Pharmacist-facilitated Patient Reported Outcome Measure (PROM) monitoring: developing an EHR SmartForm© to monitor side effects of oral oncolytics during routine telehealth encounters.

PURPOSE: Patient reported outcome measures (PROMs) are increasingly used in oncology care, but pharmacists providing direct patient care have been overlooked. We engaged pharmacists and adults receiving oral oncolytics (chemotherapy medication taken by mouth) to develop a SmartForm© in the electronic health record (EHR) for PROM monitoring. Pharmacists verbally ask the patient side effect questions during routine telehealth encounters and enter responses in real time. METHODS: Our development process was guided by the Knowledge to Action Framework. In phase 1 (Knowledge Inquiry), we prioritized side effects to assess in the EHR SmartForm© via interviews with patients and a Delphi panel with pharmacists. Adults receiving oral oncolytics for breast (n = 12), thoracic (n = 12), or hematological (n = 12) cancer were interviewed, with purposeful sampling for adults who were aged 65 + years or Black. Interviews were coded with content analysis. We conducted three Delphi rounds, with 11/19, 13/19, and 19/19 pharmacists, respectively. In phase 2 (Knowledge Synthesis), PROM items were selected and the EHR SmartForm© programmed. In phase 3 (Knowledge Tailoring), we conducted usability testing with pharmacists. RESULTS: Pharmacists and patients were consistent in prioritizing side effects of oral oncolytics and 10 were retained. Patients advocated asking whether they can do their usual activities, while pharmacists added medication adherence. Usability testing yielded suggestions to simplify the SmartForm©. CONCLUSION: By presenting screenshots of our SmartForm©, our findings are useful to other healthcare systems looking for a PROM solution integrated in the EHR, with a reasonable pharmacist/clinician workload, and no requirement for patients to have internet access/comfort.

Impact of medication bedside delivery program on hospital readmission rates.

BACKGROUND: Since the establishment of the Hospital Readmission Reduction Program by the Centers for Medicare and Medicaid Services, reducing readmission rates has been a priority for health care institutions. Many institutions have developed services to combat high readmission rates, including bedside medication delivery programs, which have demonstrated reductions in 30-day readmission rates in patients who used these services. OBJECTIVE: To evaluate the impact of health system-based bedside medication delivery programs on readmission rates in patients at a low to moderate risk of hospital readmission. METHODS: A single-center retrospective cohort study conducted on adult patients of low-to moderate-transitions of care (TOC) risk status with unplanned admissions to a large academic medical center between January 1, 2017, and January 1, 2019 who used the medication bedside delivery service or an outside pharmacy. The TOC risk status was defined using historic institutional definitions. Patients with at least a 2-day hospital stay and who were discharged to home from select primary medical services were included. The primary outcome was 30-day readmission rates between the 2 groups. Secondary outcomes included 60- and 90-day readmission rates and readmission rates stratified by primary medical service and TOC status. Coarsened exact matching was used to account for variation between groups. RESULTS: The study evaluated 6583 patients discharged with a total of 3905 patients and corresponding index admissions meeting inclusion criteria for analysis. No statistically significant difference between readmission rates at 30 days after the index admission was found between the medication bedside delivery group and the outside pharmacy group, 7.97% and 10.09%, respectively (P = 0.136). However, the readmission rate of the medication bedside delivery group was statistically significantly lower than that of the outside pharmacy group at 60 and 90 days. CONCLUSIONS: This study suggests that bedside medication delivery programs do not significantly reduce readmission rates at 30 days but may do so at 60 and 90 days.

Role of Pharmacy Analytics in Creating a Data-Driven Culture for Frontline Management.

Purpose: The purpose of this article is to offer key recommendations based on the authors' experiences for utilizing pharmacy analytics to support moving beyond standard-of-practice operational metrics towards high impact reporting to drive day-to-day decisions for frontline leaders. Summary: There is a continuous and vast amount of data generated through all facets of a health system's daily operations, yet many data elements go unused and fail to contribute to value creation and increased performance at an organizational level. It is critical, therefore, for departments of pharmacy to identify and implement effective strategies to leverage data through robust business analytics and reporting, ensuring managers at every level are provided the information they need to support data-driven decisions and meaningful interventions in the day-to-day operations of the organization. At the authors' institution, development and growth of a dedicated Pharmacy Analytics (PA) team has been instrumental to the pharmacy department for generating value and proactively supporting a business intelligence strategy that focuses on a data-driven management culture. Key recommendations to leverage pharmacy analytics are provided within four overarching themes: building transparency, leveraging synergy, optimizing actionability, and prioritizing partnerships. Conclusion: Through creation of a data-driven management culture, the authors provide recommendations for leveraging pharmacy analytics to reduce costs and impact outcomes across a range of hospital pharmacy operations.

