The Prevalence of and Factors Associated With Receiving Concurrent Controlled Substance Prescriptions

Validation of the tobacco, alcohol, prescription medication, and other substance use (TAPS) tool with the WHO alcohol, smoking, and substance Involvement screening test (ASSIST)

INTRODUCTION

Community pharmacies are emerging as a valuable setting to identify patients with substance use. Few tools have been specially validated to screen patients in these settings, particularly among those prescribed opioid medications. The goal of this study was to validate the performance of the Tobacco, Alcohol, Prescription medication, and other Substance use (TAPS) tool in community pharmacy settings compared to a reference-standard substance use assessment.

METHODS

Participants were recruited while receiving opioid medications (not solely buprenorphine) from 19 pharmacies from a large national chain in Ohio and Indiana. Adults who were not involved in the criminal justice system or receiving cancer treatment were invited to participate in a one-time, cross-sectional, self-administered, health survey which included the TAPS tool. Substance use risks calculated from the TAPS tool were compared with the reference standard, World Health Organization Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) using confusion matrices. We calculated Areas Under the Curve (AUC) of Receiver Operating Characteristics Curves (ROC) to evaluate the TAPS tool's validity.

RESULTS

The TAPS tool showed fair or better discrimination between moderate-risk use and high-risk use for tobacco, alcohol, and prescription opioids (AUCs: 0.75-0.97 and fair or better discrimination between low-risk and moderate-risk use in five of eight subscales, including tobacco, alcohol, marijuana, stimulants, and heroin (AUCs: 0.70-0.92).

CONCLUSION

The TAPS tool detected clinically relevant problem substance use in several drug classes and likely would be a valuable assessment for screening illicit drug use among community pharmacy patients prescribed opioid medications.

Defining "Doctor shopping" with Dispensing Data: A Scoping Review

BACKGROUND

"Doctor shopping" typically refers to patients that seek controlled substance prescriptions from multiple providers with the presumed intent to obtain these medications for non-medical use and/or diversion. The purpose of this scoping review is to document and examine the criteria used to identify "doctor shopping" from dispensing data in the United States.

METHODS

A scoping review was conducted on "doctor shopping" or analogous terminology from January 1, 2000 through December 31, 2020 using the Web of Science Core Collection (7 citation indices). Our search was limited to U.S. only, English-language, peer-reviewed and U.S. federal government studies. Studies without explicit "doctor shopping" criteria were excluded. Key components of these criteria included the number of prescribers and dispensers, dispensing period, and drug class (e.g., opioids).

RESULTS

Of 9,845 records identified, 95 articles met the inclusion criteria and our pool of studies ranged from years 2003 to 2020. The most common threshold-based or count definition was [≥4 Prescribers (P) AND ≥4 Dispensers (D)] (n = 12). Thirty-three studies used a 365-day detection window. Opioids alone were studied most commonly (n = 69), followed by benzodiazepines and stimulants (n = 5 and n = 2, respectively). Only 39 (41%) studies provided specific drug lists with active ingredients.

CONCLUSION

Relatively simple P × D criteria for identifying "doctor shopping" are still the dominant paradigm with the need for on-going validation. The value of P × D criteria may change through time with more diverse methods applied to dispensing data emerging.

Validation and threshold identification of a prescription drug monitoring program clinical opioid risk metric with the WHO alcohol, smoking, and substance involvement screening test

BACKGROUND

Prescription drug monitoring programs (PDMPs) are critical for pharmacists to identify risky opioid medication use. We performed an independent evaluation of the PDMP-based Narcotic Score (NS) metric.

METHODS

This study was a one-time, cross-sectional health assessment within 19 pharmacies from a national chain among adults picking-up opioid medications. The NS metric is a 3-digit composite indicator. The WHO Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) was the gold-standard to which the NS metric was compared. Machine learning determined optimal risk thresholds; Receiver Operating Characteristic curves and Spearman (P) and Kappa (K) coefficients analyzed concurrent validity. Regression analyses evaluated participant characteristics associated with misclassification.

RESULTS

The NS metric showed fair concurrent validity (area under the curve≥0.70; K=0.35; P = 0.37, p < 0.001). The ASSIST and NS metric categorized 37% of participants as low-risk (i.e., not needing screening/intervention) and 32.3% as moderate/high-risk (i.e., needing screening/intervention). Further, 17.2% were categorized as low ASSIST risk but moderate/high NS metric risk, termed false positives. These reported disability (OR=3.12), poor general health (OR=0.66), and/or greater pain severity/interference (OR=1.12/1.09; all p < 0.05; i.e., needing unmanaged-pain screening/intervention). A total of 13.4% were categorized as moderate/high ASSIST risk but low NS metric risk, termed false negatives. These reported greater overdose history (OR=1.24) and/or substance use (OR=1.81-12.66; all p < 0.05).

CONCLUSIONS

The NS metric could serve as a useful initial universal prescription opioid-risk screener given its: 1) low-burden (i.e., no direct assessment); 2) high accuracy (86.5%) of actionable data identifying low-risk patients and those needing opioid use/unmanaged pain screening/intervention; and 3) broad availability.

