Use of General Primary Care, Specialized Primary Care, and Other Veterans Affairs Services Among High-Risk Veterans

The Characteristics of People with Serious Mental Illness Who are at High Risk for Hospitalization or Death

Many individuals with serious mental illness are at high risk for hospitalization or death due to inadequate treatment of medical conditions or unhealthy behaviors. The authors describe demographic and clinical characteristics associated with increased risk in this population. Electronic data were obtained for individuals in treatment at a large Veterans' healthcare system who were at high risk according to a validated model. A random sample of these individuals was assessed in person. Multivariable regressions estimated the effect of numerous demographic, health, and clinical characteristics on risk. Emergency visits and hospitalizations were common. Greater risk was associated with being male, not married, and having more diagnoses. While risk varied by race, this effect was no longer significant after controlling for other factors. Health-related quality of life worsened with increasing risk. Routine data identify a large population of high-risk individuals who may benefit from outreach to provide healthcare services.

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.

Primary Care Telehealth Initiation and Engagement Among Veterans at High Risk, 2019-2022

Importance

During the COVID-19 pandemic, the Veterans Health Administration (VHA) expanded telehealth infrastructure. Understanding telehealth initiation and sustained engagement could inform future resource allocation for high-need populations.

Objective

To describe and examine primary care use, including initiation, use, and engagement factors, of telehealth modalities (telephone, video visits, and secure messaging) from 2020 to 2022.

Design, Setting, and Participants

This cohort study was conducted among 1 383 070 patients in the 75th or higher percentile for 90-day risk of hospitalization or mortality (using previously validated Care Assessment Need scores) engaged in VHA primary care from March 11, 2019, to March 10, 2022.

Exposures

Patient sociodemographic characteristics (age, sex, race and ethnicity, and marital and housing status), health characteristics (chronic condition count, military service disability, serious mental illness, or substance use disorder diagnoses), geographic characteristics (driving distance to clinic and rural or urban location), and Federal Communications Commission-reported broadband speed among subgroups of patients at high risk categorized by telehealth use from 2020 to 2022.

Main Outcomes and Measures

Primary care utilization by modality.

Results

A total of 1 383 070 patients at high risk were engaged in VHA primary care in March 2020 (median age, 73.0 years [IQR, 65-80 years]; 92.4% male; 77.7% regular telehealth users in 2019). With the onset of the COVID-19 pandemic from March 2020 to March 2021, 92.7% of patients at high risk (1 158 804 of 1 250 438 retained in care) became regular telehealth users. The following year, most patients continued as telehealth users (83.4% [942 151 of 1 129 683 retained]), including 38.2% retention of users at high risk newly engaged in 2020. Between 2019 and 2022 among those living and engaged in VHA primary care, adjusted exploratory multinomial logit models estimated that new telehealth users in 2020 (both sustained or only transiently engaged) were more often Black non-Hispanic individuals with greater comorbidity burdens than those who never engaged in telehealth use (Black non-Hispanic with new persistent telehealth use: adjusted relative risk ratio [ARR], 1.18 [95% CI, 1.16-1.20]; Black non-Hispanic with transient telehealth use: ARR, 1.11 [95% CI, 1.08-1.13]; ≥5 chronic conditions with new persistent telehealth use: ARR, 1.92 [95% CI, 1.88-1.96]; ≥5 chronic conditions with transient telehealth use: ARR, 1.43 [95% CI, 1.40-1.46]).

Conclusions and Relevance

This cohort study suggests that primary care telehealth initiation, use and sustained engagement differed among subgroups of patients at high risk throughout the COVID-19 pandemic. Those never or only transiently engaged with telehealth had lower illness burdens and were less likely to identify as members of racial or ethnic minority groups. Variation in telehealth use among subgroups of patients at high risk during this period could inform future resource allocation.

Factors Associated with Delayed Care Among Women Veterans Actively Engaged in Primary Care

Background: Delaying needed medical care contributes to greater health risks and higher long-term medical costs. Women Veterans with complex medical and mental health needs face increased barriers to timely care access. Objectives: In a sample of women Veterans with recent engagement in Veterans Administration (VA) primary care, we aimed to compare characteristics of women Veterans who delayed care in the past 6 months with those who did not and examine factors associated with self-reported delayed care. Our study aims to inform interventions focused on eliminating health care access disparities among women Veterans. Materials and Methods: An innovation to improve women Veterans' engagement and retention in evidence-based health care for cardiovascular (CV) risk reduction (CV Toolkit) was implemented across five primary care sites within the VA. Women Veterans who were exposed to at least one CV Toolkit component participated in a mailed survey (n = 253). We used multivariate logistic regression to model factors associated with delaying care, including trust in VA providers, positive mental health screening (i.e., positive screen for either depression or anxiety), traumatic experience, self-rated health, and age. Results: Women with any mental health symptoms (odds ratio [OR] 2.42, 95% confidence interval [CI]: 1.23-4.74) and women who had experienced a traumatic event (OR 2.61, 95%CI: 1.11-6.14) were significantly more likely to report delaying care. Conclusions: Our study identified high rates of delayed care-over one-third of respondents-among women Veterans with recent primary care engagement. Mental health symptoms were the most common reported reason for delay among those who delayed care. Clinical Trial registration: NCT02991534.

