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This article discusses two interventions implemented in different healthcare settings. The first intervention focuses on improving the efficiency and cost-effectiveness of medical procedures, such as coronary artery bypass graft and hip and knee replacements, through the use of data analysis and stakeholder collaboration. The second intervention addresses the challenges of vaccine tracking and administration during the COVID-19 pandemic, utilizing technology and data visualization to ensure accurate documentation and minimize waste. Both interventions have resulted in positive outcomes, including cost savings, improved patient outcomes, and increased patient safety. [Extracted from the article]

This document discusses a predictive dispensing-based ordering system implemented at Texas Children's Hospital to reduce medication waste and costs. The hospital digitized and centralized the ordering process, recalculated inventory levels, and utilized various data sources to generate comprehensive medication information. The program was piloted in two satellite pharmacies and resulted in a significant reduction in ordered medications and wasted or returned medications. It also improved inventory management, communication among hospital teams, and identified inventory leaks and inconsistencies. Another document mentioned in the text discusses reducing delays in antibiotic administration in the emergency department to improve sepsis care. [Extracted from the article]

Purpose The objective of this study was to understand at what level of the Autonomous Pharmacy Framework facilities are operating, in terms of the current state of data collection and analysis in the medication-use process, and to gather insights about systems integration and automation use. Methods The Autonomous Pharmacy Advisory Board, a group of chief pharmacy officers and operational leaders, developed a self-assessment instrument based on the previously published Autonomous Pharmacy Framework, made the self-assessment instrument available via the internet, and reviewed respondents' self-reported results. The data collection period for the survey started in March of 2021 and ended in January of 2023. Results A total of 119 facility-level self-assessments were completed and analyzed. On a scale of 1 to 5, where 1 represented little or no data-driven automation with lots of manual tasks and 5 represented the utmost data-driven automation with few manual tasks, the average overall facility-level score was 2.77 (range, 1.38-4.41). Results revealed slight variance by facility bed capacity. Much more variation was found in the degrees to which individual facilities have automated core processes like inventory management, intravenous medication preparation, and financial reporting. Conclusion As a baseline, this automation-focused facility self-assessment suggests that for essentially all health-system pharmacy facilities and their larger organizations, a substantial body of work needs to be done to further develop and upgrade technology and practice in tandem, greatly expand data collection and analysis, and thereby achieve better operational, financial, and clinical outcomes. Significant advancements are needed to arrive at the highly reliable, highly automated, data-driven medication-use process involving few repetitive manual tasks envisioned in the Autonomous Pharmacy Framework. [ABSTRACT FROM AUTHOR]