow of Pre-Testing the Survey Tool Figure 6. shows how Phase 1 will be carried out. There are four distinct sub-phases: identification of variables and factors, drafting of the survey tool, pretesting of the Patient Satisfaction Questionnaire (PSQ), and revision of the PSQ. The first sub-phase- identification of variables and factors- entails identifying factors and variables that may affect or are associated with 37

Underinsurance among Women who have availed of PhilHealth’s MCP underinsurance or patient satisfaction. This was done through secondary literature review. The studies that were included in the secondary literature review focused on patient satisfaction and underinsurance locally and globally, and the variables and factors identified by previous studies as significant predictors or have a significant association with underinsurance or patient satisfaction were included in this study. These factors can be found in the Conceptual Framework in Chapter 2. Two other variables- Membership Type and Beneficiary Type- were not tackled or mentioned in any previous study found in the secondary literature review. Nonetheless, this study will still consider and include them as part of the independent variables because of the instrumentality of their roles in PhilHealth’s services and other benefits packages. The researchers have already completed Phase 1.1. Drafting the survey tool follows the identification of variables and factors. The survey tool has three parts: the Patient Satisfaction Questionnaire (PSQ), the Proxy Means Test (PMT), and the Short-Form 12 Version 2 (SF-12 V2) Health Survey (Tagalog Version). The full text of the Patient Satisfaction Questionnaire can be found in Appendix C. The Proxy Means Test will be employed to supplement the study’s survey tool. The Proxy Means Test (PMT) allows for the classification of the survey respondents as either being non-poor or poor, and the results will be used to validate the gross monthly income that will be written by the respondent in the survey tool. The PMT to be used was adopted from the study of Padayao et al. (2012), which was based on the study of Reyes (2006). The full text of this PMT survey tool can be found in Appendix A. The last part is the SF12 V2 Health Survey (Tagalog Version), licensed from QualityMetric, Inc. Of the three, only the PSQ will be pre-tested since the PMT and SF-12 V2 Health Survey (Tagalog Version) have already been pre-tested by many other prior studies and researches. The full version of the SF-12 can be found in Appendix B. Pre-testing the PSQ will be accomplished through two methods: expert interviews and a mock implementation of the PSQ. The pre-testing will be done to refine the contents of the PSQ and ensure that it will accurately gather the data needed during the last phase of data collection. The first step is translating the PSQ into Filipino. An expert in Filipino, most probably a professor from the Ateneo de Manila University’s Filipino Department, will then be asked to backtranslate the Tagalog version of the PSQ into English to check whether there is language correspondence in the translation of the PSQ that was previously done by the researchers. If there is no language correspondence, then the researchers will re-translate the PSQ into Tagalog again but with new wording and phrasing. This will continue until language correspondence is reached with the backtranslation of the PSQ. Interviews with a statistician, a psychologist, a sociologist, the head of the PhilHealth Millennium Development Goals (MDGs)/Benefits Team will then be conducted in order to assess the Face and Content Validity of the PSQ. All three experts will be asked how the PSQ assesses the desired variables/factors as well as how the PSQ samples relevant content. They will do so by rating each item question on a 5-point Likert scale that ranges from “Extremely Suitable” to “Irrelevant”. Items that scored as irrelevant will be removed from the PSQ while items that scored as suitable will be retained. These experts will also be asked to judge the PSQ on specific issues regarding the form. The head of the PhilHealth MDGs/Benefits Team will be asked to assess whether the contents of the PSQ are sufficient and exhaustive of the provisions laid out in the MCP. The statistician and the psychologist/sociologist will be asked to 38

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP determine if the questions in the PSQ are phrased properly and clearly, arranged sequentially, and checked for duplicity errors. Once the PSQ has been modified based on the results and recommendations from the expert interviews, a mock use of the revised PSQ will be done. The sample size for the mock implementation will be 50 individuals, who will be women who will claim the MCP in the 17 PhilHealth-accredited lying-in clinics found in Pasig City. The sampling method to be used will be nonprobability convenience sampling, which means that women who have availed of the MCP in these clinics will be sought out continuously until the sample population has been reached. A preliminary consultation has already been conducted with the clinic owners of the 17 PhilHealth-accredited lying-in clinics. They have shown interest in cooperating with the pre-testing of the PSQ as well as the actual data collection. The group will send, along with the final study proposal, a letter asking permission to allow the researchers to conduct the pretesting in their clinics with the assistance of their clinic staff. Upon approval of the pre-testing request, the researchers will conduct a preliminary visit to the 17 PhilHealth-accredited lying-in clinics to establish rapport and to brief the clinic staff about the study and the rationale as to why the researchers were there. On the second visit, the researchers will orient the staff on the pre-testing process including administering and handling the collation of the PSQ, as well as give the staff the PSQs and ballot boxes. The entire pre-testing process will also serve as an avenue for pilot-testing the proposed survey administration and collation methodology that will be adopted for the actual data gathering as well. With regard to administering the PSQ, the clinic staff is to provide a copy of the PSQ to the woman immediately after they finish the claims process for the MCP. The clinic staff is to accommodate and clarify any questions that the survey respondents may have and the clinic staff will stay with the survey respondent until they finish answering the PSQ. Staff will also be instructed to ask respondents for complaints or suggestions about the survey. Regarding the collation of the finished PSQs, the clinic will use the ballot box for the survey respondents to drop their completed PSQ in. This is to protect the completed PSQ from being tampered or accidentally compromised by either the researchers, the clinic staff or from others. The survey respondents must drop their completed PSQ in the ballot box personally. The clinic staff is to ask the survey respondents to drop the completed PSQ into the ballot box by themselves. The researchers are to take home the ballot box filled with PSQ forms every Friday of the week. A replacement ballot box will be provided to the clinic while the researchers are still encoding the data from the previous ballot box. Random visits will also be done by the researchers twice a week to audit and observe how the staff is doing the survey administering and collation. During random visits, the researchers will conduct think-aloud sessions with survey respondents to determine if some parts are incomprehensible and will also ask single questions on how the survey can be improved. These days are to be determined by the researchers randomly. Upon reaching the quota, an FGD will be conducted with the staff of each clinic for observations during the pre-testing, the PSQ itself, the administering method, collation, and how these can be improved. It is targeted that the pre-testing of the PSQ would be done by the end of April or by mid-May. Revising the PSQ involves data analysis on the survey responses conducted to determine which items/responses will be retained, modified or 39

