Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2018 Apr 19;13(4):e0193187.
doi: 10.1371/journal.pone.0193187. eCollection 2018.

Acceptance and barriers pertaining to a general practice decision support system for multiple clinical conditions: A mixed methods evaluation

Affiliations

Acceptance and barriers pertaining to a general practice decision support system for multiple clinical conditions: A mixed methods evaluation

Derk L Arts et al. PLoS One. .

Abstract

Background: Many studies have investigated the use of clinical decision support systems as a means to improve care, but have thus far failed to show significant effects on patient-related outcomes. We developed a clinical decision support system that attempted to address issues that were identified in these studies. The system was implemented in Dutch general practice and was designed to be both unobtrusive and to respond in real time. Despite our efforts, usage of the system was low. In the current study we perform a mixed methods evaluation to identify remediable barriers which led to disappointing usage rates for our system.

Methods: A mixed methods evaluation employing an online questionnaire and focus group. The focus group was organized to clarify free text comments and receive more detailed feedback from general practitioners. Topics consisted of items based on results from the survey and additional open questions.

Results: The response rate for the questionnaire was 94%. Results from the questionnaire and focus group can be summarized as follows: The system was perceived as interruptive, despite its design. Participants felt that there were too many recommendations and that the relevance of the recommendations varied. Demographic based recommendations (e.g. age) were often irrelevant, while specific risk-based recommendations (e.g. diagnosis) were more relevant. The other main barrier to use was lack of time during the patient visit.

Conclusion: These results are likely to be useful to other researchers who are attempting to address the problems of interruption and alert fatigue in decision support.

PubMed Disclaimer

Conflict of interest statement

Competing Interests: We have the following interests: DA was Funded by Boehringer Ingelheim with an unrestricted grant through the ZORRO foundation (no website available). There are no patents, products in development or marketed products to declare. This does not alter our adherence to all the PLOS ONE policies on sharing data and materials.

Figures

Fig 1
Fig 1. The notification window in its expanded state, showing three notification items.
Fig 2
Fig 2. The window after clicking on a notification item, containing background information, an actionable recommendation and response buttons to allow the GP to indicate whether they accept (1) or decline (2) the advice (3) close the window (no action).
Fig 3
Fig 3. Overview of activities related to data collection.
Fig 4
Fig 4. Self-reported use of the system.
Percentage of users that answered yes to the listed questions.
Fig 5
Fig 5. Self-reported usage rates of the system.
Answers to the question: “How often did you use the system, e.g. clicked a notification, accepted a recommendation etc.?”.
Fig 6
Fig 6. Selected questions and Likert scales.

Similar articles

Cited by

References

    1. Shortliffe EH, Cimino JJ. Biomedical informatics: computer applications in health care and biomedicine: Springer Science & Business Media; 2013.
    1. Roshanov PS, Misra S, Gerstein HC, Garg AX, Sebaldt RJ, Mackay JA, et al. Computerized clinical decision support systems for chronic disease management: a decision-maker-researcher partnership systematic review. Implement Sci. 2011;6:92 doi: 10.1186/1748-5908-6-92 . - DOI - PMC - PubMed
    1. Hemens BJ, Holbrook A, Tonkin M, Mackay JA, Weise-Kelly L, Navarro T, et al. Computerized clinical decision support systems for drug prescribing and management: a decision-maker-researcher partnership systematic review. Implement Sci. 2011;6:89 doi: 10.1186/1748-5908-6-89 . - DOI - PMC - PubMed
    1. Bright TJ, Wong A, Dhurjati R, Bristow E, Bastian L, Coeytaux RR, et al. Effect of clinical decision-support systems: a systematic review. Ann Intern Med. 2012;157(1):29–43. Epub 2012/07/04. doi: 10.7326/0003-4819-157-1-201207030-00450 . - DOI - PubMed
    1. Moja L, Kwag KH, Lytras T, Bertizzolo L, Brandt L, Pecoraro V, et al. Effectiveness of Computerized Decision Support Systems Linked to Electronic Health Records: A Systematic Review and Meta-Analysis. Am J Public Health. 2014;104(12):E12–E22. doi: 10.2105/AJPH.2014.302164 - DOI - PMC - PubMed

Publication types

LinkOut - more resources