Implementation of a Pharmacist-Led, Multidisciplinary Naloxone Patient Education Program at an Academic Medical Center.

Background: Opioid related overdoses are a leading cause of death in the United States (U.S). National, state and local initiatives have been implemented to combat the opioid crisis. However, there is a paucity of initiatives that examine the role of comprehensive naloxone education interventions for hospitalized patients. Objective: The aim of this study was to design a multidisciplinary, pharmacist-driven, standardized, patient and product tailored, inpatient naloxone education program (NEP) at a U.S. academic medical center, targeting patients at high risk of opioid overdose, and to examine patients' retention of education. Methods: This prospective pilot study targeted hospitalized patients who were considered at high-risk for opioid overdose once discharged. Using daily screening methods and established inclusion criteria, we evaluated the impact of implementing a patient-tailored NEP. The primary outcome measures were patient knowledge and awareness of naloxone use. A paired t-test analysis was conducted to assess for improvement in patient naloxone awareness and knowledge. Results: Of ninety-five patients screened, forty-four patients met inclusion criteria and nineteen patients completed naloxone education along with pre- and post-assessments. Patients more accurately completed the assessment, indicating enhanced knowledge about naloxone use and administration, following the naloxone education (4.68 ± .13 vs 3.42 ± .31 out of 5 questions, mean ± SEM; P = .0016). Conclusion: This study found a positive impact on patient knowledge of naloxone use and administration following implementation of a robust and comprehensive NEP.

Assisted versus referred pharmacy smoking interventions for patients with thoracic malignancies or pulmonary nodules.

BACKGROUND: Tobacco use is the foremost preventable cause of death, disease, and disability in the United States. Continued tobacco use in malignant disease contributes to treatment failure and disease progression. Pharmacists are pivotal to tobacco cessation counseling, management, and follow up. METHODS: This retrospective, observational, single-center, cohort study of ambulatory cancer patients was designed to assess the impact of assisted versus "Ask, Advise, Refer" (AAR) pharmacy-driven smoking cessation interventions on patient-reported quit rates at 30- and 90-days. Those included were currently smoking or recently quit adults with a thoracic malignancy or nodule. Those in the assisted intervention were offered nicotine replacement therapy (NRT) for free according to a personalized quit plan. After July 1, 2020, patients were enrolled in the AAR intervention, whereby participants were referred to obtain NRT through insurance or external resources. Both clinical interventions were provided as standard of care. RESULTS: 129 participants were included (assisted n = 83; AAR n = 46) with baseline characteristics evenly matched. After excluding those unable to be reached at 30-days, 30 (44.8%) in the assisted intervention quit smoking versus 11 (27.5%) in the AAR intervention, p = 0.08. Lung cancer patients were more likely to report quitting at 30-days in the assisted intervention, 16 (64.0%) versus 5 (29.4%) in the AAR intervention, p = 0.03. After excluding those unable to be reached at 90-days, 30 (45.5%) in the assisted intervention quit versus 11 (35.5%) in the AAR intervention, p = 0.35. CONCLUSIONS: Pharmacy-led smoking cessation initiatives that include providing NRT are especially impactful on smoking cessation in lung cancer patients.

Assessing the Impact of a Clinical Pharmacist in a Postsurgical Inpatient Population.

OBJECTIVE: To quantify the number and type of clinical pharmacist interventions with an impact on patient care in a postsurgical nonintensive care patient population. BACKGROUND: Studies have shown that pharmacists are able to improve the quality of patient care; however, the pharmacist role in postsurgical nonintensive care areas is not well defined. METHODS: A clinical pharmacist provided care for 2 postsurgical floors for 2 weeks and collected information about the number and type of interventions made and adverse events avoided. In addition, the study team conducted an anonymous survey amongst the multidisciplinary team who collaborated with the pharmacist at the end of the trial period to understand the perception of having access to a clinical pharmacist who was designated to their floor. RESULTS: In a 2-week time period, the clinical pharmacist was able to make 218 interventions, including 38 recommendations for optimization of antimicrobials, 26 recommendations for anticoagulation optimization, and providing education for 20 patients planned for discharge on high-risk medications. Interventions made by the clinical pharmacist helped decrease adverse events, improve patient safety and knowledge, and potentially avoid readmissions and reduce hospital length of stay. The survey results revealed that 100% strongly agreed that a clinical pharmacist should be a member of the multidisciplinary team for the postsurgical floors. CONCLUSION: This data signifies that having a clinical pharmacist dedicated to the postsurgical patient population allows for optimization of antimicrobial and anticoagulant use, improves outcomes for patients through medication education, and enhances provider satisfaction.

