Hospital as a Platform: API-First Healthcare Ecosystems Where AI Agents Coordinate Multi-Institutional Care Pathways

Abstract

The traditional hospital model is increasingly strained by fragmentation, workforce shortages, and rising chronic disease burdens. This narrative review and conceptual framework proposes redefining hospitals as modular nodes within API-first digital platforms. Drawing on platform economics (Uber/Airbnb analogies), HL7 FHIR interoperability standards, and emerging agentic AI capabilities, the article introduces the Hospital-as-a-Platform model. In this architecture, autonomous AI agents orchestrate dynamic, patient-centric care chains across multiple institutions, enabling seamless coordination, optimized resource utilization, and continuity beyond institutional boundaries. Managerial implications include revenue diversification through platform participation, while applications encompass revolutionized global health tourism via algorithmically matched cross-border pathways. By 2035, hospitals are envisioned as hybrid physical-digital platforms, where physical infrastructure supports high-acuity needs and AI-driven orchestration handles the majority of coordination. The framework offers a strategic blueprint for healthcare leaders to transition toward resilient, ecosystem-centric delivery systems.

Keywords

• Hospital
• Artificial Intelligence
• Digital Health

Hastane Platform Olarak: Yapay Zeka Ajanlarının Çok Kurumlu Bakım Yollarını Koordine Ettiği API-Öncelikli Sağlık Ekosistemleri

Abstract

Geleneksel hastane modeli, parçalanma, işgücü eksikliği ve artan kronik hastalık yükü nedeniyle giderek zorlanmaktadır. Bu anlatısal derleme ve kavramsal çerçeve, hastaneleri API-öncelikli dijital platformlar içinde modüler düğümler olarak yeniden tanımlamayı önermektedir. Platform ekonomisi (Uber/Airbnb benzetmeleri), HL7 FHIR birlikte çalışabilirlik standartları ve ortaya çıkan ajanik yapay zeka yeteneklerinden yararlanarak makale Hastane-Platform-Olarak modelini sunmaktadır. Bu mimaride, otonom yapay zeka ajanları, birden fazla kurum arasında dinamik, hasta odaklı bakım zincirlerini koordine ederek kesintisiz koordinasyon, optimize kaynak kullanımı ve kurumsal sınırların ötesinde süreklilik sağlar. Yöneticilik açısından platform katılımı yoluyla gelir çeşitlendirmesi gibi etkiler söz konusudur; uygulamalar ise algoritmik olarak eşleştirilen sınır ötesi yollarla dönüştürülmüş küresel sağlık turizmini kapsamaktadır. 2035 yılına gelindiğinde hastaneler, fiziksel altyapının yüksek akut ihtiyaçları desteklediği ve yapay zeka odaklı orkestrasyonun koordinasyonun büyük kısmını üstlendiği hibrit fiziksel-dijital platformlar olarak öngörülmektedir. Çerçeve, sağlık liderlerine dayanıklı, ekosistem odaklı teslimat sistemlerine geçiş için stratejik bir taslak sunmaktadır.

Keywords

• Hastane
• Yapay Zeka
• Dijital Sağlık

References

1. 1. World Health Organization. World report on ageing and health. Geneva: WHO; 2015.
2. 2. Agyepong I, Spicer N, Ooms G, et al. The Lancet Commission on synergies between universal health coverage, health security, and health promotion. The Lancet. 2023;401(10392):1964-2012 https://doi.org/10.1016/S0140-6736(22)01930-4
3. 3. Javaid M, Haleem A, Singh RP, Suman R. Dentistry 4.0 technologies applications for dentistry during COVID-19 pandemic. Sustain Oper Comput. 2021;2:87-96. https://doi.org/10.1016/j.susoc.2021.05.002
4. 4. Kickbusch I, Piselli D, Agrawal A, Balicer R, Banner O, Adelhardt M, et al. The Lancet and Financial Times Commission on governing health futures 2030: growing up in a digital world. Lancet. 2021;398(10312):1727-1776. doi:10.1016/S0140-6736(21)01824-9.
5. 5. Parker, G. G., Van Alstyne, M. W., & Choudary, S. P. (2016). Platform revolution: How networked markets are transforming the economy and how to make them work for you. WW Norton & Company.
6. 6. Biscoe G, David AM, Effler P, Hong YC, Morgan C, Raviglione MC, et al. UH The critical platform towards a healthier and safer future in 2030 and beyond. Lancet Reg Health West Pac. 2022;25:100529. https://doi.org/10.1016/j.lanwpc.2022.100529
7. 7. HL7 FHIR Overview. https://www.hl7.org/fhir/overview.html (accessed 2026).
8. 8. Ayaz M, Pasha MF, Alzahrani MY, Budiarto R, Stiawan D. The Fast Health Interoperability Resources (FHIR) standard: systematic literature review of implementations, applications, challenges and opportunities. JMIR Med Inform. 2021;9(7):e21929. 10.2196/21929

