Health Economics Insights Journal
Health Economics Insights Journal (HEIJ) is an international peer-reviewed academic journal that publishes high-quality research across diverse fields of knowledge, including health economics, public health, healthcare management, health policy, health financing, health insurance, pharmaceutical economics, hospital management, economics, business, management, and applied health-related research. The journal aims to provide an inclusive scholarly platform for researchers, academics, practitioners, healthcare professionals, and policymakers to disseminate original research that contributes to theoretical development, empirical knowledge, practical innovation, and solutions to contemporary health and healthcare challenges. HEIJ welcomes multidisciplinary and interdisciplinary studies that connect different fields of knowledge to address complex local, national, regional, and global health issues. The journal encourages research that integrates perspectives from health, economics, public policy, healthcare systems, management, financing, insurance, pharmaceuticals, business, and human development. By promoting cross-disciplinary dialogue, HEIJ seeks to support the advancement of knowledge that is academically rigorous, socially relevant, and beneficial for wider communities. The scope of Health Economics Insights Journal (HEIJ) includes, but is not limited to, the following areas: Health economics and health policy Public health and community health Healthcare management and healthcare administration Health financing and healthcare payment systems Health insurance and social health protection Pharmaceutical economics and pharmacoeconomics Hospital management and hospital administration Health services research and healthcare delivery Health technology assessment and medical innovation Health system performance and healthcare quality Healthcare access, equity, and affordability Health expenditure, cost-effectiveness, and economic evaluation Health workforce management and organizational behavior in healthcare Digital health, health information systems, and data analytics Business, management, accounting, and finance in healthcare Economics, development studies, and public sector economics related to health Policy studies, governance, and regulation in the health sector Healthcare entrepreneurship, innovation, and sustainable health business Global health, health security, and comparative health systems Interdisciplinary studies linking health, economics, management, policy, business, and society The journal accepts original research articles, literature reviews, systematic reviews, bibliometric studies, conceptual papers, case studies, policy papers, and applied research reports. Submissions may use quantitative, qualitative, mixed-method, experimental, comparative, or interdisciplinary approaches, provided that they demonstrate originality, methodological soundness, academic contribution, and relevance to the journal’s health economics and healthcare-focused scope. Health Economics Insights Journal (HEIJ) particularly encourages manuscripts that address real-world problems and offer meaningful contributions to knowledge, practice, policy, and community development. The journal welcomes studies from various geographical contexts and disciplinary backgrounds, especially research that promotes sustainable health systems, inclusive healthcare access, effective health financing, evidence-based health policy, healthcare innovation, responsible governance, and improved public health outcomes.
Articles
10 Documents
<![CDATA[Explaining continuance intention to use telemedicine among adult patients in Jakarta, Indonesia: An extended UTAUT2, trust, and satisfaction structural equation modeling ]]>
<![CDATA[Mochamad Dandi]]>
<![CDATA[ Health Economics Insights Journal Vol. 1 No. 1 (2026): June 2026 ]]>
Publisher : <![CDATA[Privietlab ]]>
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DOI: 10.55942/heij.v1i1.1854
<![CDATA[Telemedicine has become a key pillar of Indonesia’s digital health transformation, but its long-term impact depends on whether patients keep using it after the urgency of the pandemic fades. Jakarta offers a strong research setting due to its high healthcare demand, solid digital infrastructure, diverse population, and direct exposure to national telemedicine policies. This study proposes a structural equation modeling approach to analyze continuance intention among adult telemedicine users in Jakarta. It integrates the Unified Theory of Acceptance and Use of Technology 2 with additional factors such as telemedicine service quality, eHealth literacy, trust, satisfaction, privacy concern, and affordability. Data will be collected through a cross-sectional survey targeting Jakarta residents aged 18 and above who have used telemedicine at least once in the past 12 months. The study aims to gather 400–500 valid responses through healthcare facilities, community networks, and online patient groups across Jakarta. All variables will be measured using seven-point Likert scales and analyzed with partial least squares structural equation modeling. The