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.

Associations Between Social Risks and Primary Care Utilization Among Medically Complex Veterans

BACKGROUND

Social risks contribute to poor health outcomes, especially for patients with complex medical needs. These same risks may impact access to primary care services.

OBJECTIVE

To study associations between social risks and primary care utilization among patients with medical complexity.

DESIGN

Prospective cohort study of respondents to a 2018 mailed survey, followed up to 2 years after survey completion.

PARTICIPANTS

Nationally representative sample of 10,000 primary care patients in the Veterans Affairs (VA) health care system, with high (≥ 75th percentile) 1-year risk of hospitalization or death.

MAIN MEASURES

Survey-based exposures were low social support, no family member/friend involved in health care, unemployment, transportation problem, food insecurity, medication insecurity, financial strain, low medical literacy, and less than high school graduate. Electronic health record-based outcomes were number of primary care provider (PCP) encounters, number of primary care team encounters (PCP, nurse, clinical pharmacist, and social worker), and having ≥ 1 social work encounter.

KEY RESULTS

Among 4680 respondents, mean age was 70.3, 93.7% were male, 71.8% White non-Hispanic, and 15.8% Black non-Hispanic. Unemployment was associated with fewer PCP and primary care team encounters (incident rate ratio 0.77, 95% CI 0.65-0.91; p = 0.002 and 0.75, 0.59-0.95; p = 0.02, respectively), and low medical literacy was associated with more primary care team encounters (1.17, 1.05-1.32; p = 0.006). Among those with one or more social risks, 18.4% had ≥ 1 social work encounter. Low medical literacy (OR 1.95, 95% CI 1.45-2.61; p < 0.001), transportation problem (1.42, 1.10-1.83; p = 0.007), and low social support (1.31, 1.06-1.63; p = 0.01) were associated with higher odds of  ≥ 1 social work encounter.

CONCLUSIONS

We found few differences in PCP and primary care team utilization among medically complex VA patients by social risk. However, social work use was low, despite its central role in addressing social risks. More work is needed to understand barriers to social work utilization.

Unhealthy alcohol use and brief intervention rates among high and low complexity veterans seeking primary care services in the Veterans Health Administration

INTRODUCTION

Brief intervention (BI) is recommended for all primary care (PC) patients who screen positive for unhealthy alcohol use; however, patients with multiple chronic health conditions who are at high-risk of hospitalization (i.e., "high complexity" patients) may face disparities in receiving BIs in PC. The current study investigated whether high complexity and low complexity patients in the Veterans Health Administration (VHA) differed regarding screening positive for unhealthy alcohol use, alcohol-use severity, and receipt of BI for those with unhealthy alcohol use.

METHODS

Patients were veterans receiving PC services at the VHA in a mid-Atlantic region of the United States. The study extracted VHA administrative and clinical data for a total of 282,242 patients who had ≥1 PC visits between 1/1/2014 and 12/31/2014, during which they were screened for unhealthy alcohol use by the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C). The study defined high complexity patients as those within and above the 90th percentile of risk for hospitalization per the VHA's Care Assessment Need Score. Logistic regression models assessed if being a high complexity patient was associated with screening positive for unhealthy alcohol use (AUDIT-C ≥ 5), severity of unhealthy alcohol use in those who screened positive (AUDIT-C score range 5-12), and receipt of BI in those who screened positive.

RESULTS

Our sample was 94.5% male, 83% White, 13% Black, 4% other race, and 1.7% Hispanic. A total of 10,813 (3.8%) patients screened positive for unhealthy alcohol use from which we identified 569 (5.3%) high complexity and 10,128 (93.6%) low complexity patients (n = 116 removed due to missing complexity data). Relative to low complexity patients, high complexity patients were less likely to screen positive for unhealthy alcohol use (3.3% vs. 4.1%, AOR = 0.59, p < .001); however, in patients who screened positive, high complexity patients had higher AUDIT-C scores (Mean AUDIT-C = 7.75 vs. 6.87, AOR = 1.46, p < .001) and were less likely to receive a BI (78.0% vs. 92.6%, AOR = 0.42, p < .001).

