Effectiveness of a virtual quality improvement training program to improve reach of weight management programs within a large health system.

OBJECTIVE: To test effectiveness of the LEAP (Learn Engage Act Process) Program on engaging frontline Veteran Health Administration (VHA) medical center teams in continuous quality improvement (QI), a core capability for learning health systems. DATA SOURCES AND STUDY SETTING: Data sources included VHA electronic health record (EHR) data, surveys, and LEAP coaching field notes. STUDY DESIGN: A staggered difference-in-differences study was conducted. Fifty-five facilities participated in LEAP across eight randomly assigned clusters of 6-8 facilities per cluster over 2 years. Non-participating facilities were used as controls. A MOVE! weight management program team completed a Plan-Do-Study-Act cycle of change supported by learning curriculum, coaching, and virtual collaboratives in LEAP facilities. Primary outcome was program reach to Veterans. A mixed-effects model compared pre- versus post-LEAP periods for LEAP versus control facilities. LEAP adherence, satisfaction, and cost to deliver LEAP were evaluated. DATA COLLECTION/EXTRACTION METHODS: Thirty months of facility-level EHR MOVE! enrollment data were included in analyses. LEAP Satisfaction and QI skills were elicited via surveys at baseline and 6-month post-LEAP. PRINCIPAL FINDINGS: Fifty-five facilities were randomly assigned to eight time-period-based clusters to receive LEAP (71% completed LEAP) and 82 non-participating facilities were randomly assigned as controls. Reach in LEAP and control facilities was comparable in the 12-month pre-LEAP period (p = 0.07). Though LEAP facilities experienced slower decline in reach in the 12-month post-LEAP period compared with controls (p < 0.001), this is likely due to unexplained fluctuations in controls. For LEAP facilities, satisfaction was high (all mean ratings >4 on a 5-point scale), self-reported use of QI methods increased significantly (p-values <0.05) 6 months post-LEAP, and delivery cost was $4024 per facility-based team. CONCLUSION: Control facilities experienced declining reach in the 12-month post-LEAP period, but LEAP facilities did not, plus they reported higher engagement in QI, an essential capability for learning health systems.

Longitudinal Trends in Insurer Participation in Multisector Population Health Activities.

Healthcare organizations increasingly engage in activities to identify and address social determinants of health (SDOH) among their patients to improve health outcomes and reduce costs. While several studies to date have focused on the evolving role of hospitals and physicians in these types of population health activities, much less is known about the role health insurers may play. We used data from the National Longitudinal Survey of Public Health Systems for the period 2006 to 2018 to examine trends in health insurer participation in population health activities and in the multi-sector collaborative networks that support these activities. We also used a difference-in-differences approach to examine the impact of Medicaid expansion on insurer participation in population health networks. Insurer participation increased in our study period both in the delivery of population health activities and in the integration into collaborative networks that support these activities. Insurers were most likely to participate in activities focusing on community health assessment and policy development. Results from our adjusted difference-in-differences models showed variation in association between insurer participation in population health networks and Medicaid expansion (Table 2). Population health networks in expansion states experienced significant increases insurer participation in assessment (4.48 percentage points, P < .05) and policy and planning (7.66 percentage points, P < .05) activities. Encouraging insurance coverage gains through policy mechanisms like Medicaid expansion may not only improve access to healthcare services but can also act as a driver of insurer integration into population health networks.

Technology, data, people, and partnerships in addressing unmet social needs within Medicaid Managed Care.