measurement model will assess reliability, composite reliability, average variance extracted, discriminant validity, and common method bias. The structural model will evaluate path coefficients, bootstrapped confidence intervals, explained variance, predictive relevance, and mediation effects. The hypotheses suggest that performance expectancy, effort expectancy, facilitating conditions, eHealth literacy, price value, trust, and satisfaction positively influence continuance intention, while privacy concern negatively affects trust and potentially reduces usage intention. Telemedicine service quality is expected to enhance trust and satisfaction, which then mediate continuance intention. Overall, this study contributes practical insights for improving patient-centered telemedicine services in Indonesia’s post-pandemic context.]]>
<![CDATA[Digital health in Indonesia: A literature review of adoption, infrastructure, equity, and health-system transformation ]]>
<![CDATA[Olivia Putri Dahlan]]>
<![CDATA[ Health Economics Insights Journal Vol. 1 No. 1 (2026): June 2026 ]]>
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DOI: 10.55942/heij.v1i1.1855
<![CDATA[Digital health has moved from a peripheral innovation agenda to a central health-system transformation agenda in Indonesia. This PRISMA-guided literature review synthesizes DOI-verified scientific articles, prioritizing studies from Indonesia and articles in international peer-reviewed journals visible through Scopus, Web of Science, PubMed, Crossref, or publisher metadata. The review asks how digital health has been studied in Indonesia, what evidence exists on adoption and implementation, and what managerial implications arise for sustainable health service transformation. The screening process produced 36 studies for qualitative synthesis, including empirical evaluations of COVID-19 response technologies, digital immunization monitoring, public health center information systems, personal health record design, teleconsultation readiness, telepharmacy, diabetes-focused mobile health, cancer survivorship telehealth, mental health literacy, and digital health literacy. The synthesis shows that Indonesia's digital health evidence is strongest on readiness, usability, acceptance, system fragmentation, and feasibility, while still developing on long-term clinical effectiveness, economic evaluation, cybersecurity governance, and equity-sensitive implementation. Four cross-cutting themes dominate the literature: digital health as national infrastructure, user adoption and workflow fit, disease-specific digital services, and digital divide/digital literacy. A management-oriented interpretation suggests that digital health should be treated as a sociotechnical service model rather than a software procurement project. Successful scaling requires interoperability, data governance, workforce capability, patient and community trust, monitoring systems, and value-based performance metrics. The review concludes with a practical agenda for Indonesian health leaders and researchers who seek to move from pilot projects to accountable, inclusive, and sustainable digital health ecosystems.]]>
<![CDATA[Active membership and claim pressure in Indonesia's national health insurance: An exploratory regression study of BPJS Kesehatan monitoring data ]]>
<![CDATA[Shultonnyck Adha]]>
<![CDATA[ Health Economics Insights Journal Vol. 1 No. 1 (2026): June 2026 ]]>
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DOI: 10.55942/heij.v1i1.1860
<![CDATA[Indonesia's Jaminan Kesehatan Nasional (JKN), administered by BPJS Kesehatan, is one of the world's largest single-payer social health insurance programs and has become central to Indonesia's progress toward universal health coverage. Yet high population registration is not identical to fiscal sustainability. This study examines whether the active population coverage rate is associated with claim pressure and financial resilience in JKN during the 2023-2024 monitoring period. The analysis uses official aggregate data from Dewan Jaminan Sosial Nasional's Monthly Report Monitoring JKN as of December 31, 2024. The data set contains 11 monthly observations for which active coverage, registered participants, active participants, net Dana Jaminan Sosial (DJS) health assets, fund resilience, and the claim ratio could be extracted consistently from public reporting. Ordinary least squares regressions with heteroskedasticity-robust standard errors were estimated. Descriptive results show that active population coverage increased from 76.07% in December 2023 to 78.83% in December 2024, while the claim ratio remained above 100% in every observed month. In the simplest specification, a one percentage-point increase in active population coverage was associated with a 1.84 percentage-point lower claim ratio. This relationship became statistically non-significant after adding a monthly trend, indicating that the observed association should be interpreted as exploratory rather than causal. The findings suggest that improving active membership is necessary for revenue adequacy but insufficient on its own; health economics policy should also address utilization growth, hospital payment incentives, chronic disease management, and contribution compliance. The paper contributes a transparent regression template for further BPJS research using microdata or provincial panels.]]>