CONCLUSIONS

Disparities in BI exist for highly complex patients despite having more severe unhealthy alcohol use. Future research should examine the specific patient- and/or clinic-level factors impeding BI delivery for complex patients.

Using a person-centered approach in clinical care for patients with complex chronic conditions: Perspectives from healthcare professionals caring for Veterans with COPD in the U.S. Veterans Health Administration's Whole Health System of Care

BACKGROUND

The largest nationally integrated health system in the United States, the Veterans Health Administration (VHA), has been undergoing a transformation toward a Whole Health (WH) System of Care. WH Clinical Care, a component of this system, includes holistically assessing the Veteran's life context, identifying what really matters to the Veteran, collaboratively setting and monitoring personal health and well-being goals, and equipping the Veteran with access to conventional and complementary and integrative health resources. Implementation of WH Clinical Care has been challenging. Understanding healthcare professionals' perspectives on the value of and barriers and facilitators to practicing WH Clinical Care holds relevance for not only VHA's efforts but also other health systems, in the U.S. and internationally, that are engaged in person-centered care implementation.

OBJECTIVES

We sought to understand perspectives of healthcare professionals at VHA on providing WH Clinical Care to Veterans with COPD, as a lens to understand the broader issue of WH Clinical Care for Veterans living with complex chronic conditions.

DESIGN

We interviewed 25 healthcare professionals across disciplines and services at a VA Medical Center in 2020-2021, including primary care providers, pulmonologists, palliative care providers, and chaplains. Interview transcripts were analyzed using qualitative content analysis.

KEY RESULTS

Each element of WH Clinical Care raised complex questions and/or concerns, including: (1) the appropriate depth/breadth of inquiry in person-centered assessment; (2) the rationale for elicitation of what really matters; (3) the feasibility and appropriate division of labor in personal health goal setting and planning; and (4) challenges related to referring Veterans to a broad spectrum of supportive services.

CONCLUSIONS

Efforts to promote person-centered care must account for healthcare professionals' existing comfort with its elements, advocate for a team-based approach, and continue to grapple with the conflicting structural conditions and organizational imperatives.

Insomnia in chronic obstructive pulmonary disease and associations with healthcare utilization and costs

Insomnia has been linked to adverse chronic obstructive pulmonary disease (COPD) outcomes including exacerbations, yet its impact on COPD-related healthcare utilization and costs is unknown. In this study, we investigated the associations between insomnia and healthcare utilization and costs in patients with COPD. A retrospective cohort of veterans with COPD were identified from national Veterans Affairs administration data for fiscal years 2012-2017. Insomnia was operationalized as having an insomnia diagnosis based on International Classification of Disease codes or having a prescription of > 30 doses of a sedative-hypnotic medication in a given fiscal year. The index date for insomnia was the first date when dual criteria for COPD and insomnia was met. The index date for those without insomnia was set as the COPD index date. Our primary outcomes were 1-year healthcare utilization and costs related to outpatient visits and hospitalizations after index date. COPD-related healthcare utilization variables included number of prescription fills of corticosteroids and/or antibiotics and outpatient visits and hospitalizations with a primary diagnosis of COPD. Out of 1,011,646 patients (96% men, mean age 68.4 years) diagnosed with COPD, 407,363 (38.8%) had insomnia. After adjustment for confounders, insomnia was associated with higher rates of outpatient visits, hospitalizations, and fills for corticosteroids and/or antibiotics, longer hospital length of stay, and $10,344 higher hospitalization costs in the 12 months after index date. These findings highlight the importance of insomnia as a potentially modifiable target for reducing the burden of COPD on patients and healthcare systems.

Examining telehealth use among primary care patients, providers, and clinics during the COVID-19 pandemic

Background

At the onset of COVID-19, there was a rapid expansion of telehealth (video/telephone) visits to maintain delivery of primary care (PC) services at the Veterans Health Administration (VA). This study examines patient, provider, and site-level characteristics of any virtual and video-based care in PC.

Methods

Interrupted time series (ITS) design was conducted using VA administrative/clinical, electronic healthcare data, 12-months before and 12-months after COVID-19 onset (set at March 2020) at the VA Greater Los Angeles Healthcare System (GLA), between 2019 and 2021. Patients with at least one visit to a VA PC clinic at GLA (n = 547,730 visits) were included in the analysis. The two main outcomes for this study were 1) any telehealth (versus in-person), as well as 2) video-based care (versus telephone). For the ITS analysis, segmented logistic regression on repeated monthly observations of any telehealth and video-based care was used.