BACKGROUND: Individuals with unmet social needs experience adverse health outcomes and are subject to greater inequities in health and social outcomes. Given the high prevalence of unmet needs among Medicaid enrollees, many Medicaid managed care organizations (MCOs) are now screening enrollees for unmet social needs and connecting them to community-based organizations (CBOs) with knowledge and resources to address identified needs. The use of screening and referral technology and data sharing are often considered key components in programs integrating health and social services. Despite this emphasis on technology and data collection, research suggests substantial barriers exist in operationalizing effective systems. METHODS: We used qualitative methods to examine cross-sector perspectives on the use of data and technology to facilitate MCO and CBO partnerships in Kentucky, a state with high Medicaid enrollment, to address enrollee social needs. We recruited participants through targeted sampling, and conducted 46 in-depth interviews with 26 representatives from all six Kentucky MCOs and 20 CBO leaders. Qualitative descriptive analysis, an inductive approach, was used to identify salient themes. RESULTS: We found that MCOs and CBOs have differing levels of need for data, varying incentives for collecting and sharing data, and differing valuations of what data can or should do. Four themes emerged from interviewees' descriptions of how they use data, including 1) to screen for patient needs, 2) to case manage, 3) to evaluate the effectiveness of programs, and 4) to partner with each other. Underlying these data use themes were areas of alignment between MCOs/CBOs, areas of incongruence, and areas of tension (both practical and ideological). The inability to interface with community partners for data privacy and ownership concerns contributes to division. Our findings suggest a disconnect between MCOs and CBOs regarding terms of their technology interfacing despite their shared mission of meeting the unmet social needs of enrollees. CONCLUSIONS: While data and technology can be used to identify enrollee needs and determine the most critical need, it is not sufficient in resolving challenges. People and relationships across sectors are vital in connecting enrollees with the community resources to resolve unmet needs.

Hospital outpatient department billing is a poor indicator of primary care practice integration with hospital systems.

OBJECTIVE: To test the reliability of Medicare claims in measuring vertical integration. We assess the accuracy of a commonly used measure of integration, primary care physician (PCP) practices billing Medicare as a hospital outpatient department (HOPD) in claims. DATA SOURCES AND STUDY SETTING: Medicare fee-for-service claims, IQVIA, and CPC+ practice surveys for this study. STUDY DESIGN: We compare measures of integration from Medicare claims to self-reported indicators of integration from IQVIA and a survey of CPC+ participating practice sites. DATA COLLECTION/EXTRACTION METHODS: We measure integration by using site-of-service billing in the 100% sample of Medicare Carrier claims from 2017-2020. In the IQVIA SK&A (2017-2018), OneKey (2019-2020), and practice survey data (2017-2019), we use self-reported responses to measure integration. PRINCIPAL FINDINGS: We find that currently most PCP practices sites that report themselves as being integrated with a health system do not bill as an HOPD. In 2017, 11% of CPC+ practices were identified as being vertically integrated in claims, while the equivalent numbers in SK&A and surveys were 52% and 54% integration, respectively. A t-test found that both datasets significantly differed from claims (Survey: 41.3%-45.1%; SK&A: 45.3%-51.1%); this gap persists in 2018-2019. CONCLUSION: Measuring physician-hospital vertical integration accurately is integral to determining consolidation. The overwhelming majority of PCP practice sites not billing as an HOPD may reflect Medicare regulatory changes that have reduced the financial incentives for doing so. These findings have implications for researchers that study the growth in PCP-hospital integration in health care markets.

Participation of Veterans Affairs Medical Centers in veteran-centric community-based service navigation networks: A mixed methods study.

OBJECTIVE: To understand the determinants and benefits of cross-sector partnerships between Veterans Affairs Medical Centers (VAMCs) and geographically affiliated AmericaServes Network coordination centers that address Veteran health-related social needs. DATA SOURCES AND SETTING: Semi-structured interviews were conducted with AmericaServes and VAMC staff across seven regional networks. We matched administrative data to calculate the percentage of AmericaServes referrals that were successfully resolved (i.e., requested support was provided) in each network overall and stratified by whether clients were also VAMC patients. STUDY DESIGN: Convergent parallel mixed-methods study guided by Himmelman's Developmental Continuum of Change Strategies (DCCS) for interorganizational collaboration. DATA COLLECTION: Fourteen AmericaServes staff and 17 VAMC staff across seven networks were recruited using snowball sampling and interviewed between October 2021 and April 2022. Rapid qualitative analysis methods were used to characterize the extent and determinants of VAMC participation in networks. PRINCIPAL FINDINGS: On the DCCS continuum of participation, three networks were classified as networking, two as coordinating, one as cooperating, and one as collaborating. Barriers to moving from networking to collaborating included bureaucratic resistance to change, VAMC leadership buy-in, and not having VAMCs staff use the shared technology platform. Facilitators included ongoing communication, a shared mission of serving Veterans, and having designated points-of-contact between organizations. The percentage of referrals that were successfully resolved was lowest in networks engaged in networking (65.3%) and highest in cooperating (85.6%) and collaborating (83.1%) networks. For coordinating, cooperating, and collaborating networks, successfully resolved referrals were more likely among Veterans who were also VAMC patients than among Veterans served only by AmericaServes. CONCLUSIONS: VAMCs participate in AmericaServes Networks at varying levels. When partnerships are more advanced, successful resolution of referrals is more likely, especially among Veterans who are dually served by both organizations. Although challenges to establishing partnerships exist, this study highlights effective strategies to overcome them.

