Clinical Outcome and Utilization Profiles Among Latent Groups of High-Risk Patients: Moving from Segmentation Towards Intervention.

BACKGROUND: The ability of latent class models to identify clinically distinct groups among high-risk patients has been demonstrated, but it is unclear how healthcare data can inform group-specific intervention design. OBJECTIVE: Examine how utilization patterns across latent groups of high-risk patients provide actionable information to guide group-specific intervention design. DESIGN: Cohort study using data from 2012 to 2015. PATIENTS: Participants were 934,787 patients receiving primary care in the Veterans Health Administration, with predicted probability of 12-month hospitalization in the top 10th percentile during 2014. MAIN MEASURES: Patients were assigned to latent groups via mixture-item response theory models based on 28 chronic conditions. We modeled odds of all-cause mortality, hospitalizations, and 30-day re-hospitalizations by group membership. Detailed outpatient and inpatient utilization patterns were compared between groups. KEY RESULTS: A total of 764,257 (81.8%) of patients were matched with a comorbidity group. Groups were characterized by substance use disorders (14.0% of patients assigned), cardiometabolic conditions (25.7%), mental health conditions (17.6%), pain/arthritis (19.1%), cancer (15.3%), and liver disease (8.3%). One-year mortality ranged from 2.7% in the Mental Health group to 14.9% in the Cancer group, compared to 8.5% overall. In adjusted models, group assignment predicted significantly different odds of each outcome. Groups differed in their utilization of multiple types of care. For example, patients in the Pain group had the highest utilization of in-person primary care, with a mean (SD) of 5.3 (5.0) visits in the year of follow-up, while the Substance Use Disorder group had the lowest, with 3.9 (4.1) visits. The Substance Use Disorder group also had the highest rates of using services for housing instability (25.1%), followed by the Liver group (10.1%). CONCLUSIONS: Latent groups of high-risk patients had distinct hospitalization and utilization profiles, despite having comparable levels of predicted baseline risk. Utilization profiles pointed towards system-specific care needs that could inform tailored interventions.

Components of the Patient-Centered Medical Home Associated with Perceived Access to Primary Care.

BACKGROUND: Following implementation of the patient-centered medical home (PCMH) within the Department of Veterans Affairs (VA), access to primary care improved. However, understanding of how this occurred is lacking. OBJECTIVE: To examine the association between organizational aspects of the PCMH model and access-related initiatives with patient perception of access to urgent, same-day, and routine care within the VA. DESIGN: Cross-sectional PARTICIPANTS: Veterans who responded to the annual Survey of Healthcare Experiences of Patients in 2016 (N = 241,122 patients) and primary staff who responded to VA National Primary Care Provider and Staff Survey (N = 4815 staff). MAIN MEASURES: Three outcomes of perception of access: percentage of patients responding in the highest category for same-day care (waiting ≤ 1 day), urgent care (always receiving care when needed), and routine care (always receiving checkups when desired). Predictors were staff-level report of access-related initiatives and organizational factors in the clinic. We used generalized estimating equations to model associations, adjusting for characteristics of patients and their respective clinics. KEY RESULTS: Access was significantly better in clinics where staff reviewed performance reports (+ 0.9% in the highest perception of access for urgent care, P < 0.01; + 1.2% for routine care, P < 0.001), leadership was supportive of the PCMH (+ 1.6% for urgent care, P < 0.01), and initiatives to improve access included open access (+ 0.8% to + 1.7% across all outcomes, P < 0.01) and telehealth visits (+ 1.2% to + 1.4%, P < 0.001). Perceived access was worse in clinics with moderate staff burnout (- 1.1% to - 1.4%, P < 0.001), primary care provider turnover during the past year (- 1.0% to - 1.6%, P < 0.001), or medical support assistant turnover in the past year (- 0.9% to - 1.4%, P < 0.001). CONCLUSIONS: Perception of access was strongly associated with identifiable organizational factors and access-related initiatives within VA primary care clinics that could be adopted by other health systems.

