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Understanding complex clinical decis...

Islam, Roosan.

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Understanding complex clinical decision tasks for better health information technology system design.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Understanding complex clinical decision tasks for better health information technology system design./
作者:	Islam, Roosan.
面頁冊數:	144 p.
附註:	Source: Dissertation Abstracts International, Volume: 77-10(E), Section: B.
Contained By:	Dissertation Abstracts International77-10B(E).
標題:	Behavioral sciences. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10118373
ISBN:	9781339797045

Understanding complex clinical decision tasks for better health information technology system design.
Islam, Roosan.

Understanding complex clinical decision tasks for better health information technology system design. - 144 p.

Source: Dissertation Abstracts International, Volume: 77-10(E), Section: B.

Thesis (Ph.D.)--The University of Utah, 2016.

Clinical decision support systems (CDSS) and electronic health records (EHR) have been widely adopted but do not support a high level of reasoning for the clinician. As a result, workflow incongruity and provider frustrations lead to more errors in reasoning. Other successful fields such as defense, aviation, and the military have used task complexity as a key factor in decision support system development. Task complexity arises during the interaction of the user and the tasks. Therefore, in this dissertation I have utilized different human factor methods to explore task complexity factors to understand their utility in health information technology system design.

ISBN: 9781339797045Subjects--Topical Terms:

529833
Behavioral sciences.

Understanding complex clinical decision tasks for better health information technology system design.
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100 1 $a Islam, Roosan. $3 3191174
245 1 0 $a Understanding complex clinical decision tasks for better health information technology system design.
300 $a 144 p.
500 $a Source: Dissertation Abstracts International, Volume: 77-10(E), Section: B.
500 $a Adviser: Guilherme Del Fiol.
502 $a Thesis (Ph.D.)--The University of Utah, 2016.
520 $a Clinical decision support systems (CDSS) and electronic health records (EHR) have been widely adopted but do not support a high level of reasoning for the clinician. As a result, workflow incongruity and provider frustrations lead to more errors in reasoning. Other successful fields such as defense, aviation, and the military have used task complexity as a key factor in decision support system development. Task complexity arises during the interaction of the user and the tasks. Therefore, in this dissertation I have utilized different human factor methods to explore task complexity factors to understand their utility in health information technology system design.
520 $a The first study addresses the question of generalizing complexity through a clinical complexity model. In this study, we integrated and validated a patient and task complexity model into a clinical complexity model tailored towards healthcare to serve as the initial framework for data analysis in our subsequent studies.
520 $a The second study addresses the question of the coping strategies of infectious disease (ID) clinicians while dealing with complex decision tasks. The study concluded that clinicians use multiple cognitive strategies that help them to switch between automatic cognitive processes and analytical processes.
520 $a The third study identified the complexity contributing factors from the transcripts of the observations conducted in the ID domain. The clinical complexity model developed in the first study guided the research for identifying the prominent complexity factors to recommend innovative healthcare technology system design.
520 $a The fourth study, a pilot exploratory study, demonstrated the feasibility of developing a population information display from querying real complex patient information from an actual clinical database as well as identifying the ideal features of population information display.
520 $a In summary, this dissertation adds to the knowledge about how clinicians adapt their information environment to deal with complexity. First, it contributes by developing a clinical complexity model that integrates both patient and task complexity. Second, it provides specific design recommendations for future innovative health information technology systems. Last, this dissertation also suggests that understanding task complexity in the healthcare team domain may help to better design of interface system.
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650 4 $a Health care management. $3 2122906
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773 0 $t Dissertation Abstracts International $g 77-10B(E).
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792 $a 2016
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856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10118373