A case study on variations in network structure and cross-sector alignment in two local systems serving pregnant and parenting women in recovery.

OBJECTIVE: To describe network structure and alignment across organizations in healthcare, public health, and social services sectors that serve pregnant and parenting women with substance use disorder (SUD) in an urban and a rural community. DATA SOURCES AND STUDY SETTINGS: Two community networks, one urban and one rural with each including a residential substance use treatment program, in Kentucky during 2021. STUDY DESIGN: Social network analysis measured system collaboration and cross-sector alignment between healthcare, public health, and social services organizations, applying the Framework for Aligning Sectors. To understand the alignment and structure of each network, we measured network density overall and between sectors, network centralization, and each organization's degree centrality and effective size. DATA COLLECTION/EXTRACTION METHODS: Computer-assisted telephone interviews were conducted to document alignment around shared purpose, data, financing, and governance. PRINCIPAL FINDINGS: On average, overall and cross-sector network densities in both communities were similar. However, alignment was highest for data sharing and financing in the urban community and for shared purpose and governance in the rural community. Cross-sector partnerships involving healthcare organizations were more prevalent in the rural county (44% vs. 38% for healthcare/public health, 44% vs. 29% for healthcare/social services), but more prevalent for those involving public health/social services organizations in the urban county (42% vs. 24%). A single healthcare organization had the highest degree centrality (Mdn [IQR] = 26 [26-9.5]) and effective size (Mdn [IQR] = 15.9 [20.6-8.7]) within the rural county. Social services organizations held more central positions in the urban county (degree centrality Mdn [IQR] = 13 [14.8-9.5]; effective size Mdn [IQR] = 10.4 [11.4-7.9]). CONCLUSIONS: Cross-sector alignment may strengthen local capacity for comprehensive SUD care for pregnant and parenting women. Healthcare organizations are key players in cross-sector partnerships in the rural community, where one healthcare facility holds the central brokerage role. In contrast, public health agencies are key to cross-sector collaboration with social services in the urban community.

Specialist use among privately insured children with disabilities.

OBJECTIVE: To investigate primary care practice ownership and specialist-use patterns for commercially insured children with disabilities. DATA SOURCES AND STUDY SETTING: A national commercial claims database and the Health Systems and Provider Database from 2012 to 2016 are the data sources for this study. STUDY DESIGN: This cross-sectional, descriptive study examines: (1) the most visited type of pediatric primary care physician and practice (independent or system-owned); (2) pediatric and non-pediatric specialist-use patterns; and (3) how practice ownership relates to specialist-use patterns. DATA COLLECTION/EXTRACTION METHODS: This study identifies 133,749 person-years of commercially insured children with disabilities aged 0-18 years with at least 24 months of continuous insurance coverage by linking a national commercial claims data set with the Health Systems and Provider Database and applying the validated Children with Disabilities Algorithm. PRINCIPAL FINDINGS: Three-quarters (75.9%) of children with disabilities received their pediatric primary care in independent practices. Nearly two thirds (59.6%) used at least one specialist with 45.1% using nonpediatric specialists, 28.8% using pediatric ones, and 17.0% using both. Specialist-use patterns varied by both child age and specialist type. Children with disabilities in independent practices were as likely to see a specialist as those in system-owned ones: 57.1% (95% confidence interval [95% CI] 56.7%-57.4%) versus 57.3% (95% CI 56.6%-58.0%), respectively (p = 0.635). The percent using two or more types of specialists was 46.1% (95% CI 45.4%-46.7%) in independent practices, comparable to that in systems 47.1% (95% CI 46.2%-48.0%) (p = 0.054). However, the mean number of specialist visits was significantly lower in independent practices than in systems-4.0 (95% CI 3.9%-4.0%) versus 4.4 (95% CI 4.3%-4.6%) respectively-reaching statistical significance with p < 0.0001. CONCLUSIONS: Recognizing how privately insured children with disabilities use pediatric primary care from pediatric and nonpediatric primary care specialists through both independent and system-owned practices is important for improving care quality and value.