Underinsurance among Women who have availed of PhilHealth’s MCP discarded. These may also refer to item generation, wording, and order. The generation of items during the construction of the survey tool required considerable pilot work to refine wording and content. In ensuring content/“face” validity, or how adequately the questions selected cover the themes specified in the conceptual definition of the study’s scope, the items are to be given for analysis to experts in the field and to the proposed respondents. Another key strategy in item generation is to frequently revisit the research questions to ensure that the survey items address these. The proposed subscales of the questionnaire are identified at this stage as well. Likert-type or frequency scales using fixed choice response formats will be employed. These scales are designed to measure attitudes or opinions and levels of agreement/disagreement. (Bowling 1997, Burns and Grove 1997) A Likert-type scale assumes the strength/intensity of experience is linear, i.e. on a continuum from strongly agree to strongly disagree, and makes the assumption that attitudes can be measured. The item and factor analysis stages of the questionnaire development process may then be used to establish if such items are indeed representative of the expected subscale or factor. Piloting provides the researchers with a concrete basis on which items to include or delete in the measuring tool. Item analysis is one of the ways to pilot a questionnaire – to identify items that lack clarity or that may not be appropriate for, or discriminate between, respondents. Two decision aids will be used for the closed ended survey questions included in the PSQ. The first is computing for the Frequency of Endorsement. Frequency of endorsement rates informs of the proportion of respondents who give each response alternative to a certain item. High endorsement of an option within a particular item suggests poor discriminatory power or the redundancy of an item that requires deletion (Priest et al., 1995). Frequency of Endorsement is calculated through:

Only items with endorsement rates that fall within 0.20 to 0.80 will be used, in according to the standards presented by Streiner et al., in Health Measurement Scales: A Practical Guide to their Development and Use. The second is computing for Discrimination Ability. The measure of discrimination ability distinguishes between those who score high and those who score lower in a particular test. This tells us of the propensity of high-scoring respondents to endorse specific items. The calculation involves (U-L)/n where U = the number of people above the median who score positive on an item, L = the number of people below the median who score positive on an item, and n = number of people above the median. Reliability must also be tested for the PSQ questions using Likert scales. Reliability refers to the repeatability, stability, or internal consistency of a questionnaire (Jack and Clarke, 1998). This can be assessed using a variety of tools. The first is computing for Cronbach’s Alpha. This is one of the most common ways in demonstrating reliability. Cronbach’s alpha will be used as an aid to check internal consistency for items with more than two response alternatives.This statistic uses inter-item correlations to determine whether items 40

Underinsurance among Women who have availed of PhilHealth’s MCP are measuring the same domain/grouping (Jack and Clarke, 1998). An alpha value less than 0.70 suggests poor grouping for (<7) items in a questionnaire scale responded to by less than 100 subjects, and less and 0.90 for (>11) items with the same number of subjects (Streiner et al., 2008). Items failing to meet the cut-off will consequently be discarded. A second is through Inter-Item Correlation . This is another measure for internal consistency of (sub)scales. The items on a scale are ideally moderately correlated to one another, with r values at least 0.30, to ensure homogeneity. Item analysis using inter-item correlations will also identify those items that are too similar. High inter-item correlations (>0.80) suggest that these items are indeed repetitions of each other, more commonly referred to as bloated specifics (Kline, 1993). A third is Item-Total Correlation which can be used to assess internal consistency. To identify specific items that do not add to the explanatory power of the questionnaire or (sub)scale, only an item-total correlation of greater than 0.20 will be used (Streiner et al., 2008, Rattray, 2005) Item-total correlation can also cue the homogeneity of the items in a (sub)scale by correlating each item with a scale total, filtering out those that do not meet cut-off, rank-ordering the remaining ones, and selecting items beginning with the highest correlation. A fourth is Standard Error Measurement or SEM. The standard error of measurement (SEM) as defined in the Standards for Educational and Psychological Testing (1985), is the standard deviation of errors of measurement that is associated with the test scores for a specified group of test takers Mathematically, SEM can be computed for with the formula =

√1−

If the reliability of the test is zero, the SEM will be equal to the standard deviation of the obtained test scores. If the reliability of the test is +1.00, the highest possible value, the SEM is zero. There would be no errors of measurement with a perfectly reliable test; a set of errors all equal to zero has no variability. (Harvill, 1991) The type of reliability coefficient used in calculating the SEM can make a difference, both computationally and logically. A long-term stability coefficient (e.g. test-retest with six months intervening) would be expected to be lower than a short-term stability coefficient (e.g. single administration through coefficient alpha or Kuder-Richardson 20) for the same test. Since a lower reliability estimate will provide a higher SEM estimate, the type of reliability coefficient used can have an effect on the magnitude of the SEM (Harvill, 1991). For the purpose of this study, Cronbach’s alpha will be used for a singly-administered content sampling, standing as the reliability coefficient value in computing for the SEM. Other than reliability, the results must also possess validity. Validity refers to whether a questionnaire is measuring what it intends to (Jack and Clarke, 1998). While validity may be more difficult to establish, it remains vital in the research process In assessing validity, the following tests will be used. Content Validity, as already established, refers to expert opinion concerning whether the scale items represent the themes specified in the conceptual definition of the study’s scope. However, content validity is only the initial step in establishing validity Construct validity will relate how well the items in the questionnaire represent the underlying conceptual structure. (Rattray, 2005) To aid the process, 41

