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Precision medicine, artificial intelligence, analytics, and predictive modeling hold great promise to advance healthcare, possibly as dramatically as the introduction of scientific research methodology to medicine in the past century. We are well suited to provide an indispensable and absent entity for data analytics and predictive modeling vendors. Development of temporal objects as a domain, syntactic rules and a semantic validation approach  supply a missing, mission critical component.

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No unified, functioning system currently exists for the exchange of comprehensive health-care information across the wide spectrum of health-care networks. Regional health information organizations (RHIOs) and a national health information network (NHIN) have been proposed as vital building blocks in providing such a system, but these face many challenges, including delineation and implementation of accepted standards for health-care data, accurate patient identification and record matching, and the definition of incentives for accelerated deployment of health information technology. In response to these challenges, we present in this paper an alternative option, the Health Record Banking (HRB) system. Emulating commercial banking, this approach uses health-record banks to serve the need for immediately accessible and secure data for diverse stakeholders. It provides a means for financial independence for these banks and a mechanism for fostering medical research. We conclude with 10 critical issues associated with the development and implementation of an HRB system, which require public discussion.

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Consumer demand for personal health records (PHRs) and the capabilities provided by regional health information organizations (RHIOs) will change healthcare, just as automatic teller machines have changed banking. The PHR is predicated on the existence of electronic medical records (EMRs) and electronic health records (EHRs). Patient and consumer principles guiding the development of the PHR reflect issues of access, control, privacy, and security. Working models illustrate the variations of RHIOs and PHRs possible and suggest the benefits that electronic information exchange can accrue for healthcare and healthcare consumers. Today both the private and public sectors are working to define the issues involved in efforts that are now taking place and that will transform healthcare. Consumers are ready for the type of changes that will improve healthcare quality.

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Beyond the clear advantages of shared access to a patient’s health record, through the secondary use of data and the customization of care, the health information exchange shall proffer exceptional benefits to the patient. Querying across health information exchange databases for individuals matching multiple key characteristics of a patient will enable patient-specific decision support. This dramatic shift from searching the medical literature for studies focused on a single or limited number of patient attributes to performing patient-specific research using several of the patient’s health and history data will dramatically alter the way medical decisions will be tailored to meet an individual’s needs.

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Keywords

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Temporality, Temporospatial Relationships, Predictive Modeling, Precision Medicine, Data Analytics, Population Health, Longitudinal Electronic Medical Record (LEMR), Data Visualization, Problem List Management, Data Quality, Data Normalization, Natural Language Processing (NLP), Machine Learning (ML), Artificial Intelligence (AI), Large Language Models (LLM), Unstructured Text, Health Information Exchange (HIE), Health, Medicine

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