NIH VideoCast - Transforming Electronic Health Records from Annoyances to Assistants: A Research Agenda for the Next Decade

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Transforming Electronic Health Records from Annoyances to Assistants: A Research Agenda for the Next Decade

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Air date:	Wednesday, November 1, 2017, 2:00:00 PM Time displayed is Eastern Time, Washington DC Local
Views:	Total views: 370 (208 Live, 162 On-demand)
Category:	Special
Runtime:	01:01:36
Closed captioning:	Check box to display CC outside of the video Note: You can drag the captioning window around and resize it
Description:	NLM Informatics Lecture Series Clinical informatics research, and before that, medical informatics research, has made great strides in developing tools to help clinicians improve clinical decision-making and patient care. Yet, electronic health records (EHR) systems today show little aptitude for even simple tasks, like retrieving relevant patient information, while suppressing that which is irrelevant. When bringing artificial intelligence to bear, the best EHRs seem to do is to overwhelm us with alerts that a clinician must override to take action. When the “learning health system” attempts to use data from these systems, it must rely on indirect methods, such as machine learning and natural language processing, to figure out what was actually going on with the patient. The advances that have been made to bring decision support into EHRs rely on formally represented – that is structured and coded – data, such as problem lists, laboratory results and medication lists. What’s missing is a formal representation of the clinical cognition of the patient’s situation: what we think is going on, what our goals are, what we are trying to do about it, and why we have chosen to do it that way. Adding such information to the EHR would enable informaticians to enhance their tools in ways that will improve situational awareness, reduce information overload, make decision support systems provide more relevant knowledge to clinicians, and enable clinical researchers to draw more solid inferences from observational data. Informatics research is needed to understand what needs to be captured, determine how it should be represented, design user interfaces to minimize the effort required, and develop tools that ultimately reduce the work of clinical documentation by reducing redundant data entry, anticipating and executing work plans, and improve the quality and efficiency of patient care. Dr. Cimino will provide illustrations of the formal representation and use of clinical cognition and present a roadmap for research, development and education toward that goal.

NLM Title:	Transforming electronic health records from annoyances to assistants : a research agenda for the next decade / Jim Cimino.
Author:	Cimino, James J. National Institutes of Health (U.S.),
Publisher:
Abstract:	(CIT): Clinical informatics research, and before that, medical informatics research, has made great strides in developing tools to help clinicians improve clinical decision-making and patient care. Yet, electronic health records (EHR) systems today show little aptitude for even simple tasks, like retrieving relevant patient information, while suppressing that which is irrelevant. When bringing artificial intelligence to bear, the best EHRs seem to do is to overwhelm us with alerts that a clinician must override to take action. When the "learning health system" attempts to use data from these systems, it must rely on indirect methods, such as machine learning and natural language processing, to figure out what was actually going on with the patient. The advances that have been made to bring decision support into EHRs rely on formally represented - that is structured and coded - data, such as problem lists, laboratory results and medication lists. What"s missing is a formal representation of the clinical cognition of the patient"s situation: what we think is going on, what our goals are, what we are trying to do about it, and why we have chosen to do it that way. Adding such information to the EHR would enable informaticians to enhance their tools in ways that will improve situational awareness, reduce information overload, make decision support systems provide more relevant knowledge to clinicians, and enable clinical researchers to draw more solid inferences from observational data. Informatics research is needed to understand what needs to be captured, determine how it should be represented, design user interfaces to minimize the effort required, and develop tools that ultimately reduce the work of clinical documentation by reducing redundant data entry, anticipating and executing work plans, and improve the quality and efficiency of patient care. Dr. Cimino will provide illustrations of the formal representation and use of clinical cognition and present a roadmap for research, development and education toward that goal.
Subjects:	Electronic Health Records Quality Improvement United States
Publication Types:	Lecture Webcast

NLM Classification:	WX 175
NLM ID:	101718209
CIT Live ID:	26529
Permanent link:	https://videocast.nih.gov/watch=26529

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