Underinsurance among Women who have availed of PhilHealth’s MCP an exploratory factor analysis (EFA) will be done to discover simpler patterns in the larger pattern of relationships among the variables. In particular, the factor analysis will seek to discover if the observed variables can be explained largely or entirely in terms of a much smaller number of variables called factors (Darlington, 1973) based on factor loading scores. Factor loading scores will be the basis in assessing convergent and discriminant validity by correlating the measure with related and/or dissimilar measures. (Bowling, 1997) Convergent validity sees to it that the variables within a single factor are highly correlated. Significant loadings depend on the sample size with a roughly inverse relationship. For the study’s sample size of 118, the sufficient loading score must not be less than 0.50. Discriminant validity, on the other hand, refers to the extent to which factors are distinct and uncorrelated. The rule is that variables should relate more strongly to their own factor than to another factor. Two primary methods exist for determining discriminant validity during an EFA. (Streiner et al., 2008) The first method will examine the pattern matrix. Variables should load significantly only on one factor. If “cross-loadings” do exist, then the cross loads should differ by more than 0.2. The second method will examine the factor correlation matrix. Correlations between factors should not exceed 0.7. A correlation >0.7 indicates majority of shared variance Revisions to the tool will be done after this data analysis, and may include rephrasing of questions, addition and deletion of statements, and changing the format of the tool. The specifics of the statistical tools and tests that will be used to refine the PSQ are laid out in the subsequent Data Analysis section of this chapter. Once the data analysis has been finished and the PSQ revised, the results of the data analysis, along with the revised PSQ will be presented once again to the experts previously interviewed. Comments and suggestions from the experts will be accounted for prior to making the final draft of the PSQ. The final draft of the PSQ, along with the SF-12 V2 Health Survey (Tagalog Version) and the Proxy Means Test, will comprise the survey tool to be used in Phase 2 of data collection. Actual Data Collection

Phase 2.2

Phase 2.1 Data Gathering with the Survey Tool

Data Encoding and Analysis of Survey Responses

Figure 7. Methodological Flow of Implementation of Revised Survey Tool Figure 7. shows how Phase 2 will be carried out in two distinct sub-phases, which will be explained in detail below. Data gathering using the survey tool will use methods similar to those 42

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP sought in pre-testing the PSQ. The survey tool to be used will contain all three aforementioned components: the PSQ, the PMT and the SF-12 V2 Health Survey (Tagalog version). Another letter will be sent again to the 17 clinic owners, asking permission from them to allow the researchers to conduct the actual data gathering in their clinics with the assistance of their clinic staff using the revised survey tool. Upon approval of the data gathering request, the clinic staff will be reoriented on how the survey tool will be administered and collated afterwards on the first visit. On administering the PSQ, the clinic staff are instructed to provide a copy of the PSQ to the woman immediately after she has finished with the claims process for the MCP. The clinic staff are also instructed to accommodate and clarify any questions that the survey respondent may have. Last, the clinic staff are instructed to stay with the survey respondent until she finishes answering the PSQ. In order to collate the completed PSQs, the clinic will be given a ballot box where the survey respondents must drop their completed PSQs into. This is to protect the completed PSQ from being tampered or accidentally compromised by either the clinic staff or from other external forces. The survey respondents must drop their completed PSQ in the ballot box personally. The clinic staff will be instructed to ask the survey respondents to drop the completed PSQ into the ballot box by themselves. The clinic staff are also instructed to store the filled ballot box in a secure and undisclosed location within the clinic for safekeeping until the researchers come to collect the ballot box. In the meanwhile, a replacement ballot box will be provided to the clinic while the researchers are still encoding the data from the previous ballot box. The clinic staff will also be given copies of the survey tool along with the ballot boxes on the first visit. A primer info graphic will also be provided to the clinic staff that contains a condensed representation of how to administer and collate the PSQ, which they can occasionally refer to should they experience difficulty in recalling what was discussed during the orientation seminar, on the second visit. The succeeding visits to the 17 lying-in and birthing clinics will be in order to collect the PSQs that have already been filled up so that they could already be encoded into the data management system while data collection is ongoing. The succeeding visits to the 17 lying-in clinics will be done on the Friday of every other week after the first visit or until the number of survey respondents reaches the sample size. Since the actual data gathering is projected to span the months of May to November, the ballot boxes with the completed survey tools inside of them will now be collected every Friday every other week each month starting May until November. If the sample size that is needed for data collection has not been met by November, data collection will be extended until the sample size has been achieved. Data encoding will transpire every time ballot boxes with the completed survey tools inside of them have been collected from the 17 lying-in and birthing clinics. Both the data encoding and analysis will be done using SPSS software. The specific details on data encoding and analysis will be laid out in the subsequent section on Data Analysis in this chapter.

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP Data Analysis To determine if a patient is satisfied or not, collected data will be analyzed. A sub-total for each dimension of underinsurance will be tabulated and will be analysed. The scores above the median will be classified as satisfied and those below the median will be classified as not satisfied. Since sub-totals will be used, an individual can be underinsured in either of the two dimensions or both. Whenever a mother is identified as underinsured in either of the dimensions, she will be classified as underinsured using the model of Ward (2006). An overall underinsurance will also be tabulated by adding both sub-totals. This score will be usable in the bivariate and multivariate analysis of data as a continuous type of data. And a lower satisfaction will correspond to a higher occurrence of underinsurance. Aside from simply determining the underinsured and not underinsured respondents, the research will also entail quantifying the effects of the independent variables on the dependent variable which is underinsurance. In order to analyze the data that the researchers will already be collecting in its actual data gathering, a series of statistical tests will be utilized. First, the researchers will make distribution tables and frequency tables to get a descriptive look of the data that has been gathered. More descriptive statistics such as the mean, median, and mode will also be computed. To have a more in depth analysis of these descriptive data, analytical statistics will be administered. To test for a significant association between each independent variable and the dependent variable, a number of bivariate analyses will be conducted. Given that the dependent variable of this study will be in the interval scale of measurement, the following table briefly explains how the researchers will go about the bivariate analysis including how the data will be encoded. Table 4. Bivariate data analysis and encoding Independent Variable (IV)

