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Journal of General Internal Medicine

, Volume 34, Issue 12, pp 2763–2771 | Cite as

Association between Physician Intensity of Antibiotic Prescribing and the Prescription of Benzodiazepines, Opioids and Proton-Pump Inhibitors to Nursing Home Residents: a Population-Based Observational Study

  • Kieran L. QuinnEmail author
  • Michael A. Campitelli
  • Christina Diong
  • Nick Daneman
  • Nathan M. Stall
  • Andrew M. Morris
  • Allan S. Detsky
  • Lianne Jeffs
  • Colleen J. Maxwell
  • Chaim M. Bell
  • Susan E. Bronskill
Original Research
First Online:

Abstract

Background

Prescribing patterns for episodic medications, such as antibiotics, might make useful surrogate measures of a physician’s overall prescribing practice because use is common, and variation exists across prescribers. However, the extent to which a physician’s current antibiotic prescribing practices are associated with the rate of prescription of other potentially harmful medications remains unknown.

Objective

To examine the association between a physician’s rate of antibiotic prescribing and their prescribing rate of benzodiazepines, opioids and proton-pump inhibitors in older adults.

Design

Population-based cohort study in nursing homes in Ontario, Canada, which provides comprehensive clinical, behavioural and functional information on all patients.

Participants

1926 physicians who provided care among 128,979 physician-patient pairs in 2015.

Main Measures

Likelihood of prescribing a benzodiazepine, opioid or proton-pump inhibitor between low-, average- and high-intensity antibiotic prescribers, adjusted for patient characteristics.

Key Results

Compared with average-intensity antibiotic prescribers, high-intensity prescribers had an increased likelihood of prescribing a benzodiazepine (odds ratio 1.21 [95% CI, 1.11–1.32]), an opioid (odds ratio 1.28 [95% CI, 1.17–1.39]) or a proton-pump inhibitor (odds ratio 1.38 [95% CI, 1.27–1.51]]. High-intensity antibiotic prescribers were more likely to be high prescribers of all three medications (odds ratio 6.24 [95% CI, 2.90–13.39]) and also more likely to initiate all three medications, compared with average-intensity prescribers.

Conclusions

The intensity of a physician’s episodic antibiotic prescribing was significantly associated with the likelihood of new and continued prescribing of opioids, benzodiazepines and proton-pump inhibitors in nursing homes. Patterns of episodic prescribing may be a useful mechanism to target physician-level interventions to optimize general prescribing behaviors, instead of prescribing behaviors for single medications.

KEY WORDS

physicians practice patterns drug prescriptions anti-bacterial agents inappropriate prescribing nursing home 
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Notes

Acknowledgements

We wish to thank Matthew Kumar for his assistance with the creation of some of the figures. We also thank IMS Brogan Inc. for use of their Drug Information Database.

Funding Information

This research was funded in part by the Canadian Frailty Network (SIG2014-M1) which is supported by the Government of Canada through Networks of Centres of Excellence (NCE) Program, and also the Canadian Institutes of Health Research (CIHR) through an operating grant (Exploring frailty and its role in the assessment of high risk medications and risk of poor health outcomes in vulnerable populations—MOP-136854). This study was supported by the Institute for Clinical Evaluative Sciences (ICES), which is funded by an annual grant from the Ontario Ministry of Health and Long-Term Care (MOHLTC). Kieran Quinn receives funding from the CIHR Vanier Scholarship Program, the Eliot Phillipson Clinician-Scientist Training Program and the Clinician Investigator Program at the University of Toronto.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they do not have a conflict of interest.

Disclaimer

The opinions, results and conclusions reported in this paper are those of the authors and are independent from the funding sources. No endorsement by IC/ES or the Ontario MOHLTC is intended or should be inferred. Parts of this material are based on data and information compiled and provided by the Canadian Institute for Health Information (CIHI). However, the analyses, conclusions, opinions and statements expressed herein are those of the author, and not necessarily those of CIHI.

Supplementary material

11606_2019_5333_MOESM1_ESM.docx (286 kb)
ESM 1 (DOCX 285 kb)

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Copyright information

© Society of General Internal Medicine 2019

Authors and Affiliations

  • Kieran L. Quinn
    • 1
    • 2
    • 3
    • 4
    Email author
  • Michael A. Campitelli
    • 2
  • Christina Diong
    • 2
  • Nick Daneman
    • 1
    • 2
    • 3
    • 5
    • 6
  • Nathan M. Stall
    • 3
    • 7
    • 8
  • Andrew M. Morris
    • 1
    • 4
    • 9
  • Allan S. Detsky
    • 1
    • 3
    • 4
  • Lianne Jeffs
    • 3
    • 10
  • Colleen J. Maxwell
    • 2
    • 11
  • Chaim M. Bell
    • 1
    • 2
    • 3
    • 4
  • Susan E. Bronskill
    • 2
    • 3
    • 5
    • 7
  1. 1.Department of MedicineUniversity of TorontoTorontoCanada
  2. 2.ICESTorontoCanada
  3. 3.Institute of Health Policy, Management and EvaluationUniversity of TorontoTorontoCanada
  4. 4.Department of MedicineSinai Health SystemTorontoCanada
  5. 5.Sunnybrook Research InstituteTorontoCanada
  6. 6.Division of Infectious Diseases, Sunnybrook Health Sciences CentreUniversity of TorontoTorontoCanada
  7. 7.Women’s College Research InstituteWomen’s College HospitalTorontoCanada
  8. 8.Division of Geriatric MedicineUniversity of TorontoTorontoCanada
  9. 9.Department of MedicineUniversity Health NetworkTorontoCanada
  10. 10.St. Michael’s HospitalTorontoCanada
  11. 11.Schools of Pharmacy and Public Health & Health SystemsUniversity of WaterlooWaterlooCanada

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