Primary care mental health integration to improve early treatment engagement for veterans who screen positive for depression.

OBJECTIVE: To examine the relationship between the penetration (or reach) of a national program aiming to integrate mental health clinicians into all primary care clinics (PC-MHI) and rates of guideline-concordant follow-up and treatment among clinic patients newly identified with depression in the Veterans Health Administration (VA). DATA SOURCES/STUDY SETTING: 15,155 screen-positive patients 607,730 patients with 2-item Patient Health Questionnaire scores in 82 primary care clinics, 2015-2019. STUDY DESIGN: In this retrospective cohort study, we used established depression care quality measures to assess primary care patients who (a) newly screened positive (score ≥3) and (b) were identified with depression by clinicians via diagnosis and/or medication (n = 15,155; 15,650 patient-years). Timely follow-up included ≥3 mental health, ≥3 psychotherapy, or ≥3 primary care visits for depression. Minimally appropriate treatment included ≥4 mental health visits, ≥3 psychotherapy, or ≥60 days of medication. In multivariate regressions, we examined whether higher rates of PC-MHI penetration in clinic (proportion of total primary care patients in a clinic who saw any PC-MHI clinician) were associated with greater depression care quality among cohort patients, adjusting for year, healthcare system, and patient and clinic characteristics. DATA COLLECTION/EXTRACTION METHODS: Electronic health record data from 82 VA clinics across three states. PRINCIPAL FINDINGS: A median of 9% of all primary care patients were seen by any PC-MHI clinician annually. In fully adjusted models, greater PC-MHI penetration was associated with timely depression follow-up within 84 days (∆P = 0.5; SE = 0.1; p < 0.001) and 180 days (∆P = 0.3; SE = 0.1; p = 0.01) of a positive depression screen. Completion of at least minimal treatment within 12 months was high (77%), on average, and not associated with PC-MHI penetration. CONCLUSIONS: Greater PC-MHI program penetration was associated with early depression treatment engagement at 84-/180-days among clinic patients newly identified with depression, with no effect on already high rates of completion of minimally sufficient treatment within the year.

Implementing evidence-based practices to improve primary care for high-risk patients: study protocol for the VA high-RIsk VETerans (RIVET) type III effectiveness-implementation trial.

BACKGROUND: Patients with significant multimorbidity and other factors that make healthcare challenging to access and coordinate are at high risk for poor health outcomes. Although most (93%) of Veterans' Health Administration (VHA) patients at high risk for hospitalization or death ("high-risk Veterans") are primarily managed by primary care teams, few of these teams have implemented evidence-based practices (EBPs) known to improve outcomes for the high-risk patient population's complex healthcare issues. Effective implementation strategies could increase adoption of these EBPs in primary care; however, the most effective implementation strategies to increase evidence-based care for high-risk patients are unknown. The high-RIsk VETerans (RIVET) Quality Enhancement Research Initiative (QUERI) will compare two variants of Evidence-Based Quality Improvement (EBQI) strategies to implement two distinct EBPs for high-risk Veterans: individual coaching (EBQI-IC; tailored training with individual implementation sites to meet site-specific needs) versus learning collaborative (EBQI-LC; implementation sites trained in groups to encourage collaboration among sites). One EBP, Comprehensive Assessment and Care Planning (CACP), guides teams in addressing patients' cognitive, functional, and social needs through a comprehensive care plan. The other EBP, Medication Adherence Assessment (MAA), addresses common challenges to medication adherence using a patient-centered approach. METHODS: We will recruit and randomize 16 sites to either EBQI-IC or EBQI-LC to implement one of the EBPs, chosen by the site. Each site will have a site champion (front-line staff) who will participate in 18 months of EBQI facilitation. ANALYSIS: We will use a mixed-methods type 3 hybrid Effectiveness-Implementation trial to test EBQI-IC versus EBQI-LC versus usual care using a Concurrent Stepped Wedge design. We will use the Practical, Robust Implementation and Sustainability Model (PRISM) framework to compare and evaluate Reach, Effectiveness, Adoption, Implementation, and costs. We will then assess the maintenance/sustainment and spread of both EBPs in primary care after the 18-month implementation period. Our primary outcome will be Reach, measured by the percentage of eligible high-risk patients who received the EBP. DISCUSSION: Our study will identify which implementation strategy is most effective overall, and under various contexts, accounting for unique barriers, facilitators, EBP characteristics, and adaptations. Ultimately this study will identify ways for primary care clinics and teams to choose implementation strategies that can improve care and outcomes for patients with complex healthcare needs. TRIAL REGISTRATION: ClinicalTrials.gov, NCT05050643. Registered September 9th, 2021, https://clinicaltrials.gov/study/NCT05050643 PROTOCOL VERSION: This protocol is Version 1.0 which was created on 6/3/2020.