Age

Educational Attainment

Civil Status

Scale of Measurement of IV

Expected Response/s

Interval

Nominal

Encoded As Variable

Statistical Test to Use Pearson

Age

Elementary

Ed-1

High School

Ed-2

Vocational

Ed-3

One-way

College

Ed-4

ANOVA

Post-graduate

Ed-5

No education

Ed-6

Single

CV-1

Correlation

One-way

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP

Income

Means Test

Length of Membership

Interval

Nominal

Interval

Perceived Familiarity

Married

CV-2

Separated

CV-3

Widowed

CV-4

Income

Inc

Poor

MT-1

Non-poor

MT-2

Length of Membership

LoM

Familiar

FB-1

Unfamiliar

FB-2

Interval

SF-12 score

MHealth

Interval

SF-12 score

PHealth

Nominal

with Benefits Perceived Mental Health Status Perceived Physical Health Status

Sponsored

e1=0, e2=0, e3=0, e4=0

Individually Paying

e1=1, e2=0, e3=0, e4=0

Employed

e1=0, e2=1, e3=0, e4=0

Lifetime

e1=0, e2=0, e3=1, e4=0

OFW

e1=0, e2=0, e3=0, e4=1

with Benefits Perceived Mental Health Status Perceived Physical Health Status

Membership

Nominal

Type

(dummy)

Beneficiary

Nominal

Primary

f1=0

Type

(dummy)

Dependent

f1=1

In the data encoding, dummy variables will be used for nominal scaled variables so that they can be fit into the model. A regression model which accounts for all the independent variables will be proposed by the group. Based on how the variables will be encoded, the proposed multiple linear regression model will be expressed as follows: PS(Y) = PSo + α1(age) + α2(a1) + α3(a2) + α4(a3) + α5(a4) + α6(a5) + α7(b1) + α8(b2) + α9(b3) + α10(Inc) + α11(c1) + α12(LoM) + α13(d1) + α14(MHealth) + α15(PHealth) + α16(e1) + α17(e2) + α18(e3) + α19(e4) + α20(f1) PS(Y) is a function of PSo, which is the y-intercept in the regression line, and a series of terms, each corresponding to an effect to the PS(Y). α n, which is the correlation coefficient for the corresponding variable that it is paired with, is a measure of how much a variable affects the PS(Y) with respect to the variable that it is paired with. In the conceptualizing of the study, one confounding variable has been identified. This is that the claimant might have had previous MCP claims and might therefore affect the current claim that the study entails to analyze. In order to control for this in the data analysis stage, its effect will first be measured using bivariate analysis, specifically by the use of the two independent samples t-test. If there is a significant difference between the mean patient satisfaction score of those who have had multiple claims as compared to those who are claiming for the first time, then this confounding variable will be accounted for in the model for the multiple linear regression. 47

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP TIME SCHEDULE Table 6. Time schedule for Jan to Mar 2013

Phase 1.1

1.2

1.3

Month Jan Week 1 2 Activity Identification of Variables and Factors Secondary Literature review Drafting the survey tool Obtaining the Proxy Means Test Obtaining Short-Form 12 Version 2 Writing of the PSQ Pre-testing of Patient Satisfaction Questionnaires Translate the PSQ to Filipino Back translation by expert Revising translation Second back translation Interviews with three experts Revision of PSQ

Feb 1 2

Mar 1 2

Jun 1 2

Table 7. Time schedule for Apr to Jun 2013

Phase 1.3

2.1

Month Week Activity Pre-testing of Patient Satisfaction Questionnaires Revision of PSQ Sending letters of permission to conduct pre-testing Preliminary visit First training visit Random visits for collection and monitoring Revision of PSQ Data Gathering with the Survey Tool First visit Collection visit Encoding data

Apr 1 2

May 1 2

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP Table 8. Time schedule for Jul to Sept 2013

Phase 2.1

Month Week Activity Data Gathering with the Survey Tool Collection visit Encoding data

Jul 1

Aug 1 2

Sept 1 2

Dec 1 2

Mar 1 2

Table 9. Time schedule for Oct to Dec 2013

Phase 2.1

2.2

3.1

Month Week Activity Data Gathering with the Survey Tool Collection visit Encoding data Data Encoding and Analysis of Survey Responses Descriptive Statistics Analytical Statistics Analysis and Discussion of results Formulation of discussion

Oct 1 2

Nov 1 2

Table 10. Time schedule for Jan to Mar 2014

Phase 4.1

Month Week Activity Final defense and paper Editing and finalizing of paper Preparations for defense Final defense Paper submission

Jan 1 2

Feb 1 2

RESEARCH PERSONNEL The health staff/workers of all the PhilHealth-accredited birthing and lying-in clinics which agreed to partner with the study will first be oriented on their role in the studyâ&#x20AC;&#x2122;s data collection. Specifically, the researchers will brief the health staff on how to give the survey to each MCP claimant and where to deposit the survey once it has already been answered. The researchers will also give them an infographic reminding them of their task. On a subsequent visit to these 49

Underinsurance among Women who have availed of PhilHealth’s MCP birthing and lying-in clinics, the researchers will then leave the health staff with ball pens, the actual survey forms, and a box where answered surveys will be deposited. The health staff will also be informed of the study’s incentive scheme: that they will be given PhP 40 for every three survey forms answered by MCP claimants. After the researchers have conducted these initial series of visits will the health staff of each clinic start giving survey forms to each person who files her MCP claim in these clinics from April to November of 2013. The researchers will visit each clinic every other week to collect all survey forms which have already been answered. The responses in these survey forms will subsequently be analyzed. The researchers, hence, serve as the data analysts of the study. RESEARCH FACILITIES This study will establish partnerships with all willing PhilHealthaccredited birthing and lying-in clinics offering the MCP in Pasig City. According to the Pasig City Health Department, there are 17 such facilities spanning the different barangays of the municipality (Pasig City Health Department, 2012). The names of these birthing and lying-in clinics together with their corresponding addresses are listed in the succeeding table. Table 11. The 17 PhilHealth-accredited birthing and lying-in clinics offering the MCP in Pasig City, Philippines Number Code 1 2 3 4 5

Name of Birthing Clinic/ Lying-in Clinic Che Midwife LIC Clinica Paiso-Ramos Maternity LIC Well Care Maternity, Medical, and Pediatric Clinic Inc. Well Care LIC

