How effective are clinical decision support systems?
BMJ 2020; 370 doi: https://doi.org/10.1136/bmj.m3499 (Published 17 September 2020) Cite this as: BMJ 2020;370:m3499Linked Research
Computerised clinical decision support systems and absolute improvements in care
Linked Opinion
What I have learned about clinical decision support systems over the past decade
- Urmimala Sarkar, professor12,
- Lipika Samal, assistant professor34
- 1Division of General Internal Medicine, Zuckerberg San Francisco General Hospital, San Francisco, CA, USA
- 2Center for Vulnerable Populations, University of California San Francisco, San Francisco, CA, USA
- 3Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- 4Department of Medicine, Harvard Medical School, Boston, MA, USA
- Correspondence to: U Sarkar Urmimala.Sarkar{at}ucsf.edu
The linked meta-analysis (doi:10.1136/bmj.m3216) by Kwan and colleagues of 122 trials of clinical decision support systems embedded in electronic health records shows modest improvements in care processes overall, with widely varying effects among trials.1 The authors found no significant improvement in clinical outcomes in the subset of 30 trials that included them.
The strengths of this meta-analysis include the large number of studies across a variety of clinical conditions and health systems. The authors reported absolute differences in care processes between groups (with versus without clinical decision support systems) rather than reporting the odds of receiving the recommended care, which underscores the small to moderate benefits of clinical decision support systems compared with usual care for selected care processes.
The authors also found extreme heterogeneity among studies that could not be attributed to any of the factors known to differ across interventions. The decision to include only quasi-randomized trials might have excluded studies of innovations in clinical decision support systems when randomization was either not acceptable to stakeholders or not feasible. Including rigorous …
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