Evaluating equity in health systems financing in Indonesia
Lead Research Organisation:
London School of Hygiene & Tropical Medicine
Department Name: Public Health and Policy
Abstract
Indonesia has embarked on an ambitious program to achieve universal health coverage (UHC) by 2019 with its national health insurance scheme at the forefront. While Indonesia has made steady progress, around a third of its population remains without cover and out of pocket payments for health are widespread even among the insured. Over the next 2 years, the government will be increasing its efforts to scale up the national scheme using a complex mix of demand and supply side initiatives. Amid growing concerns that the poor may be left behind in the pursuit of UHC, my research will provide much needed evidence on the equity-impact of the reforms and Indonesia's overall progress to universalism. My research will address 3 broad objectives. First, using the technique of benefit incidence analysis (BIA), I will measure the extent to which different socioeconomic groups benefit from public financing for health through their use of health services. In doing so, I will also advance conventional methodology by weighting the benefits of health spending to reflect quality of services, especially important in countries such as Indonesia where the poor typically utilise lower quality health services compared to the rich. Second, I will use econometric techniques to measure the effect of insurance ownership on a range of behavioural outcomes including utilisation of services, out-of-pockets spending, and impoverishing and catastrophic health expenditure. Third, I will conduct qualitative research to understand the context and process of implementing UHC-reforms in Indonesia. My research objectives will be met using two large cross sectional household surveys (ENHANCE Surveys), national health facility data sets, and in-depth interviews with key stakeholders in UHC reforms. This research will be critically important to understanding the true impact of Indonesia's health insurance policies, especially on the poor.
| Description | Objective 1: To measure the extent of inequalities in the availability of quality health services across the Indonesian primary health care system I used the Indonesia Family Life Survey for this objective. The IFLS is a panel socioeconomic and health survey in Indonesia, based on a sample of households representing about 83% of the Indonesian population living in 13 of the nation's 26 provinces in 1993. The survey collects data on individual respondents, their families, their households, the communities in which they live, and the health and education facilities available to them. For the purpose of objective 1, the IFLS data from 15,877 households in 312 communities were linked with a representative sample of both public and private health facilities available in the same communities to assess the quality of health facilities. Two measures of quality of care were constructed: a measure of structural quality using facility service readiness indicators (such as infrastructure, medical equipment and availability of drugs); and a measure of process quality (provider knowledge) using clinical vignettes. One of the main findings from this study was that quality of care remains worryingly low in Indonesia. In terms of health facility readiness, I found that basic equipment, essential medicines and diagnostic capacity were lacking in all health facility types. The overall level of provider knowledge was quite poor, with an average knowledge score below 50% for all provider types. The low facility readiness and provider knowledge scores were particularly striking in midwife/nurse practices. Private facilities, which are a major provider of PHC in Indonesia, had worse scores than public sector facilities. Additionally, results suggest that major geographical inequalities in the quality of care exist. The main difference was seen between islands (or grouping of provinces), where public and private facilities located in Central Java were more likely to meet basic standards of facility readiness and be staffed by more knowledgeable providers than facilities located in all other provinces. Further, inequalities in readiness scores, but not knowledge scores, went beyond the provincial level and were observed between urban and rural areas. This was particularly the case in public sector facilities, where it was found that urban location was a strong determinant of facility readiness: both puskesmas and pustus located in rural areas were more likely to have lower readiness scores than in urban areas. Finally, I discovered that public facilities located in richer communities had slightly higher readiness scores than those located in poorer communities, other things being equal. However, the size of the association was relatively small and was limited to public facilities. Objective 2: To explore the extent to which the quality of public and private primary health care in Indonesia affects provider choice I used two IFLS data sets to analyse the relationship between quality of care and provider choice. For this purpose, I linked information on household SES with information on the quality of their local PHC facilities. Within each community, the choice set of facilities that each individual faced was defined as all facilities surveyed in the community. I analysed the choice of health facility made by 1044 individuals and the quality of 2549 public and private PHC facilities located in the same communities where those individuals live. Similar to my first paper, two proxy measures of quality of care were calculated: a SSR score (capturing availability of equipment, infrastructure and supplies); and a provider knowledge score measured using clinical vignettes. I estimated an alternative specific conditional logit model of provider choice. Results suggest that facility readiness is a predictor of facility choice by patients, although the magnitude of the effect was relatively small. The marginal rates of substitution suggest that for one percentage point increase in the readiness score, individuals were willing to travel on average 50 metres further and pay an additional IDR 2411 (USD 0.2). Distance