Performance of API Design for Interoperability of Medical Information Systems

After the experience of the COVID-19 pandemic, it has become evident that efficient and secure interoperability of medical information is crucial for effective diagnoses and medical treatments. However, a significant challenge arises concerning the heterogeneity of the systems storing patient information in medical centers or hospitals. Memory management becomes a pivotal element for the effective operation of the proposed API, as it must seamlessly execute across various devices, ranging from healthcare units, such as mobile phones, to servers in cloud computing. This proposal addresses these issues through techniques designed to enhance the performance of the software architecture in creating a medical interoperability API. This API has the capacity to be cloned and distributed to facilitate the exchange of data related to a patient's medical history. To tackle heterogeneity, efficient memory management was implemented by utilizing an object-oriented approach and leveraging design patterns like abstract factory and wrapper. Regarding the evaluation of the proposal, this study showed an estimated performance of 94.5 percent, which was indirectly demonstrated through the assessment of operation sequences. This result suggests a satisfactory level based on complexity and coupling.