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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.

Pharmacists are responsible for determining which aspects of medication use and management are best handled by pharmacists, by artificial intelligence (AI), or by pharmacists who receive advice from AI-based systems. Pharmacists should use scientific approaches to determine the degree to which AI is used to automate specific medication-use tasks. Full automation using AI should be reserved for algorithmic tasks for which it is demonstrated that AI performs as well or better than pharmacists. AI of proven value should be adopted and used so that pharmacists can make better decisions and focus their expertise on solving new and confounding problems for patients, families, and organizations.

Objective Clinical pharmacists use population health methods to generate chronic disease management referrals for patients with uncontrolled chronic conditions. The purpose of this study was to compare primary care providers’ (PCPs) referral responses for 4 pharmacist-managed indications and to identify provider and patient characteristics that are predictive of PCP response. Design Retrospective cohort study. Setting This study occurred in an academic internal medicine clinic. Participants Clinical pharmacy referrals generated through a population health approach between 2012 and 2016 for hypertension, chronic pain, depression, and benzodiazepine management were included. Main outcome measures Proportion of referrals accepted, left pending, or rejected and influencing provider and patient characteristics. Results Of 1769 referrals generated, PCPs accepted 869 (49%), left pending 300 (17%), and rejected 600 (34%). Compared with referrals for hypertension, benzodiazepine management, and depression, chronic pain referrals had the lowest likelihood of rejection (odds ratio [OR] 0.31; 95% CI 0.19–0.49). Depression referrals had an equal likelihood of being accepted or rejected (OR 1.04; 95% CI 0.66–1.64). Provider characteristics were not significantly associated with referral response, but residents were more likely to accept referrals. Patient characteristics associated with lower referral rejection included black race (OR 0.39; 95% CI 0.18–0.87), higher systolic blood pressure (OR 0.98; 95% CI 0.97–0.99), and missed visits (OR 0.24; 95% CI 0.07–0.81). Conclusion The majority of referrals for clinical pharmacists in primary care settings were responded to, varying mostly between acceptance and rejection. There was variability in referral acceptance across indications, and some patient characteristics were associated with increased referral acceptance.

In November 2016, the International Pharmaceutical Federation (FIP) endeavored to create an environment to foster a shared vision to lead a transformative pharmaceutical workforce roadmap. Three milestone documents were developed and presented at the Global Conference on Pharmacy and Pharmaceutical Education. Workshops with the key themes and connecting Pharmaceutical Workforce Development Goals (PWDG) were conducted and analyzed. This Note serves to summarize the key aspects of these workshops, reporting on the innovative approaches used to generate guidance for stakeholders regarding implementation. Innovation: Seven workshops with a uniform structure were developed. These were designed to improve communication, harmonise outcome-generation, and allow for aggregate analysis. A team of seven conducted each workshop, each team consisted of: a Chair, a facilitator, one rapporteur, and four speakers purposively selected from FIP member organisations and other key stakeholders with expertise for sharing a variety of perspectives. Guidelines and templates were developed for all roles and each team was briefed in advance. Key findings: Approximately 200 personnel participated in the seven workshops, with around 20 country representatives per workshop, covering all six World Health Organisation regions. Three key aspects of workforce transformation, using the PWDGs, were explored in each workshop: drivers for implementation; challenges to implementation; and ways of encouraging implementation. Drivers for implementation mentioned were enhancing collaboration and engagement. Challenges to implementation were identified as variance in terminology. Several ways of encouraging implementation were acknowledged, such as communication strategies, advocating for workforce development and sharing best practices to foster partnerships. Next steps: The unique format of the workshops, the innovative approach to include stakeholders across an array of settings and the parallel structure in all the seven workshops, aided in creating reliable findings. The achievability of the PWDGs depends on several factors. Engagement with stakeholders and engagement from and between professional associations are important factors to achieving workforce development goals. Article Type: Note