A review of suicide prevention programs and training policies for pharmacists.

OBJECTIVES: The availability of suicide prevention training programs for pharmacists is unknown and may depend on state training requirements. This study's objectives were to: 1) report state training requirements for pharmacist suicide education; and 2) describe educational resources that are available to prepare pharmacists for interactions with patients at risk of suicide. METHODS: Each state's board of pharmacy was contacted from July to November 2017 to determine whether that state required pharmacists to complete suicide prevention training. A scoping literature review completed in August 2017 identified suicide prevention resources for pharmacy professionals. A systematic search of 5 databases and Google yielded publications and online resources that were screened for full review. Two coders reviewed articles and resources that met inclusion criteria and extracted data on program format and length, intended audience (i.e., students, practicing pharmacists), learning methods, topics covered, and outcomes assessed. RESULTS: Only Washington State requires pharmacists to obtain suicide prevention training. Sixteen suicide education programs and resources targeted pharmacists, including 8 in-person courses, 6 online courses, and 2 written resources. Five resources exclusively targeted pharmacists and 2 exclusively targeted student pharmacists. Most programs included information on suicide statistics, how to identify individuals at risk of suicide, how to communicate with someone who is suicidal, and how to refer patients to treatment resources. The long-term effectiveness of the programs at improving outcomes was not reported. CONCLUSION: Although only 1 state requires pharmacists to obtain training on suicide prevention, there are several resources available to help prepare pharmacists to interact with individuals at risk of suicide.

Proton Pump Inhibitors: Risk for Myopathy?

OBJECTIVE: The purpose of this article is to describe the relationship between proton pump inhibitors (PPIs) and symptoms of myopathy based on case reports. DATA SOURCES: A literature search was conducted in PubMed (1946 to June 2016) using MeSH terms proton pump inhibitors, omeprazole, esomeprazole, lansoprazole, dexlansoprazole, rabeprazole, pantoprazole, and muscular diseases. Additionally, a search was conducted in ToxNet and EMBASE using similar search criteria. STUDY SELECTION AND DATA ABSTRACTION: The resulting articles were scanned to assess relevance to the review. Bibliographies of all relevant articles were evaluated for additional sources; 26 articles resulted from the search of PubMed, ToxNet, and EMBASE; articles that involved medications typically considered to have myalgia-like side effects (eg, statins), or included patients who presented with a confounding disease state (eg, Guillain-Barré) were excluded. DATA SYNTHESIS: In total, 11 case reports as well as a review of an adverse event reporting database that included 292 cases were evaluated. Association of PPI use and myopathy symptoms does not have a clear etiology. Overall, the available published data do not show a high risk of myopathy with PPI use but should be considered if a patient presents with myopathy symptoms and concurrent PPI use. CONCLUSION: A limited body of published data suggests that PPI use has been associated with myopathy-like symptoms without long-term effects following discontinuation. Although myopathy is a rare adverse effect observed with PPIs, it can be a serious side effect to be considered when starting a patient on acid suppression therapy.

Modeling package size-conscious automated dispensing cabinet replenishment to improve efficiency.