Mortality Among Veterans with Major Mental Illnesses Seen in Primary Care: Results of a National Study of Veteran Deaths.

BACKGROUND: Premature mortality observed among the mentally ill is largely attributable to chronic illnesses. Veterans seen within Veterans Affairs (VA) have a higher prevalence of mental illness than the general population but there is limited investigation into the common causes of death of Veterans with mental illnesses. OBJECTIVE: To characterize the life expectancy of mentally ill Veterans seen in VA primary care, and to determine the most death rates of combinations of mental illnesses. DESIGN: Retrospective cohort study of decedents. SETTING/PARTICIPANTS: Veterans seen in VA primary care clinics between 2000 and 2011 were included. Records from the VA Corporate Data Warehouse (CDW) were merged with death information from the National Death Index. MAIN MEASURES: Mental illnesses were determined using ICD9 codes. Direct standardization methods were used to calculate age-adjusted gender and cause-specific death rates per 1000 deaths for patients with and without depression, anxiety, post-traumatic stress disorder (PTSD), substance use disorder (SUD), serious mental illness (SMI), and combinations of those diagnoses. KEY RESULTS: Of the 1,763,982 death records for Veterans with 1 + primary care visit, 556,489 had at least one mental illness. Heart disease and cancer were the two leading causes of death among Veterans with or without a mental illness, accounting for approximately 1 in 4 deaths. Those with SUD (n = 204,950) had the lowest mean age at time of death (64 ± 12 years). Among men, the death rates were as follows: SUD (55.9/1000); anxiety (49.1/1000); depression (45.1/1000); SMI (40.3/1000); and PTSD (26.2/1000). Among women, death rates were as follows: SUD (55.8/1000); anxiety (36.7/1000); depression (45.1/1000); SMI (32.6/1000); and PTSD (23.1/1000 deaths). Compared to men (10.8/1000) and women (8.7/1000) without a mental illness, these rates were multiple-fold higher in men and in women with a mental illness. A greater number of mental illness diagnoses was associated with higher death rates among men and women (p < 0.0001). CONCLUSIONS: Veterans with mental illnesses, particularly those with SUD, and those with multiple diagnoses, had shorter life expectancy than those without a mental illness. Future studies should examine both patient and systemic sources of disparities in providing chronic illness care to Veterans with a mental illness.

Use of Chronic Care Management Among Primary Care Clinicians.

The Centers for Medicare and Medicade Services (CMS) initiated chronic care management (CCM) codes to reimburse clinicians for coordination activities, but little is known about uptake over time. We find that primary care clinicians drove increasing use over 4 years-a trend that may reflect either new coordination activities or new reimbursements for existing activities. That 5% of chronic care management was denied by Medicare underscores the need for future work evaluating facilitators and barriers to use. Such insight is especially vital given the large number of eligible beneficiaries that have not received chronic care management to date, as well as the limited number of clinicians who currently deliver these services.

Patient-Reported Access in the Patient-Centered Medical Home and Avoidable Hospitalizations: an Observational Analysis of the Veterans Health Administration.

