Linking a Survey of Clinician Benzodiazepine-Related Beliefs to Risk of Benzodiazepine Prescription Fills Among Patients in Medicare

INTRODUCTION

Benzodiazepines (BZDs) are a leading contributor to prescription drug deaths,¹ with the incidence of BZD-related overdose deaths increasing more than fivefold from 1996 to 2013.² However, the proportion of adults prescribed BZDs has remained unchanged.² Interventions to decrease BZD use can entail patient-, clinician-, and health system–facing efforts.³ However, clinician beliefs (eg, regarding BZD efficacy, minimal risks of long-term use, and patient resistance to discontinuation) might limit the perceived salience of addressing BZD prescribing for their patients⁴ and help account for variation in prescribing among clinicians.^5,6

Whether clinician beliefs influence BZD prescribing is unclear, though this is critical to informing the design of clinician-facing interventions. Toward building this evidence base, we conducted a pilot study using clinician BZD-prescribing data (from Medicare Part D prescription claims linked to the American Medical Association Masterfile) to identify a national sample of primary care clinicians, who we then surveyed. Our primary goal was to show the acceptability and feasibility of this approach to survey clinicians.

METHODS

We identified all BZD prescriptions in a 20% national sample of Medicare beneficiaries with Part D coverage in 2017. After using the prescriber National Provider Identifier to identify specialty in the American Medical Association Masterfile, we limited the sample to primary care clinicians. Among BZD-prescribing primary care clinicians, we limited the potential survey population to those who prescribed a BZD to >1 beneficiary, a threshold set to limit inclusion of one-off prescribers (eg, providing cross-coverage); we then randomly sampled 100 primary care clinicians to survey.

Informed by prior qualitative work⁴ and iterative feedback from 3 primary care clinicians, we developed a 22-item survey based on the capability, opportunity, and motivation behavior (COM-B) framework⁷ to examine BZD-related decision making. For this analysis, we focused on a subset of belief-related items reflecting the capability and motivation domains. We also included an item assessing how often primary care clinicians spoke with patients about decreasing or discontinuing their BZD. We mailed surveys to clinicians via express mail, which could be returned by mail or completed online; on completion, they received a $100 gift card. The survey was conducted from November 2020 to July 2021.

For the 100 primary care clinicians sampled, we used the Part D file to identify all beneficiaries for whom they had prescribed any drug and created a patient-clinician–level data set. The outcome variable was whether or not each patient filled a BZD prescription (1 = yes, 0 = no) from that primary care clinician.

We used χ² and t tests to compare primary care clinician characteristics by response status and modified Poisson regression with robust standard errors to assess patient risk of being prescribed a BZD among clinician panels.⁸ We collapsed clinician responses from 5 to 3 levels (strongly disagree, disagree; neither agree nor disagree; agree, strongly agree) and modeled relative risk of being prescribed a BZD as a function of primary care clinician belief using the same Poisson regression approach, accounting for patient clustered within clinician.⁸ Models adjusted for patient age, gender, and Part D low-income subsidy eligibility/enrollment. All tests were 2-sided, and α was set at .05. This study was approved by the Michigan Medicine Institutional Review Board.

RESULTS

The survey response rate was 61%. Primary care clinician gender, age, and percentage of patients prescribed a BZD did not differ significantly by survey response status, though family medicine clinicians were more likely to respond (Table 1). Respondents prescribed BZDs to a clinician-level mean of 11.5% (SD 5.9) patients.

A total of 62.3% of clinician respondents reported they disagreed or strongly disagreed with the statement, “If a patient has been prescribed a benzodiazepine for years, the potential harms from continuing the benzodiazepine are low,” whereas 18.0% agreed or strongly agreed (Table 2). Relative to patients of clinicians who disagreed with the statement, patients of clinicians who agreed (that potential harms were low) were at greater risk of being prescribed a BZD, with an adjusted risk ratio of 1.31 (95% CI, 1.01-1.7). None of the other belief survey items were associated with patient-level risk of BZD prescription fill.

DISCUSSION

In this pilot study, we showed the acceptability and feasibility of using clinician prescribing as observed in a Medicare sample to identify and survey those clinicians. It is important to consider limitations of this study. Our results generalize to primary care clinicians who prescribed BZDs to >1 beneficiary in a year, and by virtue of the data, this is prescribing to age- and disability-eligible Medicare beneficiaries. Subsequent application of this method will require careful consideration of the appropriate denominator population—of both clinicians and patients—for the study question. Whereas respondents were drawn from a national sample, this pilot study, designed to assess feasibility and acceptability, was not powered to detect small effects. Claims data reflect whether a BZD prescription was filled, but there might be unobserved prescriptions (ie, written but not filled), and the analysis was not longitudinal (eg, we did not capture whether a clinician was tapering patients off BZDs). In addition, although clinicians were sampled on the basis of prescribing in 2017, the survey was conducted several years later; ideally the prescribing and clinician survey would be contemporaneous.

A recent review of deprescribing interventions using the COM-B framework emphasized that few interventions have combined capability, opportunity, and motivation elements, which might be critical to overcome prescribing inertia.⁹ Although the point estimates do not suggest that primary care clinicians’ BZD-related beliefs are consistently associated with patient likelihood of filling a BZD prescription, this pilot study shows the potential of applying this survey method to isolate key intervention targets. This study provides a method to inform the development of multipronged interventions to modify a variety of physician behaviors.