Impact of the RESPOND Toolkit on community pharmacists' opioid safety attitudes, self-efficacy, and knowledge.

OBJECTIVE: Pharmacists are well positioned to reduce risks from opioid-prescribing but often lack resources and training to effectively support these activities. The Resources Encouraging Safe Prescription Opioid and Naloxone Dispensing (RESPOND) Toolkit is an educational package developed to provide community pharmacists with a comprehensive education program and practice resources on prescription drug misuse, prescription drug monitoring programs (PDMPs), and naloxone dispensing. Our objective was to evaluate the effectiveness of the RESPOND Toolkit to improve pharmacists' knowledge and assess changes in pharmacists' attitudes and beliefs toward opioid use disorder (OUD) and PDMPs across a diverse pool of Oregon community pharmacists. METHODS: Pharmacists were recruited using an electronic mailing list of Oregon-licensed pharmacists. Pharmacists were asked to complete a preintervention survey, 3 online educational modules with pre- and post-module quizzes (optional), and a postintervention survey. Data were analyzed using paired t tests, chi-square analyses, and effect size calculations (Cohen's d). RESULTS: A total of 131 pharmacists completed the 3 educational modules and postintervention survey. Respondents were aged 37.6 ± 11.0 (mean ± SD) years and mostly frontline pharmacy staff (n = 86; 65.6%) with 10.5 ± 11.6 years of pharmacy experience. Pharmacists' knowledge and attitudes toward OUD, perceived behavioral control to address OUD, resources to address OUD, and perceptions regarding PDMP-associated difficulties improved significantly as a result of the intervention (all P < 0.001). In addition, 120 pharmacists completed the optional module quizzes, and aggregate knowledge assessment scores improved significantly (P < 0.001). CONCLUSION: The RESPOND Toolkit is an effective and scalable training resource for community pharmacists, with the potential to promote behavioral shifts that support opioid safety among patients. The results demonstrated improved attitudes, knowledge, and perceived behavioral control. Future work on the RESPOND Toolkit should evaluate the effect of implementation on pharmacist clinical activities and dispensing outcomes.

Development and pilot of a prescription drug monitoring program and communication intervention for pharmacists.

BACKGROUND: Pharmacists' role in addressing the opioid crisis continues to expand, but lack of training specifically related to standardized prescription drug monitoring program (PDMP) use and communication strategies for provider and patient interactions remains a significant issue. We developed the Resources Encouraging Safe Prescription Opioid and Naloxone Dispensing (RESPOND) Toolkit to enhance community pharmacists' understanding of their role in addressing opioid safety; improve integration of PDMP into daily workflow; and enhance communication between pharmacists, prescribers, and patients. OBJECTIVE: To describe the development of RESPOND Toolkit and summarize findings from initial pilot testing. METHODS: RESPOND development was informed by focus groups with patients, prescribers, and pharmacists and an external advisory committee. Materials developed include a patient screening & communication algorithm, a provider communication checklist and an online continuing education course with three distinct modules. The RESPOND Toolkit was pilot tested in six community pharmacies in Oregon across two 6-month intervention phases. Pilot data collection included a pre-post intervention survey, pre-post knowledge assessment quizzes within the online course, and post-intervention semi-structured interviews. Interview feedback informed revisions after each phase to shape the final content, flow, and delivery of RESPOND. RESULTS: Sixteen of 21 pharmacists completed the online training, revealing a large, significant effect on knowledge gain across the three training modules (pre-score 57, post-score 84; p < 0.001; Cohen's d = 1.85). Of these participants, 10 also completed the baseline and post intervention survey and showed non-significant moderate improvements in knowledge, perceived behavioral control, and self-efficacy to address opioid safety issues. CONCLUSION: The RESPOND Toolkit has promise as an effective and scalable approach to providing community pharmacist-tailored training, especially in the areas of effective communication and workflow integration, to promote behavioral shifts supporting opioid safety for patients. Further development and testing in a larger sample is warranted.

Opioid-Prescribing Continuity and Risky Opioid Prescriptions.