Results

Percent telehealth and video use increased from 13.9 to 63.1%, and 0.3 to 11.3%, respectively, before to after COVID-19 onset. According to adjusted percentages, GLA community-based clinics (37.7%, versus 29.8% in hospital-based clinics, p < .001), social workers/pharmacists/dietitians (53.7%, versus 34.0% for PC clinicians, p < .001), and minority groups, non-Hispanic African Americans (36.3%) and Hispanics (34.4%, versus 35.3% for Whites, p < .001) were more likely to use telephone than video. Conversely, mental health providers (43.3%) compared to PC clinicians (15.3%), and women (for all age groups, except 75+) compared to men, were more likely to use video than telephone (all p’s < .001).

Conclusions

Since telehealth care provision is likely to continue after COVID-19, additional research is needed to identify which PC outpatient services are better suited for telephone (e.g., case management) versus video-based care (e.g., integrated mental health visits). Additionally, it is important to understand how all clinics can systematically increase access to both telephone- and video-based PC services, while ensuring equitable care for all patient populations.

My Goals Are Not Their Goals: Barriers and Facilitators to Delivery of Patient-Centered Care for Patients with Multimorbidity

BACKGROUND

Patient-centered care reflecting patient preferences and needs is integral to high-quality care. Individualized care is important for psychosocially complex or high-risk patients with multiple chronic conditions (i.e., multimorbidity), given greater potential risks of interventions and reduced benefits. These patients are increasingly prevalent in primary care. Few studies have examined provision of patient-centered care from the clinician perspective, particularly from primary care physicians serving in integrated, patient-centered medical home settings within the US Veterans Health Administration.

OBJECTIVE

We sought to clarify facilitators and barriers perceived by primary care physicians in the Veterans Health Administration to delivering patient-centered care for high-risk or complex patients with multimorbidity.

DESIGN

We conducted semi-structured telephone interviews from April to July 2020 among physicians across 20 clinical sites. Findings were analyzed with deductive content analysis based on conceptual models of patient-centeredness and hierarchical factors affecting care delivery.

PARTICIPANTS

Of 23 physicians interviewed, most were female (n = 14/23, 61%), serving in hospital-affiliated outpatient clinics (n = 14/23, 61%). Participants had a mean of 21 (SD = 11.3) years of experience.

KEY RESULTS

Facilitators included the following: effective physician-patient communication to individualize care, prioritize among multiple needs, and elicit goals to improve patient engagement; access to care, enabled by interdisciplinary teams, and dictating personalized care planning; effortful but worthwhile care coordination and continuity; meeting complex needs through effective teamwork; and integrating medical and non-medical care aspects in recognition of patients' psychosocial contexts. Barriers included the following: intra- and interpersonal (e.g., perceived patient reluctance to engage in care); organizational (e.g., limited encounter time); and community or policy impediments (e.g., state decisional capacity laws) to patient-centered care.

CONCLUSIONS

Physicians perceived individual physician-patient interactions were the greatest facilitators or barriers to patient-centered care. Efforts to increase primary care patient-centeredness for complex or high-risk patients with multimorbidity could focus on targeting physician-patient communication and reducing interpersonal conflict.

Trends in Illness Severity, Hospitalization, and Mortality for Community-Onset Pneumonia at 118 US Veterans Affairs Medical Centers

BACKGROUND

Deaths from pneumonia were decreasing globally prior to the COVID-19 pandemic, but it is unclear whether this was due to changes in patient populations, illness severity, diagnosis, hospitalization thresholds, or treatment. Using clinical data from the electronic health record among a national cohort of patients initially diagnosed with pneumonia, we examined temporal trends in severity of illness, hospitalization, and short- and long-term deaths.

DESIGN

Retrospective cohort PARTICIPANTS: All patients >18 years presenting to emergency departments (EDs) at 118 VA Medical Centers between 1/1/2006 and 12/31/2016 with an initial clinical diagnosis of pneumonia and confirmed by chest imaging report.

EXPOSURES

Year of encounter.

MAIN MEASURES

Hospitalization and 30-day and 90-day mortality. Illness severity was defined as the probability of each outcome predicted by machine learning predictive models using age, sex, comorbidities, vital signs, and laboratory data from encounters during years 2006-2007, and similar models trained on encounters from years 2015 to 2016. We estimated the changes in hospitalizations and 30-day and 90-day mortality between the first and the last 2 years of the study period accounted for by illness severity using time covariate decompositions with model estimates.

RESULTS

Among 196,899 encounters across the study period, hospitalization decreased from 71 to 63%, 30-day mortality 10 to 7%, 90-day mortality 16 to 12%, and 1-year mortality 29 to 24%. Comorbidity risk increased, but illness severity decreased. Decreases in illness severity accounted for 21-31% of the decrease in hospitalizations, and 45-47%, 32-24%, and 17-19% of the decrease in 30-day, 90-day, and 1-year mortality. Findings were similar among underrepresented patients and those with only hospital discharge diagnosis codes.