Impact of Referring High-Risk Patients to Intensive Outpatient Primary Care Services: A Propensity Score-Matched Analysis.

BACKGROUND: Many healthcare systems have implemented intensive outpatient primary care programs with the hopes of reducing healthcare costs. OBJECTIVE: The Veterans Health Administration (VHA) piloted primary care intensive management (PIM) for patients at high risk for hospitalization or death, or "high-risk." We evaluated whether a referral model would decrease high-risk patient costs. DESIGN: Retrospective cohort study using a quasi-experimental design comparing 456 high-risk patients referred to PIM from October 2017 to September 2018 to 415 high-risk patients matched on propensity score. PARTICIPANTS: Veterans in the top 10th percentile of risk for 90-day hospitalization or death and recent hospitalization or emergency department (ED) visit. INTERVENTION: PIM consisted of interdisciplinary teams that performed comprehensive assessments, intensive case management, and care coordination services. MAIN OUTCOMES AND MEASURES: Change in VHA and non-VHA outpatient utilization, inpatient admissions, and costs 12 months pre- and post-index date. KEY RESULTS: Of the 456 patients referred to PIM, 301 (66%) enrolled. High-risk patients referred to PIM had a marginal reduction in ED visits (- 0.7; [95% CI - 1.50 to 0.08]; p = 0.08) compared to propensity-matched high-risk patients; overall outpatient costs were similar. High-risk patients referred to PIM had similar number of medical/surgical hospitalizations (- 0.2; [95% CI, - 0.6 to 0.16]; p = 0.2), significant increases in length of stay (6.36; [CI, - 0.01 to 12.72]; p = 0.05), and higher inpatient costs ($22,628, [CI, $3587 to $41,669]; p = 0.02) than those not referred to PIM. CONCLUSIONS AND RELEVANCE: VHA intensive outpatient primary care was associated with higher costs. Referral to intensive case management programs targets the most complex patients and may lead to increased utilization and costs, particularly in an integrated healthcare setting with robust patient-centered medical homes. TRIAL REGISTRATION: PIM 2.0: Patient Aligned Care Team (PACT) Intensive Management (PIM) Project (PIM2). NCT04521816. https://clinicaltrials.gov/study/NCT04521816.

The association between population health management tools and clinician burnout in the United States VA primary care patient-centered medical home.

BACKGROUND: Technological burden and medical complexity are significant drivers of clinician burnout. Electronic health record(EHR)-based population health management tools can be used to identify high-risk patient populations and implement prophylactic health practices. Their impact on clinician burnout, however, is not well understood. Our objective was to assess the relationship between ratings of EHR-based population health management tools and clinician burnout. METHODS: We conducted cross-sectional analyses of 2018 national Veterans Health Administration(VA) primary care personnel survey, administered as an online survey to all VA primary care personnel (n = 4257, response rate = 17.7%), using bivariate and multivariate logistic regressions. Our analytical sample included providers (medical doctors, nurse practitioners, physicians' assistants) and nurses (registered nurses, licensed practical nurses). The outcomes included two items measuring high burnout. Primary predictors included importance ratings of 10 population health management tools (eg. VA risk prediction algorithm, recent hospitalizations and emergency department visits, etc.). RESULTS: High ratings of 9 tools were associated with lower odds of high burnout, independent of covariates including VA tenure, team role, gender, ethnicity, staffing, and training. For example, clinicians who rated the risk prediction algorithm as important were less likely to report high burnout levels than those who did not use or did not know about the tool (OR 0.73; CI 0.61-0.87), and they were less likely to report frequent burnout (once per week or more) (OR 0.71; CI 0.60-0.84). CONCLUSIONS: Burned-out clinicians may not consider the EHR-based tools important and may not be using them to perform care management. Tools that create additional technological burden may need adaptation to become more accessible, more intuitive, and less burdensome to use. Finding ways to improve the use of tools that streamline the work of population health management and/or result in less workload due to patients with poorly managed chronic conditions may alleviate burnout. More research is needed to understand the causal directional of the association between burnout and ratings of population health management tools.

