Understanding How Contingency Staffing Programs Can Support Mental Health Services in the Veterans Health Administration.

Introduction: Beginning in 2019, the Department of Veterans Affairs (VA) prioritized improving access to care nationally to deliver virtual care and implemented 18 regionally based Clinical Resource Hubs (CRHs) to meet this priority. This observational study describes the quantity and types of care delivered by CRH Mental Health teams, and the professions of those hired to deliver it. Methods: A retrospective cohort study, based on national VA CRH mental health care utilization data and CRH staffing data for CRH's first 3 years, was conducted. Results: CRH Mental Health teams primarily used Telemental Health (TMH) to provide care (98.1% of all CRH MH encounters). The most common disorders treated included depression, post-traumatic stress disorder, and anxiety disorders. The amount of care delivered overtime steadily increased as did the racial and ethnic diversity of Veterans served. Psychologists accounted for the largest share of CRH staffing, followed by psychiatrists. Conclusions: CRH TMH delivered from a regional hub appears to be a feasible and acceptable visit modality, based on the continuously increasing CRH TMH visit rates. Our results showed that CRH TMH was predominantly used to address common mental health diagnoses, rather than serious mental illnesses. Traditionally marginalized patient populations increased over the 3-year window, suggesting that CRH TMH resources were accessible to many of these patients. Future research should assess barriers and facilitators for accessing CRH TMH, especially for difficult-to-service patient populations, and should consider whether similar results to ours occur when regional TMH is delivered to non-VA patient populations.

Associations Between Primary Care Providers and Staff-Reported Access Management Challenges and Patient Perceptions of Access.

BACKGROUND/OBJECTIVE: Optimizing patients' access to primary care is critically important but challenging. In a national survey, we asked primary care providers and staff to rate specific care processes as access management challenges and assessed whether clinics with more of these challenges had worse access outcomes. METHODS: Study design: Cross sectional. National Primary Care Personnel Survey (NPCPS) (2018) participants included 6210 primary care providers (PCPs) and staff in 813 clinics (19% response rate) and 158,645 of their patients. We linked PCP and staff ratings of access management challenges to veterans' perceived access from 2018-2019 Survey of Healthcare Experiences of Patients-Patient Centered Medical Home (SHEP-PCMH) surveys (35.6% response rate). MAIN MEASURES: The NPCPS queried PCPs and staff about access management challenges. The mean overall access challenge score was 28.6, SD 6.0. The SHEP-PCMH access composite asked how often veterans reported always obtaining urgent appointments same/next day; routine appointments when desired and having medical questions answered during office hours. ANALYTIC APPROACH: We aggregated PCP and staff responses to clinic level, and use multi-level, multivariate logistic regressions to assess associations between clinic-level access management challenges and patient perceptions of access. We controlled for veteran-, facility-, and area-level characteristics. KEY RESULTS: Veterans at clinics with more access management challenges (> 75th percentile) had a lower likelihood of reporting always receiving timely urgent care appointments (AOR: .86, 95% CI: .78-.95); always receiving routine appointments (AOR: .74, 95% CI: .67-.82); and always reporting same- or next-day answers to telephone questions (AOR: .79, 95% CI: .70-.90) compared to veterans receiving care at clinics with fewer (< 25th percentile) challenges. DISCUSSION/CONCLUSION: Findings show a strong relationship between higher levels of access management challenges and worse patient perceptions of access. Addressing access management challenges, particularly those associated with call center communication, may be an actionable path for improved patient experience.

Learning from national implementation of the Veterans Affairs Clinical Resource Hub (CRH) program for improving access to care: protocol for a six year evaluation.

