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Effectiveness of computerized decision support systems linked to electronic health records: A systematic review and meta-analysis

Author

Listed:
  • Moja, L.
  • Kwag, K.H.
  • Lytras, T.
  • Bertizzolo, L.
  • Brandt, L.
  • Pecoraro, V.
  • Rigon, G.
  • Vaona, A.
  • Ruggiero, F.
  • Mangia, M.
  • Iorio, A.
  • Kunnamo, I.
  • Bonovas, S.

Abstract

We systematically reviewed randomized controlled trials (RCTs) assessing the effectiveness ofcomputerized decision support systems (CDSSs) featuring rule- or algorithm-based software integrated with electronic health records (EHRs) and evidence-based knowledge. We searched MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and Cochrane Database of Abstracts of Reviews of Effects. Information on system design, capabilities, acquisition, implementation context, and effects on mortality, morbidity, and economic outcomes were extracted. Twenty-eight RCTs were included. CDSS use did not affect mortality (16 trials, 37395 patients; 2282 deaths; risk ratio [RR] = 0.96; 95%confidence interval [CI] = 0.85, 1.08; I2 = 41%).Astatistically significant effect was evident in the prevention ofmorbidity, any disease (9 RCTs; 13868 patients;RR = 0.82; 95% CI = 0.68, 0.99; I2 = 64%), but selectiveoutcomereporting or publication bias cannot be excluded. We observed differences for costs and health service utilization, although these were often small in magnitude. Across clinical settings, new generation CDSSs integrated with EHRs do not affect mortality and might moderately improvemorbidity outcomes. © 2013 American Public Health Association.

Suggested Citation

  • Moja, L. & Kwag, K.H. & Lytras, T. & Bertizzolo, L. & Brandt, L. & Pecoraro, V. & Rigon, G. & Vaona, A. & Ruggiero, F. & Mangia, M. & Iorio, A. & Kunnamo, I. & Bonovas, S., 2014. "Effectiveness of computerized decision support systems linked to electronic health records: A systematic review and meta-analysis," American Journal of Public Health, American Public Health Association, vol. 104(12), pages 12-22.
    • Handle: RePEc:aph:ajpbhl:10.2105/ajph.2014.302164_0
    DOI: 10.2105/AJPH.2014.302164
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    Cited by:

    1. Akio Kanazawa & Kazutoshi Fujibayashi & Yu Watanabe & Seiko Kushiro & Naotake Yanagisawa & Yasuko Fukataki & Sakiko Kitamura & Wakako Hayashi & Masashi Nagao & Yuji Nishizaki & Takenori Inomata & Eri , 2023. "Evaluation of a Medical Interview-Assistance System Using Artificial Intelligence for Resident Physicians Interviewing Simulated Patients: A Crossover, Randomized, Controlled Trial," IJERPH, MDPI, vol. 20(12), pages 1-11, June.

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