1. Quantitative Analysis of Uncertainty in Medical Reporting: Part 3: Customizable Education, Decision Support, and Automated Alerts.
- Author
-
Reiner, Bruce I.
- Subjects
AUTOMATION ,CLINICAL medicine ,DATABASES ,DECISION support systems ,HEALTH education ,INFORMATION storage & retrieval systems ,MEDICAL databases ,MEDICAL information storage & retrieval systems ,LANGUAGE & languages ,EVALUATION of medical care ,MEDICAL personnel ,MEDICAL protocols ,MEDICAL technology ,PUBLIC health surveillance ,QUALITY assurance ,UNCERTAINTY ,WORKFLOW ,QUANTITATIVE research ,DATA analytics - Abstract
In order to better elucidate and understand the causative factors and clinical implications of uncertainty in medical reporting, one must first create a referenceable database which records a number of standardized metrics related to uncertainty language, clinical context, technology, and provider and patient data. The resulting analytics can in turn be used to create context and user-specific reporting guidelines, real-time decision support, educational resources, and quality assurance measures. If this technology can be directly integrated into reporting technology and workflow, the goal is to proactively improve clinical outcomes at the point of care. [ABSTRACT FROM AUTHOR]
- Published
- 2018
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