Practical utility of mixed methods research in pharmacy practice.

PURPOSE: Our aim was to review key methodological concepts and provide a practical guide to employing mixed methods research to enhance pharmacy practice research. SUMMARY: Mixed methods research provides multiple organized analytic perspectives to thoroughly investigate complex social and scientific problems in a methodologically rigorous manner. This research design incorporates collection and analysis of both qualitative and quantitative data components to create a thorough understanding of a complex question. The 5 most commonly identified reasons for conducting mixed methods research include triangulation, complementarity, development, initiation, and expansion of results. For research questions that benefit from mixed methods research, we review how to structure the study, including timing, sequencing, and prioritization of methods. Illustrative examples from the literature highlight the utility of this methodology for clinical and operational pharmacy research questions. CONCLUSION: Mixed methods designs can enhance pharmacy research inquiry, provide a means to understand complicated issues, and uncover optimal interventions.

Defects in Processes of Care for Pharmacologic Prophylaxis Are Common Among Neurosurgery Patients Who Develop In-Hospital Postoperative Venous Thromboembolism.

BACKGROUND: Venous thromboembolism (VTE) is a cause of considerable morbidity and mortality in hospitalized patients. An evidence-based algorithm was developed and implemented at our institution to guide perioperative VTE prophylaxis management. OBJECTIVE: We evaluated compliance with prescription of risk-appropriate VTE prophylaxis and administration of prescribed VTE prophylaxis in neurosurgery patients. METHODS: This was a retrospective analysis of postoperative neurosurgery patients at a single institution with subsequent diagnosis of acute VTE during their inpatient stay. Descriptive statistics were used to characterize pharmacologic VTE prophylaxis and prescribing patterns. RESULTS: The incidence of VTE in our neurosurgery population was 248/13,913 (1.8%). Of the 123 patients, the median time to VTE diagnosis was 96 hours after surgery (interquartile range [IQR], 58-188 hours). A total of 108 patients (87.8%) were prescribed risk-appropriate VTE prophylaxis, among whom 61 (56.5%) received all doses as prescribed. Fifty-three patients (43.1%) missed ≥1 dose of prescribed prophylaxis and the median missed doses was 3 (IQR, 0-3). The median time to first dose of pharmacologic VTE prophylaxis was 42 hours (IQR, 28-51). More than half (n = 63, 51.2%) of the VTE risk assessments contained ≥1 error, of which 15 (23.8%) would have resulted in a change in recommendation. CONCLUSIONS: Our evidence-based VTE prophylaxis algorithm was not accurately completed in more than half of patients. Many patients who developed VTE had a defect in their VTE prophylaxis management during their inpatient stay. Research to improve optimal VTE prevention practice in neurosurgery patients is needed.

Evaluating the Impact of Prescription Fill Rates on Risk Stratification Model Performance.

BACKGROUND: Risk adjustment models are traditionally derived from administrative claims. Prescription fill rates-extracted by comparing electronic health record prescriptions and pharmacy claims fills-represent a novel measure of medication adherence and may improve the performance of risk adjustment models. OBJECTIVE: We evaluated the impact of prescription fill rates on claims-based risk adjustment models in predicting both concurrent and prospective costs and utilization. METHODS: We conducted a retrospective cohort study of 43,097 primary care patients from HealthPartners network between 2011 and 2012. Diagnosis and/or pharmacy claims of 2011 were used to build 3 base models using the Johns Hopkins ACG system, in addition to demographics. Model performances were compared before and after adding 3 types of prescription fill rates: primary 0-7 days, primary 0-30 days, and overall. Overall fill rates utilized all ordered prescriptions from electronic health record while primary fill rates excluded refill orders. RESULTS: The overall, primary 0-7, and 0-30 days fill rates were 72.30%, 59.82%, and 67.33%. The fill rates were similar between sexes but varied across different medication classifications, whereas the youngest had the highest rate. Adding fill rates modestly improved the performance of all models in explaining medical costs (improving concurrent R by 1.15% to 2.07%), followed by total costs (0.58% to 1.43%), and pharmacy costs (0.07% to 0.65%). The impact was greater for concurrent costs compared with prospective costs. Base models without diagnosis information showed the highest improvement using prescription fill rates. CONCLUSIONS: Prescription fill rates can modestly enhance claims-based risk prediction models; however, population-level improvements in predicting utilization are limited.