Literature DB >> 29730649

Diagnostic accuracy in Family Medicine residents using a clinical decision support system (DXplain): a randomized-controlled trial.

Adrian Israel Martinez-Franco1, Melchor Sanchez-Mendiola2, Juan Jose Mazon-Ramirez3, Isaias Hernandez-Torres3, Carlos Rivero-Lopez3, Troy Spicer4, Adrian Martinez-Gonzalez5.   

Abstract

BACKGROUND: Clinical reasoning is an essential skill in physicians, required to address the challenges of accurate patient diagnoses. The goal of the study was to compare the diagnostic accuracy in Family Medicine residents, with and without the use of a clinical decision support tool (DXplain http://www.mghlcs.org/projects/dxplain).
METHODS: A total of 87 first-year Family Medicine residents, training at the National Autonomous University of Mexico (UNAM) Postgraduate Studies Division in Mexico City, participated voluntarily in the study. They were randomized to a control group and an intervention group that used DXplain. Both groups solved 30 clinical diagnosis cases (internal medicine, pediatrics, gynecology and emergency medicine) in a multiple-choice question test that had validity evidence.
RESULTS: The percent-correct score in the Diagnosis Test in the control group (44 residents) was 74.1±9.4 (mean±standard deviation) whereas the DXplain intervention group (43 residents) had a score of 82.4±8.5 (p<0.001). There were significant differences in the four knowledge content areas of the test.
CONCLUSIONS: Family Medicine residents have appropriate diagnostic accuracy that can improve with the use of DXplain. This could help decrease diagnostic errors, improve patient safety and the quality of medical practice. The use of clinical decision support systems could be useful in educational interventions and medical practice.

Entities:  

Keywords:  clinical decision making; clinical decision support systems; diagnostic errors; medical education; randomized controlled trial

Mesh:

Year:  2018        PMID: 29730649     DOI: 10.1515/dx-2017-0045

Source DB:  PubMed          Journal:  Diagnosis (Berl)        ISSN: 2194-802X


  7 in total

1.  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

2.  Investigating the Potential for Clinical Decision Support in Sub-Saharan Africa With AFYA (Artificial Intelligence-Based Assessment of Health Symptoms in Tanzania): Protocol for a Prospective, Observational Pilot Study.

Authors:  Marcel Schmude; Nahya Salim; Hila Azadzoy; Mustafa Bane; Elizabeth Millen; Lisa O'Donnell; Philipp Bode; Ewelina Türk; Ria Vaidya; Stephen Gilbert
Journal:  JMIR Res Protoc       Date:  2022-06-07

Review 3.  Survey of Image Processing Techniques for Brain Pathology Diagnosis: Challenges and Opportunities.

Authors:  Martin Cenek; Masa Hu; Gerald York; Spencer Dahl
Journal:  Front Robot AI       Date:  2018-11-02

Review 4.  Data Integration Challenges for Machine Learning in Precision Medicine.

Authors:  Mireya Martínez-García; Enrique Hernández-Lemus
Journal:  Front Med (Lausanne)       Date:  2022-01-25

Review 5.  Characteristics of Complex Systems in Sports Injury Rehabilitation: Examples and Implications for Practice.

Authors:  Kate K Yung; Clare L Ardern; Fabio R Serpiello; Sam Robertson
Journal:  Sports Med Open       Date:  2022-02-22

Review 6.  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.  Effects of a Differential Diagnosis List of Artificial Intelligence on Differential Diagnoses by Physicians: An Exploratory Analysis of Data from a Randomized Controlled Study.

Authors:  Yukinori Harada; Shinichi Katsukura; Ren Kawamura; Taro Shimizu
Journal:  Int J Environ Res Public Health       Date:  2021-05-23       Impact factor: 3.390

  7 in total

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