Hub and spoke framework for study of surgical centralization within United States health systems.

BACKGROUND: Hospital consolidation into health systems has mixed effects on surgical quality, potentially related to degree of surgical centralization at high-volume (hub) sites. We developed a novel measure of centralization and evaluated a hub and spoke framework. METHODS: Surgical centralization within health systems was measured using hospital surgical volumes (American Hospital Association) and health system data (Agency for Healthcare Research and Quality). Hub and spoke hospitals were compared using mixed effects logistic regression and system characteristics associated with surgical centralization were identified using a linear model. RESULTS: Within 382 health systems containing 3022 hospitals, system hubs perform 63% of cases (IQR 40-84%). Hubs are larger, in metropolitan and urban areas, and more often academically affiliated. Degree of surgical centralization varies ten-fold. Larger, multistate, and investor-owned systems are less centralized. Adjusting for these factors, there is less centralization among teaching systems (p â€‹< â€‹0.001). CONCLUSIONS: A hub-spoke framework applies to most health systems but centralization varies significantly. Future studies of health system surgical care should assess the contributions of surgical centralization and teaching status on differential quality.

Impact of state Medicaid expansion on cross-sector health and social service networks: Evidence from a longitudinal cohort study.

OBJECTIVE: To examine the impact of state Medicaid expansion on the delivery of population health activities in cross-sector health and social services networks. Community networks are multisector, interorganizational networks that provide services ranging from the direct provision of individual social services to the implementation of population-level initiatives addressing community outcomes. DATA SOURCES: We used data measuring the composition of cross-sector population health networks 2006-2018 National Longitudinal Survey of Public Health Systems (NALSYS) linked with the Area Health Resource File. STUDY DESIGN: A difference-in-differences approach was used to examine the impact of expansion on organization engagement in population health activities and network structure. DATA COLLECTION/EXTRACTION METHODS: Stratified random sampling of local public health jurisdictions in the United States. We restricted our data to jurisdictions serving populations of 100,000 or more and states that had NALSYS observations across all time periods, resulting in a final sample size of 667. PRINCIPAL FINDINGS: Results from our adjusted difference-in-differences estimates indicated that Medicaid expansion was associated with a 2.3 percentage point increase in the density of population health networks (p < 0.10). Communities in states that expanded Medicaid experienced significant increases in the participation of local public health, local government, hospital, nonprofit, insurer, and K-12 schools. Of the organizations with significant increases in expansion communities, nonprofits (7.7 percentage points, p < 0.01), local public health agencies (6.5 percentage points, p < 0.01), hospitals (5.8 percentage points, p < 0.01), and local government agencies (6.0 percentage points, p < 0.05) had the largest gains. CONCLUSIONS: Our study found increases in cross-sector participation in population health networks in states that expanded Medicaid compared with nonexpansion states, suggesting that additional coverage gains are associated with positive changes in population health network structure.

Overcoming Barriers to the Implementation of Integrated Musculoskeletal Pain Management Programs: A Multi-Stakeholder Qualitative Study.

Integrated pain management (IPM) programs can help to reduce the substantial population health burden of musculoskeletal pain, but are poorly implemented. Lessons learned from existing programs can inform efforts to expand IPM implementation. This qualitative study describes how health care systems, payers, providers, health policy researchers, and other stakeholders are overcoming barriers to developing and sustaining IPM programs in real-world settings. Primary data were collected February 2020 through September 2021 from a multi-sector expert panel of 25 stakeholders, 53 expert interviews representing 30 distinct IPM programs across the United States, and 4 original case studies of exemplar IPM programs. We use a consensual team-based approach to systematically analyze qualitative findings. We identified 4 major themes around challenges and potential solutions for implementing IPM programs: navigating coverage, payment, and reimbursement; enacting organizational change; making a business case to stakeholders; and overcoming regulatory hurdles. Strategies to address payment challenges included use of group visits, linked visits between billable and nonbillable providers, and development of value-based payment models. Organizational change strategies included engagement of clinical and administrative champions and co-location of services. Business case strategies involved demonstrating the ability to initially break even and potential to reduce downstream costs, while improving nonfinancial outcomes like patient satisfaction and provider burnout. Regulatory hurdles were overcome with innovative credentialing methods by leveraging available waivers and managed care contracting to expand access to IPM services. Lessons from existing programs provide direction on to grow and support such IPM delivery models across a variety of settings. PERSPECTIVE: Integrated pain management (IPM) programs face numerous implementation challenges related to payment, organizational change, care coordination, and regulatory requirements. Drawing on real-world experiences of existing programs and from diverse IPM stakeholders, we outline actionable strategies that health care systems, providers, and payers can use to expand implementation of these programs.