Concurrent prescriptions for opioids and benzodiazepines and risk of opioid overdose: protocol for a retrospective cohort study using linked administrative data

INTRODUCTION

Opioid overdoses have increased substantially over the last 20 years, with over 400 000 deaths in North America. While opioid prescribing has been a target of research, benzodiazepine and opioid co-intoxication has emerged as a potential risk factor. Our aim was to assess the risk of opioid overdose associated with concurrent use of opioids and benzodiazepines relative to opioids alone.

METHODS AND ANALYSIS

A retrospective cohort study will be conducted using medical claims data from adult residents of Montréal, Canada. We will create a cohort of new users of opioids (ie, no opioid dispensations in prior year) in 2000-2014 from people with at least 2 years of continuous health insurance. Those with any diagnosis or hospitalisation for cancer or palliative care in the 2 years before their first opioid dispensation will be excluded. On each person-day of follow-up, exposure status will be classified into one of four mutually exclusive categories: (1) opioid-only, (2) benzodiazepine-only, (3) both opioid and benzodiazepine (concurrent use) or (4) neither. Opioid overdose will be measured using diagnostic codes documented in the hospital discharge abstract database, physician billing claims from emergency department visits and death records. Using a marginal structural Cox proportional hazards model, we will compare the hazard of overdose during intervals of concurrent opioid and benzodiazepine use to intervals of opioid use alone, adjusted for sociodemographics, medical and psychiatric comorbidities, and substance use disorders.

ETHICS AND DISSEMINATION

This study is approved by the McGill Faculty of Medicine Institutional Review Board and the Commission d'access à l'information (Québec privacy commission). Results will be relevant to clinicians, policymakers and other researchers interested in co-prescribing practices of opioids and benzodiazepines. Study findings will be disseminated at relevant conferences and published in biomedical and epidemiological peer-reviewed journals.

Clinical decision making involving prescription drug monitoring programs: A factorial, vignette-based study among student pharmacists

OBJECTIVES

Prescription drug monitoring programs (PDMPs) are state-maintained databases that providers may reference when deciding to prescribe or dispense controlled substances. As more states begin to mandate PDMP use at the point of care, it is imperative to assess how pharmacists use PDMP information when determining whether to fill a controlled substance prescription (CSP). The objective of this study was to evaluate which factors affected fourth-year student pharmacists' decision to fill an opioid prescription, their level of confidence in their decision making, and familiarity with the PDMP.

METHODS

We used a 2⁴ factorial design to present a series of text-based vignettes to fourth-year student pharmacists. Each participant received 8 vignettes (5 randomly selected, 3 fixed), representing a hypothetical hydrocodone-acetaminophen combination prescription with varying levels of the following dichotomous factors: doctor shopping, dosage, pharmacy shopping, and concurrent benzodiazepine prescription. Participants were asked to decide whether or not they would fill each of the hypothetical prescriptions they received. A multilevel model was used to measure the association between each of the vignette factors, age, race, sex, experience with PDMP, and the decision to refuse to fill a prescription. Each vignette response served as an independent observation.

RESULTS

A total of 87 participants yielded 696 vignette responses. Participants were significantly more likely to refuse to fill prescriptions with doctor shopping (adjusted odds ratio [aOR] 19.86 [95% CI 10.78-36.58]), pharmacy shopping (6.78 [4.13-11.12]), dosage (1.83 [1.16-2.90]), or if the student pharmacist was of female sex (1.73 [1.02-2.93]). Concomitant benzodiazepine use was not associated with a no-fill decision (1.45 [0.92-2.27]).

CONCLUSION

This study reveals that student pharmacists' decision to fill a prescription is dependent on both prescription characteristics and a patient's CSP history. The importance of PDMP history cannot be downplayed and suggests that PDMP use may be effective in informing patient care decisions. Still, the variability in filling decision highlights the need to teach a formulaic approach to CSP dispensing in colleges of pharmacy.

Concurrent Opioid and Benzodiazepine Utilization Patterns and Predictors Among Community-Dwelling Adults in the United States

OBJECTIVE

Using benzodiazepines and opioids together substantially increases the risk of fatal overdose. Yet, concurrent benzodiazepine and opioid prescribing rates continue to increase amid the opioid overdose epidemic. Therefore, this study sought to identify patterns and predictors associated with self-reported concurrent benzodiazepine and opioid use among community-dwelling adults.

METHODS

This retrospective, cross-sectional study used Medical Expenditure Panel Survey data from 2011, 2013, and 2015. The study population included adults (age ≥18) who did not die during the calendar year. The dependent variable was concurrent benzodiazepine and opioid use, which was identified with Multum Lexicon therapeutic class codes. Multivariable logistic regression analysis was conducted to examine the association of various individual-level factors with concurrent benzodiazepine and opioid use.

