A Learning Health System Approach to Hospital Quality Performance Benchmarking: The Composite Hospital Quality Index.

US hospital quality rankings and ratings use disparate methodologies and are weakly correlated. This causes confusion for patients and hospital quality staff. At the authors' institution, a Composite Hospital Quality Index (CHQI) was developed to combine hospital quality ratings. This approach is described and a calculator is shared here for other health systems to explore their performance. Among the US News and World Report Top 50 Hospitals, hospital-specific numeric summary scores were aggregated from the 2021 Centers for Medicare and Medicaid Services (CMS) Hospital Overall Star Rating, the Spring 2021 Leapfrog Safety Grade, and the April 2021 Hospital Consumer Assessment of Healthcare Providers and Systems Star Rating. The CHQI is the hospital-specific sum of the national percentile-rankings across these 3 ratings. In this example, mean (SD) percentiles were as follows: CMS Stars 74 (19), Hospital Consumer Assessment of Healthcare Providers and Systems 63 (19), Leapfrog 65 (24), with mean (SD) CHQI of 202 (49). The CHQI is used at the authors' institution to identify improvement opportunities and ensure that high-quality care is delivered across the health system.

Deployment of an Interdisciplinary Predictive Analytics Task Force to Inform Hospital Operational Decision-Making During the COVID-19 Pandemic.

In March 2020, our institution developed an interdisciplinary predictive analytics task force to provide coronavirus disease 2019 (COVID-19) hospital census forecasting to help clinical leaders understand the potential impacts on hospital operations. As the situation unfolded into a pandemic, our task force provided predictive insights through a structured set of visualizations and key messages that have helped the practice to anticipate and react to changing operational needs and opportunities. The framework shared here for the deployment of a COVID-19 predictive analytics task force could be adapted for effective implementation at other institutions to provide evidence-based messaging for operational decision-making. For hospitals without such a structure, immediate consideration may be warranted in light of the devastating COVID-19 third-wave which has arrived for winter 2020-2021.

A Citation Tracking System to Facilitate Sponsoring Institution Oversight of ACGME-Accredited Programs.

BACKGROUND: The Accreditation Council for Graduate Medical Education (ACGME) requires the graduate medical education committee and the designated institutional official to ensure that citations for noncompliance with the accreditation standards and institutional trends in citations are reviewed and corrected. OBJECTIVE: To describe a citation tracking system (CTS) that uses Microsoft Office Access to efficiently catalogue, monitor, and document resolution of citations. INNOVATION: The CTS was implemented in a sponsoring institution with oversight of 133 ACGME-accredited programs. The designated institutional official and the graduate medical education committee review all program letters of notification and enter citations into the CTS. A program-correction plan is required for each citation and is entered into the database. Open citations and action plans are reviewed by the graduate medical education committee and the designated institutional official on a quarterly basis, with decisions ranging from "closing" the citation to approving the action plan in process to requiring a new or modified action plan. Citation categories and subcategories are accessed on the ACGME website and entered into the CTS to identify trends. RESULTS: All 236 citations received since the 2006 Mayo School of Graduate Medical Education institutional site visit were entered into the CTS. On November 22, 2011, 26 of 236 citations (11%) were in active status with ongoing action plans, and 210 (89%) citations had been resolved and were closed. CONCLUSIONS: The CTS uses commercially available software to ensure citations are monitored and addressed and to simplify analysis of citation trends. The approach requires minimal staff time for data input and updates and can be performed without institutional information technology assistance.