Factors Associated With Use of the Preventive Health Inventory in US Veterans.

Importance: The COVID-19 pandemic caused significant declines in the quality of preventive and chronic disease care. The Veterans Health Administration (VHA) used the Preventive Health Inventory (PHI), a multicomponent care management intervention, to catch up on care disrupted by the pandemic. Objective: To identify key factors associated with PHI use. Design, Setting, and Participants: This cohort study of veterans receiving primary care used administrative data from national VHA primary care clinics for February 1, 2021, through February 1, 2022. Exposure: Patient PHI receipt. Main Outcomes and Measures: The main outcomes were patient, practitioner, and clinic factors associated with PHI receipt. Binomial generalized linear models with fixed effects for clinic were used to analyze factors associated with receipt of PHI. Least absolute shrinkage and selection operator procedures were used for variable selection. Results: A total of 4 358 038 veterans (mean [SD] age, 63.7 [16.0] years; 90% male; 76% non-Hispanic White) formed the study cohort, of whom 389 757 (9%) received the PHI. Veterans who received the PHI had higher mean Care Assessment Need (CAN) scores, which indicate the likelihood of hospitalization or death within 1 year (mean [SD], 51.9 [28.6] vs 47.2 [28.6]; standardized mean difference [SMD], -0.16). They were also more likely to live in urban areas (77% vs 64%; SMD, 0.28) and have a shorter drive distance to primary care (mean [SD], 13.2 [12.4] vs 15.7 [14.6] miles; SMD, 0.19). The mean outpatient use was higher among PHI recipients compared with non-PHI recipients (mean [SD], 18.4 [27.8] vs 15.1 [24.1] visits; SMD, -0.13). In addition, veterans with primary care practitioners with higher caseloads were more likely to receive the PHI (mean [SD], 778 [231] vs 744 [249] patients; SMD, -0.14), and they were more likely to be seen at larger clinics (mean [SD], 9670 [6876] vs 8786 [6892] patients; SMD, -0.13). Prior outpatient use and CAN score were associated with PHI receipt in the final model. Conclusions and Relevance: In this cohort study of the VHA's PHI, patients with higher CAN scores and more outpatient use in the previous year were more likely to receive the PHI. This study identifies potential intervention points to improve care coordination for veterans.

Meeting high-risk patient pain care needs through intensive primary care: a secondary analysis.

OBJECTIVE: Chronic pain disproportionately affects medically and psychosocially complex patients, many of whom are at high risk of hospitalisation. Pain prevalence among high-risk patients, however, is unknown, and pain is seldom a focus for improving high-risk patient outcomes. Our objective is to (1) evaluate pain frequency in a high-risk patient population and (2) identify intensive management (IM) programme features that patients and providers perceive as important for promoting patient-centred pain care within primary care (PC)-based IM. DESIGN: Secondary observational analysis of quantitative and qualitative evaluation data from a multisite randomised PC-based IM programme for high-risk patients. SETTING: Five integrated local Veterans Affairs (VA) healthcare systems within distinct VA administrative regions. PARTICIPANTS: Staff and high-risk PC patients in the VA. INTERVENTION: A multisite randomised PC-based IM programme for high-risk patients. OUTCOME MEASURES: (a) Pain prevalence based on VA electronic administrative data and (b) transcripts of interviews with IM staff and patients that mentioned pain. RESULTS: Most (70%, 2593/3723) high-risk patients had at least moderate pain. Over one-third (38%, 40/104) of the interviewees mentioned pain or pain care. There were 89 pain-related comments addressing IM impacts on pain care within the 40 interview transcripts. Patient-identified themes were that IM improved communication and responsiveness to pain. PC provider-identified themes were that IM improved workload and access to expertise. IM team member-identified themes were that IM improved pain care coordination, facilitated non-opioid pain management options and mitigated provider compassion fatigue. No negative IM impacts on pain care were mentioned. CONCLUSIONS: Pain is common among high-risk patients. Future IM evaluations should consider including a focus on pain and pain care, with attention to impacts on patients, PC providers and IM teams.

