Document Detail


Computer-based decision support for pediatric asthma management: description and feasibility of the Stop Asthma Clinical System.
MedLine Citation:
PMID:  17092998     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Clinical guidelines can assist in the management of asthma. Decision support systems (DSSs) can enhance adherence to clinical guidelines but tend not to provide clinicians with cues for behavioral change strategies to promote patient self-management. The Stop Asthma Clinical System (SACS) is a DSS designed for this purpose. To assess feasibility, seven clinicians used SACS to guide well visits with 26 predominantly persistent pediatric asthma patients. Data were collected via survey and in-depth semi-structured interviews. SACS improved assessment of asthma severity and control, classification of and intervention in medicine and environmental trigger management problems, and development of an action plan (all p < 0.05). Clinician-patient communication was enhanced. The primary challenge was that SACS increased clinic visit time. SACS can enhance clinician behavior to improve patient asthma self-management, but more studies are indicated to mitigate temporal constraints and evaluate impact on clinician and patient communication and behavior as well as clinical outcomes.
Authors:
Ross Shegog; Leona K Bartholomew; Marianna M Sockrider; Danita I Czyzewski; Susan Pilney; Patricia Dolan Mullen; Stuart L Abramson
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural    
Journal Detail:
Title:  Health informatics journal     Volume:  12     ISSN:  1460-4582     ISO Abbreviation:  Health Informatics J     Publication Date:  2006 Dec 
Date Detail:
Created Date:  2006-11-09     Completed Date:  2007-03-01     Revised Date:  2007-11-15    
Medline Journal Info:
Nlm Unique ID:  100883604     Medline TA:  Health Informatics J     Country:  England    
Other Details:
Languages:  eng     Pagination:  259-73     Citation Subset:  IM    
Affiliation:
Center for Health Promotion and Prevention Research, UT-School of Public Health, 7000 Fannin, Suite 2668, Houston, TX 77030, USA. Ross.Shegog@uth.tmc.edu
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Asthma / psychology,  therapy*
Child
Computer Systems*
Decision Making, Computer-Assisted*
Decision Support Systems, Clinical*
Feasibility Studies
Guideline Adherence
Health Care Surveys
Humans
Interviews as Topic
Physician-Patient Relations
Self Care
Grant Support
ID/Acronym/Agency:
R18 AI39782/AI/NIAID NIH HHS

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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