<![CDATA[Artificial intelligence in healthcare management: Clinical applications, evidence, governance, and implementation challenges ]]>
<![CDATA[Wiky Fhalyang Razaki]]>
<![CDATA[ Health Economics Insights Journal Vol. 1 No. 1 (2026): June 2026 ]]>
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DOI: 10.55942/heij.v1i1.1861
<![CDATA[Artificial intelligence (AI) has evolved from experimental computer science into a practical component of modern healthcare systems. AI is increasingly applied in medical imaging, oncology, dermatology, ophthalmology, electronic health record analytics, clinical decision support, drug discovery, patient communication, and hospital management. However, the effectiveness of AI depends not only on algorithmic performance but also on safety, equity, explainability, workflow integration, regulatory oversight, and public trust. This paper presents an integrative narrative review of AI in healthcare based on evidence from peer-reviewed literature indexed in major databases, particularly Scopus and Web of Science. The review focuses on five key themes: diagnostic support, predictive analytics, treatment personalization, generative AI, and responsible implementation. Evidence indicates that AI can achieve specialist-level performance in tasks such as skin cancer classification, diabetic retinopathy detection, breast cancer screening, and medical image interpretation. AI systems using electronic health records can also predict deterioration, mortality, readmission, and acute kidney injury. Recent advances in large language models demonstrate potential for medical question answering, documentation assistance, and patient communication. Despite these benefits, many AI systems remain inadequately validated in real-world settings. Major concerns include algorithmic bias, lack of transparency, privacy risks, automation bias, and weak external validity. Safe AI adoption therefore requires rigorous clinical validation, continuous monitoring, transparent governance, and human-centered implementation that supports rather than replaces professional clinical judgment.]]>
<![CDATA[Mobile health application adoption and service performance in Indonesian private hospitals: A JASP-compatible panel data study ]]>
<![CDATA[Sahara Putri Dahlan]]>
<![CDATA[ Health Economics Insights Journal Vol. 1 No. 1 (2026): June 2026 ]]>
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DOI: 10.55942/heij.v1i1.1862
<![CDATA[Mobile health applications have become a visible component of Indonesia's hospital digital transformation; however, management research still has limited longitudinal evidence on how hospital-level readiness factors translate into adoption and service outcomes. This manuscript presents a JASP-compatible panel data study of mobile health application adoption among Indonesian private hospitals. A balanced synthetic panel was constructed for 72 private hospitals observed over eight quarters from 2023Q1 to 2024Q4, yielding 576 hospital-quarter observations. The data structure was designed to mimic the operational indicators that private hospitals can extract from outpatient registration systems, mobile applications, customer relationship management logs, and digital governance scorecards. Linear mixed models with random intercepts were estimated for three outcomes: active mHealth use rate, patient satisfaction, and average outpatient waiting time. The results indicate that higher system quality, information quality, privacy assurance, management support, staff training, marketing support, and SATUSEHAT integration are positively associated with active mHealth use. Active use is also associated with higher patient satisfaction and shorter outpatient waiting times after controlling for service quality, hospital size, time trends, and digital integration. The findings should be interpreted as an instructional and planning-oriented demonstration rather than as evidence of identifiable hospitals because the dataset is synthetic. This study contributes a replicable IMRAD manuscript template, an APA-style reporting format, and a JASP-ready CSV file that can be replaced with real hospital panel data for journal submission or hospital management evaluation.]]>
<![CDATA[Mapping the digital health research landscape of the gulf cooperation council: A bibliometric synthesis of two decades of scholarship (2000–2024) ]]>
<![CDATA[Khaled Ouanes]]>;
<![CDATA[Marouane Zouine]]>;
<![CDATA[Muhammad Ali]]>
<![CDATA[ Health Economics Insights Journal Vol. 1 No. 1 (2026): June 2026 ]]>
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DOI: 10.55942/heij.v1i1.2108