Burnout, employee engagement, and changing organizational contexts in VA primary care during the early COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic involved a rapid change to the working conditions of all healthcare workers (HCW), including those in primary care. Organizational responses to the pandemic, including a shift to virtual care, changes in staffing, and reassignments to testing-related work, may have shifted more burden to these HCWs, increasing their burnout and turnover intent, despite their engagement to their organization. Our objectives were (1) to examine changes in burnout and intent to leave rates in VA primary care from 2017-2020 (before and during the pandemic), and (2) to analyze how individual protective factors and organizational context affected burnout and turnover intent among VA primary care HCWs during the early months of the pandemic. METHODS: We analyzed individual- and healthcare system-level data from 19,894 primary care HCWs in 139 healthcare systems in 2020. We modeled potential relationships between individual-level burnout and turnover intent as outcomes, and individual-level employee engagement, perceptions of workload, leadership, and workgroups. At healthcare system-level, we assessed prior-year levels of burnout and turnover intent, COVID-19 burden (number of tests and deaths), and the extent of virtual care use as potential determinants. We conducted multivariable analyses using logistic regression with standard errors clustered by healthcare system controlled for individual-level demographics and healthcare system complexity. RESULTS: In 2020, 37% of primary care HCWs reported burnout, and 31% reported turnover intent. Highly engaged employees were less burned out (OR = 0.57; 95% CI 0.52-0.63) and had lower turnover intent (OR = 0.62; 95% CI 0.57-0.68). Pre-pandemic healthcare system-level burnout was a major predictor of individual-level pandemic burnout (p = 0.014). Perceptions of reasonable workload, trustworthy leadership, and strong workgroups were also related to lower burnout and turnover intent (p < 0.05 for all). COVID-19 burden, virtual care use, and prior year turnover were not associated with either outcome. CONCLUSIONS: Employee engagement was associated with a lower likelihood of primary care HCW burnout and turnover intent during the pandemic, suggesting it may have a protective effect during stressful times. COVID-19 burden and virtual care use were not related to either outcome. Future research should focus on understanding the relationship between engagement and burnout and improving well-being in primary care.

Telework Arrangements and Physician Burnout in the Veterans Health Administration.

This survey study of physicians in the Veterans Health Administration examines the association of burnout with various telework arrangements.

Frontline perspectives on adoption and non-adoption of care management tools for high-risk patients in primary care.

BACKGROUND: Population health management tools (PHMTs) embedded within electronic health records (EHR) could improve management of high-risk patients and reduce costs associated with potentially avoidable emergency department visits or hospitalizations. Adoption of PHMTs across the Veterans Health Administration (VA) has been variable and previous research suggests that understaffed primary care (PC) teams might not be using the tools. METHODS: We conducted a retrospective content analysis of open-text responses (n = 1804) from the VA's 2018 national primary care personnel survey to, 1) identify system-level and individual-level factors associated with why clinicians are not using the tools, and 2) to document clinicians' recommendations to improve tool adoption. RESULTS: We found three themes pertaining to low adoption and/or tool use: 1) IT burden and administrative tasks (e.g., manually mailing letters to patients), 2) staffing shortages (e.g., nurses covering multiple teams), and 3) no training or difficulty using the tools (e.g., not knowing how to access the tools or use the data). Frontline clinician recommendations included automating some tasks, reconfiguring team roles to shift administrative work away from providers and nurses, consolidating PHMTs into a centralized, easily accessible repository, and providing training. CONCLUSIONS: Healthcare system-level factors (staffing) and individual-level factors (lack of training) can limit adoption of PHMTs that could be useful for reducing costs and improving patient outcomes. Future research, including qualitative interviews with clinicians who use/don't use the tools, could help develop interventions to address barriers to adoption. IMPLICATIONS: Shifting more administrative tasks to clerical staff would free up clinician time for population health management but may not be possible for understaffed PC teams. Additionally, healthcare systems may be able to increase PHMT use by making them more easily accessible through the electronic health record and providing training in their use.