We aimed to better understand the association between opioid-prescribing continuity, risky prescribing patterns, and overdose risk. For this retrospective cohort study, we included patients with long-term opioid use, pulling data from Oregon's Prescription Drug Monitoring Program (PDMP), vital records, and hospital discharge registry. A continuity of care index (COCI) score was calculated for each patient, and we defined metrics to describe risky prescribing and overdose. As prescribing continuity increased, likelihood of filling risky opioid prescriptions and overdose hospitalization decreased. Prescribing continuity is an important factor associated with opioid harms and can be calculated using administrative pharmacy data.

Use of prescription opioids before and after an operation for chronic pain (lumbar fusion surgery).

Lumbar fusion surgery is usually prompted by chronic back pain, and many patients receive long-term preoperative opioid analgesics. Many expect surgery to eliminate the need for opioids. We sought to determine what fraction of long-term preoperative opioid users discontinue or reduce dosage postoperatively; what fraction of patients with little preoperative use initiate long-term use; and what predicts long-term postoperative use. This retrospective cohort study included 2491 adults undergoing lumbar fusion surgery for degenerative conditions, using Oregon's prescription drug monitoring program to quantify opioid use before and after hospitalization. We defined long-term postoperative use as ≥4 prescriptions filled in the 7 months after hospitalization, with at least 3 occurring >30 days after hospitalization. Overall, 1045 patients received long-term opioids preoperatively, and 1094 postoperatively. Among long-term preoperative users, 77.1% continued long-term postoperative use, and 13.8% had episodic use. Only 9.1% discontinued or had short-term postoperative use. Among preoperative users, 34.4% received a lower dose postoperatively, but 44.8% received a higher long-term dose. Among patients with no preoperative opioids, 12.8% became long-term users. In multivariable models, the strongest predictor of long-term postoperative use was cumulative preoperative opioid dose (odds ratio of 15.47 [95% confidence interval 8.53-28.06] in the highest quartile). Cumulative dose and number of opioid prescribers in the 30-day postoperative period were also associated with long-term use. Thus, lumbar fusion surgery infrequently eliminated long-term opioid use. Opioid-naive patients had a substantial risk of initiating long-term use. Patients should have realistic expectations regarding opioid use after lumbar fusion surgery.

High-risk prescribing and opioid overdose: prospects for prescription drug monitoring program-based proactive alerts.

To develop a simple, valid model to identify patients at high risk of opioid overdose-related hospitalization and mortality, Oregon prescription drug monitoring program, Vital Records, and Hospital Discharge data were linked to estimate 2 logistic models; a first model that included a broad range of risk factors from the literature and a second simplified model. Receiver operating characteristic curves, sensitivity, and specificity of the models were analyzed. Variables retained in the final model were categories such as older than 35 years, number of prescribers, number of pharmacies, and prescriptions for long-acting opioids, benzodiazepines or sedatives, or carisoprodol. The ability of the model to discriminate between patients who did and did not overdose was reasonably good (area under the receiver operating characteristic curve = 0.82, Nagelkerke R = 0.11). The positive predictive value of the model was low. Computationally simple models can identify high-risk patients based on prescription history alone, but improvement of the predictive value of models may require information from outside the prescription drug monitoring program. Patient or prescription features that predict opioid overdose may differ from those that predict diversion.

Pharmacists' Role in Opioid Safety: A Focus Group Investigation.