DISCLAIMER: In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. PURPOSE: Optimization of automated dispensing cabinets (ADCs) has traditionally focused on modifying the inventory within these devices and ignored the replenishment process itself. Rounding replenishment quantities to the nearest package size, termed package size-conscious replenishment (PSCR), was investigated as a way to optimize labor needs for ADC replenishment. METHODS: A simulation of PSCR for a subset of medications stocked in ADCs at the University of North Carolina Medical Center was conducted. The simulation utilized real-world vend data and rounding factors to model the impact of PSCR on key ADC metrics. The final simulation utilized 2 months of ADC transactions across 410 medications in 149 ADCs. Four replenishment methodologies were simulated: standard replenishment and 3 PSCR strategies, including rounding down, rounding any direction, and rounding up. RESULTS: All 3 PSCR methodologies had significantly lower stockout frequencies than standard replenishment at 0.722% (P = 0.026) for rounding down, 0.698% (P = 0.024) for rounding any direction, and 0.680% (P = 0.024) for rounding up vs 0.773% for standard replenishment. PSCR methods were associated with significant time savings for both technician and pharmacist activities (P < 0.001 for all 3 strategies), with a savings of up to 0.27 technician and 0.52 pharmacist full-time equivalents estimated for the rounding-up methodology. Maximum carrying cost was higher for all 3 PSCR methodologies. CONCLUSION: PSCR was modeled to significantly decrease both pharmacist and technician time needed to replenish ADCs while also decreasing stockout frequency. Modest increases in maximum carrying cost were also shown. The simulation created for this evaluation could also be utilized to model other components of the ADC replenishment process.

Development and assessment of an abbreviated medication regimen complexity index (the A-MRCI).

DISCLAIMER: In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. PURPOSE: Adaptation of the Medication Regimen Complexity Index (MRCI) for automation in an electronic medical record has the potential to improve medication optimization and patient outcomes. The purpose of this study was to develop and evaluate an abbreviated medication regimen complexity index (A-MRCI) and compare its associations with patient-level factors to those of the MRCI. METHODS: The MRCI was modified via several rounds of review with an expert panel of clinical pharmacists and outcomes researchers. Medication data from 138 electronic health records were abstracted to calculate MRCI and A-MRCI scores for dosage form, dosing frequency, and additional directions. Comparison between indices was performed using inferential statistics for a 1-month sample of patients admitted to a cardiology or advanced heart failure service in 2017. RESULTS: A-MRCI scores were higher than MRCI scores (mean difference of 3.97, P < 0.0005; 95% CI, 2.21-5.71). A significant association was observed between the A-MRCI score and both length of stay (P = 0.0005) and polypharmacy (P < 0.0005), whereas an association between MRCI score and the patient-level factors examined was not demonstrated. CONCLUSION: On average, A-MRCI scores were higher and more likely to be associated with several patient-level factors. Internal analyses show the potential for integration into an electronic health record for automation. However, further exploration of the A-MRCI in a larger external validation sample is warranted.

Impact of pharmacist participation in the patient care team on value-based health measures.

PURPOSE: To evaluate whether pharmacist engagement on the interdisciplinary team leads to improved performance on diabetes-related quality measures. METHODS: This was a retrospective observational study of patients seen in primary care and specialty clinics from October 2014 to October 2020. Patients were included if they had a visit with a physician, nurse practitioner, physician's assistant, or clinical pharmacist practitioner (CPP) within the study period and had a diagnosis of diabetes. The intervention group included patients with at least one visit with a CPP, while the control group consisted of patients who were exclusively managed by non-CPP providers. The primary outcome of this study was the median change in glycosylated hemoglobin (HbA1c) from baseline to follow-up at 3, 6, and 12 months. The secondary outcome was the probability of achieving the HbA1c targets of <7% and <8% at 3, 6, and 12 months. RESULTS: Patients referred to a CPP had higher HbA1c levels at baseline and were more likely to have concomitant hypertension (P < 0.01). Patients seen by a CPP had 0.31%, 0.41%, and 0.44% greater reductions in HbA1c compared to patients in the control group at 3, 6, and 12 months, respectively (P < 0.01). Patients managed by a CPP were also more likely to achieve the identified HbA1c targets of <7% and <8%. CONCLUSION: Patients referred to a CPP were more complex, but had greater reductions in HbA1c and were more likely to achieve HbA1c goals included in the organization's quality measures. This study demonstrates the value of pharmacists in improving patient care and their role in supporting an organization's achievement of value-based quality measures.

Identifying health-system pharmacy operational process categories and corresponding tasks across a diverse health system using a modified Delphi process.

