Integrating computerized clinical decision support systems into clinical work: A meta-synthesis of qualitative research

•Research associated CDSS has increased but little of it is high quality qualitative research.•Lack of qualitative research suggests that understanding about CDSS is also lacking.•Most CDSS applications involved alerts and reminders associated with well-defined, criterion-based processes.•The majority of CDSS applications involved outpatient settings clinical decision making in inpatient lacking.•Future directions unintended adaptation to CDSS; clinicians extract meaning from.

PurposeComputerized clinical decision support systems (CDSS) are an emerging means for improving healthcare safety, quality and efficiency, but meta-analyses findings are mixed. This meta-synthesis aggregates qualitative research findings as possible explanations for variable quantitative research outcomes.Inclusion criteriaQualitative studies published between 2000 and 2013 in English, involving physicians, registered and advanced practice nurses’ experience of CDSS use in clinical practice were included.Search strategyPubMed and CINAHL databases were searched. Study titles and abstracts were screened against inclusion criteria. Retained studies were appraised against quality criteria. Findings were extracted iteratively from studies in the 4th quartile of quality scores. Two reviewers constructed themes inductively. A third reviewer applied the defined themes deductively achieving 92% agreement.Results3798 unique records were returned; 56 met inclusion criteria and were reviewed against quality criteria. 9 studies were of sufficiently high quality for synthetic analysis. Five major themes (clinician-patient-system integration; user interface usability; the need for better ‘algorithms’; system maturity; patient safety) were defined.ConclusionsDespite ongoing development, CDSS remains an emerging technology. Lack of understanding about and lack of consideration for the interaction between human decision makers and CDSS is a major reason for poor system adoption and use. Further high-quality qualitative research is needed to better understand human—system interaction issues. These issues may continue to confound quantitative study results if not addressed.