Depression care quality among patients with solid tumor cancers detected to have depression in Veterans Health Administration primary care clinics.

Patients with cancer, especially advanced cancer, experience depression at high rates. We aimed to evaluate the quality of depression care received by patients with solid tumor cancer and advanced solid tumor cancer in Veterans Affairs (VA) primary care clinics. This is a retrospective cohort study of patients seen in 82 VA primary care clinics who newly screened positive for depression on the Patient Health Questionnaire (PHQ-2). Outcomes included timely follow-up within 84 or 180 days (3+ mental health specialty, 3+ psychotherapy, or 3+ primary care visits with depression diagnosis codes) and minimum treatment within 1 year (60+ days antidepressants prescribed, 4+ mental health specialty visits, or 3+ psychotherapy visits). 608,042 individuals were seen in VA primary care clinics during this period; 49,839 patients (8.2%) had solid tumor cancer and 9,278 (1.5%) had advanced or poor-prognosis solid tumor cancer. For 686 observations of patients with cancer and new depression, rates of appropriate follow-up were 22.3% within 84 days and 38.2% within 180 days. For 73 observations of patients with advanced or poor-prognosis cancer and new depression, rates of appropriate follow-up were 21.9% within 84 days and 34.3% within 180 days. Rates of minimum treatment within 1 year were 68.4% and 64.4% for patients with cancer and patients with advanced or poor-prognosis cancer, respectively. Quality of timely depression management is low in patients with solid tumor cancers. Even in health systems with well-integrated mental health services, care gaps remain for patients with cancer and depression. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Types of Engagement Strategies to Engage High-Risk Patients in VA.

BACKGROUND: Many healthcare systems seek to improve care for complex high-risk patients, but engaging such patients to actively participate in their healthcare can be challenging. OBJECTIVE: To identify and describe types of patient engagement strategies reported as successfully deployed by providers/teams and experienced by patients in a Veterans Health Administration (VA) intensive primary care (IPC) pilot program. METHODS: We conducted semi-structured qualitative telephone interviews with 29 VA IPC staff (e.g., physicians, nurses, psychologists) and 51 patients who had at least four IPC team encounters. Interviews were recorded, transcribed, and analyzed thematically using a combination a priori/inductive approach. RESULTS: The engagement strategies successfully deployed by the IPC providers/teams could be considered either more "facilitative," i.e., facilitated by and dependent on staff actions, or more "self-sustaining," i.e., taught to patients, thus cultivating their ongoing patient self-care. Facilitative strategies revolved around enhancing patient access and coordination of care, trust-building, and addressing social determinants of health. Self-sustaining strategies were oriented around patient empowerment and education, caregiver and/or community support, and boundaries and responsibilities. When patients described their experiences with the "facilitative" strategies, many discussed positive proximal outcomes (e.g., increased access to healthcare providers). Self-sustaining strategies led to positive (self-reported) longer-term clinical outcomes, such as behavior change. CONCLUSION: We identified two categories of strategies for successfully engaging complex, high-risk patients: facilitative and self-sustaining. Intensive primary care program leaders may consider thoughtfully building "self-sustaining" engagement strategies into program development. Future research can confirm their effectiveness in improving health outcomes.

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.

The Clinical Resource Hub Initiative: First-Year Implementation of the Veterans Health Administration Regional Telehealth Contingency Staffing Program.

