title: The Effectiveness of Electronic Differential Diagnoses (DDX) Generators: A Systematic Review and Meta-Analysis.
abstract: BACKGROUND
  Diagnostic errors are costly and they can contribute to adverse patient outcomes, including avoidable deaths. Differential diagnosis (DDX) generators are electronic tools that may facilitate the diagnostic process.
  
  
  RESULTS
  We conducted a systematic review and meta-analysis to investigate the efficacy and utility of DDX generators. We undertook a comprehensive search of the literature including 16 databases from inception to May 2015 and specialist patient safety databases. We also searched the reference lists of included studies. Article screening, selection and data extraction were independently conducted by 2 reviewers. 36 articles met the eligibility criteria and the pooled accurate diagnosis retrieval rate of DDX tools was high with high heterogeneity (pooled rate = 0.70, 95% CI = 0.63 to 0.77; I2 = 97%, p<0.0001). DDX generators did not demonstrate improved diagnostic retrieval compared to clinicians but small improvements were seen in the before and after studies where clinicians had the opportunity to revisit their diagnoses following DDX generator consultation. Clinical utility data generally indicated high levels of user satisfaction and significant reductions in time taken to use for newer web-based tools. Lengthy differential lists and their low relevance were areas of concern and have the potential to increase diagnostic uncertainty. Data on the number of investigations ordered and on cost-effectiveness remain inconclusive.
  
  
  CONCLUSIONS
  DDX generators have the potential to improve diagnostic practice among clinicians. However, the high levels of heterogeneity, the variable quality of the reported data and the minimal benefits observed for complex cases suggest caution. Further research needs to be undertaken in routine clinical settings with greater consideration of enablers and barriers which are likely to impact on DDX use before their use in routine clinical practice can be recommended.
authors.affiliation: NIHR Greater Manchester Primary Care Patient Safety Translational Research Centre (Greater Manchester PSTRC), Williamson Building, The University of Manchester, Manchester, United Kingdom.
authors.forename: Nicholas
authors.initials: N
authors.lastname: Riches
authors.affiliation: NIHR School for Primary Care Research, Centre for Primary Care, Institute of Population Health, University of Manchester, Manchester, United Kingdom.
authors.forename: Maria
authors.initials: M
authors.lastname: Panagioti
authors.affiliation: NIHR Greater Manchester Primary Care Patient Safety Translational Research Centre (Greater Manchester PSTRC), Williamson Building, The University of Manchester, Manchester, United Kingdom.
authors.forename: Rahul
authors.initials: R
authors.lastname: Alam
authors.affiliation: NIHR Greater Manchester Primary Care Patient Safety Translational Research Centre (Greater Manchester PSTRC), Williamson Building, The University of Manchester, Manchester, United Kingdom.
authors.forename: Sudeh
authors.initials: S
authors.lastname: Cheraghi-Sohi
authors.affiliation: NIHR Greater Manchester Primary Care Patient Safety Translational Research Centre (Greater Manchester PSTRC), Williamson Building, The University of Manchester, Manchester, United Kingdom.
authors.forename: Stephen
authors.initials: S
authors.lastname: Campbell
authors.affiliation: NIHR Greater Manchester Primary Care Patient Safety Translational Research Centre (Greater Manchester PSTRC), Williamson Building, The University of Manchester, Manchester, United Kingdom.
authors.forename: Aneez
authors.initials: A
authors.lastname: Esmail
authors.affiliation: NIHR Greater Manchester Primary Care Patient Safety Translational Research Centre (Greater Manchester PSTRC), Williamson Building, The University of Manchester, Manchester, United Kingdom.
authors.forename: Peter
authors.initials: P
authors.lastname: Bower
mesh_terms: D003936:Diagnosis, Computer-Assisted / Q000379:methods* / Q000592:standards / Q000639:trends; D003937:Diagnosis, Differential; D006801:Humans