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Assessing Decision Fatigue in General Practitioners’ Prescribing Decisions Using the Australian BEACH Data Set

Author

Listed:
  • Mona Maier

    (Health Psychology, Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, UK)

  • Daniel Powell

    (Health Psychology, Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, UK)

  • Christopher Harrison

    (School of Public Health, University of Sydney, Sydney, Australia)

  • Julie Gordon

    (School of Health Sciences, University of Sydney, Sydney, Australia)

  • Peter Murchie

    (Academic Primary Care, Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, UK)

  • Julia L. Allan

    (Division of Psychology, University of Stirling, Stirling, UK)

Abstract

Background General practitioners (GPs) make numerous care decisions throughout their workdays. Extended periods of decision making can result in decision fatigue, a gradual shift toward decisions that are less cognitively effortful. This study examines whether observed patterns in GPs’ prescribing decisions are consistent with the decision fatigue phenomenon. We hypothesized that the likelihood of prescribing frequently overprescribed medications (antibiotics, benzodiazepines, opioids; less effortful to prescribe) will increase and the likelihood of prescribing frequently underprescribed medications (statins, osteoporosis medications; more effortful to prescribe) will decrease over the workday. Methods This study used nationally representative primary care data on GP-patient encounters from the Bettering the Evaluation and Care of Health program from Australia. The association between prescribing decisions and order of patient encounters over a GP’s workday was assessed with generalized linear mixed models accounting for clustering and adjusting for patient, provider, and encounter characteristics. Results Among 262,456 encounters recorded by 2,909 GPs, the odds of prescribing antibiotics significantly increased by 8.7% with 15 additional patient encounters (odds ratio [OR] = 1.087; confidence interval [CI] = 1.059–1.116). The odds of prescribing decreased significantly with 15 additional patient encounters by 6.3% for benzodiazepines (OR = 0.937; CI = 0.893–0.983), 21.9% for statins (OR = 0.791; CI = 0.753–0.831), and 25.0% for osteoporosis medications (OR = 0.750; CI = 0.690–0.814). No significant effects were observed for opioids. All findings were replicated in confirmatory analyses except the effect of benzodiazepines. Conclusions GPs were increasingly likely to prescribe antibiotics and were less likely to prescribe statins and osteoporosis medications as the workday wore on, which was consistent with decision fatigue. There was no convincing evidence of decision fatigue effects in the prescribing of opioids or benzodiazepines. These findings establish decision fatigue as a promising target for optimizing prescribing behavior. Highlights We found that as general practitioners progress through their workday, they become more likely to prescribe antibiotics that are reportedly overprescribed and less likely to prescribe statins and osteoporosis medications that are reportedly underprescribed. This change in decision making over time is consistent with the decision fatigue phenomenon. Decision fatigue occurs when we make many decisions without taking a rest break. As we make those decisions, we become gradually more likely to make decisions that are less difficult. The findings of this study show that decision fatigue is a possible target for improving guideline-compliant prescribing of pharmacologic medications.

Suggested Citation

  • Mona Maier & Daniel Powell & Christopher Harrison & Julie Gordon & Peter Murchie & Julia L. Allan, 2024. "Assessing Decision Fatigue in General Practitioners’ Prescribing Decisions Using the Australian BEACH Data Set," Medical Decision Making, , vol. 44(6), pages 627-640, August.
    • Handle: RePEc:sae:medema:v:44:y:2024:i:6:p:627-640
    DOI: 10.1177/0272989X241263823
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    References listed on IDEAS

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    1. Daniel Kahneman, 2003. "Maps of Bounded Rationality: Psychology for Behavioral Economics," American Economic Review, American Economic Association, vol. 93(5), pages 1449-1475, December.
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