BACKGROUND: Computer-based medical diagnostic decision support systems have been used for decades, initially as stand-alone applications. More recent versions have been tested for their effectiveness in enhancing the diagnostic ability of clinicians. OBJECTIVE: To determine if viewing a rank-ordered list of diagnostic possibilities from a medical diagnostic decision support system improves residents' differential diagnoses or management plans. METHOD: Twenty first-year internal medicine residents at Massachusetts General Hospital viewed 3 deidentified case descriptions of real patients. All residents completed a web-based questionnaire, entering the differential diagnosis and management plan before and after seeing the diagnostic decision support system's suggested list of diseases. In all 3 exercises, the actual case diagnosis was first on the system's list. Each resident served as his or her own control (pretest/posttest). RESULTS: For all 3 cases, a substantial percentage of residents changed their primary considered diagnosis after reviewing the system's suggested diagnoses, and a number of residents who had not initially listed a "further action" (laboratory test, imaging study, or referral) added or changed their management options after using the system. Many residents (20% to 65% depending on the case) improved their differential diagnosis from before to after viewing the system's suggestions. The average time to complete all 3 cases was 15.4 minutes. Most residents thought that viewing the medical diagnostic decision support system's list of suggestions was helpful. CONCLUSION: Viewing a rank-ordered list of diagnostic possibilities from a diagnostic decision support tool had a significant beneficial effect on the quality of first-year medicine residents' differential diagnoses and management plans.
BACKGROUND: Computer-based medical diagnostic decision support systems have been used for decades, initially as stand-alone applications. More recent versions have been tested for their effectiveness in enhancing the diagnostic ability of clinicians. OBJECTIVE: To determine if viewing a rank-ordered list of diagnostic possibilities from a medical diagnostic decision support system improves residents' differential diagnoses or management plans. METHOD: Twenty first-year internal medicine residents at Massachusetts General Hospital viewed 3 deidentified case descriptions of real patients. All residents completed a web-based questionnaire, entering the differential diagnosis and management plan before and after seeing the diagnostic decision support system's suggested list of diseases. In all 3 exercises, the actual case diagnosis was first on the system's list. Each resident served as his or her own control (pretest/posttest). RESULTS: For all 3 cases, a substantial percentage of residents changed their primary considered diagnosis after reviewing the system's suggested diagnoses, and a number of residents who had not initially listed a "further action" (laboratory test, imaging study, or referral) added or changed their management options after using the system. Many residents (20% to 65% depending on the case) improved their differential diagnosis from before to after viewing the system's suggestions. The average time to complete all 3 cases was 15.4 minutes. Most residents thought that viewing the medical diagnostic decision support system's list of suggestions was helpful. CONCLUSION: Viewing a rank-ordered list of diagnostic possibilities from a diagnostic decision support tool had a significant beneficial effect on the quality of first-year medicine residents' differential diagnoses and management plans.
Authors: Padmanabhan Ramnarayan; Ritika R Kapoor; Michael Coren; Vasantha Nanduri; Amanda L Tomlinson; Paul M Taylor; Jeremy C Wyatt; Joseph F Britto Journal: J Am Med Inform Assoc Date: 2003-08-04 Impact factor: 4.497
Authors: Nidhi R Shah; Andrew C Seger; Diane L Seger; Julie M Fiskio; Gilad J Kuperman; Barry Blumenfeld; Elaine G Recklet; David W Bates; Tejal K Gandhi Journal: J Am Med Inform Assoc Date: 2005-10-12 Impact factor: 4.497
Authors: Charles P Friedman; Guido G Gatti; Timothy M Franz; Gwendolyn C Murphy; Fredric M Wolf; Paul S Heckerling; Paul L Fine; Thomas M Miller; Arthur S Elstein Journal: J Gen Intern Med Date: 2005-04 Impact factor: 5.128
Authors: C P Friedman; A S Elstein; F M Wolf; G C Murphy; T M Franz; P S Heckerling; P L Fine; T M Miller; V Abraham Journal: JAMA Date: 1999-11-17 Impact factor: 56.272
Authors: Padmanabhan Ramnarayan; Andrew Winrow; Michael Coren; Vasanta Nanduri; Roger Buchdahl; Benjamin Jacobs; Helen Fisher; Paul M Taylor; Jeremy C Wyatt; Joseph Britto Journal: BMC Med Inform Decis Mak Date: 2006-11-06 Impact factor: 2.796