BACKGROUND: The Veterans Affairs (VA) Clinical Resource Hub (CRH) program aims to improve patient access to care by implementing time-limited, regionally based primary or mental health staffing support to cover local staffing vacancies. VA's Office of Primary Care (OPC) designed CRH to support more than 1000 geographically disparate VA outpatient sites, many of which are in rural areas, by providing virtual contingency clinical staffing for sites experiencing primary care and mental health staffing deficits. The subsequently funded CRH evaluation, carried out by the VA Primary Care Analytics Team (PCAT), partnered with CRH program leaders and evaluation stakeholders to develop a protocol for a six-year CRH evaluation. The objectives for developing the CRH evaluation protocol were to prospectively: 1) identify the outcomes CRH aimed to achieve, and the key program elements designed to achieve them; 2) specify evaluation designs and data collection approaches for assessing CRH progress and success; and 3) guide the activities of five geographically dispersed evaluation teams. METHODS: The protocol documents a multi-method CRH program evaluation design with qualitative and quantitative elements. The evaluation's overall goal is to assess CRH's return on investment to the VA and Veterans at six years through synthesis of findings on program effectiveness. The evaluation includes both observational and quasi-experimental elements reflecting impacts at the national, regional, outpatient site, and patient levels. The protocol is based on program evaluation theory, implementation science frameworks, literature on contingency staffing, and iterative review and revision by both research and clinical operations partners. DISCUSSION: Health systems increasingly seek to use data to guide management and decision-making for newly implemented clinical programs and policies. Approaches for planning evaluations to accomplish this goal, however, are not well-established. By publishing the protocol, we aim to increase the validity and usefulness of subsequent evaluation findings. We also aim to provide an example of a program evaluation protocol developed within a learning health systems partnership.

Eight Priorities for Improving Primary Care Access Management in Healthcare Organizations: Results of a Modified Delphi Stakeholder Panel.

OBJECTIVE: To identify priorities for improving healthcare organization management of patient access to primary care based on prior evidence and a stakeholder panel. BACKGROUND: Studies on healthcare access show its importance for ensuring population health. Few studies show how healthcare organizations can improve access. METHODS: We conducted a modified Delphi stakeholder panel anchored by a systematic review. Panelists (N = 20) represented diverse stakeholder groups including patients, providers, policy makers, purchasers, and payers of healthcare services, predominantly from the Veterans Health Administration. A pre-panel survey addressed over 80 aspects of healthcare organization management of access, including defining access management. Panelists discussed survey-based ratings during a 2-day in-person meeting and re-voted afterward. A second panel process focused on each final priority and developed recommendations and suggestions for implementation. RESULTS: The panel achieved consensus on definitions of optimal access and access management on eight urgent and important priorities for guiding access management improvement, and on 1-3 recommendations per priority. Each recommendation is supported by referenced, panel-approved suggestions for implementation. Priorities address two organizational structure targets (interdisciplinary primary care site leadership; clearly identified group practice management structure); four process improvements (patient telephone access management; contingency staffing; nurse management of demand through care coordination; proactive demand management by optimizing provider visit schedules), and two outcomes (quality of patients' experiences of access; provider and staff morale). Recommendations and suggestions for implementation, including literature references, are summarized in a panelist-approved, ready-to-use tool. CONCLUSIONS: A stakeholder panel informed by a pre-panel systematic review identified eight action-oriented priorities for improving access and recommendations for implementing each priority. The resulting tool is suitable for guiding the VA and other integrated healthcare delivery organizations in assessing and initiating improvements in access management, and for supporting continued research.

Sequelae of an Evidence-based Approach to Management for Access to Care in the Veterans Health Administration.

BACKGROUND: Access to health care is a critical concept in the design, delivery, and evaluation of high quality care. Meaningful evaluation of access requires research evidence and the integration of perspectives of patients, providers, and administrators. OBJECTIVE: Because of high-profile access challenges, the Department of Veterans Affairs (VA) invested in research and implemented initiatives to address access management. We describe a 2-year evidence-based approach to improving access in primary care. METHODS: The approach included an Evidence Synthesis Program (ESP) report, a 22-site in-person qualitative evaluation of VA initiatives, and in-person and online stakeholder panel meetings facilitated by the RAND corporation. Subsequent work products were disseminated in a targeted strategy to increase impact on policy and practice. RESULTS: The ESP report summarized existing research evidence in primary care management and an evaluation of ongoing initiatives provided organizational data and novel metrics. The stakeholder panel served as a source of insights and information, as well as a knowledge dissemination vector. Work products included the ESP report, a RAND report, peer-reviewed manuscripts, presentations at key conferences, and training materials for VA Group Practice Managers. Resulting policy and practice implications are discussed. CONCLUSIONS: The commissioning of an evidence report was the beginning of a cascade of work including exploration of unanswered questions, novel research and measurement discoveries, and policy changes and innovation. These results demonstrate what can be achieved in a learning health care system that employs evidence and expertise to address complex issues such as access management.

The Association Between Neighborhood Environment and Mortality: Results from a National Study of Veterans.