BACKGROUND: The Patient-Centered Medical Home (PCMH) has emphasized timely access to primary care, often by using non-traditional modes of delivery, such as care in person after-hours or by phone during or after normal hours. Limited data exists on whether improving patient-reported access with these service types reduces hospitalization. OBJECTIVE: To examine the association of patient-reported access to primary care within the Veteran Health Administration (VHA) via five service types and hospitalizations for ambulatory care sensitive conditions (ACSCs). DESIGN: Retrospective cohort study, using multivariable logistic regression adjusting for patient demographics, comorbidity, characteristics of patients' area of residence, and clinic-level random effects. PARTICIPANTS: A total of 69,710 VHA primary care patients who responded to the 2012 Survey of Healthcare Experiences of Patients (SHEP), PCMH module. MAIN MEASURES: Survey questions captured patients' ability to obtain care from VHA for five service types: routine care, immediate care, after-hours care, care by phone during regular office hours, and care by phone after normal hours. Outcomes included binary measures of hospitalization for overall, acute, and chronic ACSCs in 2013, identified in VHA administrative data and Medicare fee-for-service claims. KEY RESULTS: Patients who reported "always" able to obtain after-hours care compared to "never" were less likely to be hospitalized for chronic ACSCs (OR 0.62, 95% CI 0.44-0.89, p = 0.009). Patients reporting "usually" getting care by phone during regular hours were more likely have a hospitalization for chronic ACSC (OR 1.49, 95% CI 1.03-2.17, p = 0.034). Experiences with routine care, immediate care, and care by phone after-hours demonstrated no significant association with hospitalization for ACSCs. CONCLUSIONS: Improving patients' ability to obtain after-hours care was associated with fewer hospitalizations for chronic ACSCs, while access to care by phone during regular hours was associated with more hospitalizations. Health systems should consider the benefits, including reduced hospitalizations for chronic ACSCs, against the costs of implementing each of these PCMH services.

Coordinating Care Across VA Providers and Settings: Policy and Research Recommendations from VA's State of the Art Conference.

Delivering well-coordinated care is essential for optimizing clinical outcomes, enhancing patient care experiences, minimizing costs, and increasing provider satisfaction. The Veterans Health Administration (VA) has built a strong foundation for internally coordinating care. However, VA faces mounting internal care coordination challenges due to growth in the number of Veterans using VA care, high complexity in Veterans' care needs, the breadth and depth of VA services, and increasing use of virtual care. VA's Health Services Research and Development service with the Office of Research and Development held a conference assessing the state-of-the-art (SOTA) on care coordination. One workgroup within the SOTA focused on coordination between VA providers for high-need Veterans, including (1) Veterans with multiple chronic conditions; (2) Veterans with high-intensity, focused, specialty care needs; (3) Veterans experiencing care transitions; (4) Veterans with severe mental illness; (5) and Veterans with homelessness and/or substance use disorders. We report on this workgroup's recommendations for policy and organizational initiatives and identify questions for further research. Recommendations from a separate workgroup on coordinating VA and non-VA care are contained in a companion paper. Leaders from research, clinical services, and VA policy will need to partner closely as they develop, implement, assess, and spread effective practices if VA is to fully realize its potential for delivering highly coordinated care to every Veteran.

Identifying Latent Subgroups of High-Risk Patients Using Risk Score Trajectories.

OBJECTIVE: Many healthcare systems employ population-based risk scores to prospectively identify patients at high risk of poor outcomes, but it is unclear whether single point-in-time scores adequately represent future risk. We sought to identify and characterize latent subgroups of high-risk patients based on risk score trajectories. STUDY DESIGN: Observational study of 7289 patients discharged from Veterans Health Administration (VA) hospitals during a 1-week period in November 2012 and categorized in the top 5th percentile of risk for hospitalization. METHODS: Using VA administrative data, we calculated weekly risk scores using the validated Care Assessment Needs model, reflecting the predicted probability of hospitalization. We applied the non-parametric k-means algorithm to identify latent subgroups of patients based on the trajectory of patients' hospitalization probability over a 2-year period. We then compared baseline sociodemographic characteristics, comorbidities, health service use, and social instability markers between identified latent subgroups. RESULTS: The best-fitting model identified two subgroups: moderately high and persistently high risk. The moderately high subgroup included 65% of patients and was characterized by moderate subgroup-level hospitalization probability decreasing from 0.22 to 0.10 between weeks 1 and 66, then remaining constant through the study end. The persistently high subgroup, comprising the remaining 35% of patients, had a subgroup-level probability increasing from 0.38 to 0.41 between weeks 1 and 52, and declining to 0.30 at study end. Persistently high-risk patients were older, had higher prevalence of social instability and comorbidities, and used more health services. CONCLUSIONS: On average, one third of patients initially identified as high risk stayed at very high risk over a 2-year follow-up period, while risk for the other two thirds decreased to a moderately high level. This suggests that multiple approaches may be needed to address high-risk patient needs longitudinally or intermittently.