St. Christiana Maternity Hospital F.B. Ancheta Childrens Maternity and LIC Pasig Medical and Maternity Hospital Foundation Gertrudes Luderico Well Family Clinic T/V’s Medical Clinic

10 11 12 13 14

MCLC Maternity Clinic L. Salonga Birthing Home Divine Grace Maternity Clinic Abelido’s Birthing Center Immaculate Concepcion LIC

6 7 8

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP

15 16

Catapang-Combate OB-Gyne Clinic Liza Aguilar-Racuya LIC

God Gift LIC Services

Miguel 318 Willa Rey Hi-way, Urbano Velasco Ave., Bgy. Pinagbuhatan Noah Rd., Dreamville, Centennial II-B, Nagpayong, Bgy. Pinagbuhatan Aries St., Maryland, Centennial II-A, Bgy. Pinagbuhatan

Appendix E depicts a map of Pasig City indicating the location of each of these facilities. Each facility is number-coded to indicate its position in the map.

BUDGET REQUIREMENTS The group identified the need for personnel, materials and supplies, equipment, and travel for the duration of this study. These categories have been considered with the expenses that the study will require. The following table shows the general breakdown of the budget. Table 12. Breakdown of budget for thesis work Budget Allocation Personnel Materials and Supplies Travel TOTAL COST

Estimated Expenses 1820.00 6603.00 16576.81 PhP 24999.81

To break down this further, the general budget considered the following for the expenses in terms of the personnel: training and incentives. For the personnel training, the group would provide the primers for instructions on data collection and food for the personnel during the orientation. For the incentives, the group decided to put on a system in which the personnel would be motivated to provide the group with data needed. This system would give an incentive of PhP 40.00 for every 3 survey forms accomplished. Table 13. Budget for personnel training and incentives Budget Allocation Primer (Printing) Food(Mamon) Incentives for every 3 survey forms TOTAL PERSONNEL COST

Unit Price (PhP) 10 20

Quantity 34 34

Cost (Php) 340.00 680.00

800.00 PhP 1820.00

On the other hand, the general budget considered the following for the expenses in terms of the materials and equipment needed for: pretesting, data collection and thesis writing. For both pretesting and data collection, the group 51

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP would provide photocopy expenses for questionnaires to be used for pretesting and data collection, ball pens for survey administration, survey collection box for data storage. For thesis writing, the group considered the printing for an approximated 100 pages for the final thesis and bookbinding services for the final thesis output. Table 14. Budget for materials and equipment Budget Allocation Survey Collection Box Ballpens Photocopy (5 pages X 0.60) Padlock Printing for 100 pages Bookbinding TOTAL PERSONNEL COST

Unit Price (PhP) 200 4.5

Quantity 17 34

Cost (Php) 3400.00 153.00

3 80 100 60

350 17 4 4

1050.00 1360.00 400.00 600.00 PhP6603.00

The general budget considered for the travel is divided into two parts: gasoline consumption expenses and transportation cost. For the first leg of the travel, the group will be travelling to Pasig by car. The budget required for the trips is computed by multiplying the amount of the gas consumed based on the distance travelled and the mileage of the car. Table 15. Budget for gasoline consumption Mileage (km/L)

9.4

Distance from Ateneo to Pasig (km) 14

Gas Consumed (L)

Cost of Gas Consumed (PhP)

Total Number of Trips

TOTAL GASOLINE COST

1.49

PhP 2126.81

For other half of the leg, the group will be going to the health centers via tricycle trips for some streets are not accessible by car. Considering the amount for special rides, the total number of health centers and the total number of visits, the bulk of the budget, in general, would consist of transportation costs. Table 16. Budget for tricycle rides Tricycle Ride Cost for Special Trips (PhP) 25.00

Total Number of Health Centers

Total Number of Visits

TOTAL TRANSPORTATION COST PhP 14 450.00

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP In order to finance the study, the group is primarily going to spend out of the memberâ&#x20AC;&#x2122;s pocket to compensate. In order to do this, each member will shelve out PhP 4166.35. In order to lessen this amount, the group intends to apply in thesis research funding grants such as the annual Sanggunian student subsidy system and other research grants across the country.

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Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP APPENDICES Appendix A Means Test A. Katangian ng Tirahan 1. Kubeta: Wala Flush gamit ang Poso Negro Flush gamit ang isang butas sa sahig Diretso sa butas Diretso sa Kanal, Ilog o Dagat Binubuhusan Iba: 2. Pinanggagalingan ng Iniiinom na Tubig: May gripo sa loob ng bahay May gripo sa loob ng bakuran Pampublikong poso Batis/Lawa/Ilog Tubig mula sa Ulan Tubig na nabibili Iba: 3. Koneksyon sa Kuryente (Meralco): Meron Wala B. Kagamitan sa Bahay Gamit Radyo/Stereo TV VCD/VHS/DVD Telepono (Landline) Cellphone Computer Refrigerator Washing Machine Air Conditioner Microwave Oven Kotse/Jeep/Motorsiklo

___________

Meron

Wala

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP Appendix B The Short-Form-12 Health Status Survey This SF-12 survey which has been adopted from QualityMetric, Inc., will serve as the basis for scoring the perceived health status component for the study. While answering this survey, tick the box which corresponds to the answer that you feel is most appropriate to your situation based on the question asked. A. General Health Subdomain 1. In general, would you say your health is excellent, very good, good, fair, or poor?

Excellent Very Good Good Fair Poor B. Physical Functioning Subdomain 2. Are you now limited in moderate activities, such as moving a table, pushing a vacuum cleaner, bowling or playing golf? Does your health now limit you a lot, limit you a little or does not limit you at all?

Yes, limited a lot. Yes, limited a little. No, not limited at all 3. How about climbing several flights of stairs? Would you say your health now limits you a lot, limits you a little, or does not limit you at all?

Yes, limited a lot. Yes, limited a little. No, not limited at all. C. Role Functioning (Physical Subdomain) 4. During the past 4 weeks, how much of the time have you had any of the following problems with your work or regular daily activities as a result of your physical health? How much of the time have you accomplished less than you would like?

