Literature DB >> 16696260

The potential of training to increase acceptance and use of computerized decision support systems for medical diagnosis.

Fuji Lai1, Jean Macmillan, Denise H Daudelin, David M Kent.   

Abstract

OBJECTIVE: The goals of this study were to understand the reasons underlying the limited use of medical decision-support tools and to explore the potential of a computer-based tutorial to mitigate barriers to use.
BACKGROUND: Medical decision-support tools such the Acute Cardiac Ischemia Time-Insensitive Predictive Instrument (ACI-TIPI) have demonstrated statistical validity and clinical impact for patient safety but have seen limited adoption and use.
METHODS: The study developed a brief Web-based "demystifying" ACI-TIPI tutorial employing case-based training and evaluated the effectiveness of that tutorial in changing self-reported attitudes and behaviors.
RESULTS: Clinicians using the tutorial reported greater understanding of how to use the ACI-TIPI score appropriately and increased confidence in the score. Case studies in the tutorial that provided examples of how to use the score for actual cases were rated as especially helpful.
CONCLUSION: This study suggests that a primary barrier to the use of statistical decision support tools for patient diagnosis is lack of training or experience in combining a population-based numerical risk score with other diagnostic information about the individual patient's case that is not considered in that score. The results of this study indicate that there is a potential for a relatively brief tutorial to increase acceptance and use of decision support tools for medical diagnosis. APPLICATION: These findings have the potential for the identification of methods to help clinicians learn how to use statistical and probabilistic information to better assess risk and to promote integration of decision support tools into medical decision making for improvement of patient safety.

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Mesh:

Year:  2006        PMID: 16696260     DOI: 10.1518/001872006776412306

Source DB:  PubMed          Journal:  Hum Factors        ISSN: 0018-7208            Impact factor:   2.888


  7 in total

Review 1.  Systematic review of factors influencing the adoption of information and communication technologies by healthcare professionals.

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Journal:  J Med Syst       Date:  2010-03-30       Impact factor: 4.460

Review 2.  Rethinking health numeracy: a multidisciplinary literature review.

Authors:  Jessica S Ancker; David Kaufman
Journal:  J Am Med Inform Assoc       Date:  2007-08-21       Impact factor: 4.497

3.  Association of Disparities in Family History and Family Cancer History in the Electronic Health Record With Sex, Race, Hispanic or Latino Ethnicity, and Language Preference in 2 Large US Health Care Systems.

Authors:  Daniel Chavez-Yenter; Melody S Goodman; Yuyu Chen; Xiangying Chu; Richard L Bradshaw; Rachelle Lorenz Chambers; Priscilla A Chan; Brianne M Daly; Michael Flynn; Amanda Gammon; Rachel Hess; Cecelia Kessler; Wendy K Kohlmann; Devin M Mann; Rachel Monahan; Sara Peel; Kensaku Kawamoto; Guilherme Del Fiol; Meenakshi Sigireddi; Saundra S Buys; Ophira Ginsburg; Kimberly A Kaphingst
Journal:  JAMA Netw Open       Date:  2022-10-03

Review 4.  Interventions for promoting information and communication technologies adoption in healthcare professionals.

Authors:  Marie-Pierre Gagnon; France Légaré; Michel Labrecque; Pierre Frémont; Pierre Pluye; Johanne Gagnon; Josip Car; Claudia Pagliari; Marie Desmartis; Lucile Turcot; Karine Gravel
Journal:  Cochrane Database Syst Rev       Date:  2009-01-21

5.  Acceptability and Barriers to Use of the ASMAN Provider-Facing Electronic Platform for Peripartum Care in Public Facilities in Madhya Pradesh and Rajasthan, India: A Qualitative Study Using the Technology Acceptance Model-3.

Authors:  Gulnoza Usmanova; Ashley Gresh; Megan A Cohen; Young-Mi Kim; Ashish Srivastava; Chandra Shekhar Joshi; Deepak Chandra Bhatt; Rachel Haws; Rajni Wadhwa; Pompy Sridhar; Nupur Bahl; Pratibha Gaikwad; Jean Anderson
Journal:  Int J Environ Res Public Health       Date:  2020-11-11       Impact factor: 3.390

6.  Factors That Impact the Adoption of Clinical Decision Support Systems (CDSS) for Antibiotic Management.

Authors:  Mah Laka; Adriana Milazzo; Tracy Merlin
Journal:  Int J Environ Res Public Health       Date:  2021-02-16       Impact factor: 3.390

Review 7.  An overview of clinical decision support systems: benefits, risks, and strategies for success.

Authors:  Reed T Sutton; David Pincock; Daniel C Baumgart; Daniel C Sadowski; Richard N Fedorak; Karen I Kroeker
Journal:  NPJ Digit Med       Date:  2020-02-06
  7 in total

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