Health care systems face challenges providing accessible health care across geographically disparate sites. The Veterans Health Administration (VHA) developed regional telemedicine service focusing initially on primary care and mental health services. The objective of this study is to describe the program and progress during the early implementation. In its first year, the Clinical Resource Hub program provided 244 515 encounters to 95 684 Veterans at 475 sites. All 18 regions met or exceeded minimum implementation requirements. The regionally based telehealth contingency staffing hub met early implementation goals. Further evaluation to review sustainability and impact on provider experience and patient outcomes is needed.

Changes in Primary Care Quality Associated With Implementation of the Veterans Health Administration Preventive Health Inventory.

Importance: The COVID-19 pandemic caused significant disruptions in primary care delivery. The Veterans Health Administration (VHA) launched the Preventive Health Inventory (PHI) program-a multicomponent care management intervention, including a clinical dashboard and templated electronic health record note-to support primary care in delivering chronic disease care and preventive care that had been delayed by the pandemic. Objectives: To describe patient, clinician, and clinic correlates of PHI use in primary care clinics and to examine associations between PHI adoption and clinical quality measures. Design, Setting, and Participants: This quality improvement study used VHA administrative data from February 1, 2021, through February 28, 2022, from a national cohort of 216 VHA primary care clinics that have implemented the PHI. Participants comprised 829 527 veterans enrolled in primary care in clinics with the highest and lowest decile of PHI use as of February 2021. Exposure: Templated electronic health record note documenting use of the PHI. Main Outcomes and Measures: Diabetes and blood pressure clinical quality measures were the primary outcomes. Interrupted time series models were applied to estimate changes in diabetes and hypertension quality measures associated with PHI implementation. Low vs high PHI use was stratified at the facility level to measure whether systematic differences in uptake were associated with quality. Results: A total of 216 primary clinics caring for 829 527 unique veterans (mean [SD] age, 64.1 [16.9] years; 755 158 of 829 527 [91%] were men) formed the study cohort. Use of the PHI varied considerably across clinics. The clinics in the highest decile of PHI use completed a mean (SD) of 32 997.4 (14 019.3) notes in the electronic health record per 100 000 veterans compared with 56.5 (35.3) notes per 100 000 veterans at the clinics in the lowest decile of use (P < .001). Compared with the clinics with the lowest use of the PHI, clinics with the highest use had a larger mean (SD) clinic size (12 072 [7895] patients vs 5713 [5825] patients; P < .001), were more likely to be urban (91% vs 57%; P < .001), and served more non-Hispanic Black veterans (16% vs 5%; P < .001) and Hispanic veterans (14% vs 4%; P < .001). Staffing did not differ meaningfully between high- and low-use clinics (mean [SD] ratio of full-time equivalent staff to clinician, 3.4 [1.2] vs 3.4 [0.8], respectively; P < .001). After PHI implementation, compared with the clinics with the lowest use, those with the highest use had fewer veterans with a hemoglobin A1c greater than 9% or missing (mean [SD], 6577 [3216] per 100 000 veterans at low-use clinics; 9928 [4236] per 100 000 veterans at high-use clinics), more veterans with an annual hemoglobin A1c measurement (mean [SD], 13 181 [5625] per 100 000 veterans at high-use clinics; 8307 [3539] per 100 000 veterans at low-use clinics), and more veterans with adequate blood pressure control (mean [SD], 20 582 [12 201] per 100 000 veterans at high-use clinics; 12 276 [6850] per 100 000 veterans at low-use clinics). Conclusions and Relevance: This quality improvement study of the implementation of the VHA PHI suggests that higher use of a multicomponent care management intervention was associated with improved quality-of-care metrics. The study also found significant variation in PHI uptake, with higher uptake associated with clinics with more racial and ethnic diversity and larger, urban clinic sites.

Evidence-Based Quality Improvement: a Scoping Review of the Literature.

