Achieving Universal Health Coverage with an Unenforceable Mandate: Evidence from the Government of Indonesia's JKN Mandiri Program

The trial will be conducted in two locations. The first part of the trial took place in Medan in March 2015. The second part of the trial will take place in Bandung starting from mid-October 2015. Some of the treatments are going to be the same in both location; however the second part of the pilot also includes additional treatments based on the results of the first pilot and also changes in the health insurance scheme.

1) Discount level
What is the effect of changing prices on the pool of individuals who sign up? This is important for two reasons: first, if lowering the price means that more and more healthy people register for insurance, a lower price could reduce the government’s total net cost. Second, if certain groups are especially price sensitive (e.g. poorer households), changing the level of the premium may increase coverage of individuals belonging to these groups. By exploring how enrollment and health care cost vary with prices, we can test whether “adverse selection” is occurring and then compute the optimal level of the insurance premium for non-poor non-wage workers.

We offer three different subsidy levels: (1) no subsidy; (2) 50% subsidy in the form of a buy-one-get-one free bonus (if the family enrolls, they only have to pay the premium for half of the family members); (3) 100% subsidy. The duration of the subsidy is a year. The subsidy offer is made by a trained enumerator at the end of the interview. In addition, in Bandung we will also offer a no inpatient treatment bonus. Families randomly assigned to this treatment have to cover the full premium for all family members but, if they have no inpatient claim for a year, receive 50% of the premiums they paid back.

2) Online Assistance
Households will be randomly selected to either be offered the opportunity to register on the spot or to the status quo, which requires them to go to the BPJS office to enroll. The idea of this treatment is to test whether reducing hassle costs in the registration process such as long queues at BPJS office and difficulties in understanding the forms affect enrollment.

In this treatment, households will be randomly assigned to two sub-treatment groups: (1) assistance for online registration – randomly selected families are offered to register for JKN insurance program on the spot through online registration; (2) status Quo – no offer of assistance during households visit.

3) Information Content of Socialization
Randomly selected families will receive basic information about JKN, while others will receive additional information focusing on different aspects of the health insurance program. Overall the trial explores three different information treatments (each of these treatments is cross-cut with the others).

To test this, in Medan some randomly selected families will receive basic information on JKN, while others will receive additional information on health care costs for some of the most prevalent chronic diseases. In Badnung, we will also randomly select some families to receive some information on waiting period for new registrant of JKN while others will receive no such information at all. Moreover, we will also test out the effect of providing information about the possibility of government imposing a sanction for people who don’t have JKN insurance to some randomly selected households.

4) Deadline
If households know that they will be able to enroll in JKN whenever they are sick and need coverage, they have no incentive to register and pay their premia in advance. This increases the proportion of high-risk individuals enrolled in the health insurance, further increasing the chances of adverse selection. This treatment will help inform whether having an incentive to enroll in the program within a certain period affects enrollment, payments and retention of non-wage workers, especially healthy non-wage workers.

Households who receive a discount will be randomly assigned to the following three sub-treatments: (1) one week deadline: the household will be able to use the subsidy only if they registers within a week; (2) two week deadline – the household will be able to use the subsidy only if they registers within two weeks; (3) choice: the household will be asked to choose between a one and a two week deadline. This treatment will be dropped in Bandung. Every household will receive a two week deadline.

2014-11-03

2015-12-31

The first key outcome is enrollment or how each of the treatment affects the take-up of JKN. Relatedly, we will look at how different treatment affect the premium payment behavior. In addition, we will look at health care seeking behavior in the form of outpatient and inpatient claims from administrative data. Lastly, we will look at how pre-existing variables differ across treatments. The variables we will focus on are pre-trial health care system utilization together with demographic variables.

The trial consists of four different treatment arms, that will be all cross-cut with each other. Firstly, we will randomly assign households to different subsidy levels. Some households will receive a 50% subsidy in the form of a buy-one-get-one free bonus (if the family enrolls, they only have to pay the premium for half of the family members), some households will receive a full subsidy and some households will receive a no inpatient bonus (the household has to cover the full premium for all family members but, if they have no inpatient claim for a year, receive 50% of the premiums they paid back). The remaining households will receive no subsidy. Secondly, we will offer to half of the households the possibility to register on the spot as opposed to following the procedure that requires them to go to a central office. Thirdly, we will test three different information treatments focusing on health care costs of certain illnesses, a waiting period, and potential penalties for non-enrollment. Lastly, we will also vary the length of time for which the subsidy offer is valid (Medan only).

Randomization done in the field on a computer using CSPro

Households

No

2000 households in Medan and 4750 households in Bandung.

2000 households in Medan and 4750 households in Bandung.

The study has 4 main treatments to test. All treatments will be cross-cut one to another. In Medan, all treatments had equal probability. In Bandung a higher number of households (2500) will be assigned to the treatment group; 1000 households will be assigned to the half subsidy and no inpatient bonus and 500 households will be assigned to the full subsidy treatment. All other treatments have equal probability.

The analysis for this study will be divided into two main parts. First, we estimate the effect that the different incentives schemes have on enrollment into JKN. This uses the entire sample. Second, we study whether different incentives schemes attract different individuals and differentially affect individuals’ health seeking behavior. To perform this analysis, we compare families which took up across different treatments. This part of the analysis restricts the sample to taker-uppers. As a result, we perform two sets of power calculations. Power calculations for enrollment use the entire sample and, in particular, the size of groups assigned to each treatment. Given the number of individuals assigned to each group, we calculate a predicted number of taker-uppers for each treatment group based on the enrollment rates that we saw in the previous pilot. We then use these group sizes for all power calculations related to adverse selection or health seeking behavior. All power calculations calculate MDEs based on control means and standard deviations from the previous pilot. We assume β=0.80 and α=0.05. All MDEs are expressed as fraction of control group standard deviation. Overall, for the Bandung pilot, MDEs for the enrollment regressions are in the order of 0.10 to 0.20 standard deviations, whereas MDEs for the adverse selection regressions are in the order of 0.20 to 0.40 standard deviations. The tables (uploaded separately) report the assumptions on take-up rates and MDEs for the different treatment arms and main outcomes of interest. Note that these MDEs are lower bounds for the onsite registration treatment and for the half-subsidy and full-subsidy treatment. These treatments are the same in the Medan and in the Bandung pilot, which means that we will be able to pool together the data from the two sites in the analysis.