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

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First Edition

Introduction

Clinical decision support systems (CDSS) are integrated into electronic health records and intended to influence clinical decisions and improve quality of care processes. Evidence has shown improved clinical performance yet the improved health care quality and improved outcomes have been mixed. [1]

Interesting research question

What are the possible reasons and causes from healthcare clinicians’ perspectives for difficulties in integrating CDSS?

Methods

The authors did a meta-synthesis associated with CDSS integration using research studies from actual CDSS clinical settings. They conducted a literature search using key words “CDSS in healthcare” and “clinicians experience of CDSS adoption”. PubMed and CINAHL databases were searched. Only peer reviewed journal articles from years 2000-2013 were selected. From the results, the bibliographies were reviewed for any additional relevant studies.

Results

PubMed returned 3797 studies and CINAHL returned 361 studies for a total of 4158. Selecting only those studies that met criteria further narrowed the results. In total 81 studies were used.

Conclusions

Overall, there was a lack of quality studies that addressed the clinicians experience with CDSS and overall studies with limited understanding of the clinicians’ workflow. CDSS provided alerts and reminders based on well-defined objectives yet provided little natural decision support or situational awareness. Five areas identified which needed further study. They were usability, clinician-patient-system integration, algorithm immaturity, and system immaturity.

Area of interest

The human-computer interactions and the need to better understand the relationship between computational and human reasoning and problem solving.

References

  1. Miller, A. Integrating computerized clinical decision support systems into clinical work: A meta-synthesis of qualitative research. http://www.ncbi.nlm.nih.gov/pubmed/26391601


Second Edition

Introduction

The outcomes of the use of Clinical decision support systems (CDSSs) are largely controversial, despite they are an emerging tool that is promising to improve healthcare quality, safety, and efficiency. A recent meta-analysis revealed that the results of using CDSSs are still mixing [1].

Methods

  • Inclusion criteria: Qualitative studies published between 2000 and 2013 in English, including physicians, registered and advanced practice nurses who had CDSS user experience in the clinic.
  • Search strategy: PubMed and CINAHL databases were searched and three reviewers made final judgement for each publication against pre-defined criteria for evaluation. The details can be found in the article [1].

Results

56 out of 3798 selected unique records met inclusion criteria and were reviewed against quality criteria. Of which, "nine 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." [1].

Conclusions

Despite ongoing development and requirements in response to the meaningful use, CDSS seems to remain as an emerging technology at its infancy in terms of meeting the meaningful use such as quality and safety improvement, and clinical care efficiency. “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.” [1]. The key issue is to better understand how to optimize human-system interaction that can ultimately eliminate unwanted consequences while maximizing its potentials as to achieve desired clinical care outcomes.

References

  1. 1.0 1.1 1.2 1.3 Miller, A., Moon, B., Anders, S., Walden, R., Brown, S., & Montella, D. (2015). Integrating computerized clinical decision support systems into clinical work: A meta-synthesis of qualitative research. International Journal of Medical Informatics. http://doi.org/10.1016/j.ijmedinf.2015.09.005

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