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Abstract Background Patients presenting to academic medical centers (AMC) typically receive primary care, specialty care, or both. Resources needed for each type of care vary, requiring different levels of care coordination. We propose a novel method to determine whether a patient primarily receives primary or specialty care to allow for optimization of care coordination. Objectives We aimed to define the concepts of a Lifer Patient and Destination Patient and analyze the current state of care utilization in those groups to inform opportunities for improving care coordination. Methods Using AMC data for a 36-month study period (FY17-19), we evaluated the number of unique patients by residence zip code. Patients with at least one primary care visit and patients without a primary care visit were classified as Lifer and Destination patients, respectively. Cohen’s effect sizes were used to evaluate differences in mean utilization of different care delivery settings. Results The AMC saw 35,909 Lifer patients and 744,037 Destination patients during the study period. Most patients were white, non-Hispanic females; however, the average age of a Lifer was seventy-two years whereas that of a Destination patient was thirty-eight. On average, a Lifer had three times more ambulatory care visits than a Destination patient. The proportion of Inpatient encounters is similar between the groups. Mean Inpatient length of stay (LOS) is similar between the groups, but Destination patients have more variance in LOS. The rate of admission from the emergency department (ED) for Destination patients is nearly double Lifers’. Conclusion There were differences in ED, ambulatory care, and inpatient utilization between the Lifer and Destination patients. Furthermore, there were incongruities between rate of hospital admissions and LOS between two groups. The Lifer and Destination patient definitions allow for identification of opportunities to tailor care coordination to these unique groups and to allocate resources more efficiently.

Abstract Large- and small-scale transformation of healthcare delivery toward improved patient experience through promotion of patient-centered and coordinated care continues to be at the forefront of health system efforts in the United States. As part of a Quality Improvement (QI) project at a large, midwestern health system, a case series of high-performing organizations was explored with the goal of identifying best practices in patient-centered care and/or care coordination (PCC/CC). Identification of best practices was done through rapid realist review of peer-reviewed literature supporting three PCC/CC interventions per case. Mechanisms responsible for successful intervention outcomes and associated institutional-level facilitators were evaluated, and cross-case analysis produced high-level focus items for health system leadership, including (1) institutional values surrounding PCC/CC, (2) optimization of IT infrastructure to enhance performance and communication, (3) pay structures and employment models that enhance accountability, and (4) organizing bodies to support implementation efforts. Health systems may use this review to gain insight into how institutional-level factors may facilitate small-scale PCC/CC behaviors, or to conduct similar assessments in their own QI projects. Based on our analysis, we recommend health systems seeking to improve PCC/CC at any level or scale to evaluate how IT infrastructure affects provider-provider and provider-patient communication, and the extent to which institutional prioritization of PCC/CC is manifest and held accountable in performance feedback, incentivization, and values shared among departments and settings. Ideally, this evaluation work should be performed and/or supported by cross-department organizing bodies specifically devoted to PCC/CC implementation work.

Objective: To describe trends in the pediatric mental health care continuum and identify potential gaps in care coordination. Methods: We used electronic medical record data from October 2016 to September 2019 to characterize the prevalence of mental health issues in the pediatric population at a large American health system. This was a single institution case study. From the electronic medical record data, primary mental health discharge and readmission diagnoses were identified using International Classification of Diseases (ICD-9-CM, ICD-10-CM) codes. The electronic medical record was queried for mental health-specific diagnoses as defined by International Classification of Diseases classification, analysis of which was facilitated by the fact that only 176 mental health codes were billed for. Additionally, prevalence of care navigation encounters was assessed through electronic medical record query, as care navigation encounters are specifically coded. These encounter data was then segmented by care delivery setting. Results: Major depressive disorder and other mood disorders comprised 49.6% and 89.4% of diagnoses in the emergency department and inpatient settings respectively compared to 9.0% of ambulatory care diagnoses and were among top reasons for readmission. Additionally, only 1% of all ambulatory care encounters had a care navigation component, whereas 86% of care navigation encounters were for mental health-associated reasons. Conclusions: Major depressive disorder and other mood disorders were more common diagnoses in the emergency department and inpatient settings, which could signal gaps in care coordination. Bridging potential gaps in care coordination could reduce emergency department and inpatient utilization through increasing ambulatory care navigation resources, improving training, and restructuring financial incentives to facilitate ambulatory care diagnosis and management of major depressive disorder and mood disorders. Furthermore, health systems can use our descriptive analytic approach to serve as a reasonable measure of the current state of pediatric mental health care in their own patient population.

Introduction Out-of-hospital cardiac arrest (OHCA) is a common, life-threatening event encountered routinely by first responders, including police, fire and emergency medical services (EMS). Current literature suggests that there is significant regional variation in outcomes, some of which may be related to modifiable factors. Yet, there is a persistent knowledge gap regarding strategies to guide quality improvement efforts in OHCA care and, by extension, survival. The Enhancing Prehospital Outcomes for Cardiac Arrest (EPOC) study aims to fill these gaps and to improve outcomes.Methods and analysis This mixed-methods study includes three aims. In aim I, we will define variation in OHCA survival to the emergency department (ED) among EMS agencies that participate in the Michigan Cardiac Arrest Registry to Enhance Survival (CARES) in order to sample EMS agencies with high-survival and low-survival outcomes. In aim II, we will conduct site visits to emergency medical systems—including 911/dispatch, police, non-transport fire, and EMS agencies—in approximately eight high-survival and low-survival communities identified in aim I. At each site, key informant interviews and a multidisciplinary focus group will identify themes associated with high OHCA survival. Transcripts will be coded using a structured codebook and analysed through thematic analysis. Results from aims I and II will inform the development of a survey instrument in aim III that will be administered to all EMS agencies in Michigan. This survey will test the generalisability of factors associated with increased OHCA survival in the qualitative work to ultimately build an EPOC Toolkit which will be distributed to a broad range of stakeholders as a practical ‘how-to’ guide to improve outcomes.Ethics and dissemination The EPOC study was deemed exempt by the University of Michigan Institutional Review Board. Findings will be compiled in an ‘EPOC Toolkit’ and disseminated in the USA through partnerships including, but not limited to, policymakers, EMS leadership and health departments.

Background: Community-engaged research engages the community in a collaborative manner to improve the local setting and has been increasingly applied to health services research. These complex studies require collaboration and team building among clinical experts, methodologists, and community stakeholders, yet few examples of this process have been published. Aim: Through a study of community emergency medical services, our aim was to understand team building among content experts and methodologists to advance the framework for adaptive community-engaged research. Methods: We collected process field notes and transcripts from the project kick-off meetings and analyzed the data using an immersion/crystallization process, which is an exploratory qualitative analysis characterized by continual review of the data collected. All 25 members of the study’s research team, who are both local to Michigan and reside out-of-state, were invited to attend. Results: We describe the process of the kick-off event for this community-engaged study and report major themes: collaborating throughout each stage of the kick-off meeting, building trusting relationships by challenging each other’s perspectives and sharing expertise, and gaining shared experiences of learning and understanding of study content and goals. Conclusion: Team-building in community engaged health research requires thoughtful effort, and planned kick-off meeting can be a useful strategy to build a shared vision among content experts and methodologists.