RESULTS

The final study sample consisted of 44,808 individuals (unweighted), of which 680 (1.6%) (weighted frequency=7,806,636) reported concurrent benzodiazepine and opioid use. Several individual-level factors were significantly associated with reporting use of this combination. For example, individuals with anxiety were more likely to report using both benzodiazepines and opioids (odds ratio [OR]=9.61, 95% confidence interval [CI]=7.37-12.5), and those with extreme pain levels were more likely to report concurrent use (OR=5.11, 95% CI=2.98-8.78). Other predictors of reporting concurrent benzodiazepine and opioid use were depression, arthritis, region, race-ethnicity, insurance, activities disability, general and mental health status, and smoking status.

CONCLUSIONS

Several individual-level factors were associated with reporting concurrent benzodiazepine and opioid use. Therefore, enhanced educational interventions targeting both clinicians and community-dwelling adults are warranted to minimize use of this high-risk medication combination.

Provider Characteristics Associated With Outpatient Opioid Prescribing After Surgery

OBJECTIVE

To characterize differences in postoperative opioid prescribing across surgical, nonsurgical, and advanced practice providers.

BACKGROUND

There is a critical need to identify best practices around perioperative opioid prescribing. To date, differences in postoperative prescribing among providers are poorly understood.

METHODS

This is a retrospective multicenter analysis of commercial insurance claims from a statewide quality collaborative. We identified 15,657 opioid-naïve patients who underwent a range of surgical procedures between January 2012 and October 2015 and filled an opioid prescription within 30 days postoperatively. Our primary outcome was total amount of opioid filled per prescription within 30 days postoperatively [in oral morphine equivalents (OME)]. Hierarchical linear regression was used to determine the association between provider characteristics [specialty, advanced practice providers (nurse practitioners and physician assistants) vs. physician, and gender] and outcome while adjusting for patient factors.

RESULTS

Average postoperative opioid prescription amount was 326 ± 285 OME (equivalent: 65 tablets of 5 mg hydrocodone). Advanced practice providers accounted for 19% of all prescriptions, and amount per prescription was 18% larger in this group compared with physicians (315 vs. 268, P < 0.001). Primary care providers accounted for 13% of all prescriptions and prescribed on average 279 OME per prescription. The amount of opioid prescribed varied by surgical specialty and ranged from 178 OME (urology) to 454 OME (neurosurgery).

CONCLUSIONS

Advanced practice providers account for 1-in-5 postoperative opioid prescriptions and prescribe larger amounts per prescription relative to surgeons. Engaging all providers involved in postoperative care is necessary to understand prescribing practices, identify barriers to reducing prescribing, and tailor interventions accordingly.

Provider beliefs on the Barriers and Facilitators to Prescription Monitoring Programs and Mandated Use

Background: Underutilization of Prescription monitoring programs (PMP), especially in states where participation is voluntary could limit their impact against opioid epidemic. Objectives: To (1) examine PMP use among Iowa healthcare providers (HCPs); (2) identify factors prompting and impeding PMP use, and (3) assess beliefs toward mandating PMP use. Methods: A cross-sectional survey of Iowa HCPs was conducted using a 12-item questionnaire. Survey domains include demographics, current PMP utilization, conditions and barriers associated with PMP use, and perspectives on use mandates. Analyses were based on descriptive statistics, proportional odds and poisson regression models. Results: There were 704 usable responses. Almost all respondents were registered with the PMP with dentists having the lowest rate (p < .001). Nurse practitioners consulted the PMP for the largest proportion of prescriptions, while pharmacists and dentists used significantly less (p < .001). Lack of time was the most common reported barrier impeding PMP use. Red flag behaviors and unfamiliarity with patient were the most common conditions prompting PMP review. HCPs estimated their use of the PMP would significantly increase if integrated into their electronic health records (p < .001). Almost half of HCPs held the opinion that PMP use should never be mandated, although inter-provider variation was present with nurse practitioners most amenable to mandates. Discussion: HCPs displayed variation in PMP use. EMR integration appears to be a strategy for increasing PMP use. There was resistance to mandating PMP use for all controlled substances prescribed and dispensed, with some interest in mandates for new patients only or new controlled substance prescriptions only.

Screening tools for detecting problematic opioid use and potential application to community pharmacy practice: a review

Problematic opioid use, constituted by a myriad of conditions ranging from misuse to use disorders, has continued to receive an increasing amount of attention in recent years resulting from the high use of opioids in the United States coinciding with morbidity and mortality. Deaths from drug overdoses increased by over 11% between 2014 and 2015, which supports the need for identification of problematic opioid use in additional health care settings. One of these settings is community pharmacy. The community pharmacy is a unique health service setting to identify and potentially intervene with patients at risk of or exhibit problematic opioid use. Problematic opioid use can be identified using one of the various screening tools in conjunction with evaluating prescription drug monitoring systems. A total of 12 tools were identified that could be employed in community pharmacy settings for identifying problematic opioid use. This review highlights these tools and strategies for use that can be utilized in the community pharmacy, which should be adapted to individual pharmacy settings and local needs. Future research should assess pharmacy personnel's knowledge and perceptions of problematic opioid use and associated screening tools and interventions, which tools can be most effectively used in a community pharmacy, workflow needs to implement problematic opioid use screenings, and the impact of pharmacist engagement in problematic opioid use screening on patient clinical outcomes.