Objective: The pharmacist's role and responsibilities in addressing the opioid epidemic have yet to be clearly defined, particularly from the patient's point of view. This qualitative study explores the pharmacist's role in promoting opioid safety from the perspective of pharmacists and patients. Design: Focus groups. Setting: Patient groups were held in person, and pharmacist groups were held online. Subjects: Oregon pharmacists (N = 19, Mage = 39.0 years, range = 26-57 years, 58% female) and patients (N = 18, Mage = 60.1 years, range = 30-77 years, 71% female) with current experience dispensing or receiving opioid medications. Methods: Pharmacists were asked about the challenges and opportunities for opioid safety monitoring and prescription dispensing. Patients were asked about their experiences accessing care, medications, and safety information. Focus group data were analyzed by a multidisciplinary team using an immersion-crystallization approach. Results: Pharmacists and patients agreed that pharmacists are responsible for medication safety. Pharmacists expressed discomfort filling potentially high-risk opioid prescriptions and noted barriers such as lack of clinical information and discomfort policing high-risk prescribing. Patients were concerned about pharmacists potentially overstepping their professional responsibilities by interfering with prescribers' clinical decisions. Conclusions: Feedback from both pharmacists and patient participants suggests that there is uncertainty in the degree to which pharmacists can and should confront the prescription opioid epidemic directly. Ambiguities in the pharmacist's role may be best clarified through structured training promoting enhanced between-party communication.

Association of Prescription Drug Monitoring Program Use With Opioid Prescribing and Health Outcomes: A Comparison of Program Users and Nonusers.

Prescription drug monitoring programs (PDMPs) are a response to the prescription opioid epidemic, but their effects on prescribing and health outcomes remain unclear, with conflicting reports. We sought to determine if prescriber use of Oregon's PDMP led to fewer high-risk opioid prescriptions or overdose events. We conducted a retrospective cohort study from October 2011 through October 2014, using statewide PDMP data, hospitalization registry, and vital records. Early PDMP registrants (n = 927) were matched with clinicians who never registered during the study period, using baseline prescribing metrics in a propensity score. Generalized estimating equations were used to examine prescribing trends after PDMP registration, using 2-month intervals. We found a statewide decline in measures of per capita opioid prescribing. However, compared with nonregistrants, PDMP registrants did not subsequently have significantly fewer patients receiving high-dose prescriptions, overlapping opioid and benzodiazepine prescriptions, inappropriate prescriptions, prescriptions from multiple prescribers, or overdose events. At baseline, frequent PDMP users wrote fewer high-risk opioid prescriptions than infrequent users; this persisted during follow-up with few significant group differences in trend. Thus, although opioid prescribing declined statewide after implementing the PDMP, registrants did not show greater declines than nonregistrants. PERSPECTIVE: Factors other than PDMP use may have had greater influence on prescribing trends. Refinements in the PDMP program and related policies may be necessary to increase PDMP effects.

Association Between Initial Opioid Prescribing Patterns and Subsequent Long-Term Use Among Opioid-Naïve Patients: A Statewide Retrospective Cohort Study.

BACKGROUND: Long-term efficacy of opioids for non-cancer pain is unproven, but risks argue for cautious prescribing. Few data suggest how long or how much opioid can be prescribed for opioid-naïve patients without inadvertently promoting long-term use. OBJECTIVE: To examine the association between initial opioid prescribing patterns and likelihood of long-term use among opioid-naïve patients. DESIGN: Retrospective cohort study; data from Oregon resident prescriptions linked to death certificates and hospital discharges. PARTICIPANTS: Patients filling opioid prescriptions between October 1, 2012, and September 30, 2013, with no opioid fills for the previous 365 days. Subgroup analyses examined patients under age 45 who did not die in the follow-up year, excluding most cancer or palliative care patients. MAIN MEASURES: Exposure: Numbers of prescription fills and cumulative morphine milligram equivalents (MMEs) dispensed during 30 days following opioid initiation ("initiation month"). OUTCOME: Proportion of patients with six or more opioid fills during the subsequent year ("long-term users"). KEY RESULTS: There were 536,767 opioid-naïve patients who filled an opioid prescription. Of these, 26,785 (5.0 %) became long-term users. Numbers of fills and cumulative MMEs during the initiation month were associated with long-term use. Among patients under age 45 using short-acting opioids who did not die in the follow-up year, the adjusted odds ratio (OR) for long-term use among those receiving two fills versus one was 2.25 (95 % CI: 2.17, 2.33). Compared to those who received < 120 total MMEs, those who received between 400 and 799 had an OR of 2.96 (95 % CI: 2.81, 3.11). Patients initiating with long-acting opioids had a higher risk of long-term use than those initiating with short-acting drugs. CONCLUSIONS: Early opioid prescribing patterns are associated with long-term use. While patient characteristics are important, clinicians have greater control over initial prescribing. Our findings may help minimize the risk of inadvertently initiating long-term opioid use.

