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Prescribers' Perceptions of Medication Discontinuation: Survey Instrument Development and Validation
Amy Linsky, MD, MSc; Steven R. Simon, MD, MPH; Kelly Stolzmann, MS; Barbara G. Bokhour, PhD; and Mark Meterko, PhD
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Prescribers' Perceptions of Medication Discontinuation: Survey Instrument Development and Validation

Amy Linsky, MD, MSc; Steven R. Simon, MD, MPH; Kelly Stolzmann, MS; Barbara G. Bokhour, PhD; and Mark Meterko, PhD
The authors developed and validated a survey instrument to assess primary care providers’ and pharmacists’ experiences, attitudes, and beliefs regarding medication discontinuation.

Primary care providers (PCPs) and clinical pharmacists have concerns about the adverse consequences of using medications inappropriately and generally support the notion of reducing unnecessary drugs. Despite this attitude, many factors impede clinicians’ ability to discontinue medication in clinical settings. We sought to develop a survey instrument that assesses PCPs' and pharmacists’ experiences, attitudes, and beliefs toward medication discontinuation.

Study Design: Survey development and psychometric assessment.

Methods: Based on a conceptual framework, we developed a questionnaire and surveyed a national sample of Department of Veterans Affairs PCPs with prescribing privileges, including physicians, nurse practitioners, physician assistants, and clinical pharmacy specialists. We randomly divided respondents into derivation and validation samples and used iterations of multi-trait analysis to assess the psychometric properties of the proposed measures. Multivariable regression models identified factors associated with the outcome of self-rated comfort with medication discontinuation.

Results: Using established criteria for scale development, we identified 5 scales: Medication Characteristics, Current Patient Clinical Factors, Predictions of Future Health States, Patients’ Resources to Manage Their Own Health, and Education and Experience. Three of these dimensions predicted providers’ self-rated comfort with making decisions to discontinue medication (Current Patient Clinical Factors, Predictions of Future Health States, and Education and Experience).

Conclusions: We developed a psychometrically sound instrument to measure prescribers’ attitudes toward, and experiences with, medication discontinuation. This survey will enable identification of perceived barriers to, and facilitators of, proactive discontinuation—an important step toward developing interventions that improve the quality and safety of care in medication use.

Am J Manag Care. 2016;22(11):747-754
Take-Away Points
  • We developed a psychometrically sound instrument to measure prescribers’ attitudes toward, and experiences with, medication discontinuation, an emerging area of importance in healthcare. 
  • Using this survey instrument can identify provider attitudes, beliefs, and/or other specific decision-making considerations that are associated with reluctance to discontinue a medication. 
  • Having identified these barriers, future interventions can be designed to improve the quality and safety of medication prescribing.
Use of 5 or more medicines, often considered polypharmacy, is associated with adverse drug events (ADEs).1 ADEs, in turn, lead to increased healthcare utilization, costs, and morbidity.2,3 Approximately 40% of adults 65 years or older are exposed to polypharmacy, with similar prevalence in Department of Veterans Affairs (VA) patients.4,5 One approach to prevent polypharmacy-related ADEs is to reduce medications that are outdated, not indicated, or of limited benefit relative to risk.6

Discontinuation, also known as de-prescribing, has been defined as a “systematic process of identifying and discontinuing drugs in instances in which existing or potential harms outweigh existing or potential benefits within the context of an individual patient’s care goals, current level of functioning, life expectancy, values, and preferences. De-prescribing is part of the good prescribing continuum.”7 Although discontinuing a medication can be considered “doing less,” it often requires more provider effort, as patients may require more frequent visits and closer monitoring after de-prescribing. Moreover, discussions about medication discontinuation may take time during already busy clinical encounters, especially to ensure accurate communication between patients and clinicians.8

Prescribers’ voice concerns about the adverse consequences of inappropriate medication use and general support for the notion of discontinuing unnecessary drugs.9 Nonetheless, many factors impede clinicians’ ability to de-prescribe, including patient complexity, clinical uncertainty, and shared management with other healthcare providers, all of which can contribute to “clinical inertia” around medication discontinuation.10 Taking these findings in the context of the broader literature on de-implementation, we undertook the present study to develop and administer a survey to a national sample of VA primary care providers (PCPs) to characterize their experiences, attitudes, and beliefs toward medication discontinuation.


Instrument Development

Based on our qualitative work with PCPs assessing their attitudes toward discontinuation and on the literature on medication prescribing during the past 30 years, we developed a conceptual model of factors that influence medication discontinuation decisions.9 The hierarchical model identified 4 larger, overarching domains: Medications, Patients, Providers, and System Factors. Within these broad domains, we distinguish 10 more specific dimensions (Table 1). Each dimension represents a construct, or abstract idea, that we sought to measure in the survey instrument.11 Medication includes 2 dimensions: “medication characteristics,” such as dosing frequency, and “medication uncertainty,” which includes medication reconciliation difficulties. Patients comprises 4 dimensions: “clinical status” includes the patient’s current health conditions, “desired role” reflects patient activation and shared decision making, “adherence” is taking medication as prescribed, and “patient knowledge and beliefs about medications.” Providers has 2 dimensions: “providers’ personal beliefs” reflects respondents’ views about medications; and “professional identity” encompasses responsibility, jurisdiction, and authority regarding medications. System Factors has 2 dimensions: “multiple providers” addresses complexities of care, and “workplace structure and process” refers to external factors.