BACKGROUND: As the largest integrated US health system, the Veterans Health Administration (VHA) provides unique national data to expand knowledge about the association between neighborhood socioeconomic status (NSES) and health. Although living in areas of lower NSES has been associated with higher mortality, previous studies have been limited to higher-income, less diverse populations than those who receive VHA care. OBJECTIVE: To describe the association between NSES and all-cause mortality in a national sample of veterans enrolled in VHA primary care. DESIGN: One-year observational cohort of veterans who were alive on December 31, 2011. Data on individual veterans (vital status, and clinical and demographic characteristics) were abstracted from the VHA Corporate Data Warehouse. Census tract information was obtained from the US Census Bureau American Community Survey. Logistic regression was used to model the association between NSES deciles and all-cause mortality during 2012, adjusting for individual-level income and demographics, and accounting for spatial autocorrelation. PARTICIPANTS: Veterans who had vital status, demographic, and NSES data, and who were both assigned a primary care physician and alive on December 31, 2011 (n = 4,814,631). MAIN MEASURES: Census tracts were used as proxies for neighborhoods. A summary score based on census tract data characterized NSES. Veteran addresses were geocoded and linked to census tract NSES scores. Census tracts were divided into NSES deciles. KEY RESULTS: In adjusted analysis, veterans living in the lowest-decile NSES tract were 10 % (OR 1.10, 95 % CI 1.07, 1.14) more likely to die than those living in the highest-decile NSES tract. CONCLUSIONS: Lower neighborhood SES is associated with all-cause mortality among veterans after adjusting for individual-level socioeconomic characteristics. NSES should be considered in risk adjustment models for veteran mortality, and may need to be incorporated into strategies aimed at improving veteran health.

Prevalence, Comorbidity, and Prognosis of Mental Health Among US Veterans.

OBJECTIVES: We evaluated the association of mental illnesses with clinical outcomes among US veterans and evaluated the effects of Primary Care-Mental Health Integration (PCMHI). METHODS: A total of 4 461 208 veterans were seen in the Veterans Health Administration's patient-centered medical homes called Patient Aligned Care Teams (PACT) in 2010 and 2011, of whom 1 147 022 had at least 1 diagnosis of depression, posttraumatic stress disorder (PTSD), substance use disorder (SUD), anxiety disorder, or serious mental illness (SMI; i.e., schizophrenia or bipolar disorder). We estimated 1-year risk of emergency department (ED) visits, hospitalizations, and mortality by mental illness category and by PCMHI involvement. RESULTS: A quarter of all PACT patients reported 1 or more mental illnesses. Depression, SMI, and SUD were associated with increased risk of hospitalization or death. PTSD was associated with lower odds of ED visits and mortality. Having 1 or more contact with PCMHI was associated with better outcomes. CONCLUSIONS: Mental illnesses are associated with poor outcomes, but integrating mental health treatment in primary care may be associated with lower risk of those outcomes.

The Primary Care Analytics Team: Integrating research and clinical care within the Veterans Health Administration Office of Primary Care.

By designing and evaluating health system improvements and providing evidence to clinical decision-makers, embedded researchers are a critical part of a Learning Health System (LHS). In this article, we describe the evolution and mission of the Primary Care Analytics Team (PCAT), an integrated research team within the Veterans Health Administration Office of Primary Care. We discuss challenges and strategies for success in working with clinical operations partners and provide recommendations for other Learning Health Systems units embedded in large integrated health care organizations.

Defining Access Management in Health Care Delivery Organizations.

Managing patient access to care in health care delivery organizations is instrumental in shaping patient experiences. We convened an inclusive stakeholder panel, informed by evidence, to understand the dimensions and establish definitions of access and access management. The literature varies in access definitions, but the temporal measure "time to third next available appointment" was consistently used as an indicator of access. Panel deliberations highlighted the importance of patient-centeredness and resulted in comprehensive definitions for access management, optimal access management, and optimal access. Health care organizations and researchers can use the developed definitions and concepts as starting points for initiatives to improve access management.

Integrating social and behavioral determinants of health into patient care and population health at Veterans Health Administration: a conceptual framework and an assessment of available individual and population level data sources and evidence-based measurements.

The premise of this project was that social and behavioral determinants of health (SBDH) affect the use of healthcare services and outcomes for patients in an integrated healthcare system such as the Veterans Health Administration (VHA), and thus individual patient level socio-behavioral factors in addition to the neighborhood characteristics and geographically linked factors could add information beyond medical factors mostly considered in clinical decision making, patient care, and population health. To help VHA better address SBDH risk factors for the veterans it cares for within its primary care clinics, we proposed a conceptual and analytic framework, a set of evidence-based measures, and their data source. The framework and recommended SBDH metrics can provide a road map for other primary care-centric healthcare organizations wishing to use health analytic tools to better understand how SBDH affect health outcomes.