PURPOSE: The purpose of this study was to identify and build consensus on operational tasks that occur within a health-system pharmacy. METHODS: An expert panel of 8 individuals was invited to participate in a 3-round modified Delphi process. In the first round, the expert panel independently reviewed an initial list and provided feedback. All feedback was incorporated into the second round and then reviewed and discussed as a group. The expert panel reviewed an updated list based on feedback from the second round and reached consensus on a final list of operational processes and corresponding tasks. RESULTS: All 8 participants agreed to serve on the Delphi expert panel and reviewed an initial list of 9 process categories (hazardous intravenous [IV] medications, nonhazardous IV medications, hazardous oral medications, nonhazardous oral medications, controlled substances, total parenteral nutrition [TPN]/fluid preparations, distribution and delivery, clinical tasks, and miscellaneous operational tasks) and 44 corresponding tasks. Through the Delphi process, 72 new tasks were identified in the first round, while 34 new tasks were identified in the second round. In the third and final round, the expert panel reviewed the updated list of 9 process categories and 150 corresponding tasks, made additional edits, and reached consensus on a final list of 9 processes and 138 corresponding tasks that represented operational work within a health-system pharmacy. CONCLUSION: The modified Delphi process effectively identified operational processes and corresponding tasks occurring within hospital pharmacies in a diverse health system. This process facilitated consensus building, and the findings may inform development of an operational workload model.

Development of a system-wide pharmacy operational weighted workload model at a large academic health system.

PURPOSE: The purpose of this study is to develop a standard operational and distributional weighted workload model that is applicable across an integrated, diverse healthcare system. This model aims to not only demonstrate the operational intensity of pharmacy practice but also to inform opportunities to decrease waste, increase efficiency, facilitate growth, and demonstrate value across operational and distributional pharmacy services. SUMMARY: Time studies were conducted at 8 hospitals within the UNC Health system to objectively measure time spent within each operational process in order to create a system-wide weighted workload model. Time study results informed the development of a system-wide weighted workload model. Data from December 29, 2019, through December 26, 2020, was then applied to this weighted workload model. With this model, acute care hospital and infusion center operational areas were compared in thousands of combinations within single operational areas and across any and all operational areas by dispense code, weighted work, and ratio of weighted work to total sum of dispenses at each site. CONCLUSION: The model successfully achieved the objective to develop a standard operational weighted workload model that is applicable across the integrated, diverse care system. This model provides a foundation for UNC Health to further productivity measurement and fills a gap in the literature by offering a novel method of developing a system-level operational workload model that can be used to evaluate and compare operational workloads across health-system sites.

Transforming data into insight: Establishment of a pharmacy analytics and outcomes team.

PURPOSE: The importance of a data management strategy is increasingly necessary for demonstrating value and driving performance within pharmacy departments. Data analytics capabilities often do not match the pace of data accumulation. At our organization, the establishment of an embedded pharmacy analytics and outcomes (PAO) team has been instrumental to pharmacy services in generating and demonstrating value and proactively supporting a business intelligence strategy grounded in a data-driven culture. SUMMARY: The PAO team was established to support the operational and strategic needs of clinical, financial, and operational pharmacy services. The team is charged with implementing the vision of extending medication-use influence and data insight to drive value-based patient care outcomes while decreasing waste, optimizing therapeutic decisions, and achieving medication management standardization across the continuum of healthcare. The PAO team is composed of 3 pharmacist full-time equivalents (FTEs), 5 business analyst FTEs, 1 biostatistician FTE, 0.2 pharmacy intern FTE, and 1 pharmacy manager FTE. Pharmacy services leaders believe it is necessary to have a mix of both clinical and analytical skill sets, given the clinical nature of the data managed by team and complexities of the medication-use process. CONCLUSION: Pharmacy reporting and analytics should require the same depth of scrutiny and overview as any other step in the medication-use process where pharmacists are held accountable. For our organization, it was critical to establish pharmacist-level oversight into every portion of the analytics process where medication data are involved. This structure has led to measurable improvements in patient outcomes, operational efficiency, and financial performance.

Development and perceived value of a master's degree in health-system pharmacy administration training.

PURPOSE: To describe the development, format, and alumni and employer perceptions of a program combining a master of science (MS) degree with a residency in health-system pharmacy administration and leadership (HSPAL). SUMMARY: A multisite combined MS and HSPAL residency program was developed within the University of North Carolina at Chapel Hill Eshelman School of Pharmacy to increase leadership and management education. The program balances clinical and administrative experiences with didactic courses over 2 years. The program format and perceived value of MS degree training for HSPAL residents had not been previously described in the literature. In an online survey, alumni of the program, as well as their first supervisors after completion of HSPAL training, indicated perceived attainment of the program core competencies and outcomes. Supervisors also indicated that they were more likely to hire MS degree-trained pharmacists for administrative positions. CONCLUSION: Didactic training in the form of an MS degree as a part of comprehensive HSPAL residency training is perceived as beneficial by alumni and employers for promoting the development of core leadership and management skills and knowledge.

