RESUMEN
BACKGROUND: The increasing population of older adults has led to a rise in the demand for health care services, with chronic diseases being a major burden. Person-centered integrated care is required to address these challenges; hence, the Turkish Ministry of Health has initiated strategies to implement an integrated health care model for chronic disease management. We aim to present the design, development, nationwide implementation, and initial performance results of the national Disease Management Platform (DMP). OBJECTIVE: This paper's objective is to present the design decisions taken and technical solutions provided to ensure successful nationwide implementation by addressing several challenges, including interoperability with existing IT systems, integration with clinical workflow, enabling transition of care, ease of use by health care professionals, scalability, high performance, and adaptability. METHODS: The DMP is implemented as an integrated care solution that heavily uses clinical decision support services to coordinate effective screening and management of chronic diseases in adherence to evidence-based clinical guidelines and, hence, to increase the quality of health care delivery. The DMP is designed and implemented to be easily integrated with the existing regional and national health IT systems via conformance to international health IT standards, such as Health Level Seven Fast Healthcare Interoperability Resources. A repeatable cocreation strategy has been used to design and develop new disease modules to ensure extensibility while ensuring ease of use and seamless integration into the regular clinical workflow during patient encounters. The DMP is horizontally scalable in case of high load to ensure high performance. RESULTS: As of September 2023, the DMP has been used by 25,568 health professionals to perform 73,715,269 encounters for 16,058,904 unique citizens. It has been used to screen and monitor chronic diseases such as obesity, cardiovascular risk, diabetes, and hypertension, resulting in the diagnosis of 3,545,573 patients with obesity, 534,423 patients with high cardiovascular risk, 490,346 patients with diabetes, and 144,768 patients with hypertension. CONCLUSIONS: It has been demonstrated that the platform can scale horizontally and efficiently provides services to thousands of family medicine practitioners without performance problems. The system seamlessly interoperates with existing health IT solutions and runs as a part of the clinical workflow of physicians at the point of care. By automatically accessing and processing patient data from various sources to provide personalized care plan guidance, it maximizes the effect of evidence-based decision support services by seamless integration with point-of-care electronic health record systems. As the system is built on international code systems and standards, adaptation and deployment to additional regional and national settings become easily possible. The nationwide DMP as an integrated care solution has been operational since January 2020, coordinating effective screening and management of chronic diseases in adherence to evidence-based clinical guidelines.
RESUMEN
Integrating healthcare enterprise (IHE) specifies integration profiles describing selected real world use cases to facilitate the interoperability of healthcare information resources. While realizing a complex real-world scenario, IHE profiles are combined by grouping the related IHE actors. Grouping IHE actors implies that the associated business processes (IHE profiles) that the actors are involved must be combined, that is, the choreography of the resulting collaborative business process must be determined by deciding on the execution sequence of transactions coming from different profiles. There are many IHE profiles and each user or vendor may support a different set of IHE profiles that fits to its business need. However, determining the precedence of all the involved transactions manually for each possible combination of the profiles is a very tedious task. In this paper, we describe how to obtain the overall business process automatically when IHE actors are grouped. For this purpose, we represent the IHE profiles through a standard, machine-processable language, namely, Organization for the Advancement of Structured Information Standards (OASIS) ebusiness eXtensible Markup Language (ebXML) Business Process Specification (ebBP) Language. We define the precedence rules among the transactions of the IHE profiles, again, in a machine-processable way. Then, through a graphical tool, we allow users to select the actors to be grouped and automatically produce the overall business process in a machine-processable format.