Evidence map›Paper›PMID 38331790›Full record

ArticleInternational journal for equity in health2024

The optimal co-insurance rate for outpatient drug expenses of Iranian health insured based on the data mining method.

Shekoofeh Sadat Momahhed, Sara Emamgholipour Sefiddashti, Behrouz Minaei, Maryam Arab

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Article in International journal for equity in health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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4 citing papers in PubMed.

  1. Article
  2. Article
  3. Artificial intelligence applications in health insurances: a scoping review.Cost effectiveness and resource allocation : C/E · 2025
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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Shekoofeh Sadat MomahhedDepartment of Health Management and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Sara Emamgholipour SefiddashtiDepartment of Health Management and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran. s-emamgholipour@tums.ac.ir.
Behrouz MinaeiSchool of Computer Engineering, Iran University of Science and Technology, Tehran, Iran.
Maryam ArabNational Center for Health Insurance Research (Iran Health Insurance Organization), Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveA more equal allocation of healthcare funds for patients who must pay high costs of care ensures the welfare of society. This study aimed to estimate the optimal co-insurance for outpatient drug costs for health insurance.

settingThe research population includes outpatient prescription claims made by the Health Insurance Organization that outpatient prescriptions in a timely manner in 2016, 2017, 2018, and 2019 were utilized to calculate the optimal co-insurance. The study population was representative of the research sample.

designAt the secondary level of care, 11 features of outpatient claims were studied cross-sectionally and retrospectively using data mining. Optimal co-insurance was estimated using Westerhut and Folmer's utility model.

participantsOne hundred ninety-three thousand five hundred fifty-two individuals were created from 21 776 350 outpatient claims of health insurance. Because of cost-sharing, insured individuals in a low-income subsidy plan and those with refractory diseases were excluded.

resultsInsureds were divided into three classes of low, middle, and high risk based on IQR and were separated to three clusters using the silhouette coefficient. For the first, second, and third clusters of the low-risk class, the optimal co-insurance estimates are 0.81, 0.76, and 0.84, respectively. It was equal to one for all middle-class clusters and 0.38, 0.45, and 0.42, respectively, for the high-risk class. The insurer's expenses were altered by $3,130,463, $3,451,194, and $ 1,069,859 profit for the first, second, and third clusters, respectively, when the optimal co-insurance strategy is used for the low-risk class. For middle risks, it was US$29,239,815, US$13,863,810, and US$ 14,573,432 while for high risks, US$4,722,099, US$ 6,339,317, and US$19,627,062, respectively.

conclusionsThese findings can improve vulnerable populations' access to costly medications, reduce resource waste, and help insurers distribute funds more efficiently.

Indexed as

Insurance, HealthOutpatientsCost SharingHumansIranRetrospective StudiesData miningHealth insuranceOptimal co-insurance

Identifiers

PMID38331790
PMCPMC10854021

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