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Development of a Visualization Tool for Healthcare Decision-Making using Electronic Medical Records: A Systems Approach to Viewing a Patient Record.
Mandell, Georgia A; Keating, Matthew B; Khayal, Inas S.
Afiliação
  • Mandell GA; Department of Computer Science, Dartmouth College, Hanover, NH, 03768.
  • Keating MB; Department of Computer Science, Dartmouth College, Hanover, NH, 03768.
  • Khayal IS; The Dartmouth Institute and Biomedical Data Science, Geisel School of Medicine at Dartmouth, Department of Computer Science, Dartmouth College, Hanover, NH, USA.
Annu IEEE Syst Conf ; 20222022 Apr.
Article em En | MEDLINE | ID: mdl-37681014
ABSTRACT
Healthcare delivery systems are widely accepted as socio-technical systems. Unlike other socio-technical systems, healthcare systems leave very little decision-making to technical automation and control. Instead, the healthcare delivery system relies on human healthcare resources for decision-making. Human decision-making is imperative to the clinical delivery of care to patients and to the operational processes that support care delivery, quality improvement, and other organizational management activities. For these clinical and operational activities, human resources make healthcare decisions using healthcare data typically housed in electronic medical records (EMRs). Unfortunately, EMR systems were first designed with the functional capability to store data, and, second to a lesser degree, to retrieve data. The literature recognizes the need to improve the retrieval of information from EMR systems. More specifically, there remains the need to directly view a patient's holistic health and healthcare trajectory. At this time, decision-makers are left to mentally build this holistic picture in their mind by sequentially clicking through many sections of the EMR. Therefore, in this paper, we develop a visualization tool to organize and present an individual's health and healthcare trajectory by describing a patient record holistically from a system architecture perspective. This approach is based on a previously developed system model for healthcare delivery and individual health outcomes.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Annu IEEE Syst Conf Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Annu IEEE Syst Conf Ano de publicação: 2022 Tipo de documento: Article