The Burden of Mental Illness Among Veterans: Use of VHA Health Care Services by Those With Service-connected Conditions.

BACKGROUND: Little is known about how Veterans with service-connected conditions use health care provided by the Veterans Health Administration (VHA). OBJECTIVES: To ascertain what proportion of Veterans with service-connected conditions used VHA health care and whether it varied according to type of condition, combined disability rating, age, sex, military rank, or other characteristics and whether there were differences in receipt of inpatient and outpatient care. RESEARCH DESIGN: Cross-sectional analysis of administrative benefits and claims data for 2015 and 2016. SUBJECTS: In total, 4,029,672 Veterans who had an active award status for service-connected conditions in October 2016. MEASURES: Independent variables included age, sex, military rank, service branch, combined disability rating, Agent Orange exposure, and type of service-connected condition. The key-dependent variable was VHA health care use including specific types of health care utilization such as inpatient and outpatient services. RESULTS: In total, 52% of those with service-connected conditions used VHA health care. Type of condition and disability rating were associated with use. Over 65% of those with major depression, posttraumatic stress disorder (PTSD), Agent Orange exposure, or diabetes used VHA health care, as did 76% of those with a 100% rating. Almost one third of users of VHA health care were compensated for PTSD. In general, both inpatient and outpatient mental health services were frequently used by Veterans with service-connected mental health conditions. CONCLUSIONS: Veterans with service-connected conditions, particularly those with diabetes or mental illness such as depression or PTSD, depend heavily upon VHA for health care, including mental health services.

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.

The Association of Team-Specific Workload and Staffing with Odds of Burnout Among VA Primary Care Team Members.

BACKGROUND: Work-related burnout is common in primary care and is associated with worse patient safety, patient satisfaction, and employee mental health. Workload, staffing stability, and team completeness may be drivers of burnout. However, few studies have assessed these associations at the team level, and fewer still include members of the team beyond physicians. OBJECTIVE: To study the associations of burnout among primary care providers (PCPs), nurse care managers, clinical associates (MAs, LPNs), and administrative clerks with the staffing and workload on their teams. DESIGN: We conducted an individual-level cross-sectional analysis of survey and administrative data in 2014. PARTICIPANTS: Primary care personnel at VA clinics responding to a national survey. MAIN MEASURES: Burnout was measured with a validated single-item survey measure dichotomized to indicate the presence of burnout. The independent variables were survey measures of team staffing (having a fully staffed team, serving on multiple teams, and turnover on the team), and workload both from survey items (working extended hours), and administrative data (patient panel overcapacity and average panel comorbidity). KEY RESULTS: There were 4610 respondents (estimated response rate of 20.9%). The overall prevalence of burnout was 41%. In adjusted analyses, the strongest associations with burnout were having a fully staffed team (odds ratio [OR] = 0.55, 95% CI 0.47-0.65), having turnover on the team (OR = 1.67, 95% CI 1.43-1.94), and having patient panel overcapacity (OR = 1.19, 95% CI 1.01-1.40). The observed burnout prevalence was 30.1% lower (28.5% vs. 58.6%) for respondents working on fully staffed teams with no turnover and caring for a panel within capacity, relative to respondents in the inverse condition. CONCLUSIONS: Complete team staffing, turnover among team members, and panel overcapacity had strong, cumulative associations with burnout. Further research is needed to understand whether improvements in these factors would lower burnout.

Facility-Level Variation in Hospitalization, Mortality, and Costs in the 30 Days After Percutaneous Coronary Intervention: Insights on Short-Term Healthcare Value From the Veterans Affairs Clinical Assessment, Reporting, and Tracking System (VA CART) Program.