Formation and validation of an acute care clinical pharmacist productivity model: Part 2.

PURPOSE: The purpose of the project described here was to use the work outputs identified in part 1 of a 2-part research initiative to build and validate an acute care clinical pharmacist productivity model. METHODS: Following the identification of work outputs in part 1 of the project, relative weighting was assigned to all outputs based on the time intensity and complexity of each task. The number of pharmacists verifying an inpatient medication order each day was selected to represent the labor input. A multivariable linear regression was performed to determine the final work outputs for inclusion in the model. Productivity and productivity index values were calculated for each day from July 1, 2018, through June 30, 2019. RESULTS: Of the 27 work outputs identified via consensus by the clinical pharmacist working team, 17 work outputs were ultimately included in the productivity model. The average productivity during the period July 2018 through June 2019 was derived from the model and will serve as the baseline productivity for acute care clinical pharmacists. CONCLUSION: Validated consensus methodology can be useful for engaging clinical pharmacist in decision-making and developing a clinical productivity model. When thoughtfully designed, the model can replace obsolete measures of productivity that do not account for the responsibilities of clinical pharmacists.

The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many centers. MATERIALS AND METHODS: The Clinical and Translational Science Award Program and scientific community created N3C to overcome technical, regulatory, policy, and governance barriers to sharing and harmonizing individual-level clinical data. We developed solutions to extract, aggregate, and harmonize data across organizations and data models, and created a secure data enclave to enable efficient, transparent, and reproducible collaborative analytics. RESULTS: Organized in inclusive workstreams, we created legal agreements and governance for organizations and researchers; data extraction scripts to identify and ingest positive, negative, and possible COVID-19 cases; a data quality assurance and harmonization pipeline to create a single harmonized dataset; population of the secure data enclave with data, machine learning, and statistical analytics tools; dissemination mechanisms; and a synthetic data pilot to democratize data access. CONCLUSIONS: The N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics. We expect this effort to save lives by enabling rapid collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care and thereby reduce the immediate and long-term impacts of COVID-19.

Community pharmacy staff interactions with patients who have risk factors or warning signs of suicide.

BACKGROUND: Little is known about community pharmacy staff members' interactions with patients at risk of suicide. OBJECTIVES: To: 1) develop a measure to assess the frequency with which pharmacy staff encounter patients with suicide risk factors and warning signs; 2) to assess the measure's validity and reliability; and 3) describe pharmacy staff members' interactions with at-risk patients and their suicide prevention training preferences. METHODS: A convenience sample of 501 community pharmacy staff members who worked in North Carolina completed an anonymous online survey. A 10-item measure (the Pharmacy Suicide Interaction Scale (PSIS)) assessed how often respondents encountered patients with suicide risk factors or warning signs, and one open-ended question elicited barriers to interacting with these patients. Psychometric analyses, including an exploratory factor analysis, were performed to examine the validity and reliability of the PSIS. Descriptive statistics were calculated, and responses to open-ended questions were analyzed thematically. RESULTS: The PSIS possessed two factors (or subscales): a non-verbal suicide warning signs and risk factors subscale (Cronbach's alpha = 0.79) and a verbal warning signs subscale (Cronbach's alpha = 0.67). Respondents who knew a patient who had died by suicide had higher mean scores on the non-verbal and verbal subscales, indicating that the PSIS had construct validity. Many respondents (22.4%) knew a patient who died by suicide, and 21.6% of respondents had patients request a lethal dose of medication. Interactions occurred both face-to-face and over the phone, and respondents most commonly reacted to patients by contacting others or offering emotional support. Few respondents (8.8%) had suicide prevention training or resources, but most (89.6%) desired additional training. CONCLUSION: Many community pharmacy staff members have interacted with patients who exhibited suicide warning signs or died by suicide. Suicide prevention training may help prepare pharmacy staff to recognize, communicate with, and refer at-risk patients.