<![CDATA[Digital health has become a strategic pillar of health system reform across the Gulf Cooperation Council (GCC). However, the scholarly evidence base for this transformation remains fragmented and unevenly mapped. This study synthesizes two decades of bibliometric evidence (2000–2024) on digital health research originating in the six GCC states—Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates—and specifies a reproducible Scopus and Web of Science extraction protocol for primary science mapping. Drawing on the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) framework and established bibliometric guidelines, the analysis integrates macro-indicators of research productivity, thematic structure, and collaboration patterns reported in peer-reviewed regional studies. The evidence documents an accelerating publication trajectory, punctuated by a pronounced COVID-19 inflection and a marked concentration of output in Saudi Arabia and the United Arab Emirates, with Qatar exhibiting the region's steepest relative growth. Thematically, the field has migrated from foundational concerns with e-health infrastructure, electronic health records, and telemedicine toward Artificial Intelligence (AI), m-health, and personalized medicine. Collaboration is oriented predominantly toward extra-regional partners in the United Kingdom and the United States, whereas intra-GCC co-authorship remains comparatively weak. A persistent gap separates the region's world-leading translational deployments, exemplified by the Guinness-recognized Seha Virtual Hospital, from its comparatively modest knowledge production. This study offers a consolidated research agenda and a transparent methodological roadmap to advance rigorous, policy-relevant digital health scholarship in the Gulf.]]>
<![CDATA[Rethinking strategic purchasing for the financial sustainability of Indonesia's National Health Insurance or Jaminan Kesehatan Nasional (JKN): An opinion ]]>
<![CDATA[Wiky Fhalyang]]>
<![CDATA[ Health Economics Insights Journal Vol. 1 No. 2 (2026): December 2026 ]]>
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DOI: 10.55942/heij.v1i2.2137
<![CDATA[Indonesia's National Health Insurance or Jaminan Kesehatan Nasional (JKN), launched in 2014 and now covering more than 95% of the population, is the largest single-payer health insurance scheme in the world. However, its rapid expansion of population coverage has been shadowed by chronic financial deficits that have required repeated government injections and contribution increases. This Opinion advances the thesis that JKN's sustainability problem has been misframed as primarily a revenue problem, when the more decisive and underused lever is the way BPJS Kesehatan spends the money it pools—that is, its purchasing function. I argue that JKN still purchases largely passively: it contracts providers on a near-automatic basis, pays primary care through blunt capitation, and hospitals through case-based the Indonesian Case Base Groups (INA-CBG) tariffs that are weakly linked to quality or value, and under-uses Health Technology Assessment (HTA), claims analytics, and selective contracting. Drawing on the strategic-purchasing literature and evidence from Indonesia and comparable middle-income countries, I contend that shifting from passive to strategic purchasing—value-based benefit design, selective and performance-linked contracting, outcome-oriented provider payment, and data- and HTA-informed decisions—can simultaneously restrain expenditure growth, improve quality, and protect equity. Revenue reforms, including contribution adequacy and earmarked tobacco excise, remain necessary but are insufficient without purchasing reforms. I set out the trade-offs, political economy constraints, and a concrete sequenced reform agenda. Strategic purchasing, not perpetual bailouts, is the JKN's most credible path to financial sustainability and meaningful universal health coverage.]]>
<![CDATA[Artificial intelligence in health technology assessment: A commentary on promise, pitfalls, and governance ]]>
<![CDATA[Rifky Aqil Asyrof]]>
<![CDATA[ Health Economics Insights Journal Vol. 1 No. 2 (2026): December 2026 ]]>
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DOI: 10.55942/heij.v1i2.2138
<![CDATA[Generative and predictive Artificial Intelligence (AI) have moved from the periphery to the center of the methodological debate in Health Technology Assessment (HTA) and economic evaluation. Large language models now draft evidence summaries, machine-learning classifiers screen thousands of records in minutes, and emulators accelerate decision-analytic simulation—capabilities that arrived faster than the field's appraisal norms could adapt. This commentary reacts to that development and argues a deliberately dual thesis: AI can materially improve the efficiency, timeliness, and reach of HTA, but only if its adoption is disciplined by governance that treats validity, transparency, and equity as non-negotiable issues. Mapping AI methods onto the HTA workflow, I identify where value is most plausible—evidence identification and living reviews, evidence synthesis, real-world evidence and predictive modelling, decision-analytic modelling, and horizon scanning—and set against each the corresponding threats to validity, including data and label bias, opacity and irreproducibility, poor generalizability, unquantified model uncertainty, algorithmic unfairness, and automation-driven de-skilling. I contend that existing instruments (the National Institute for Health and Care Excellence evidence standards framework, ISPOR good-practice and generative-AI reports, reporting guidelines such as TRIPOD+AI and CHEERS 2022, and emerging regulatory principles) form a usable but incomplete scaffold, and that HTA bodies, researchers, and journals should converge on a governance-by-design model built on transparency, validation, human accountability, and standardized reporting. Particular attention is paid to low- and middle-income countries, where AI could widen or narrow the assessment capacity. I conclude with concrete recommendations for practice, research, and editorial policy.]]>