9. 9. Liu F, Niu Y, Zhang Q, Wang K, Dong Z, Wong IN, et al. A foundational architecture for AI agents in healthcare. Cell Rep Med. 2025;6(10):102374. doi:10.1016/j.xcrm.2025.102374.
10. 10. Moritz M, Topol E, Rajpurkar P. Coordinated AI agents for advancing healthcare. Nat Biomed Eng. 2025;9(4):432-438. doi:10.1038/s41551-025-01363-2.
11. 11. Nopour R. Using FHIR for data sharing: A scoping review of challenges and facilitators in healthcare settings. Int J Med Inform. 2026;205:106128. doi:10.1016/j.ijmedinf.2025.106128
12. 12. Schünemann HJ, Reinap M, Piggott T, Laidmäe E, Köhler K, Põld M, et al. The ecosystem of health decision making: from fragmentation to synergy. Lancet Public Health. 2022;7(4):e378-e390. doi:10.1016/S2468-2667(22)00057-3.
13. 13. Hanson K, Brikci N, Erlangga D, Alebachew A, De Allegri M, Balabanova D, et al. The Lancet Global Health Commission on financing primary health care: putting people at the centre. Lancet Glob Health. 2022;10(5):e715-e772. doi:10.1016/S2214-109X(22)00005-5.
14. 14. World Health Organization. Digital Health Platform Handbook: Building a Digital Information Infrastructure (Infostructure) for Health. Geneva: WHO-ITU; 2020.
15. 15. Mantri M, Sunder G, Kadam S, Abhyankar A. A perspective on digital health platform design and its implementation at national level. Front Digit Health. 2024;6:1260855. doi:10.3389/fdgth.2024.1260855
16. 16. Tabari P, Costagliola G, De Rosa M, Boeker M. State-of-the-art fast healthcare interoperability resources (FHIR)–based data model and structure implementations: systematic scoping review. JMIR Med Inform. 2024;12:e58445. doi:10.2196/58445. doi: 10.2196/58445
17. 17. Vorisek CN, Lehne M, Klopfenstein SAI, Mayer PJ, Bartschke A, Haese T, et al. Fast Healthcare Interoperability Resources (FHIR) for interoperability in health research: systematic review. JMIR Med Inform. 2022;10(7):e35724. doi:10.2196/35724.
18. 18. Rigas ES, Lagakis P, Karadimas M, Logaras E, Latsou D, Hatzikou M, et al. Semantic interoperability for an AI-based applications platform for smart hospitals using HL7 FHIR. J Syst Softw. 2024;215:112093. doi:10.1016/j.jss.2024.112093.
19. 19. Amar F, April A, Abran A. Electronic health record and semantic issues using fast healthcare interoperability resources: systematic mapping review. J Med Internet Res. 2024;26:e45209. doi:10.2196/45209
20. 20. Li Y, Wang H, Yerebakan HZ, Shinagawa Y, Luo Y. FHIR-GPT enhances health interoperability with large language models. NEJM AI. 2024;1(8):AIcs2300301. doi:10.1056/AIcs2300301.
21. 21. Borkowski AA, Ben-Ari A. Multiagent AI systems in health care: envisioning next-generation intelligence. Fed Pract. 2025;42(5):188-194. doi:10.12788/fp.0589.
22. 22. Reinhart E, Dawes D, Maybank A. Structural medicine: towards an economy of care. Lancet. 2021;397(10286):1691-1693. doi:10.1016/S0140-6736(21)00937-5
23. 23. Gutierriz I, Ferreira JJ, Fernandes PO. Digital transformation and the new combinations in tourism: A systematic literature review. Int J Contemp Hosp Manag. 2025;37(1):14673584231198414.
24. 24. Niţulescu A, Ciuciulete G, Manda C, Popa MC. Data Standardization in the Medical Field Through FHIR and FAIR Implementation. JMIR Med Inform. 2024;12:e56637.
25. 25. Kwee A, Oh S, Chua M. Digital health in medicine: Important considerations in evaluating health economic analysis. Lancet West Pac. 2022;31:100606.
26. 26. Njei B, Chukwudi O, Njei M. Artificial intelligence agents in healthcare research: A scoping review. J Med Internet Res. 2026;28:e12890167.