BACKGROUND: Quality improvement (QI) initiatives often reflect approaches based on anecdotal evidence, but it is unclear how initiatives can best incorporate scientific literature and methods into the QI process. Review of studies of QI initiatives that aim to systematically incorporate evidence review (termed evidence-based quality improvement (EBQI)) may provide a basis for further methodological development. METHODS: In this scoping review (registration: https://osf.io/hr5bj ) of EBQI, we searched the databases PubMed, CINAHL, and SCOPUS. The review addressed three central questions: How is EBQI defined? How is evidence used to inform evidence-informed QI initiatives? What is the effectiveness of EBQI? RESULTS: We identified 211 publications meeting inclusion criteria. In total, 170 publications explicitly used the term "EBQI." Published definitions emphasized relying on evidence throughout the QI process. We reviewed a subset of 67 evaluations of QI initiatives in primary care, including both studies that used the term "EBQI" with those that described an evidence-based initiative without using EBQI terminology. The most frequently reported EBQI components included use of evidence to identify previously tested effective QI interventions; engaging stakeholders; iterative intervention development; partnering with frontline clinicians; and data-driven evaluation of the QI intervention. Effectiveness estimates were positive but varied in size in ten studies that provided data on patient health outcomes. CONCLUSIONS: EBQI is a promising strategy for integrating relevant prior scientific findings and methods systematically in the QI process, from the initial developmental phase of the IQ initiative through to its evaluation. Future QI researchers and practitioners can use these findings as the basis for further development of QI initiatives.

Predictors of VA Primary Care Clerical Staff Burnout Using the Job Demands-Resources Model.

Primary care clerical staff may experience burnout if not adequately prepared and supported for patient-facing customer service tasks. Guided by the Job Demands-Resources (JD-R) model, we use national survey data from 707 primary care clerks at 349 VA clinics (2018; response rate: 12%) to evaluate associations between clerks' perceptions of tasks, work environment, training, and burnout. We found challenges with customer-facing tasks contribute to higher burnout, and supportive work environment was associated with lower burnout. Although perceptions of training were not associated with burnout, our results combined with the JD-R model suggest that customer service training may protect against burnout.

Factors Associated With Patient-Centered Medical Home Teams' Use of Resources for Identifying and Approaches for Managing Patients With Complex Needs.

Using data from a Veterans Health Administration national primary care survey, this study identified the most highly rated tools and care approaches for patients with complex needs and how preferences varied by professional role, staffing, and training. Nurses were significantly more likely to rate most tools as very important as compared with primary care providers. Having a fully staffed team was also significantly associated with a very important rating on all tools. Nurses and fully staffed teams reported a greater likeliness to use most care approaches, and those with perceived need for training reporting a lower likeliness to use.

Patient selection strategies in an intensive primary care program.

BACKGROUND: Intensive primary care programs have had variable impacts on clinical outcomes, possibly due to a lack of consensus on appropriate patient-selection. The US Veterans Health Administration (VHA) piloted an intensive primary care program, known as Patient Aligned Care Team Intensive Management (PIM), in five medical centers. We sought to describe the PIM patient selection process used by PIM teams and to explore perspectives of PIM team members regarding how patient selection processes functioned in context. METHODS: This study employs an exploratory sequential mixed-methods design. We analyzed qualitative interviews with 21 PIM team and facility leaders and electronic health record (EHR) data from 2,061 patients screened between July 2014 and September 2017 for PIM enrollment. Qualitative data were analyzed using a hybrid inductive/deductive approach. Quantitative data were analyzed using descriptive statistics. RESULTS: Of 1,887 patients identified for PIM services using standardized criteria, over half were deemed inappropriate for PIM services, either because of not having an ambulatory care sensitive condition, living situation, or were already receiving recommended care. Qualitative analysis found that team members considered standardized criteria to be a useful starting point but too broad to be relied on exclusively. Additional data collection through chart review and communication with the current primary care team was needed to adequately assess patient complexity. Qualitative analysis further found that differences in conceptualizing program goals led to conflicting opinions of which patients should be enrolled in PIM. CONCLUSIONS: A combined approach that includes clinical judgment, case review, standardized criteria, and targeted program goals are all needed to support appropriate patient selection processes.