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.

The role of the chief pharmacy officer in leading analytics strategy to support the enterprise.

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.

Development and implementation of a standardized process for identifying ambulatory pharmacy clinical outcomes measures.

PURPOSE: There is minimal available guidance on the process for selection of clinical outcomes measures to demonstrate the impact of clinic-based pharmacists (CBPs) despite an increased need and desire for outcomes data. The overall aims of this project were to (1) develop a standardized process for identifying clinical outcomes measures impacted by CBPs and (2) identify and prioritize potential clinical outcomes measures to track for CBPs within 4 specialty clinic pilot sites. METHODS: To develop a standardized process for identification and prioritization of measures, 4 consecutive Plan-Do-Study-Act (PDSA) cycles were performed with 4 different specialty clinics serving as pilot sites. Following each pilot cycle, rapid cycle improvements were implemented. A modified Delphi methodology served as the framework for measure selection and included gathering expert stakeholder insights regarding importance, feasibility, and validity of potential measures. Measures were identified via environmental scan of existing validated quality metrics, clinical guidelines, and other relevant literature. RESULTS: The primary outcome for this project was the development and refinement of a standardized process for measure identification and prioritization. The secondary outcome was narrowed and ranked lists of stakeholder-prioritized measures for 4 CBP-embedded pilot specialty clinics. These lists included 12 cardiothoracic transplant, 6 breast oncology, 9 neurology, and 7 gynecologic oncology measures. CONCLUSION: The measure identification and prioritization process developed was successfully utilized to identify and prioritize outcomes measures to track for 4 CBP-embedded specialty clinics. Due to the successful use of the process in a variety of specialty clinics, the standardized process has significant potential for expansion.

Telehealth medication management and health care spending in a Medicare Accountable Care Organization.

BACKGROUND: Value-based care is an opportunity for medication optimization services to improve medication management and reduce health care spending. The reach of these services may be extended through telehealth. However, as health care systems and payers grapple with the long-term financing of telehealth, real-world assessments are needed to evaluate the potential economic impact of pharmacy-driven telehealth services. OBJECTIVE: To evaluate the impact of a scalable pharmacist-driven telehealth intervention to improve medication management on health care spending for clinically complex patients who were enrolled in a Medicare Next Generation Accountable Care Organization. METHODS: Data for this pretest-posttest nonequivalent group design study came from Medicare claims from 2015 to 2020 and linked pharmacist care activity data derived from the electronic medical record. Patients in the intervention group were identified as those who received the telehealth medication management service. Patients in the control group were offered the service and refused or could not be contacted. The primary outcome was total medical spending over a 6-month period, and impact was assessed using a covariate-adjusted difference-in-difference model. RESULTS: There were 581 patients who received the intervention and 1,765 who served as controls. The telehealth intervention reduced total medical spending by $2,331.85 per patient over the first 6 months of the service ($388.50 per month; P = 0.0261). Across a range of estimates for the cost of service delivery, we find a return on investment of 3.6:1 to 5.2:1. CONCLUSIONS: The $388.50 monthly savings found in this study represent a substantial reduction in health care spending and emphasize the opportunity for telehealth delivery of medication management services to improve value as a part of alternative payment models. DISCLOSURES: This study was funded by the UNC Health Care Department of Pharmacy. Dr Urick has received personal fees from Pharmacy Quality Solutions and Cardinal Health. Drs Peters, Vest, Colmenares, Foushee, and DeFalco are employees of UNC Health Care Department of Pharmacy. Mr Easter received a Co-PI grant from NACDS Foundation to implement Community-based Value Care Initiative (CVCI) in a community pharmacy setting. He also received a grant to Eshelman School of Pharmacy. He has an individual consulting agreement with digital health company Truentity Health to provide go to market strategy for medication management services. He also has stock options from Truentity Health as a component of the consulting agreement. Dr Foushee has a leadership or fiduciary role at Member-At-Large and the Ambulatory Care Academy of the North Carolina Association of Pharmacists. At the time this work was conducted, Dr Urick, Dr Pathak, and Dr Blanchard were all employees of the UNC Eshelman School of Pharmacy.

Implementation and results of a standardized process for identifying ambulatory pharmacy clinical outcome measures.