CONCLUSIONS

Outcomes for community-onset pneumonia have improved across the VA healthcare system after accounting for illness severity, despite an increase in cases and comorbidity burden.

Mental Health Reform: Design and Implementation of a System to Optimize Outcomes for Veterans and Their Families

The social, health, and economic burden of mental health problems in the veteran community is heavy. Internationally, the array of services and support available to veterans and their families are extensive but vary in quality, are often disconnected, complex to navigate, and lack clear coordination. This paper describes a conceptual framework to guide the design and implementation of a system of services and supports to optimize the mental health and wellbeing of all veterans and their families. The framework recognizes the diversity of veterans across intersecting identities that uniquely shape experiences of posttraumatic mental health and wellbeing. It brings together several strands of research: the values and principles that should underpin the system; the needs of diverse veterans and their families; challenges in the current services and supports; evidence-based interventions; and principles of effective implementation. Central to the future system design is a next generation stepped model of care that organizes best and next practice interventions in a coherent system, matches service provision to level of need and addresses access and navigation. Practical guidance on implementation provides an aspirational and flexible structure for system evolution, and a template for all stakeholders-individuals, groups, agencies and organizations-to effect system change.

Association of Integrated Mental Health Services with Physical Health Quality Among VA Primary Care Patients

BACKGROUND

Integrated care for comorbid depression and chronic medical disease improved physical and mental health outcomes in randomized controlled trials. The Veterans Health Administration (VA) implemented Primary Care-Mental Health Integration (PC-MHI) across all primary care clinics nationally to increase access to mental/behavioral health treatment, alongside physical health management.

OBJECTIVE

To examine whether widespread, pragmatic PC-MHI implementation was associated with improved care quality for chronic medical diseases.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study included 828,050 primary care patients with at least one quality metric among 396 VA clinics providing PC-MHI services between October 2013 and September 2016.

MAIN MEASURE(S)

For outcome measures, chart abstractors rated whether diabetes and cardiovascular quality metrics were met for patients at each clinic as part of VA's established quality reporting program. The explanatory variable was the proportion of primary care patients seen by integrated mental health specialists in each clinic annually. Multilevel logistic regression models examined associations between clinic PC-MHI proportion and patient-level quality metrics, adjusting for regional, patient, and time-level effects and clinic and patient characteristics.

KEY RESULTS

Median proportion of patients seen in PC-MHI per clinic was 6.4% (IQR=4.7-8.7%). Nineteen percent of patients with diabetes had poor glycemic control (hemoglobin A1c >9%). Five percent had severely elevated blood pressure (>160/100 mmHg). Each two-fold increase in clinic PC-MHI proportion was associated with 2% lower adjusted odds of poor glycemic control (95% CI=0.96-0.99; p=0.046) in diabetes. While there was no association with quality for patients diagnosed with hypertension, patients without diagnosed hypertension had 5% (CI=0.92-0.99; p=0.046) lower adjusted odds of having elevated blood pressures.

CONCLUSIONS AND RELEVANCE

Primary care clinics where integrated mental health care reached a greater proportion of patients achieved modest albeit statistically significant gains in key chronic care quality metrics, providing optimism about the expected effects of large-scale PC-MHI implementation on physical health.

Quality Measures for Patients at Risk of Adverse Outcomes in the Veterans Health Administration: Expert Panel Recommendations

IMPORTANCE

Despite longstanding efforts to improve health care quality for patients with complex needs who are at highest risk for hospitalization or death, to our knowledge, no guidance exists on what constitutes measurable high-quality care for this heterogeneous population. Identifying quality measures that are cross-cutting (ie, relevant to multiple chronic conditions and disease states) may enable health care professionals and health care systems to better design and report on quality improvement efforts for this patient population.

OBJECTIVE

To identify quality measures of care and prioritize quality-of-care concepts in the ambulatory primary care setting for patients in the Veterans Health Administration (VHA) who have complex care needs and are at high risk for adverse outcomes, such as hospitalization or death.

EVIDENCE REVIEW

In this expert panel assessment and prioritization, relevant measure concepts for future quality measure development in 3 care categories (assessment, management, and other features of health care) were extracted from a systematic review, conducted from June 2020 to June 2021, of published studies that suggested, evaluated, or used indicators of quality care for patients at high risk of adverse outcomes. Measure concepts associated with single conditions, surgical or other specialty care settings, and inpatient care were excluded. A panel of 14 experts (10 VHA leaders and staff, 2 non-VHA physician investigators, and 2 veterans) discussed and rated the importance of the remaining set of potentially relevant measure concepts using a modified RAND/UCLA Appropriateness Method on January 15, 2021. Measure concepts were rated on a scale of 1 to 9, with 9 being the highest priority. A median rating of 7.5 or greater was used as the cutoff to identify the highest-priority items.

