Abstract
Patient-centric medical record systems provide patients control over their health data versus electronic health record (EHR) systems that are health provider based and typically geared around bill presentment and payment. There are several limitations in current EHR systems, such as details of healthcare not making it into the system, the loss of out of network healthcare and potential for malicious cyber exploitations. This research effort posits the potential of utilizing blockchain to support a patient-centered personal health record (PHR) system focused on the healthcare needs of older adults. Such a system expands the data collected to include every source of healthcare provider from optometrists to chiropractors to oncologists. Blockchain technologies would provide architecture and security for such a system.
Specifically, we present the framework geared to track older adult health records including modules that provide early disease detection and drug-drug interaction for the top chronic diseases experienced by older adults using various machine learning classification algorithms. The algorithms evaluate the entirety of diagnoses and symptoms to find co-morbidities that may be an indicator of latent disease such as early signs of dementia and Alzheimer’s diseases. The patient’s health information is interpreted by a nurse practitioner or hospitalist who can determine if a specialist needs to be involved to evaluate the predicted disease. The proposed approach will provide a secure way to have a comprehensive view of the patient’s health data and arm the patient with the most inclusive set of information for doctors to provide the best health care.
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Osborn, S., Choo, KK.R. (2024). A Blockchain Patient-Centric Records Framework for Older Adult Healthcare. In: Perakovic, D., Knapcikova, L. (eds) Future Access Enablers for Ubiquitous and Intelligent Infrastructures. FABULOUS 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 542. Springer, Cham. https://doi.org/10.1007/978-3-031-50051-0_2
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