Barriers and facilitators to the adoption of electronic clinical decision support systems: a qualitative interview study with UK general practitioners

Elizabeth Ford; Natalie Edelman; Laura  Somers; Duncan Shrewsbury; Marcela Lopez Levy; Harm Van Marwijk; Vasa  Curcin; Talya  Porat

doi:10.1186/s12911-021-01557-z

Barriers and facilitators to the adoption of electronic clinical decision support systems: a qualitative interview study with UK general practitioners

Elizabeth Ford, Natalie Edelman, Laura Somers, Duncan Shrewsbury, Marcela Lopez Levy, Harm Van Marwijk, Vasa Curcin, Talya Porat

Research output: Contribution to journal › Article › peer-review

Abstract

Background: Well-established electronic data capture in UK general practice means that algorithms, developed on patient data, can be used for automated clinical decision support systems (CDSSs). These can predict patient risk, help with prescribing safety, improve diagnosis and prompt clinicians to record extra data. However, there is persistent evidence of low uptake of CDSSs in the clinic. We interviewed UK General Practitioners (GPs) to understand what features of CDSSs, and the contexts of their use, facilitate or present barriers to their use. Methods: We interviewed 11 practicing GPs in London and South England using a semi-structured interview schedule and discussed a hypothetical CDSS that could detect early signs of dementia. We applied thematic analysis to the anonymised interview transcripts. Results: We identified three overarching themes: trust in individual CDSSs; usability of individual CDSSs; and usability of CDSSs in the broader practice context, to which nine subthemes contributed. Trust was affected by CDSS provenance, perceived threat to autonomy and clear management guidance. Usability was influenced by sensitivity to the patient context, CDSS flexibility, ease of control, and non-intrusiveness. CDSSs were more likely to be used by GPs if they did not contribute to alert proliferation and subsequent fatigue, or if GPs were provided with training in their use. Conclusions: Building on these findings we make a number of recommendations for CDSS developers to consider when bringing a new CDSS into GP patient records systems. These include co-producing CDSS with GPs to improve fit within clinic workflow and wider practice systems, ensuring a high level of accuracy and a clear clinical pathway, and providing CDSS training for practice staff. These recommendations may reduce the proliferation of unhelpful alerts that can result in important decision-support being ignored.

Original language	English
Article number	193
Journal	BMC Medical Informatics and Decision Making
Volume	21
Issue number	1
DOIs	https://doi.org/10.1186/s12911-021-01557-z
Publication status	Published - 21 Jun 2021

Bibliographical note

Funding Information:
This project was funded by a grant from the Wellcome Trust ref. 202133/Z/16/Z. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. VC is also supported by the National Institute for Health Research (NIHR) Biomedical Research Centre based at Guy's and St Thomas' National Health Service NHS) Foundation Trust and King's College London, and the Public Health and Multimorbidity Theme of the National Institute for Health Research’s Applied Research Collaboration (ARC) South London. The opinions in this paper are those of the authors and do not necessarily reflect the opinions of the funders.

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Keywords

General Practice
clinical prediction
decision-making
electronic health records
qualitative
Alert fatigue
Primary health care
Barriers
General practice
Clinical decision support
Adoption

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Ford, E., Edelman, N., Somers, L., Shrewsbury, D., Lopez Levy, M., Van Marwijk, H., Curcin, V., & Porat , T. (2021). Barriers and facilitators to the adoption of electronic clinical decision support systems: a qualitative interview study with UK general practitioners. BMC Medical Informatics and Decision Making, 21(1), Article 193. https://doi.org/10.1186/s12911-021-01557-z

