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I would like to congratulate the authors of the article titled “National health insurance databases in Indonesia, Vietnam and the Philippines”, which was recently published in PharmacoEconomics Open [1]. This article has correctly underlined the importance of social health insurance administrative data to support these Southeast Asian countries toward the achievement of universal health coverage (UHC) [1]. Experiences in other countries have shown that administrative data could significantly contribute to knowledge development, public health decision making, and various other purposes if the data were available and easily accessible [2]. The authors mentioned that accessibility to administrative data was among the main challenges, especially for Indonesian researchers. After submitting a data request, researchers could wait up to 6 months to get a response, along with additional waiting time queuing for access to data, and onsiteonly analysis, until finally generating the data in an aggregated format [1]. The Indonesian Social Health Security Agency (BPJS Kesehatan) maintained such procedures to protect data privacy and confidentiality, as well as to facilitate researchers for direct consultation with data custodians due to the complexity and huge volume of data. Fortunately, this situation changed just a few weeks before the article appeared online. In February 2019, BPJS Kesehatan launched the 2015–2016 social health insurance sample data (SHISD), a nationally representative administrative dataset that was randomly sampled from strata of BPJS Kesehatan members in 2015–2016. The sampling frame of the SHISD was a list of 73,441,160 families who were enrolled as members at 22,024 ‘gatekeepers’, including primary health care sites (Puskesmas), family physicians, and clinics. ‘Gatekeepers’ subgrouped these families into three categories: (1) families who have never utilized any health care services; (2) families who have ever visited gatekeepers; and (3) families who have visited primary and referral care. Within each category, a minimum of 10 families were randomly sampled. If selected, all individuals in the family were included in the dataset. Finally, from the 66,072 strata, a sample of 586,969 families was selected, constituting a total of 1,697,452 individuals [3]. The SHISD consists of four relational tables, namely membership, capitation-based primary care services, noncapitation-based primary care services, and referral care services. The membership table contains the necessary variables, including an identifier of individuals and families, details of demographic and membership characteristics, and a weight variable of each record. In this dataset, the weight variable represents a certain number of BPJS Kesehatan members. The remaining tables consist of details of visits, health facility characteristics, and individual identifiers. The SHISD has been distributed to universities, research institutions, and other relevant stakeholders in Indonesia. This anonymized dataset, as well as the book code, is available from BPJS Kesehatan upon reasonable request [3]. I have tried to analyze the table of referral care services to generate the unweighted temporal distribution of hospitalized dengue hemorrhagic fever (DHF) cases and the association between length of stay (LOS) and the reimbursement amount for hospitalized DHF cases (Figs. 1 and 2). From approximately 911,000 referral visits, including outpatient and inpatient care, 6104 records were inpatient cases with a primary diagnosis of DHF (International Classification of Diseases, Tenth Revision [ICD-10] code A91). Samples of inpatient cases in the year 2016 were more than double the number in the year 2015 (4130 vs. 1974 records). The surge of cases in 2016 was slightly higher than the official surveillance report. The Indonesian * Anis Fuad anisfuad@ugm.ac.id

Indonesian Social Health Insurance Sample Data are Now Available and Accessible for Research