Organization of pulmonary hypertension care in non-expert care settings: Lessons learned from a multi-site study.

OBJECTIVE: To examine how select Veterans Health Administration (VA) sites organized care for patients with pulmonary hypertension (PH), with a focus on describing existing practices and identifying unmet needs within the sites. DATA SOURCES AND STUDY SETTING: Semi-structured interviews across seven diverse VA sites. STUDY DESIGN: Qualitative multiple-site study. DATA COLLECTION/EXTRACTION METHODS: We interviewed 54 key informants including pulmonologists, cardiologists, primary care providers, advanced care practitioners, pharmacists, and clinical leaders to assess the structures and processes of PH care delivery. We analyzed transcripts using directed content analysis and constructed site profiles for each site, comparing profiles to existing guidelines for PH expert centers. PRINCIPAL FINDINGS: Sites varied considerably in how they organized PH care, with wide variation in the availability of structures and processes recommended for expert centers, including availability of PH expertise and PH-specific resources, multidisciplinary approach to care, establishment of clear referral pathways, and presence of PH education. Further, participants identified three areas of unmet need not directly addressed within current guidelines, including better integration of pharmacists into multidisciplinary teams, early and routine involvement of palliative care, and improved care coordination efforts. CONCLUSIONS: The rising prevalence of PH and evolution of treatments for common PH subgroups underscore the need to standardize PH care delivery in non-expert care settings to improve care quality and patient outcomes. The insight gained from this study may inform the development of guidance appropriate for care settings outside of expert centers.

Impact of a selective narrow network with comprehensive patient navigation on access, utilization, expenditures, and enrollee experiences.

OBJECTIVE: To examine the effect of enrollee switching from a broad-network accountable care organization (ACO) health maintenance organization (HMO) to a "high performance" ACO-HMO with a selective narrow network and comprehensive patient navigation system on access, utilization, expenditures, and enrollee experiences. DATA SOURCES: Secondary administrative data were obtained for 2016-2020, and primary interview and survey data in 2021. STUDY DESIGN: Fixed-effects instrumental variable analyses of administrative data and regression analyses of survey data. Outcomes included access, utilization, expenditures, and enrollee experience. Background information was gathered via interviews. DATA COLLECTION/EXTRACTION METHODS: We obtained medical expenditure/enrollment and access data on continuously enrolled members in a broad-network ACO-HMO (n = 24,555), a subset of those who switched to a high-performance ACO-HMO in 2018 (n = 7664); interviews of organizational leaders (n = 13); and an enrollee survey (n = 512). PRINCIPAL FINDINGS: Health care effectiveness data and information Set (HEDIS) access measures were not different across plans. However, annual utilization dropped by 15.5 percentage points (95% CI: 18.1, 12.9) more in the high-performance ACO-HMO, with relative annual expenditures declining by $1251 (95% CI: $1461, $1042) per person per year. High-performance ACO-HMO enrollees were 10.1 percentage points (95% CI 0.001, 0.201) more likely to access primary care usually or always as soon as needed and 11.2 percentage points (95% CI 0.007, 0.217) more likely to access specialty care usually or always as soon as needed. Plan satisfaction was 7.1 percentage points (95% CI: -0.001, 0.138) higher in the high-performance ACO-HMO. Interviewees noted the comprehensive patient navigation system was designed to ensure patients remained in the narrow network to receive care. CONCLUSIONS: ACO and HMO contracts with selective narrow networks supported by comprehensive patient navigation can reduce expenditures and improve specialty access and patient satisfaction compared to broad-network plans that lack these features. Payers should consider implementing narrow networks with comprehensive support systems.

Growing inequities in mental health crisis services offered to indigent patients in Puerto Rico versus the US states before and after Hurricanes Maria and Irma.

