Nia Budi Puspitasari

Choosing the benefit package from the BPJS program: Findings from CHAT experiment

Abstract Aim: This study aims to design the benefit–package composition of health insurance benefits in accordance with the priority of the needs of the participants of BPJS and the amount of their willingness to pay the premium rate. Background: This design aimed at ensuring the relevance of the benefit packages to beneficiary communities, so the implementation of the design is expected to increase peoples’ contributions in joining BPJS for health program. Method: This study use Choosing Health plans All Together (CHAT) as a method for design the benefit–package composition. The CHAT exercise enabled participants to choose from nine benefit type and for each benefit type, the participants could choose three coverage levels, i.e. basic, medium, and high. There were 246 participants as a sample for CHAT exercise. The sample size was calculated as optimal based on a 5% margin of error and a 95% confidence interval and randomly selected based on two-stage cluster sampling method. Result: According to their willingness to pay, a sample size of 246 participants was divided into three groups. A total of 72 (29.3%) participants chose a premium rate at IDR 59 500 and called group 1 participants, 84 (34.1%) participants chose a premium rate at 42 500 IDR and called group 2 participants, and 90 (36.6%) participants chose a premium rate at 25 500 IDR and called group 3 participants. Basically, the CHAT experiment results for group 1 until group 3 of the participants can be divided into two types of package, i.e. package with maternity benefit and package without maternity benefit. As example, for group 1 of participant, package with maternity benefit consists of hospitalization (medium), ICU (high), surgery (high), doctor (high), and maternity (high), whereas package without maternity benefit for group 1 of participant consists of hospitalization (high), ICU (high), surgery (high), doctor (high), tests (high) and dental care (high). Conclusion: This study resulted that CHAT experiment can help groups of individuals to identify their preferred health insurance package under cost constraints to demonstrate various managed care insurance packages that are likely to be acceptable to uninsured individuals.