FINDINGS

The systematic review identified 519 measure concepts, from which 15 domains and 49 measure concepts were proposed for expert panel consideration. After panel discussions and changes to measure concepts, the expert panel rated 63 measure concepts in 13 domains. The measure concepts with the highest median ratings focused on caregiver availability and support, COVID-19 vaccination, and pneumonia vaccination (all rated 9.0); housing instability (rated 8.5); and physical function, depression symptoms, cognitive impairment, prescription regimen, primary care follow-up after an emergency department visit or hospitalization, and timely transmission of discharge information to primary care (all rated 8.0). Recommendations to improve care included timely assessment of housing instability, caregiver support, physical function, depression symptoms, and cognitive impairment; annual prescription regimen review; coordinated transitions in care; and preventive care including vaccinations.

CONCLUSIONS AND RELEVANCE

The expert panelists identified a parsimonious set of high-priority, evidence-based, cross-cutting quality measure concepts for improving care of patients at high risk for adverse health outcomes in the VHA. These quality measures may inform both future research for patients at high risk and health care system quality improvement.

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.

Factors affecting primary care physician decision-making for patients with complex multimorbidity: a qualitative interview study

BACKGROUND

Patients with multiple chronic conditions (multimorbidity) and additional psychosocial complexity are at higher risk of adverse outcomes. Establishing treatment or care plans for these patients must account for their disease interactions, finite self-management abilities, and even conflicting treatment recommendations from clinical practice guidelines. Despite existing insight into how primary care physicians (PCPs) approach care decisions for their patients in general, less is known about how PCPs make care planning decisions for more complex populations particularly within a medical home setting. We therefore sought to describe factors affecting physician decision-making when care planning for complex patients with multimorbidity within the team-based, patient-centered medical home setting in the integrated healthcare system of the U.S. Department of Veterans Affairs, the Veterans Health Administration (VHA).

METHODS

This was a qualitative study involving semi-structured telephone interviews with PCPs working > 40% time in VHA clinics. Interviews were conducted from April to July, 2020. Content was analyzed with deductive and inductive thematic analysis.

RESULTS

23 physicians participated in interviews; most were MDs (n = 21) and worked in hospital-affiliated clinics (n = 14) across all regions of the VHA's national clinic network. We found internal, external, and relationship-based factors, with developed subthemes describing factors affecting decision-making for complex patients with multimorbidity. Physicians described tailoring decisions to individual patients; making decisions in keeping with an underlying internal style or habit; working towards an overarching goal for care; considering impacts from patient access and resources on care plans; deciding within boundaries provided by organizational structures; collaborating on care plans with their care team; and impacts on decisions from their own emotions and relationship with patient.

CONCLUSIONS

PCPs described internal, external, and relationship-based factors that affected their care planning for high-risk and complex patients with multimorbidity in the VHA. Findings offer useful strategies employed by physicians to effectively conduct care planning for complex patients in a medical home setting, such as delegation of follow-up within multidisciplinary care teams, optimizing visit time vs frequency, and deliberate investment in patient-centered relationship building to gain buy-in to care plans.

Empiric segmentation of high-risk patients: a structured literature review

OBJECTIVES

Empiric segmentation is a rapidly growing, learning health system approach that uses large health care system data sets to identify groups of high-risk patients who may benefit from similar interventions. We aimed to review studies that used data-driven approaches to segment high-risk patient populations and describe how their designs and findings can inform health care leaders who are interested in applying similar techniques to their patient populations.

STUDY DESIGN

Structured literature review.

METHODS

We searched for original research articles published since 2000 that identified high-risk adult patient populations and applied data-driven analyses to segment the population. Two reviewers independently extracted study population source and criteria for high-risk designation, segmentation method, data types included, model selection criteria, and model results from the identified studies.

RESULTS

Our search identified 224 articles, 12 of which met criteria for full review. Of these, 8 segmented high-risk patients and 4 segmented diagnoses without assigning patients to unique groups. Studies segmenting patients more often had clinically interpretable results. Common groups were defined by high prevalence of diabetes, cardiovascular disease, psychiatric conditions including substance use disorders, and neurologic disease (eg, stroke). Few studies incorporated patients' functional or social factors. Resulting patient and diagnosis clusters varied in ways closely linked to the model inputs, patient population inclusion criteria, and health care system context.