The Association Between Neighborhood Socioeconomic and Housing Characteristics with Hospitalization: Results of a National Study of Veterans.

BACKGROUND: Social determinants of health (SDOH) have an inextricable impact on health. If remained unaddressed, poor SDOH can contribute to increased health care utilization and costs. We aimed to determine if geographically derived neighborhood level SDOH had an impact on hospitalization rates of patients receiving care at the Veterans Health Administration's (VHA) primary care clinics. METHODS: In a 1-year observational cohort of veterans enrolled in VHA's primary care medical home program during 2015, we abstracted data on individual veterans (age, sex, race, Gagne comorbidity score) from the VHA Corporate Data Warehouse and linked those data to data on neighborhood socioeconomic status (NSES) and housing characteristics from the US Census Bureau on census tract level. We used generalized estimating equation modeling and spatial-based analysis to assess the potential impact of patient-level demographic and clinical factors, NSES, and local housing stock (ie, housing instability, home vacancy rate, percentage of houses with no plumbing, and percentage of houses with no heating) on hospitalization. We defined hospitalization as an overnight stay in a VHA hospital only and reported the risk of hospitalization for veterans enrolled in the VHA's primary care medical home clinics, both across the nation and within 1 specific case study region of the country: King County, WA. RESULTS: Nationally, 6.63% of our veteran population was hospitalized within the VHA system. After accounting for patient-level characteristics, veterans residing in census tracts with a higher NSES index had decreased odds of hospitalization. After controlling all other factors, veterans residing in census tracts with higher percentage of houses without heating had 9% (Odds Ratio, 1.09%; 95% CI, 1.04 to 1.14) increase in the likelihood of hospitalization in our regional Washington State analysis, though not our national level analyses. CONCLUSIONS: Our results present the impact of neighborhood characteristics such as NSES and lack of proper heating system on the likelihood of hospitalization. The application of placed-based data at the geographic level is a powerful tool for identification of patients at high risk of health care utilization.

The Impact of Social Determinants of Health on Hospitalization in the Veterans Health Administration.

INTRODUCTION: This study aims to assess the effect of individual and geographic-level social determinants of health on risk of hospitalization in the Veterans Health Administration primary care clinics known as the Patient Aligned Care Team. METHODS: For a population of Veterans enrolled in the primary care clinics, the study team extracted patient-level characteristics and healthcare utilization records from 2015 Veterans Health Administration electronic health record data. They also collected census data on social determinants of health factors for all U.S. census tracts. They used generalized estimating equation modeling and a spatial-based GIS analysis to assess the role of key social determinants of health on hospitalization. Data analysis was completed in 2018. RESULTS: A total of 6.63% of the Veterans Health Administration population was hospitalized during 2015. Most of the hospitalized patients were male (93.40%) and white (68.80%); the mean age was 64.5 years. In the generalized estimating equation model, white Veterans had a 15% decreased odds of hospitalization compared with non-white Veterans. After controlling for patient-level characteristics, Veterans residing in census tracts with the higher neighborhood SES index experienced decreased odds of hospitalization. A spatial-based analysis presented variations in the hospitalization rate across the Veterans Health Administration primary care clinics and identified the clinic sites with an elevated risk of hospitalization (hotspots) compared with other clinics across the country. CONCLUSIONS: By linking patient and population-level data at a geographic level, social determinants of health assessments can help with designing population health interventions and identifying features leading to potentially unnecessary hospitalization in selected geographic areas that appear to be outliers.

Comparing Patient-Centered Medical Home Implementation in Urban and Rural VHA Clinics: Results From the Patient Aligned Care Team Initiative.

Rural Veterans Health Administration (VHA) primary care clinics are smaller, have fewer staff, and serve more rural patients compared with urban VHA primary care clinics. This may lead to different challenges to implementation of the Patient-Centered Medical Home (PCMH) model, the Patient Aligned Care Team, in the VHAs' large integrated health system. In this cross-sectional observational study of 905 VHA primary clinics in the United States and Puerto Rico, we found overall PCMH implementation was greater in rural compared to urban primary care clinics. Urban-rural differences in PCMH implementation may largely be related to clinic organizational factors.

Elements of the Veterans Health Administration Patient-Centered Medical Home are Associated with Greater Adherence to Oral Hypoglycemic Agents in Patients with Diabetes.