and price remained the major determinants of facility choice. Provider knowledge scores did not seem to have an effect on facility choice. In contrast, sector of care was an important determinant of facility choice, with patients preferring to seek care from public health facilities, all else being equal. All components of facility readiness except infection prevention had an effect on facility choice with essential medicines having the greatest effect. Insured individuals, those living in urban areas, and those using curative care were more responsive to an increase in facility readiness. Readiness scores did not affect the probability of facility choice for the uninsured, those living in rural areas, and those seeking preventative care. Importantly, both rich and poor individuals valued facility readiness. Objective 3: To evaluate the impact of the Indonesian Social Health Insurance scheme on health service utilisation and financial protection This analysis is based on primary survey data from the Equity and Health Care Financing in Indonesia study, also known as the ENHANCE study, that included a panel household survey at two time points (February-April 2018 and September-December 2019). I used a panel of 2096 households and 7982 individuals from this survey to evaluate the impact of the JKN on health care utilisation and to measure financial protection using propensity score matching combined with difference-in-differences methods. Findings on health care utilisation suggest that the highest impact of the JKN was on inpatient use (1.7% point increase compared to the control group), and this result was robust to the different model specifications. This impact was driven by an increased probability of using private hospitals. I also found that the JKN group had a higher probability of using any outpatient care in public hospitals than the control group. These results are in line with previous findings from Indonesia, despite the fact that they relied on less rigorous study designs (Erlangga, Ali, & Bloor, 2019; Pratiwi et al., 2021). Regarding financial protection, JKN members had a 7.4% point lower probability of incurring OOP spending for outpatient care compared to the control group. They also had an increased probability of incurring OOP costs for inpatient care, although this result was not significant. Overall, it seems that the JKN had a protective effect on the total level of yearly OOP spending per capita (mean decrease of IDR 78295 or USD 5.5), although this result did not reach the standard significance level. These results are in line with the few studies that indicate that OOP payments remain an issue for the JKN (Pratiwi et al., 2021). Objective 4: To explore the adaptation of a popular quantitative method for measuring equity in health financing, benefit incidence analysis, by incorporating a quality of care weighting. The first wave of the ENHANCE dataset, consisting of a sample of 7020 households surveyed in 10 provinces of Indonesia in early-2018, was used to conduct a conventional BIA. This research was a pre-defined aim of the overall ENHANCE study. For my PhD, I extended the method by incorporating quality of care weighting into the BIA framework. This involved linking the ENHANCE household dataset to a survey of 50 public health facilities conducted in the same geographical areas, where information about health facility infrastructure and basic equipment was collected. In each facility, an index of service readiness was computed as a measure of quality of care. Individuals who reported visiting a PHC facility in the month before the interview were matched to their chosen facility, thereby enabling quality indicators to be linked to those individuals. In this study, I integrated the quality scores into the BIA computation, thereby enabling the estimation of quality-adjusted subsidies for PHC. Results showed that the distribution of subsidies for public PHC facilities became less 'pro-poor' and subsidies for private PHC facilities became more pro-rich after accounting for quality of care. While the magnitude of the difference between the distributions of quality-adjusted and unadjusted subsidies was not large in this instance, the gap between the two distributions is likely to be underestimated since the data contained important limitations such as the small health facility sample size. A key contribution of the study was to advance methods in the field, that can in turn be applied and tested by other researchers seeking to assess whether the poor or the better off (disproportionately) benefit from public health expenditure. |
| Exploitation Route | Academic publication will follow, as well as presentation to relevant audiences (including in Indonesia) |
| Sectors | Healthcare |
| Description | Presentations to various stakeholders have contributed to policy debate on social health insurance in Indonesia |
| First Year Of Impact | 2021 |
| Sector | Healthcare |
| Impact Types | Policy & public services |
| Description | Poster Presentation of preliminary findings to Health System Global conference |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Third sector organisations |
| Results and Impact | Title of the poster: Implementing pro-poor universal health coverage: is quality of care a game changer? Health Systems Global 2020 (online conference) |
| Year(s) Of Engagement Activity | 2020 |
| Description | Presentation of preliminary findings at the UK Health Economics Study Group |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Other audiences |
| Results and Impact | Title: Poor quality for the poor? A study of inequalities in service readiness and provider knowledge in Indonesian primary health care facilities Received feedback from the audience of health economists |
| Year(s) Of Engagement Activity | 2021 |
| Description | Presentation to Center for Health Economics in London (CHIL at LSHTM) |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Other audiences |
| Results and Impact | Presentation of paper 1: Poor quality for the poor? A study of inequalities in service readiness and provider knowledge in Indonesian primary health care facilities Received feedback from audience |
| Year(s) Of Engagement Activity | 2020,2021 |