OBJECTIVE: To assess changes in the availability of mental health crisis services in Puerto Rico relative to US states before and after Hurricanes Maria and Irma. DATA SOURCES/STUDY SETTING: National Mental Health Services Surveys conducted in 2016 and 2020. STUDY DESIGN: Repeated cross-sectional design. The independent variable was mental health facility location in Puerto Rico or a US state. Dependent variables were the availability of three mental health crisis services (psychiatric emergency walk-in services, suicide prevention services, and crisis intervention team services). DATA COLLECTION/EXTRACTION METHODS: The proportion and per 100,000 population rate of facilities offering crisis services were calculated. PRINCIPAL FINDINGS: The availability of crisis services at mental health facilities in Puerto Rico remained stable between 2016 and 2020. These services were offered less at indigent care facilities in Puerto Rico than US states (e.g., 38.2% vs. 49.5% for suicide prevention, p = 0.06) and the magnitude of difference increased following Hurricane Maria. CONCLUSIONS: There are disparities between Puerto Rico and US states in the availability of mental health crisis services for indigent patients.

Effects of an electronic health record-based mobility assessment and automated referral for inpatient physical therapy on patient outcomes: A quasi-experimental study.

OBJECTIVE: To assess the effectiveness of a hospital physical therapy (PT) referral triggered by scores on a mobility assessment embedded in the electronic health record (EHR) and completed by nursing staff on hospital admission. DATA SOURCES: EHR and billing data from 12 acute care hospitals in a western Pennsylvania health system (January 2017-February 2018) and 11 acute care hospitals in a northeastern Ohio health system (August 2019-July 2021). STUDY DESIGN: We utilized a regression discontinuity design to compare patients admitted to PA hospitals with stroke who reached the mobility score threshold for an EHR-PT referral (treatment) to those who did not (control). Outcomes were hospital length of stay (LOS) and 30-day readmission or mortality. Control variables included demographics, insurance, income, and comorbidities. Hospital systems with EHR-PT referrals were also compared to those without (OH hospitals as alternative control). Subgroup analyses based on age were also conducted. DATA EXTRACTION: We identified adult patients with a primary or secondary diagnosis of stroke and mobility assessments completed by nursing (n = 4859 in PA hospitals, n = 1749 in OH hospitals) who completed their inpatient stay. PRINCIPAL FINDINGS: In the PA hospitals, patients with EHR-PT referrals had an 11.4 percentage-point decrease in their 30-day readmission or mortality rates (95% CI -0.57, -0.01) relative to the control. This effect was not observed in the OH hospitals for 30-day readmission (ß = 0.01; 95% CI -0.25, 0.26). Adults over 60 years old with EHR-PT referrals in PA had a 26.2 percentage-point (95% CI -0.88, -0.19) decreased risk of readmission or mortality compared to those without. Unclear relationships exist between EHR-PT referrals and hospital LOS in PA. CONCLUSIONS: Health systems should consider methodologies to facilitate early acute care hospital PT referrals informed by mobility assessments.

Association between non-profit hospital community benefit spending and health outcomes.

OBJECTIVE: To determine if greater non-profit hospital spending for community benefits is associated with better health outcomes in the county where they are located. DATA SOURCES AND STUDY SETTING: Community benefit data from IRS Form 990/Schedule H was linked to health outcome data from Area Health Resource Files, Map the Meal Gap, and Medicare claims from the Center for Medicare and Medicaid Services at the county level. Counties with at least one non-profit hospital in the United States from 2015 to 2019 (N = 5469 across the 5 years) were included. STUDY DESIGN: We ran multiple regressions on community benefit expenditures linked with the number of health professionals, food insecurity, and adherence to diabetes and hypertension medication for each county. DATA COLLECTION: The three outcomes were chosen based on prior studies of community benefit and a recent survey sent to 12 health care executives across four regions of the U.S. Data on community benefit expenditures and health outcomes were aggregated at the county level. PRINCIPAL FINDINGS: Average hospital community benefit spending in 2019 was $63.6 million per county ($255 per capita). Multivariable regression results did not demonstrate significant associations of total community benefit spending with food insecurity or medication adherence for diabetes. Statistically significant associations with the number of health professionals per 1000 (coefficient, 12.10; SE, 0.32; p < 0.001) and medication adherence for hypertension (marginal effect, 0.27; SE, 0.09; p = 0.003) were identified, but both would require very large increases in community benefit spending to meaningfully improve outcomes. CONCLUSIONS: Despite varying levels of non-profit hospital community benefit investment across counties, higher community benefit expenditures are not associated with an improvement in the selected health outcomes at the county level. Hospitals can use this information to reassess community benefit strategies, while federal, state, and local governments can use these findings to redefine the measures of community benefit they use to monitor and grant tax exemption.