PURPOSE: Given the variation in clinical practice, a clinician-centric, standardized process to implement and validate clinical pharmacy outcome measures was developed. SUMMARY: Four specialty clinics with embedded clinic-based pharmacists underwent an iterative process to define, refine, and implement the build of electronic health record functionality for outcome measure data collection and reporting. Starting with a list of identified measures, clinic workgroups met to discuss each measure and identify gaps in measure implementation. Information technology experts created electronic documentation forms with discrete data and reports based on criteria specified by the clinic workgroups. Of 32 outcome measures identified as priorities for demonstrating pharmacists' impact in previous research, 29 were implemented for routine monitoring through this project. Implementation strategies included identification through existing reporting, development of discrete documentation tools within the electronic health record, and development of new reporting tools from available discrete data fields. Time to implementation decreased from the first to the last pilot clinic implementation, as demonstrated through a 9-day reduction in electronic documentation form development and 31-day reduction in report development turnaround time. CONCLUSION: A standardized and reproducible process was developed for the implementation of clinical pharmacy outcomes measures for 4 specialty clinics. The process was successfully utilized to develop measurable outputs for a variety of oncology and nononcology specialty disease states based upon multidisciplinary stakeholder input.

Implementation of a strategy for identification and monitoring of clinical outcome measures in a department of pharmacy.

PURPOSE: To describe a department of pharmacy strategy to identify and monitor outcome measures that represent the impact of clinical pharmacy services on patient outcomes. SUMMARY: Our department established the Clinical Impact Committee, with the goal of developing and maintaining an approach to demonstrate the impact of clinical pharmacists on patient care outcomes. We describe the committee's structure, aims, and key stakeholders, inclusive of both departmental leadership and clinical pharmacist representatives across service lines. We also describe the systematic process used by the committee for identifying clinical outcome measures that are both aligned with organizational priorities and representative of pharmacists' impact. This involved assembly of a crosswalk of clinical outcome measures that are prioritized by the organization and attributable to the work of clinical pharmacists. We found it imperative to connect pharmacists' efforts to the priorities of the organization to demonstrate value and continue to justify pharmacy resources. Once the crosswalk of clinical outcome measures was assembled, the Clinical Impact Committee leveraged modified Delphi methodology to build consensus on the measures to prioritize. Once determined, the final outcome measures were developed into outcomes dashboards, to be monitored by the committee and leveraged by frontline pharmacists. CONCLUSION: Our organization was successful in developing a structure, the Clinical Impact Committee, to identify, prioritize, and monitor measures that demonstrate pharmacist contributions to patient care outcomes. Further, our approach includes an intentional alignment with organizational priorities, allowing us to understand and communicate the contributions of our teams to meeting-defined organizational quality priorities.

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.

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.

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 an innovative partnership between a health-system department of pharmacy and external community pharmacies.

PURPOSE: Our organization implemented a health-system pharmacy/community pharmacy transitions of care (TOC) program, developing a scalable model to improve care transitions from the health system to the community setting for shared patients. SUMMARY: In this report, we describe our organization's experiences in taking a purposeful approach to building and pilot testing a partnership between our department of pharmacy and 14 community pharmacies within a larger statewide network to improve TOC across care settings. We have been successful in partnering with our electronic health record (EHR) vendor to enhance access capabilities to allow for documentation by community pharmacists (external to the organization) to be included in the patient record as a note. The goal of the partnership with community pharmacies is to elevate TOC for patients, identify and resolve medication therapy problems that may occur post discharge and lead to poor outcomes, and improve continuity of care across practice settings. CONCLUSION: Our department of pharmacy has led a successful initiative to promote collaboration with local external community pharmacies. This program has led to innovative advancements in EHR capabilities, promoting transparency in the documentation of pharmacy services and making this documentation visible to all care team members.

A deprescribing medication program to evaluate falls in older adults: methods for a randomized pragmatic clinical trial.

BACKGROUND: Opioids and benzodiazepines (BZDs) are some of the most commonly prescribed medications that contribute to falls in older adults. These medications are challenging to appropriately prescribe and monitor, with little guidance on safe prescribing of these medications for older patients. Only a handful of small studies have evaluated whether reducing opioid and BZD use through deprescribing has a positive impact on outcomes. Leveraging the strengths of a large health system, we evaluated the impact of a targeted consultant pharmacist intervention to deprescribe opioids and BZDs for older adults seen in primary care practices in North Carolina. METHODS: We developed a toolkit and process for deprescribing opioids and BZDs in older adults based on a literature review and guidance from an interprofessional team of pharmacists, geriatricians, and investigators. A total of fifteen primary care practices have been randomized to receive the targeted consultant pharmacist service (n = 8) or usual care (n = 7). The intervention consists of several components: (1) weekly automated reports to identify chronic users of opioids and BZDs, (2) clinical pharmacist medication review, and (3) recommendations for deprescribing and/or alternate therapies routed to prescribers through the electronic health record. We will collect data for all patients presenting one of the primary care clinics who meet the criteria for chronic use of opioids and/or BZDs, based on their prescription order history. We will use the year prior to evaluate baseline medication exposures using morphine milligram equivalents (MMEs) and diazepam milligram equivalents (DMEs). In the year following the intervention, we will evaluate changes in medication exposures and medication discontinuations between control and intervention clinics. Incident falls will be evaluated as a secondary outcome. To date, the study has enrolled 914 chronic opioid users and 1048 chronic BZD users. We anticipate that we will have 80% power to detect a 30% reduction in MMEs or DMEs. DISCUSSION: This clinic randomized pragmatic trial will contribute valuable evidence regarding the impact of pharmacist interventions to reduce falls in older adults through deprescribing of opioids and BZDs in primary care settings. TRIAL REGISTRATION: Clinicaltrials.gov NCT04272671 . Registered on February 17, 2020.

