Context:The Center for Medicare and Medicaid Innovation (CMMI) awarded Denver Health’s (DH) integrated, safety net health care system $19.8 million to implement a “population health” approach into the delivery of primary care. This major practice transformation builds on the Patient Centered Medical Home (PCMH) and Wagner’s Chronic Care Model (CCM) to achieve the “Triple Aim”: improved health for populations, care to individuals, and lower per capita costs.Case description:This paper presents a case study of how DH integrated published predictive models and front-line clinical judgment to implement a clinically actionable, risk stratification of patients. This population segmentation approach was used to deploy enhanced care team staff resources and to tailor care-management services to patient need, especially for patients at high risk of avoidable hospitalization. Developing, implementing, and gaining clinical acceptance of the Health Information Technology (HIT) solution for patient risk stratification was a major grant objective.Findings:In addition to describing the Information Technology (IT) solution itself, we focus on the leadership and organizational processes that facilitated its multidisciplinary development and ongoing iterative refinement, including the following: team composition, target population definition, algorithm rule development, performance assessment, and clinical-workflow optimization. We provide examples of how dynamic business intelligence tools facilitated clinical accessibility for program design decisions by enabling real-time data views from a population perspective down to patient-specific variables.Conclusions:We conclude that population segmentation approaches that integrate clinical perspectives with predictive modeling results can better identify high opportunity patients amenable to medical home-based, enhanced care team interventions.

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Background The first Multi-center Medication Reconciliation Quality Improvement Study (MARQUIS1) demonstrated that implementation of a medication reconciliation best practices toolkit decreased total unintentional medication discrepancies in five hospitals. We sought to implement the MARQUIS toolkit in more diverse hospitals, incorporating lessons learned from MARQUIS1. Methods MARQUIS2 is a pragmatic, mentored implementation QI study which collected clinical and implementation outcomes. Sites implemented a revised toolkit, which included interventions from these domains: 1) best possible medication history (BPMH)-taking; 2) discharge medication reconciliation and patient/caregiver counseling; 3) identifying and defining clinician roles and responsibilities; 4) risk stratification; 5) health information technology improvements; 6) improved access to medication sources; 7) identification and correction of real-time discrepancies; and, 8) stakeholder engagement. Eight hospitalists mentored the sites via one site visit and monthly phone calls over the 18-month intervention period. Each site’s local QI team assessed opportunities to improve, implemented at least one of the 17 toolkit components, and accessed a variety of resources (e.g. implementation manual, webinars, and workshops). Outcomes to be assessed will include unintentional medication discrepancies per patient. Discussion A mentored multi-center medication reconciliation QI initiative using a best practices toolkit was successfully implemented across 18 medical centers. The 18 participating sites varied in size, teaching status, location, and electronic health record (EHR) platform. We introduce barriers to implementation and lessons learned from MARQUIS1, such as the importance of utilizing dedicated, trained medication history takers, simple EHR solutions, clarifying roles and responsibilities, and the input of patients and families when improving medication reconciliation.

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BACKGROUND: The Statin Use in Persons with Diabetes (SUPD) measure, developed and endorsed by the Pharmacy Quality Alliance and National Quality Forum, has been adopted by the Centers for Medicare & Medicaid Services as part of the star rating measure set. It was added as a display measure in 2015 and, as of 2019, has become a star measure. Clinical pharmacy specialists (CPS) embedded in the patient-centered medical home (PCMH) are well positioned to review and recommend statin therapy for patients with diabetes in order to improve patient care and health plan performance.OBJECTIVE: To improve rates of statin prescribing and performance on the SUPD measure in the Denver Health Medical Plan (DHMP) population with diabetes by creating a CPS-led intervention to initiate statin prescriptions in eligible patients.