Financial Simulation of Remote Healthcare Implementation Strategies in Türkiye: A Monte Carlo Analysis Based on Specialty-Specific Eligibility

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  • SDG 3 · Sağlık ve Kaliteli Yaşam

Özet

The expansion of universal health coverage in Türkiye has intensified pressure on public healthcare providers through high outpatient volumes that strain capacity and financial sustainability. Remote healthcare delivery has emerged as a potential strategy to improve efficiency and access. However, limited evidence exists on how remote outpatient care should be implemented across medical specialties within a universal payer system, or how alternative implementation strategies perform financially. This study evaluates the specialty-specific feasibility and financial impact of remote outpatient care using comprehensive administrative data from a large public training and research hospital in Izmir, supplemented by qualitative input from clinical specialists. The analysis includes 577,984 outpatient visits recorded in 2022 across major medical specialties. Eligibility for remote delivery is identified using observable clinical proxies—imaging requests, laboratory tests, and prescription issuance—to capture visits not requiring physical examination or procedural intervention. Results show that 121,248 visits (21.0%) are suitable for remote delivery, accounting for 16.2% of expenditures ($0.68 million out of $4.20 million). Remote eligibility varies substantially across specialties, with high suitability in dermatology and infectious diseases but limited applicability in device-dependent fields such as pulmonology. Four implementation scenarios are simulated over a 10-year horizon: Regulatory Compliance, Evidence-Based Specialty-Specific, Follow-Up Only, and Hybrid Progressive. The Regulatory Compliance scenario yields the shortest break-even period (3 years) and highest ROI (1185%). The Hybrid Progressive scenario, incorporating phased specialty expansion and AI-supported triage, requires higher upfront costs but generates the largest cumulative net savings ($1.39 million). The findings demonstrate that financially sustainable remote outpatient care can be achieved through carefully designed, specialty-specific implementation strategies.

Anahtar Kelimeler

RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/gumushane/13710Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.1002/hpm.70118Yayıncı resmi DOI adresi
Tam Kayıt
AlanDeğerDil
dc.contributor.authorDemir, Hüseyin
dc.contributor.authorAkar, Tuncay
dc.contributor.authorMertoğlu, Süleyman
dc.contributor.authorBurmaoğlu, Serhat
dc.contributor.authorTekinarslan, Merve
dc.date.accessioned2026-10-22T10:21:40.748732674Z
dc.date.available2026-10-22T10:21:40.748732674Z
dc.date.issued2026
dc.description.abstractThe expansion of universal health coverage in Türkiye has intensified pressure on public healthcare providers through high outpatient volumes that strain capacity and financial sustainability. Remote healthcare delivery has emerged as a potential strategy to improve efficiency and access. However, limited evidence exists on how remote outpatient care should be implemented across medical specialties within a universal payer system, or how alternative implementation strategies perform financially. This study evaluates the specialty-specific feasibility and financial impact of remote outpatient care using comprehensive administrative data from a large public training and research hospital in Izmir, supplemented by qualitative input from clinical specialists. The analysis includes 577,984 outpatient visits recorded in 2022 across major medical specialties. Eligibility for remote delivery is identified using observable clinical proxies—imaging requests, laboratory tests, and prescription issuance—to capture visits not requiring physical examination or procedural intervention. Results show that 121,248 visits (21.0%) are suitable for remote delivery, accounting for 16.2% of expenditures ($0.68 million out of $4.20 million). Remote eligibility varies substantially across specialties, with high suitability in dermatology and infectious diseases but limited applicability in device-dependent fields such as pulmonology. Four implementation scenarios are simulated over a 10-year horizon: Regulatory Compliance, Evidence-Based Specialty-Specific, Follow-Up Only, and Hybrid Progressive. The Regulatory Compliance scenario yields the shortest break-even period (3 years) and highest ROI (1185%). The Hybrid Progressive scenario, incorporating phased specialty expansion and AI-supported triage, requires higher upfront costs but generates the largest cumulative net savings ($1.39 million). The findings demonstrate that financially sustainable remote outpatient care can be achieved through carefully designed, specialty-specific implementation strategies.
dc.identifier.doi10.1002/hpm.70118
dc.identifier.eissn1099-1751
dc.identifier.issn0749-6753
dc.identifier.pmid42525879
dc.identifier.scopus2-s2.0-105046237512
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/gumushane/13710
dc.identifier.wosWOS:001834822600001
dc.language.isoen
dc.publisherJohn Wiley and Sons Ltd
dc.relation.ispartofInternational Journal of Health Planning and Management
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjecthealthcare
dc.subjectoutpatient visits
dc.subjectpatient density
dc.subjectpayer institution
dc.subjectremote healthcare
dc.subjectTürkiye
dc.subject.classificationHealth Policy & Services
dc.subject.classificationPublic, Environmental & Occupational Health
dc.subject.classificationHealth Care Sciences & Services
dc.titleFinancial Simulation of Remote Healthcare Implementation Strategies in Türkiye: A Monte Carlo Analysis Based on Specialty-Specific Eligibility
dc.typeArticle
dspace.entity.typePublication
rdl.citation.openalex0
rdl.citation.scopus0
rdl.citation.wos0
rdl.departmentDepartment of Health Management, Faculty of Health Sciences, Gümüşhane University, Gümüşhane, Türkiye
rdl.oa.statusclosed
rdl.publication.statusinPress
rdl.sdgSDG03
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.source.indexPUBMED
rdl.wos.indexSocial Science Citation Index (SSCI)