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Factors That Impact the Adoption of Clinical Decision Support Systems (CDSS) for Antibiotic Management

Author

Listed:
  • Mah Laka

    (School of Public Health, University of Adelaide, Adelaide 5005, Australia)

  • Adriana Milazzo

    (School of Public Health, University of Adelaide, Adelaide 5005, Australia)

  • Tracy Merlin

    (Adelaide Health Technology Assessment (AHTA), School of Public Health, University of Adelaide, Adelaide 5005, Australia)

Abstract

The study evaluated individual and setting-specific factors that moderate clinicians’ perception regarding use of clinical decision support systems (CDSS) for antibiotic management. A cross-sectional online survey examined clinicians’ perceptions about CDSS implementation for antibiotic management in Australia. Multivariable logistic regression determined the association between drivers of CDSS adoption and different moderators. Clinical experience, CDSS use and care setting were important predictors of clinicians’ perception concerning CDSS adoption. Compared to nonusers, CDSS users were less likely to lack confidence in CDSS (OR = 0.63, 95%, CI = 0.32, 0.94) and consider it a threat to professional autonomy (OR = 0.47, 95%, CI = 0.08, 0.83). Conversely, there was higher likelihood in experienced clinicians (>20 years) to distrust CDSS (OR = 1.58, 95%, CI = 1.08, 2.23) due to fear of comprising their clinical judgement (OR = 1.68, 95%, CI = 1.27, 2.85). In primary care, clinicians were more likely to perceive time constraints (OR = 1.96, 95%, CI = 1.04, 3.70) and patient preference (OR = 1.84, 95%, CI = 1.19, 2.78) as barriers to CDSS adoption for antibiotic prescribing. Our findings provide differentiated understanding of the CDSS implementation landscape by identifying different individual, organisational and system-level factors that influence system adoption. The individual and setting characteristics can help understand the variability in CDSS adoption for antibiotic management in different clinicians.

Suggested Citation

  • Mah Laka & Adriana Milazzo & Tracy Merlin, 2021. "Factors That Impact the Adoption of Clinical Decision Support Systems (CDSS) for Antibiotic Management," IJERPH, MDPI, vol. 18(4), pages 1-14, February.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:4:p:1901-:d:500233
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    References listed on IDEAS

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    1. Christopher E Curtis & Fares Al Bahar & John F Marriott, 2017. "The effectiveness of computerised decision support on antibiotic use in hospitals: A systematic review," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-15, August.
    2. Kakoli Bandyopadhyay & Cynthia Barnes, 2012. "An Analysis of Factors Affecting User Acceptance of ERP Systems in the United States," International Journal of Human Capital and Information Technology Professionals (IJHCITP), IGI Global, vol. 3(1), pages 1-14, January.
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    Cited by:

    1. Ming-Pey Lu & Zunarni Kosim, 2024. "An empirical study to explore the influence of the COVID-19 crisis on consumers' behaviour towards cashless payment in Malaysia," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 29(1), pages 33-44, March.
    2. Oleg E. Karpov & Elena N. Pitsik & Semen A. Kurkin & Vladimir A. Maksimenko & Alexander V. Gusev & Natali N. Shusharina & Alexander E. Hramov, 2023. "Analysis of Publication Activity and Research Trends in the Field of AI Medical Applications: Network Approach," IJERPH, MDPI, vol. 20(7), pages 1-17, March.
    3. Syed Imran Ali & Su Woong Jung & Hafiz Syed Muhammad Bilal & Sang-Ho Lee & Jamil Hussain & Muhammad Afzal & Maqbool Hussain & Taqdir Ali & Taechoong Chung & Sungyoung Lee, 2021. "Clinical Decision Support System Based on Hybrid Knowledge Modeling: A Case Study of Chronic Kidney Disease-Mineral and Bone Disorder Treatment," IJERPH, MDPI, vol. 19(1), pages 1-28, December.

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