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abstract = "Background: Well-established electronic data capture in UK general practice means that algorithms, developed on patient data, can be used for automated clinical decision support systems (CDSSs). These can predict patient risk, help with prescribing safety, improve diagnosis and prompt clinicians to record extra data. However, there is persistent evidence of low uptake of CDSSs in the clinic. We interviewed UK General Practitioners (GPs) to understand what features of CDSSs, and the contexts of their use, facilitate or present barriers to their use. Methods: We interviewed 11 practicing GPs in London and South England using a semi-structured interview schedule and discussed a hypothetical CDSS that could detect early signs of dementia. We applied thematic analysis to the anonymised interview transcripts. Results: We identified three overarching themes: trust in individual CDSSs; usability of individual CDSSs; and usability of CDSSs in the broader practice context, to which nine subthemes contributed. Trust was affected by CDSS provenance, perceived threat to autonomy and clear management guidance. Usability was influenced by sensitivity to the patient context, CDSS flexibility, ease of control, and non-intrusiveness. CDSSs were more likely to be used by GPs if they did not contribute to alert proliferation and subsequent fatigue, or if GPs were provided with training in their use. Conclusions: Building on these findings we make a number of recommendations for CDSS developers to consider when bringing a new CDSS into GP patient records systems. These include co-producing CDSS with GPs to improve fit within clinic workflow and wider practice systems, ensuring a high level of accuracy and a clear clinical pathway, and providing CDSS training for practice staff. These recommendations may reduce the proliferation of unhelpful alerts that can result in important decision-support being ignored.",

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note = "Funding Information: This project was funded by a grant from the Wellcome Trust ref. 202133/Z/16/Z. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. VC is also supported by the National Institute for Health Research (NIHR) Biomedical Research Centre based at Guy's and St Thomas' National Health Service NHS) Foundation Trust and King's College London, and the Public Health and Multimorbidity Theme of the National Institute for Health Research{\textquoteright}s Applied Research Collaboration (ARC) South London. The opinions in this paper are those of the authors and do not necessarily reflect the opinions of the funders. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.",

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AU - Edelman, Natalie

AU - Somers, Laura

AU - Shrewsbury, Duncan

AU - Lopez Levy, Marcela

AU - Van Marwijk, Harm

AU - Curcin, Vasa

AU - Porat , Talya

N1 - Funding Information: This project was funded by a grant from the Wellcome Trust ref. 202133/Z/16/Z. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. VC is also supported by the National Institute for Health Research (NIHR) Biomedical Research Centre based at Guy's and St Thomas' National Health Service NHS) Foundation Trust and King's College London, and the Public Health and Multimorbidity Theme of the National Institute for Health Research’s Applied Research Collaboration (ARC) South London. The opinions in this paper are those of the authors and do not necessarily reflect the opinions of the funders. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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N2 - Background: Well-established electronic data capture in UK general practice means that algorithms, developed on patient data, can be used for automated clinical decision support systems (CDSSs). These can predict patient risk, help with prescribing safety, improve diagnosis and prompt clinicians to record extra data. However, there is persistent evidence of low uptake of CDSSs in the clinic. We interviewed UK General Practitioners (GPs) to understand what features of CDSSs, and the contexts of their use, facilitate or present barriers to their use. Methods: We interviewed 11 practicing GPs in London and South England using a semi-structured interview schedule and discussed a hypothetical CDSS that could detect early signs of dementia. We applied thematic analysis to the anonymised interview transcripts. Results: We identified three overarching themes: trust in individual CDSSs; usability of individual CDSSs; and usability of CDSSs in the broader practice context, to which nine subthemes contributed. Trust was affected by CDSS provenance, perceived threat to autonomy and clear management guidance. Usability was influenced by sensitivity to the patient context, CDSS flexibility, ease of control, and non-intrusiveness. CDSSs were more likely to be used by GPs if they did not contribute to alert proliferation and subsequent fatigue, or if GPs were provided with training in their use. Conclusions: Building on these findings we make a number of recommendations for CDSS developers to consider when bringing a new CDSS into GP patient records systems. These include co-producing CDSS with GPs to improve fit within clinic workflow and wider practice systems, ensuring a high level of accuracy and a clear clinical pathway, and providing CDSS training for practice staff. These recommendations may reduce the proliferation of unhelpful alerts that can result in important decision-support being ignored.

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KW - Adoption

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Barriers and facilitators to the adoption of electronic clinical decision support systems: a qualitative interview study with UK general practitioners

Abstract

Bibliographical note

Keywords

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