27. 27. Gorenshtein A, Mermelstein S, Yanover C. AI Agents in Clinical Medicine: A Systematic Review. J Med Internet Res. 2025;27:e40909853.
28. 28. Engelke M, Bönninghoff B, et al. FHIR-Former: enhancing clinical predictions through Fast Healthcare Interoperability Resources and large language models. JAMIA. 2025;32(12):1793-1801.
29. 29. Lehne M, Luijten S, Imbusch PVG, Thun S. FHIR meets large language models: perspectives and use cases. JAMIA Open. 2024;7(1):ooad100.
30. 30. Meskó B, Topol EJ. The imperative for regulatory-grade real-world evidence in AI-driven healthcare. Nat Med. 2023;29(10):2395-2397.
31. 31. Zong N, Wen A, Moon S, et al. Interoperability and machine-to-machine translation model with mappings to machine learning algorithms. J Am Med Inform Assoc. 2020;27(10):1612-1621.
32. 32. Williams E, Martin G, Gagnaire L, et al. A Standardized Clinical Data Harmonization Pipeline for Scalable AI Application Deployment (FHIR-DHP): Validation and Usability Study. JMIR Med Inform. 2023;11:e43847.
33. 33. Alper BS, Dehnbostel J, Webber S, et al. Evidence-based medicine on FHIR augments the standards-based approach to digital health research. J Am Med Inform Assoc. 2026;33(1):ocag024.
34. 34. Sayeed R, Gottlieb D, Mandel JC, et al. A standards-based approach to digital health research: implementing the people heart study. J Am Med Inform Assoc. 2025;32(12):1811-1820.
35. 35. Busch F, Adams LC, Bressem KK. Navigating the European Union Artificial Intelligence Act for Healthcare. NPJ Digit Med. 2024;7(1):211.
36. 36. Azure API for FHIR. Microsoft Azure Documentation. 2025. https://azure.microsoft.com/en-us/products/health-data-services/.
37. 37. Google Cloud Healthcare API. Google Cloud Documentation. 2025. https://cloud.google.com/healthcare-api.
38. 38. van Kolfschooten H, van der Veen A. The EU Artificial Intelligence Act (2024): Implications for healthcare. Health Policy. 2024;138:105152.
39. 39. Lathan, Ross, et al. "Telemedicine for sustainable postoperative follow-up: a prospective pilot study evaluating the hybrid life-cycle assessment approach to carbon footprint analysis." Frontiers in Surgery 11 (2024): 1300625.
40. 40. Trejo Omeñaca, A., Llargués Rocabruna, E., Sloan, J., Catta-Preta, M., Ferrer i Picó, J., Alfaro Álvarez, J. C., ... & Bayes Genis, B. (2025). Leave as fast as you can: using generative AI to automate and accelerate hospital discharge reports. Computers, 14(6), 210.
41. 41. Li, J., Lai, Y., Li, W., Ren, J., Zhang, M., Kang, X., ... & Liu, Y. (2024). Agent hospital: A simulacrum of hospital with evolvable medical agents. arXiv preprint arXiv:2405.02957.
42. 42. Rani S, Arora V, Chauhan M, et al. Machine Learning-Powered Smart Healthcare Systems in the Era of Big Data: Applications, Diagnostic Insights, Challenges, and Ethical Implications. Diagnostics (Basel). 2025;15(15):1914.
43. 43. Rokni L. Technology Adoption in Tourism to Deal with Global Health Crisis: A Narrative Review. J Med Internet Res. 2025;27:e12675962.
44. 44. Jlassi, Nouha, et al. "Collaborative, autonomous, and partially selfish agents: An innovative approach to managing crisis decisions in a hospital merger." 2025 International Conference on Software, Knowledge, Information Management & Applications (SKIMA). IEEE, 2025.
45. 45. Zhu, H. (2022). Spatial matching and policy-planning evaluation of urban elderly care facilities based on multi-agent simulation: Evidence from Shanghai, China. Sustainability, 14(23), 16183.
46. 46. World Health Organization. Global Strategy on Digital Health 2020-2025. Geneva: WHO; 2021.