Assessing the Added Value of Vital Signs Extracted from Electronic Health Records in Healthcare Risk Adjustment Models.

Purpose: Patient vital signs are related to specific health risks and outcomes but are underutilized in the prediction of health-care utilization and cost. To measure the added value of electronic health record (EHR) extracted Body Mass Index (BMI) and blood pressure (BP) values in improving healthcare risk and utilization predictions. Patients and Methods: A sample of 12,820 adult outpatients from the Johns Hopkins Health System (JHHS) were identified between 2016 and 2017, having high data quality and recorded values for BMI and BP. We evaluated the added value of BMI and BP in predicting health-care utilization and cost through a retrospective cohort design. BMI, mean arterial pressure (MAP), systolic and diastolic BPs were summarized as annual aggregated values. Concurrent annual BMI and MAP changes were quantified as the difference between maximum and minimum recorded values. Model performance estimates consisted of repeated 10-fold cross validation, compared to base model point estimates for demographic and diagnostic, coded events: (1) patient age and sex, (2) age, sex, and the Charlson weighted index, (3) age, sex and the Johns Hopkins ACG system's DxPM risk score. Results: Both categorical BMI and BP were progressively indicative of disease comorbidity, but not uniformly related to health-care utilization or cost. Annual change in BMI and MAP improved predictions for most concurrent year outcomes when compared to base models. Conclusion: When a healthcare system lacks relevant diagnostic or risk assessment information for a patient, vital signs may be useful for a simple estimation of disease risk, cost and utilization.

Rural Medicare beneficiaries are increasingly likely to be admitted to urban hospitals.

OBJECTIVE: To determine whether rural Medicare FFS beneficiaries are more likely to be admitted to an urban hospital in 2018 than in 2010. DATA SOURCES: We combined data from the 2010 to 2018 Hospital Service Area File (HSAF) and the 2010-2017 American Hospital Association (AHA) survey. STUDY DESIGN: We conducted a fixed-effects negative-binomial regression to determine whether urban hospital admissions from rural ZIP codes were increasing over time. We also conducted an exploratory geographically weighted regression. DATA COLLECTION: We transformed the HSAF data into a ZIP code-level file with all rural ZIP codes. We defined rural as having a Rural-Urban Commuting Area (RUCA) code ≥4. A hospital's system affiliation status was incorporated from the AHA survey. PRINCIPAL FINDINGS: Controlling for distance to the nearest hospitals, an increase of 1 year was associated with a 2.0% increase (p < 0.001) in the number of admissions to urban hospitals from each rural ZIP code. New system affiliation of the nearest rural hospital was associated with an increase of 1.7% (p < 0.001). CONCLUSIONS: Even when controlling for distance to the nearest rural hospital (which reflects hospital closures), rural patients were increasingly likely to be admitted to an urban hospital.

From patient outcomes to system change: Evaluating the impact of VHA's implementation of the Whole Health System of Care.

OBJECTIVE: To describe how a partnered evaluation of the Whole Health (WH) system of care-comprised of the WH pathway, clinical care, and well-being programs-produced patient outcomes findings, which informed Veterans Health Administration (VA) policy and system change. DATA SOURCES: Electronic health records (EHR)-based cohort of 1,368,413 patients and a longitudinal survey of Veterans receiving care at 18 WH pilot medical centers. STUDY DESIGN: In partnership with VA operations, we focused the evaluation on the impact of WH services utilization on Veterans' (1) use of opioids and (2) care experiences, care engagement, and well-being. Outcomes were compared between Veterans who did and did not use WH services identified from the EHR. DATA COLLECTION: Pharmacy records and WH service data were obtained from the VA EHR, including WH coaching, peer-led groups, personal health planning, and complementary, integrative health therapies. We surveyed veterans at baseline and 6 months to measure patient-reported outcomes. PRINCIPAL FINDINGS: Opioid use decreased 23% (31.5-6.5) to 38% (60.3-14.4) among WH users depending on level of WH use compared to a secular 11% (12.0-9.9) decrease among Veterans using Conventional Care. Compared to Conventional Care users, WH users reported greater improvements in perceptions of care (SMD = 0.138), engagement in health care (SMD = 0.118) and self-care (SMD = 0.1), life meaning and purpose (SMD = 0.152), pain (SMD = 0.025), and perceived stress (SMD = 0.191). CONCLUSIONS: Evidence developed through this partnership yielded key VA policy changes to increase Veteran access to WH services. Findings formed the foundation of a congressionally mandated report in response to the Comprehensive Addiction and Recovery Act, highlighting the value of WH and complementary, integrative health and well-being programs for Veterans with pain. Findings subsequently informed issuance of an Executive Decision Memo mandating the integration of WH into mental health and primary care across VA, now one lane of modernization for VA.