All of the time Most of the time Some of the time A little of the time None of the time 5. How much of the time were you limited in the kind of work or other activities you could do?

All of the time Most of the time Some of the time A little of the time None of the time D. Bodily Pain Subdomain 6. During the past four weeks, how much did pain interfere with your normal work including both outside the home and housework, would you say...? 62

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP Extremely Quite a bit Moderately A little bit Not at all E. Vitality Subdomain 7. How much of the time during the past four weeks did you have a lot of energy? Would you say...?

All of the time Most of the time Some of the time A little of the time None of the time F. Role Functioning (Emotional) Subdomain 8. During the past four weeks, how much of the time have you had any of the following problems with your work or other daily activities as a result of any emotional problems, such as feeling depressed or anxious. How much of the time have you accomplished less than you would like?

All of the time Most of the time Some of the time A little of the time None of the time 9. How much of the time did you have trouble doing work or other activities as carefully as usual?

All of the time Most of the time Some of the time A little of the time None of the time G. Mental Health Subdomain 10. How much of the time during the past four weeks have you felt calm and peaceful? Would you say...?

All of the time Most of the time Some of the time A little of the time None of the time 11. How much of the time during the past four weeks have you felt downhearted and blue?

All of the time Most of the time Some of the time 63

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP A little of the time None of the time H. Social Functioning Subdomain 12. During the last four weeks, how much of the time has your physical health or emotional problems interfered with your social activities, like visiting with friends, relatives, etc.?

All of the time Most of the time Some of the time A little of the time None of the time

Underinsurance among Women who have availed of PhilHealth’s MCP Appendix C Patient Satisfaction Questionnaire ATENEO DE MANILA UNIVERSITY HEALTH SCIENCES PROGRAM Maternity Care Package Patient Satisfaction Survey Good day! We are a group of BS Health Sciences Batch 2014 students currently undertaking our data collection for our study entitled “A Cross-sectional Study on the Factors affecting Underinsurance among Women who have availed of the Maternity Care Package of the Philippine Health Insurance Corporation in Pasig City”. We ask you to answer this survey questionnaire to the full extent of your capability. While answering this survey, keep in mind that we are measuring satisfaction for the most recent claim that you just filed and not other past claims if you have had any. Your response will be much appreciated. DISCALIMER: This is the Survey Questionnaire for Pre-testing Predisposing Factors 1. Name (optional) ___________________________________________________________ 1.1 Date Questionnaire was Answered (MM/DD/YYYY) _________________ 1.2 Is this your first time to claim of the MCP?

Yes No If no, how many times have you claimed in the past? 2.1 Age _________ 2.2 Date of Birth (MM/DD/YYYY) ______/______/____________ 3. Civil Status/Marital Status

Single Married Separated Widowed 4. Highest Educational Attainment

Possible Question Phrasing What is the highest educational level you have attained? What is the highest educational degree you have attained? What is the highest level of formal education that you have received?

Response/s Elementary High School Vocational/Technical School College Post-Graduate Degree No formal education

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP Enabling Factors 1. Gross Monthly Household Income (in pesos) Member of the Monthly Income Member of the Family Family Mother Child Father Child Others Others

Monthly Income

2. Perceived Familiarity with Benefits I am fully aware of the benefits that the Maternity Care Package of PhilHealth offers

Yes No 3. Length of Membership

Possible Question Phrasing How long have you been a member of PhilHealth? How many years have you been a member of PhilHealth? Since when were you a member of PhilHealth? Since when did you start being a PhilHealth member?

Response/s __________ Years

Date (MM/DD/YYYY)

4. Membership Type

Possible Question Phrasing What is your membership type under PhilHealth? What kind of PhilHealth member are you categorized under? What kind of PhilHealth member are you?

Response/s Individually Paying Employed Sponsored OFW Lifetime Member

5. Beneficiary Type

Possible QuestionPhrasing What beneficiary type are you? Are you a dependent or a primary beneficiary of PhilHealth?

Response/s Dependent Primary Beneficiary

PATIENT SATISFACTION A. COST COVERED 1. Did you pay anything additional to the amount that PhilHealth provides?

Yes No

Underinsurance among Women who have availed of PhilHealth’s MCP

2. Addition Cost Incurred

Possible Question Phrasing How much out-of-pocket expenses did you incur? How much balance did you have after the PhilHealth insurance was deducted?

Response/s Amount (in pesos)____________

From here on, encircle the number that corresponds to how you agree to the statements presented: 1 – strongly disagree 2 – slightly disagree 3 – slightly agree 4 – strongly agree 3. Satisfaction with Additional Cost Incurred

Possible Questions Phrasing I think the additional out-of-pocket expenses I uncured were reasonable I think the additional out-of-pocket expense I incurred were understandable

Response/s

I think the additional out-of-pocket expenses I incurred were realistic I think the additional out-of-pocket expenses I incurred were tolerable I think the additional out-of-pocket expenses I incurred were acceptable I think the additional out-of-pocket expenses I incurred were fair I think the additional out-of-pocket expenses I incurred were bearable I think the additional out-of-pocket expenses I incurred were necessary to ensure my good health I think the additional out-of-pocket expenses I incurred guaranteed that me and my baby had good health I think the additional out-of-pocket expenses I incurred were warranted I think the additional out-of-pocket expenses I incurred were unobjectionable I think the additional out-of-pocket expenses I incurred were allowable I think the additional out-of-pocket expenses I incurred were justified

1 1 1 1 1

2 2 2 2 2

3 3 3 3 3

4 4 4 4 4

1 1

2 2

3 3

4 4

4. Satisfaction will allotted financial coverage of P 6500

Possible Question Phrasing I believe that P6500 is enough to cover all the costs during my pregnancy I feel that P6500 is sufficient to pay for my maternal health expenses I think that P6500 is an adequate amount to protect me from financial risk due to disease I think P6500 is enough to ensure good maternal health for me I think P6500 is enough to address all my maternal health needs I believe that P6500 is an amount that can guarantee the good health of me and my child I believe P6500 is an adequate amount to provide me with all the maternal health services I’ll need I think P6500 can provide all the necessary maternal health services