CONCLUSIONS

Empiric segmentation can yield clinically relevant groups of patients with complex medical needs. Segmentation results are context dependent, suggesting the need for careful design and interpretation of segmentation models to ensure that results can inform clinical care and program design in the target setting.

What Is the Return on Investment of Caring for Complex High-need, High-cost Patients?

Randomized controlled trials to improve care for complex, high-need, high-cost patients have not consistently demonstrated a relative decrease in acute care utilization or cost savings. However, the Veterans Health Administration (VHA) has been able to glean lessons from these trials and generate realistic expectations for success. Lessons include the following: (1) combining population management tools (e.g., risk scores) and clinician judgment is more effective than either alone to identify the patients best suited for intensive management; (2) treatment adherence and engagement may contribute more to preventable emergency department visits and hospitalizations than care coordination; and (3) efforts should focus on assessing for and treating those risk factors that are most amenable to intervention. Because it is unlikely that cost savings can fund add-on intensive management programs, the VHA Office of Primary Care plans to incorporate those intensive management practices that are feasible into existing patient-centered medical homes as a high reliability organization.

Outcomes of a randomized quality improvement trial for high-risk Veterans in year two

OBJECTIVE

The Veterans Health Administration (VHA) conducted a randomized quality improvement evaluation to determine whether augmenting patient-centered medical homes with Primary care Intensive Management (PIM) decreased utilization of acute care and health care costs among patients at high risk for hospitalization. PIM was cost-neutral in the first year; we analyzed changes in utilization and costs in the second year.

DATA SOURCES

VHA administrative data for five demonstration sites from August 2013 to March 2019.

DATA SOURCES

Administrative data extracted from VHA's Corporate Data Warehouse.

STUDY DESIGN

Veterans with a risk of 90-day hospitalization in the top 10th percentile and recent hospitalization or emergency department (ED) visit were randomly assigned to usual primary care vs primary care augmented by PIM. PIM included interdisciplinary teams, comprehensive patient assessment, intensive case management, and care coordination services. We compared the change in mean VHA inpatient and outpatient utilization and costs (including PIM expenses) per patient for the 12-month period before randomization and 13-24 months after randomization for PIM vs usual care using difference-in-differences.

PRINCIPAL FINDINGS

Both PIM patients (n = 1902) and usual care patients (n = 1882) had a mean of 5.6 chronic conditions. PIM patients had a greater number of primary care visits compared to those in usual care (mean 4.6 visits/patient/year vs 3.7 visits/patient/year, p < 0.05), but ED visits (p = 0.45) and hospitalizations (p = 0.95) were not significantly different. We found a small relative increase in outpatient costs among PIM patients compared to those in usual care (mean difference + $928/patient/year, p = 0.053), but no significant differences in mean inpatient costs (+$245/patient/year, p = 0.97). Total mean health care costs were similar between the two groups during the second year (mean difference + $1479/patient/year, p = 0.73).

CONCLUSIONS

Approaches that target patients solely based on the high risk of hospitalization are unlikely to reduce acute care use or total costs in VHA, which already offers patient-centered medical homes.

Implementation of Telehealth Services at the US Department of Veterans Affairs During the COVID-19 Pandemic: Mixed Methods Study

Background

At the onset of the COVID-19 pandemic, there was a rapid increase in the use of telehealth services at the US Department of Veterans Affairs (VA), which was accelerated by state and local policies mandating stay-at-home orders and restricting nonurgent in-person appointments. Even though the VA was an early adopter of telehealth in the late 1990s, the vast majority of VA outpatient care continued to be face-to-face visits through February 2020.

Objective

We compared telehealth service use at a VA Medical Center, Greater Los Angeles across 3 clinics (primary care [PC], cardiology, and home-based primary care [HBPC]) 12 months before and 12 months after the onset of COVID-19 (March 2020).

Methods

We used a parallel mixed methods approach including simultaneous quantitative and qualitative approaches. The distribution of monthly outpatient and telehealth visits, as well as telephone and VA Video Connect encounters were examined for each clinic. Semistructured telephone interviews were conducted with 34 staff involved in telehealth services within PC, cardiology, and HBPC during COVID-19. All audiotaped interviews were transcribed and analyzed by identifying key themes.

Results

Prior to COVID-19, telehealth use was minimal at all 3 clinics, but at the onset of COVID-19, telehealth use increased substantially at all 3 clinics. Telephone was the main modality of patient choice. Compared with PC and cardiology, video-based care had the greatest increase in HBPC. Several important barriers (multiple steps for videoconferencing, creation of new scheduling grids, and limited access to the internet and internet-connected devices) and facilitators (flexibility in using different video-capable platforms, technical support for patients, identification of staff telehealth champions, and development of workflows to help incorporate telehealth into treatment plans) were noted.