Preparing a prescription drug monitoring program data set for research purposes.

PURPOSE: To develop a complete and consistent prescription drug monitoring program (PDMP) data set for use by drug safety researchers in evaluating patterns of high-risk use and potential abuse of scheduled drugs. METHODS: Using publically available data references from the US Food and Drug Administration and the Centers for Disease Control and Prevention, we developed a strategic methodology to assign drug categories based on pharmaceutical class for the majority of prescriptions in the PDMP data set. We augmented data elements required to calculate morphine milligram equivalents and assigned duration of action (short-acting or long acting) properties for a majority of opioids in the data set. RESULTS: About 10% of prescriptions in the PDMP data set did not have a vendor-assigned drug category, and 20% of opioid prescriptions were missing data needed to calculate risk metrics. Using inclusive methods, 19 133 167 (>99.9%) of prescriptions in the PDMP data set were assigned a drug category. For the opioid category, augmenting data elements resulted in 10 760 669 (99.8%) having required values to calculate morphine milligram equivalents and evaluate duration of action properties. CONCLUSIONS: Drug safety researchers who require a complete and consistent PDMP data set can use the methods described here to ensure that prescriptions of interest are assigned consistent drug categories and complete opioid risk variable values. Copyright © 2016 John Wiley & Sons, Ltd.

How clinicians use prescription drug monitoring programs: a qualitative inquiry.

OBJECTIVES: Prescription drug monitoring programs (PDMPs) are now active in most states to assist clinicians in identifying potential controlled drug misuse, diversion, or excessive prescribing. Little is still known about the ways in which they are incorporated into workflow and clinical decision making, what barriers continue to exist, and how clinicians are sharing PDMP results with their patients. DESIGN: Qualitative data were collected through online focus groups and telephone interviews. SETTING: Clinicians from pain management, emergency and family medicine, psychiatry/behavioral health, rehabilitation medicine, internal medicine and dentistry participated. PATIENTS: Thirty-five clinicians from nine states participated. METHODS: We conducted two online focus groups and seven telephone interviews. A multidisciplinary team then used a grounded theory approach coupled with an immersion-crystallization strategy for identifying key themes in the resulting transcripts. RESULTS: Some participants, mainly from pain clinics, reported checking the PDMP with every patient, every time. Others checked only for new patients, for new opioid prescriptions, or for patients for whom they suspected abuse. Participants described varied approaches to sharing PDMP information with patients, including openly discussing potential addiction or safety concerns, avoiding discussion altogether, and approaching discussion confrontationally. Participants described patient anger or denial as a common response and noted the role of patient satisfaction surveys as an influence on prescribing. CONCLUSION: Routines for accessing PDMP data and how clinicians respond to it vary widely. As PDMP use becomes more widespread, it will be important to understand what approaches are most effective for identifying and addressing unsafe medication use.

Measures such as interstate cooperation would improve the efficacy of programs to track controlled drug prescriptions.

In response to increasing abuse of prescription drugs, forty-four states have implemented--and five more states will soon adopt--monitoring programs to track prescriptions of controlled medications. Although these programs were originally designed to help law enforcement officials and regulatory agencies spot possible illegal activity, health care providers have begun to use data from them to help improve patient safety and quality of care. For this article we reviewed government documents, expert white papers, articles from the peer-reviewed medical literature, and reports of the experiences of local health officials. We found some evidence that prescription drug monitoring programs are a benefit to both law enforcement and health care delivery. However, the programs have strengths and weaknesses, and their overall impact on drug abuse and illegal activity remains unclear. We believe that improving the efficacy of prescription drug monitoring programs will require such changes as more standardization and interstate cooperation, better training of providers, more secure funding, and further evaluation.