1 1

2 2

Response/s 3 4 3 4

1 1

2 2

3 3

4 4

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP B. SERVICE COVERAGE 1. Satisfaction with prenatal component provided by the MCP

Possible Question Phrasing I find the scope of pre-natal services covered by the MCP is sufficient I believe the kind of pre-natal services included in the MCP are appropriate I think the type of pre-natal services contained in the MCP are adequate I think the pre-natal services that the MCP covers address my health needs I feel that the pre-natal services I am entitled to under the MCP address my health needs I feel the choice of pre-natal services offered by the MCP are helpful I believe the scope of pre-natal services of the MCP are relevant to my health needs I believe the pre-natal services under the MCP are beneficial to my health I believe the range of pre-natal services available to me through the MCP are useful I believe that the pre-natal services listed under the MCP are worth availing I think the pre-natal services under the MCP make me and my baby healthy I feel the pre-natal services covered by the MCP prepare me well for giving birth

Response/s 1 2 3 4 1

2. Satisfaction with reproductive health education component covered by the MCP

Possible Question Phrasing I think health education services covered by the MCP are appropriate to my context I find the health education services under the MCP relevant I think the health education services of the MCP are useful I feel that the health education services in the MCP help me cope with my health needs I feel that the health education services covered by the MCP are sufficient I think the health education services offered by the MCP are informative I believe the health education services of the MCP are beneficial to my health I believe the health education services of the MCP provide useful information I believe that availing of the health education services of the MCP contributes to better health for me I believe that the health education services of the MCP are important I believe that the health education services of the MCP are needed I believe that the health education services contained in the MCP are an important component of the MCP I believe the health education services contained in the MCP are worth availing

Response/s 1

1 1

2 2

3 3

4 4

1 1

2 2

3 3

4 4

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP

3. Satisfaction with delivery proper component of the MCP

Possible Question Phrasing I think delivery proper services covered by the MCP is appropriate to my context I find the delivery proper services under the MCP relevant I think the delivery proper services of the MCP are useful I feel that the delivery proper services in the MCP address my health needs I feel that the delivery proper services covered by the MCP are sufficient for my health needs I believe the delivery proper services of the MCP are beneficial to my health I believe that availing of the delivery proper services of the MCP contributes to better health after giving birth for me I believe that the delivery proper services of the MCP are important I believe that the delivery proper services of the MCP are needed I believe that the delivery proper services contained in the MCP are an important component of the MCP I think the delivery proper services covered by the MCP are safe I think the range of delivery proper services under the MCP are vital to ensuring my health while giving birth I think the array of delivery proper services are crucial to the delivery of my baby

Response/s 1

1 1

2 2

3 3

4 4

1 1

2 2

3 3

4 4

4. Satisfaction with postpartum component covered by MCP

Possible Question Phrasing I think postpartum services covered by the MCP are appropriate to my context I find the postpartum services under the MCP relevant I think the postpartum services of the MCP are useful I feel that the postpartum services in the MCP help me cope with my health needs I feel that the postpartum services covered by the MCP are sufficient I believe the postpartum services of the MCP are beneficial to my health I believe that availing of the postpartum services of the MCP contributes to my better health after giving birth I believe that the postpartum services of the MCP are important I believe that the postpartum services of the MCP are needed I believe that the postpartum services contained in the MCP are an important component of the MCP I think the postpartum services covered by the MCP help me recover from giving birth I believe the postpartum services included in the MCP aid my recovery after delivery I believe the postpartum services contained in the MCP help me get better after giving birth I believe the postpartum services included in the MCP improve my health post-delivery I think the range of postpartum services under the MCP adequately address my health needs after giving birth I think the array of postpartum services are crucial to helping me maintain good health after delivery 69

1 1 1 1 1 1

Response/s 2 3 2 3 2 3 2 3 2 3 2 3

4 4 4 4 4 4

1 1

2 2

3 3

4 4

1 1

2 2

3 3

4 4

Underinsurance among Women who have availed of PhilHealth’s MCP

C. AVAILMENT PRE-REQUISITES 1. Satisfaction with pre-requisite of 4 pre-natal visits before delivery to avail MCP

Possible Question Phrasing I believe that 4 pre-natal visits are necessary I think that doing 4 pre-natal visits is important I think that going to 4 pre-natal visits is reasonable I think that going to 4 pre-natal visits is essential to maintain good maternal health I feel that going to 4 pre-natal visits is crucial to ensure a successful delivery I think 4 pre-natal visits is helpful during the pregnancy period I think 4 pre-natal visits is an understandable requirement I think 4 pre-natal visits is an appropriate request I think 4 pre-natal visits is needed to guarantee my health and the baby’s health I think 4 pre-natal visits is needed so that I’m aware of my own health status I think 4 pre-natal visits is crucial because it helps me maintain good health throughout the pregnancy period I think 4 pre-natal visits is easy to comply with I think 4 pre-natal visits is a task that can be done I feel that going to 4 pre-natal visits is crucial to ensure a successful delivery

Response/s 1 2 3 4 1 2 3 4 1 2 3 4 1

1 1 1

2 2 2

3 3 3

4 4 4

1 1

2 2

3 3

4 4

2. Satisfaction with pre-requisite of having first pre-natal visit within 16 weeks AOG

Possible Question Phrasing I believe that having my 1st pre-natal visit before 16 weeks of AOG is necessary I think that having my 1st pre-natal visit before 16 weeks of AOG is important I think that having my 1st pre-natal visit before 16 weeks of AOG is reasonable I think that having my 1st pre-natal visit before 16 weeks of AOG is essential to maintain good maternal health I think having my 1st pre-natal visit before 16 weeks of AOG is helpful during the pregnancy period I think having my 1st pre-natal visit before 16 weeks of AOG is an understandable requirement I think having my 1st pre-natal visit before 16 weeks of AOG is an appropriate request I think having my 1st pre-natal visit before 16 weeks of AOG is needed to guarantee my health and the baby’s health I think having my 1st pre-natal visit before 16 weeks of AOG is crucial because it helps me maintain good health throughout the pregnancy period st I think having my 1 pre-natal visit before 16 weeks of AOG is easy to comply with I think having my 1st pre-natal visit before 16 weeks of AOG is a task that can be done