<![CDATA[Determinants of catastrophic health expenditure and impoverishment in low- and middle-income countries: A narrative review ]]>
<![CDATA[Siri Hurul Aini]]>
<![CDATA[ Health Economics Insights Journal Vol. 1 No. 2 (2026): December 2026 ]]>
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DOI: 10.55942/heij.v1i2.2140
<![CDATA[Financial protection—ensuring that people can use the health services they need without suffering financial hardship—is a defining pillar of Universal Health Coverage (UHC) and is monitored globally through Sustainable Development Goal (SDG) indicator 3.8.2. In Low- and Middle-Income Countries (LMICs), where Out-of-Pocket (OOP) payments finance a large share of health spending, Catastrophic Health Expenditure (CHE) and medical impoverishment remain widespread and worsening on several metrics. This narrative review synthesizes the conceptual, methodological, and empirical literature on the determinants of CHE and impoverishment in LMICs. Drawing on seminal methodological contributions and country and multi-country studies published mainly between 2003 and 2025 and identified through structured searches of Scopus, Web of Science, and PubMed, the review maps competing definitions and thresholds (the budget-share 10%/25% SDG indicators and the World Health Organization’s 40% capacity-to-pay threshold), measurement debates, and the pathways that link illness to financial hardship. Determinants were organized thematically into household-level factors (economic status, chronic and non-communicable disease, hospitalization, ageing, and household composition), health-system factors (OOP financing share, absence of prepayment and pooling, provider payment, and medicine costs), and contextual factors (rural residence and regional inequality). Evidence on prepayment, insurance expansion, benefit design, exemptions, and essential medicines policy is appraised alongside its heterogeneity. The review concludes by identifying methodological limitations and a research agenda emphasizing longitudinal designs, distress financing, and the measurement of forgone care.]]>
<![CDATA[Cost-effectiveness of telemedicine interventions: A systematic literature review ]]>
<![CDATA[Dimvy Rusefani Asetya]]>
<![CDATA[ Health Economics Insights Journal Vol. 1 No. 2 (2026): December 2026 ]]>
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DOI: 10.55942/heij.v1i2.2141
<![CDATA[Telemedicine has expanded rapidly, accelerating during the COVID-19 pandemic; however, decision-makers require robust economic evidence to guide sustained investment and reimbursement. However, whether it represents value for money versus in-person care remains contested. To systematically identify, appraise, and synthesize full economic evaluations comparing telemedicine interventions with usual or in-person care and to summarize their cost-effectiveness across clinical domains. This systematic literature review was conducted and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. PubMed/MEDLINE, Scopus, and Web of Science were searched from database inception to 31 October 2025. Eligible studies were full economic evaluations (cost-effectiveness, cost-utility, cost-benefit, or cost-minimization analyses) of telemedicine versus usual or in-person care, reporting incremental costs and consequences. Records were dual-screened, data were extracted in duplicate, and reporting quality was appraised against CHEERS 2022 and the Drummond framework. Heterogeneity precluded meta-analysis; therefore, a structured narrative synthesis was undertaken. Of the 3,311 records identified, 17 full economic evaluations (published 2007–2025; eight countries) met the inclusion criteria. The interventions included chronic disease telemonitoring and telerehabilitation, teleconsultation and specialist access, mental health teletherapy, and diagnostic or acute care telemedicine. The findings were mixed but frequently favorable: several teleconsultation, teledermatology, telestroke, and teletherapy interventions were cost-saving or dominant, whereas home telemonitoring for chronic disease was often not cost-effective at conventional thresholds. Cost-effectiveness was strongly context-dependent and driven by avoided travel, activity volume, and intervention delivery costs. Telemedicine can be cost-effective, but its value is conditional on modality, clinical context, and scale rather than universal.]]>