Based on these 10 dimensions, we generated a pool of 75 items, ensuring that each dimension was represented by at least 3 items. An additional item asked providers to indicate their current overall comfort level with deciding to discontinue a medication on a 0 to 10 scale ranging from “not at all comfortable” to “completely comfortable.” To assess providers’ general attitudes regarding the use and efficacy of medications, we included the 4-item Beliefs about Medications Questionnaire (BMQ) overuse scale.12

We circulated the draft Provider Perceptions of Medication Discontinuation survey to a 7-member expert panel of researchers and PCPs, including experts in survey development and medication safety; all provided feedback on the draft items, which were revised accordingly. The updated draft was then presented to a non-VA academic research forum composed of 20 to 30 internists and researchers similar to the target population of survey respondents, where the items were reviewed and suggested improvements were again incorporated.

Next, we used a semi-structured cognitive interview protocol with specific probes in 1-on-1 sessions with VA PCPs.13 Using a modified form of retrospective debriefing, subjects completed the survey 1 section at a time and answered questions about how they interpreted the items and decided on a response.14 Participants included professionals representing the most likely future respondents: physicians, nurse practitioners, and clinical pharmacy specialists. The cognitive interviews were conducted in 2 rounds (8 and 4 clinicians, respectively). Between rounds, we modified items and instructions based on feedback with additional edits after the second round. The resulting pilot-ready version of the survey included 56 items related to medication discontinuation, organized around the 10 dimensions noted above, plus 8 demographic items. The substantive content of the pilot-ready survey is summarized in Table 1.

Pilot Study and Psychometric Evaluation

Sample. We surveyed VA PCPs with prescribing privileges. Our sampling frame was the Primary Care Management Module, a centralized VA database containing information for all PCPs. From this listing, we identified all providers nationwide with the title of physician–primary care, physician–attending, PCP, nurse practitioner (NP), or physician assistant (PA). Using another centralized database, we identified clinical pharmacy specialists by selecting “pharmacy service providers” who had primary care clinical encounters. We determined  the sample size based on our primary objective to achieve adequate power (0.80) for the multi-trait analysis (MTA), assuming, based on our general experience with survey-based attitude measures, that item-scale correlations would be moderate (0.3-0.5). This yielded an estimated effect size for the difference between correlations in the moderate range (Jacob Cohen’s effect size index [q] = 0.30) and a target sample of 180 for both the derivation and validation samples. Assuming a response rate of 20%, we randomly selected an initial mail-out sample of 2500 providers from those eligible, we stratified evenly across 4 geographic regions, and oversampled NP/PAs and pharmacists to ensure adequate representation and to enable comparisons across the 3 provider types.

Survey administration. We sent each provider an e-mail introducing the survey objectives and containing a link to the survey website. If an e-mail was undeliverable, we selected a replacement subject of the same provider type and geographic stratum. Nonrespondents received up to 2 reminder e-mails at 1-week intervals. The survey remained open for 3 months. All responses were anonymous.

Analysis strategy. We applied MTA to evaluate the psychometric properties of the proposed scales. In MTA, scale reliability is assessed by Cronbach’s alpha coefficient. Item convergence was evaluated by examining the correlation of each item with its assigned scale (item-scale correlations), and item discrimination compared each item’s item-scale correlations with its correlations with all other scales.15 We randomly split respondents into derivation and validation groups and ran the initial MTA in the derivation sample. We made iterative modifications guided by both empirical findings and conceptual considerations, reassigning items to scales to improve the psychometric properties of the scales while also clarifying and focusing scale content. After arriving at a final model in the derivation sample, we tested it by repeating the MTA in the validation sample. To evaluate the proposed final questionnaire produced by the MTA, 4 expert-panel members reviewed the results for face validity via independent appraisal and group discussion. We assessed nonresponse bias by comparing respondents and nonrespondents on 4 factors available for all subjects from VA centralized databases: geographic region, job type, age, and gender. All analyses were conducted in SAS version 9.3 (SAS Institute Inc, Cary, North Carolina).


A total of 411 prescribers completed online questionnaires. After accounting for unreachable prescribers (n = 25), the response rate was 16.6%. Nonresponders were more likely to be physicians than NP/PAs or pharmacists, but were otherwise similar with respect to age, gender, and geographic region. Details regarding respondent demographics are in Table 2. Regarding data quality, the median percent of missing responses per item on the substantive questions was 11.7% (range = 0.01%-16%; n = 4-65); the median percent missing on the demographic questions was 17.2% (range = 16%-19%; n = 64-79).

The respondents were randomly divided into a derivation sample (n = 205) and validation sample (n = 206). We conducted a series of MTAs in the derivation sample, beginning with the hypothesized model of 10 scales. Upon review of the data, we felt 2 of the hypothesized scales (Indication Uncertainty and Multiple Providers) represented the frequency with which various events occurred rather than representing respondents’ beliefs. The items combine to describe and define a scale (ie, a formative measure) rather than reflect an underlying latent construct driving item responses (ie, a reflective measure).16,17 Formative measures will, by their nature, not necessarily exhibit high internal consistency, reliability, or item convergence and discrimination. Therefore, we omitted these questions from the MTA, but retained them as indices for use in future analyses.

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