Response/s 1

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP

3. Satisfaction with required premium contributions

Possible Question Phrasing I think the required amount of premium contributions before I could of the MCP was reasonable I think the required amount of premium contributions before I could of the MCP was understandable I think the required amount of premium contributions before I could of the MCP was realistic I think the required amount of premium contributions before I could of the MCP was tolerable I think the required amount of premium contributions before I could of the MCP was acceptable I think the required amount of premium contributions before I could of the MCP was fair I think the required amount of premium contributions before I could of the MCP was bearable I think the required amount of premium contributions before I could of the MCP was warranted I think the required amount of premium contributions before I could of the MCP was unobjectionable I think the required amount of premium contributions before I could of the MCP was allowable I think the required amount of premium contributions before I could of the MCP was justified

Response/s 1

D. CLAIMS PROCESS 1. Satisfaction with requirements for filing MCP claim

Possible Question Phrasing I believe that the requirements for filing a claim are necessary I think that the requirements for filing a claim are important I think that the requirements for filing a claim are reasonable I think that doing the requirements for filing a claim is understandable I think the requirements for filing a claim is an appropriate request I think the requirements for filing a claim is easy to comply with I think the requirements for filing a claim is a task that can be done I think the requirements for filing a claim can be achieved I find the requirements for filing a claim as pertinent needs of PhilHealth I believe the requirements for filing a claim are valid requests I believe the requirements for filing a claim are doable

1 1 1 1 1 1 1 1

Response/s 2 3 2 3 2 3 2 3 2 3 2 3 2 3 2 3

4 4 4 4 4 4 4 4

1 1

2 2

3 3

4 4

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP 2. Satisfaction with having separate forms (form 4A and 4B) for claiming MCP

Possible Question Phrasing I believe that having a separate form for MCP is necessary I think that having a separate form for MCP is important I think that having a separate form for MCP is reasonable I think that having a separate form for MCP is understandable I think having a separate form for MCP is an appropriate request I think having a separate form for MCP is easy to comply with I think having a separate form for MCP is a task that can be done I think having a separate form for MCP can be achieved I believe having a separate form for MCP are valid requests I believe having a separate form for MCP is logical I believe having a separate form for MCP is doable

1 1 1 1 1 1 1 1 1 1 1

Response/s 2 3 2 3 2 3 2 3 2 3 2 3 2 3 2 3 2 3 2 3 2 3

4 4 4 4 4 4 4 4 4 4 4

3. Satisfaction with allotted days to file an MCP claim

Possible Question Phrasing I believe that a maximum of 60 days allotted to file the claim is necessary I think that a maximum of 60 days allotted to file the claim is important I think that a maximum of 60 days allotted to file the claim is reasonable I think that having a separate form for MCP is understandable I think a maximum of 60 days allotted to file the claim is an appropriate request I think a maximum of 60 days allotted to file the claim is easy to comply with I think a maximum of 60 days allotted to file the claim is a task that can be done I think a maximum of 60 days allotted to file the claim can be achieved I believe a maximum of 60 days allotted to file the claim is valid requests I believe a maximum of 60 days allotted to file the claim is doable I believe a maximum of 60 days allotted to file the claim is enough time I feel a maximum of 60 days allotted to file the claim is sufficient leeway I feel a maximum of 60 days is needed to file the claim

Thank You Very Much for your time! God bless! ď &#x160;

Response/s 1

Underinsurance among Women who have availed of PhilHealth’s MCP Appendix D Letter for Maternity Clinics 1 February 2013 Abelido’s Birthing Center Good day sir/madame! We are a group of BS Health Sciences students of the Ateneo de Manila University (ADMU) currently doing our undergraduate thesis. Our thesis specifically focuses on determining the proportion of underinsurance among women in Pasig City who have availed of PhilHealth’s Maternity Care Package (MCP) and the factors affecting underinsurance among such women. Once completed, our study has the great potential to improve the design of the MCP with regards to its financial risk protection and service coverage. More importantly, our study also has the great potential of ensuring that all women who avail the MCP get the most out of it. As such, we are humbly requesting for your assistance in our endeavor. If it is alright with your clinic, we would wish to leave with you a few survey forms our group has crafted and distribute these, through your clinic staff, to all women who will be claiming their MCP from April to October of 2013 at your clinic. We do not expect all of the survey forms we will be leaving you with to have been completed. We would just like to ask for your assistance in giving them to all such women. Recognizing that such a request may produce some minor inconvenience on your part, our group is very much open to providing additional financial resources or incentives to your clinic or to your clinic staff should you desire such an option. Rest assured that we shall be going to your clinic every week after we give you the survey forms so that we can collect back all surveys which have already been answered by respondents. Thank you very much! Should you have any questions/concerns, please do call: 6340838 or 09214693629. More power to your clinic! Thank you for believing in our endeavor. Respectfully,

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP Appendix E Statement of Mutual Understanding

Underinsurance among Women who have availed of PhilHealthâ&#x20AC;&#x2122;s MCP Appendix F Map of Pasig City showing the 17 PhilHealth-accredited birthing and lying-in clinics offering the MCP

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101 3

111 3 13

121 3 14 15

Underinsurance among Women who have availed of PhilHealth’s MCP Number Code 1 2 3

4 5 6 7

8 9 10 11 12 13 14 15

Name of Birthing Clinic/ Lying-in Clinic Che Midwife LIC Clinica Paiso-Ramos Maternity LIC Well Care Maternity, Medical, and Pediatric Clinic Inc. Well Care LIC St. Christiana Maternity Hospital F.B. Ancheta Childrens Maternity and LIC Pasig Medical and Maternity Hospital Foundation Gertrudes Luderico Well Family Clinic T/V’s Medical Clinic MCLC Maternity Clinic L. Salonga Birthing Home Divine Grace Maternity Clinic Abelido’s Birthing Center Immaculate Concepcion LIC Catapang-Combate OBGyne Clinic

Liza Aguilar-Racuya LIC

God Gift LIC Services