Conclusions

Technological issues must be addressed at the forefront of telehealth evolution to achieve access for all patient populations with different socioeconomic backgrounds, living situations and locations, and health conditions. The unprecedented expansion of telehealth during COVID-19 provides opportunities to create lasting telehealth solutions to improve access to care beyond the pandemic.

Enhancing Primary Care Experiences for Homeless Patients with Serious Mental Illness: Results from a National Survey

Objectives:

Patients experiencing homelessness (PEH) with serious mental illness (SMI) have poor satisfaction with primary care. We assessed if primary care teams tailored for homeless patients (Homeless-Patient Aligned Care Teams (H-PACTs)) provide this population with superior experiences than mainstream primary care and explored whether integrated behavioral health and social services were associated with favorable experiences.

Methods:

We surveyed VA PEH with SMI (n = 1095) to capture the valence of their primary care experiences in 4 domains (Access/Coordination, Patient-Clinician Relationships, Cooperation, and Homeless-Specific Needs). We surveyed clinicians (n = 52) from 29 H-PACTs to elucidate if their clinics had embedded mental health, addiction, social work, and/or housing services. We counted these services in each H-PACT (0-4) and classified H-PACTs as having high (3-4) versus low (0-2) service integration. We controlled for demographics, housing history, and needs in comparing H-PACT versus mainstream experiences; and experiences in high versus low integration H-PACTs.

Results:

Among respondents, 969 (91%) had complete data and 626 (62%) were in H-PACTs. After covariate adjustment, compared to mainstream respondents, H-PACT respondents were more likely (P < .01) to report favorable experiences (AORs = 1.7-2.1) and less likely to report unfavorable experiences (AORs = 0.5-0.6) in all 4 domains. Of 29 H-PACTs, 27.6% had high integration. High integration H-PACT respondents were twice as likely as low integration H-PACT respondents to report favorable access/coordination experiences (AOR = 1.7).

Conclusions:

Homeless-tailored clinics with highly-integrated services were associated with better care experiences among PEH with SMI. These observational data suggest that tailored primary care with integrated services may improve care perceptions among complex patients.

Diagnostic Accuracy and Acceptability of the Primary Care Posttraumatic Stress Disorder Screen for the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) Among US Veterans

Importance

Posttraumatic stress disorder (PTSD) is a serious mental health disorder that can be effectively treated with empirically based practices. PTSD screening is essential for identifying undetected cases and providing patients with appropriate care.

Objective

To determine whether the Primary Care PTSD screen for the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (PC-PTSD-5) is a diagnostically accurate and acceptable measure for use in Veterans Affairs (VA) primary care clinics.

Design, Setting, and Participants

This cross-sectional, diagnostic accuracy study enrolled participants from May 19, 2017, to September 26, 2018. Participants were recruited from primary care clinics across 2 VA Medical Centers. Session 1 was conducted in person, and session 2 was completed within 30 days via telephone. A consecutive sample of 1594 veterans, aged 18 years or older, who were scheduled for a primary care visit was recruited. Data analysis was performed from March 2019 to August 2020.

Exposures

In session 1, participants completed a battery of questionnaires. In session 2, a research assistant administered the PC-PTSD-5 to participants, and then a clinician assessor blind to PC-PTSD-5 results conducted a structured diagnostic interview for PTSD.

Main Outcomes and Measures

The range of PC-PTSD-5 cut points overall and across gender was assessed, and diagnostic performance was evaluated by calculating weighted κ values.

Results

In total, 495 of 1594 veterans (31%) participated, and 396 completed all measures and were included in the analyses. Participants were demographically similar to the VA primary care population (mean [SD] age, 61.4 [15.5] years; age range, 21-93 years) and were predominantly male (333 participants [84.1%]) and White (296 of 394 participants [75.1%]). The PC-PTSD-5 had high levels of diagnostic accuracy for the overall sample (area under the receiver operating characteristic curve [AUC], 0.927; 95% CI, 0.896-0.959), men (AUC, 0.932; 95% CI, 0.894-0.969), and women (AUC, 0.899, 95% CI, 0.824-0.974). A cut point of 4 ideally balanced false negatives and false positives for the overall sample and for men. However, for women, this cut point resulted in high numbers of false negatives (6 veterans [33.3%]). A cut point of 3 fit better for women, despite increasing the number of false positives. Participants rated the PC-PTSD-5 as highly acceptable.

Conclusions and Relevance

The PC-PTSD-5 is an accurate and acceptable screening tool for use in VA primary care settings. Because performance parameters will change according to sample, clinicians should consider sample characteristics and screening purposes when selecting a cut point.