Integrating the complexity of healthcare improvement with implementation science: a longitudinal qualitative case study.

BACKGROUND: Implementation science seeks to enable change, underpinned by theories and frameworks such as the Consolidated Framework for Implementation Research (CFIR). Yet academia and frontline healthcare improvement remain largely siloed, with limited integration of implementation science methods into frontline improvement where the drivers include pragmatic, rapid change. Using the CIFR lens, we aimed to explore how pragmatic and complex healthcare improvement and implementation science can be integrated. METHODS: Our research involved the investigation of a case study that was undertaking the implementation of an improvement intervention at a large public health service. Our research involved qualitative data collection methods of semi-structured interviews and non-participant observations of the implementation team delivering the intervention. Thematic analysis identified key themes from the qualitative data. We examined our themes through the lens of CFIR to gain in-depth understanding of how the CFIR components operated in a 'real-world' context. RESULTS: The key themes emerging from our research outlined that leadership, context and process are the key components that dominate and affect the implementation process. Leadership which cultivates connections with front line clinicians, fosters engagement and trust. Navigating context was facilitated by 'bottom-up' governance. Multi-disciplinary and cross-sector capability were key processes that supported pragmatic and agile responses in a changing complex environment. Process reflected the theoretically-informed, and iterative implementation approach. Mapping CFIR domains and constructs, with these themes demonstrated close alignment with the CFIR. The findings bring further depth to CFIR. Our research demonstrates that leadership which has a focus on patient need as a key motivator to engage clinicians, which applies and ensures iterative processes which leverage contextual factors can achieve successful, sustained implementation and healthcare improvement outcomes. CONCLUSIONS: Our longitudinal study highlights insights that strengthen alignment between implementation science and pragmatic frontline healthcare improvement. We identify opportunities to enhance the relevance of CFIR in the 'real-world' setting through the interconnected nature of our themes. Our study demonstrates actionable knowledge to enhance the integration of implementation science in healthcare improvement.

The Utilization of an Electronic Consultation Service During the Coronavirus Disease 2019 Pandemic.

Objective: The coronavirus disease 2019 (COVID-19) pandemic forced many clinicians to rapidly adopt changes in their practice. In this study, we compared patterns of utilization of Ontario eConsult before and after the onset of the COVID-19 pandemic, to assess COVID 19's impact on how eConsult is used. Materials and Methods: We conducted a longitudinal analysis of registration and utilization data for Ontario eConsult. All primary care providers (PCPs) and specialists who joined the service between March 2019 and November 2020, and all eConsult cases closed during the same period were included. The data were divided into two timeframes for comparison: prepandemic (March 2019-February 2020) and pandemic (March 2020-November 2020). Results: In total, 5,925 PCPs joined during the study period, more than doubling total enrollment to 11,397. The average monthly number of eConsults increased from 2,405 (standard deviation [SD] = 260) prepandemic to 3,906 (SD = 420) pandemic. Case volume jumped to 24.3% in the first month of the pandemic, and increased by 71% during the COVID-19 pandemic timeframe. The median response time was similar in both timeframes (prepandemic: 1.0 days; pandemic: 0.9 days). The proportion of cases resulting in new/additional information (prepandemic: 55%, pandemic: 57%) or avoidance of a contemplated referral (prepandemic: 52%, pandemic: 51%) remained consistent between timeframes. Conclusions: Registration to and usage of eConsult increased during the pandemic. Metrics of the service's impact, including response time, percentage of cases resulting in new or additional information, and avoidance of originally contemplated referrals were all consistent between the prepandemic and COVID-19 pandemic timeframes, suggesting scalability.