Evidence map›Paper›PMID 40703178›Full record

ArticleFrontiers in public health2025

The influence of provider payment mechanisms on TB service provider behavior in Indonesia: insights from National Health Insurance data and provider perspectives.

Meghan O'Connell, Firdaus Hafidz, Sarah Saragih, Cheryl Cashin, Aditia Nugroho, Laurel Hatt, Yuli Farianti, Ackhmad Afflazier, Imran Pambudi

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Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Meghan O'ConnellResults for Development, Washington, DC, United States.
Firdaus HafidzDepartment of Health Policy and Management, Faculty of Medicine, Public Health, and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia.
Sarah SaragihResults for Development, Jakarta, Indonesia.
Cheryl CashinResults for Development, Washington, DC, United States.
Aditia NugrohoResults for Development, Jakarta, Indonesia.
Laurel HattResults for Development, Washington, DC, United States.
Yuli FariantiMinistry of Health, Jakarta, Indonesia.
Ackhmad AfflazierMinistry of Health, Jakarta, Indonesia.
Imran PambudiMinistry of Health, Jakarta, Indonesia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The impact of provider payment mechanisms under Indonesia's National Health Insurance (NHI) scheme on healthcare providers' behavior-particularly in tuberculosis (TB) service delivery- remains underexplored. This study examines the consequences of provider payment incentives on TB service provider behavior. Methods: A mixed-methods study was conducted using quantitative analysis of NHI claims data from 2015 to 2016 and qualitative data from focus group discussions with healthcare providers-22 primary care facilities and 14 hospitals across five provinces-. Quantitative analysis examined TB service utilization patterns, assessed referral appropriateness based on case complexity, and claim of TB services. Qualitative data were thematically analyzed to explore factors influencing provider decision-making in the context of payment mechanisms and service delivery under the NHI scheme. Results: Findings indicate that primary care facilities refer a high proportion of TB cases to secondary-level care, even for uncomplicated cases (81% of 782 visits). Secondary care recorded significantly more TB visits than primary care (5,249 vs. 1,094 visits), resulting in an estimated USD 14.1 million in potentially avoidable costs for the NHI program. If these cases had been managed at the primary level, potential cost savings could have been substantial. Qualitative analysis revealed that provider referral decisions were influenced by capitation-based payment structures, limited diagnostic tools, absence of dedicated TB rooms, lack of provider capacity, patient preferences, financial incentives favoring more profitable diseases, and providers' social ties. The high rate of up-referrals may negatively impact service quality and TB treatment outcomes. Conclusion: Current provider payment mechanisms under NHI contribute to inefficiencies in TB service delivery by incentivizing unnecessary referrals to secondary care. Optimizing payment methods and strengthening implementation by addressing weak provider capacity at the primary care level could enhance incentives for primary-level management of TB cases, improving cost-effectiveness and service quality.

Indexed as

Health PersonnelNational Health ProgramsReimbursement MechanismsTuberculosisAdultFemaleFocus GroupsHumansIndonesiaMalePrimary Health CareQualitative ResearchIndonesiaNational Health Insuranceprovider paymentreferraltuberculosis

Identifiers

PMID40703178
PMCPMC12283726

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.