In 2010, Veterans Health Administration (VHA) primary care clinics adopted a patient-centered medical home (PCMH) model. This study sought to examine the association between the organizational features related to adoption of PCMH and the level of adherence to oral hypoglycemic agents (OHAs) among patients with diabetes. This retrospective cohort study involved 757 VA clinics that provide primary care to 440,971 patients with diabetes who were taking OHAs in fiscal year 2012. One-year refill-based medication possession ratios (MPRs) were calculated at the patient level. Clinic-level adherence was defined as the proportion of clinics with MPR ≥80%. Risk adjustment of adherence was performed using logistic regression to account for differences in patient populations at clinics. Eight domains of the PCMH model (ie, access, continuity, coordination, teamwork, comprehensive care, self-management, communication, shared decision making) were assessed using items from a previously validated index. Multivariate linear regression was applied to identify PCMH components associated with clinic-level adherence. Patients with diabetes per clinic ranged from 100 to 5011. The average level of adherence to OHAs among clinics ranged from 52.8% to 61.9% (interquartile range = 57.9% to 59.4%). In multivariate analysis, organizational features associated with higher clinic-level adherence included access to routine care (standardized beta [Sß] = .21, P = .004), having a respectful office staff (Sß = 0.21, P = .002), and utilization of telephone encounters (Sß = 0.23, P < .001). Among a national cohort of veterans with diabetes, overall PCMH implementation did not significantly increase adherence to oral hypoglycemic agents, although aspects of implementation were associated with increased adherence. Measures of access to care appear the most significant.

Patient-Centered Medical Home Implementation and Burnout Among VA Primary Care Employees.

Burnout is widespread throughout primary care and is associated with negative consequences for providers and patients. The relationship between the patient-centered medical home model and burnout remains unclear. Using survey data from 8135 and 7510 VA primary care employees in 2012 and 2013, respectively, we assessed whether clinic-level medical home implementation was independently associated with burnout prevalence and estimated whether burnout changed among this workforce from 2012 to 2013. Adjusting for differences in respondent and clinic characteristics, we found that burnout was common among primary care employees, increased by 3.9% from 2012 to 2013, and was not associated with the extent of medical home implementation.

Implementation of the patient-centered medical home in the Veterans Health Administration: associations with patient satisfaction, quality of care, staff burnout, and hospital and emergency department use.

IMPORTANCE: In 2010, the Veterans Health Administration (VHA) began implementing the patient-centered medical home (PCMH) model. The Patient Aligned Care Team (PACT) initiative aims to improve health outcomes through team-based care, improved access, and care management. To track progress and evaluate outcomes at all VHA primary care clinics, we developed and validated a method to assess PCMH implementation. OBJECTIVES: To create an index that measures the extent of PCMH implementation, describe variation in implementation, and examine the association between the implementation index and key outcomes. DESIGN, SETTING, AND PARTICIPANTS: We conducted an observational study using data on more than 5.6 million veterans who received care at 913 VHA hospital-based and community-based primary care clinics and 5404 primary care staff from (1) VHA clinical and administrative databases, (2) a national patient survey administered to a weighted random sample of veterans who received outpatient care from June 1 to December 31, 2012, and (3) a survey of all VHA primary care staff in June 2012. Composite scores were constructed for 8 core domains of PACT: access, continuity, care coordination, comprehensiveness, self-management support, patient-centered care and communication, shared decision making, and team-based care. MAIN OUTCOMES AND MEASURES: Patient satisfaction, rates of hospitalization and emergency department use, quality of care, and staff burnout. RESULTS: Fifty-three items were included in the PACT Implementation Progress Index (Pi2). Compared with the 87 clinics in the lowest decile of the Pi2, the 77 sites in the top decile exhibited significantly higher patient satisfaction (9.33 vs 7.53; P < .001), higher performance on 41 of 48 measures of clinical quality, lower staff burnout (Maslach Burnout Inventory emotional exhaustion subscale, 2.29 vs 2.80; P = .02), lower hospitalization rates for ambulatory care-sensitive conditions (4.42 vs 3.68 quarterly admissions for veterans 65 years or older per 1000 patients; P < .001), and lower emergency department use (188 vs 245 visits per 1000 patients; P < .001). CONCLUSIONS AND RELEVANCE: The extent of PCMH implementation, as measured by the Pi2, was highly associated with important outcomes for both patients and providers. This measure will be used to track the effectiveness of implementing PACT over time and to elucidate the correlates of desired health outcomes.