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 validation of a predictive model to predict and manage drug shortages.

PURPOSE: Pharmacy departments across the country are problem-solving the growing issue of drug shortages. We aim to change the drug shortage management strategy from a reactive process to a more proactive approach using predictive data analytics. By doing so, we can drive our decision-making to more efficiently manage drug shortages. METHODS: Internal purchasing, formulary, and drug shortage data were reviewed to identify drugs subject to a high shortage risk ("shortage drugs") or not subject to a high shortage risk ("nonshortage drugs"). Potential candidate predictors of drug shortage risk were collected from previous literature. The dataset was trained and tested using 2 methods, including k-fold cross-validation and a 70/30 partition into a training dataset and a testing dataset, respectively. RESULTS: A total of 1,517 shortage and nonshortage drugs were included. The following candidate predictors were used to build the dataset: dosage form, therapeutic class, controlled substance schedule (Schedule II or Schedules III-V), orphan drug status, generic versus branded status, and number of manufacturers. Predictors that positively predicted shortages included classification of drugs as intravenous-only, both oral and intravenous, antimicrobials, analgesics, electrolytes, anesthetics, and cardiovascular agents. Predictors that negatively predicted a shortage included classification as an oral-only agent, branded-only agent, antipsychotic, Schedule II agent, or orphan drug, as well as the total number of manufacturers. The calculated sensitivity was 0.71; the specificity, 0.93; the accuracy, 0.87; and the C statistic, 0.93. CONCLUSION: The study demonstrated the use of predictive analytics to create a drug shortage model using drug characteristics and manufacturing variables.

Implementation of a pharmacy-focused morbidity, mortality, and improvement conference.

PURPOSE: Review lessons learned during the development and implementation of a pharmacy-focused Morbidity, Mortality, and Improvement conference at an academic medical center. SUMMARY: Since the early 1900s, Morbidity and Mortality conferences have provided a forum for clinicians to discuss medical errors and adverse outcomes. Many institutions have now added "improvement" to the conference title to emphasize the goal of approaching these conferences in a systems-oriented manner. To date, a gap remains in the literature evaluating the impact of a pharmacy-focused Morbidity, Mortality, and Improvement (MM&I) conference. The primary goal in establishing this pharmacy-focused conference was to foster and strengthen the culture of medication safety within our department. In establishing our program, we identified an opportunity to leverage pharmacy residents similar to a medical resident-facilitated conference. After gaining leadership buy-in, a core planning team was formed to identify events and create conference materials. Primary metrics to gauge the success of implementation included event reporting trends and medication-safety strategic initiative tracking. The first year of MM&I conferences provided forward momentum for our department's safety culture. Safety event reporting by pharmacy staff increased by 150% over the fiscal year, and more frontline staff expressed a personal interest in becoming involved in safety projects and initiatives outside of their normal shift responsibilities. CONCLUSION: We have learned several important lessons that may be helpful to others, the primary of which is that improving a culture of safety takes time.

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.

Impact of an innovative partnership in patient care between an academic medical center department of pharmacy and a school of pharmacy.

PURPOSE: Pharmacy departments and schools of pharmacy have long held professional affiliations. However, the success of each entity is often not interdependent and aligned. In 2010, our institutions found ourselves in a position where the complementary motivations of each aligned to support a more meaningful and committed engagement, leading to the development of the Partnership in Patient Care. The impact of the partnership was evaluated 7 years postimplementation, and both the successes realized and the lessons learned are described. SUMMARY: The partnership provided many advantages to our pharmacy department and the school of pharmacy. This initial iteration of the partnership was a strong proof of concept that an intentional approach to the relationship between a school of pharmacy and a pharmacy department can lead to substantive improvements in a wide array of meaningful outcomes. We experienced an increase in the number of student rotation months completed, growth in the American Society of Health-System Pharmacists-accredited residency programs, and enhanced clinical services. However, the partnership was not without challenges. For instance, lack of a formalized tracking method made certain outcomes difficult to track. CONCLUSION: The purposeful establishment of the Partnership in Patient Care, built on the needs of a school of pharmacy and an academic medical center pharmacy department, allowed our institutions to develop an intertwined mission and vision. Over the initial years of the partnership, many successes were realized and lessons were learned. Both the successes and the challenges are serving as the foundation for future iterations of the partnership.