BACKGROUND: Policies to reduce unnecessary hospitalizations after percutaneous coronary intervention (PCI) are intended to improve healthcare value by reducing costs while maintaining patient outcomes. Whether facility-level hospitalization rates after PCI are associated with cost of care is unknown. METHODS AND RESULTS: We studied 32,080 patients who received PCI at any 1 of 62 Veterans Affairs hospitals from 2008 to 2011. We identified facility outliers for 30-day risk-standardized hospitalization, mortality, and cost. Compared with the risk-standardized average, 2 hospitals (3.2%) had a lower-than-expected hospitalization rate, and 2 hospitals (3.2%) had a higher-than-expected hospitalization rate. We observed no statistically significant variation in facility-level risk-standardized mortality. The facility-level unadjusted median per patient 30-day total cost was $23,820 (interquartile range, $19,604-$29,958). Compared with the risk-standardized average, 17 hospitals (27.4%) had lower-than-expected costs, and 14 hospitals (22.6%) had higher-than-expected costs. At the facility level, the index PCI accounted for 83.1% of the total cost (range, 60.3%-92.2%), whereas hospitalization after PCI accounted for only 5.8% (range, 2.0%-12.7%) of the 30-day total cost. Facilities with higher hospitalization rates were not more expensive (Spearman ρ=0.16; 95% confidence interval, -0.09 to 0.39; P=0.21). CONCLUSIONS: In this national study, hospitalizations in the 30 day after PCI accounted for only 5.8% of 30-day cost, and facility-level cost was not correlated with hospitalization rates. This challenges the focus on reducing hospitalizations after PCI as an effective means of improving healthcare value. Opportunities remain to improve PCI value by reducing the variation in total cost of PCI without compromising patient outcomes.

A First Look at PCMH Implementation for Minority Veterans: Room for Improvement.

BACKGROUND: Implementation of Patient Aligned Care Teams (PACT), a patient-centered medical home model, has been inconsistent among the >900 primary care facilities in the Veterans Health Administration. OBJECTIVE: Estimate if the degree of PACT implementation at a facility varied with the percentage of minority veteran patients at the facility. RESEARCH DESIGN: Cross-sectional, facility-level analysis of PACT implementation measures in 2012. SUBJECTS: Veterans Health Administration hospital-based and community-based primary care facilities. MEASURES: We used a previously validated PACT Implementation Progress Index (Pi) and its 8 domains: access, continuity of care, care coordination, comprehensiveness, self-management support, and patient-centered care and communication, shared decision-making domains, and team functioning. Facilities were categorized as low (<5.2%, n=208), medium (5.2%-25.8%, n=413), and high (>25.8%, n=206) percent minority based on the percent of their own veteran population. RESULTS: Most minority veterans received care in high minority (69%) and medium minority facilities (29%). In adjusted analyses, medium and high minority facilities scored 0.773 (P=0.009) and 0.930 (P=0.008) points lower on the Pi score relative to low minority facilities. Relative to low minority facilities, both medium and high minority facilities were less likely of having high Pi scores (≥2) and more likely of having low Pi scores (≤-2). Both medium and high minority facilities had the same 3 domain scores lower than low minority facilities (care coordination, comprehensiveness, and self-management). CONCLUSION: Overall PACT implementation varied with respect to the racial/ethnic composition of a facility, with medium and high minority facilities having a lower implementation scores.

Patient-Centered Medical Home Implementation in the Veterans Health Administration and Primary Care Use: Differences by Patient Comorbidity Burden.

BACKGROUND: The patient-centered medical home (PCMH) model has several components to improve care for patients with high comorbidity, including greater access to face-to-face primary care. OBJECTIVE: We examined whether high-comorbidity patients had larger increases in primary care provider (PCP) visits attributable to PCMH implementation in a large integrated health system relative to other patients enrolled in primary care. DESIGN, SUBJECTS AND MAIN MEASURES: This longitudinal study examined a 1 % random sample of 9.3 million patients enrolled in the Veterans Health Administration (VHA) at any time between 2003 and 2013. Face-to-face visits with PCPs per quarter were identified through VHA administrative data. Comorbidity was measured using the Gagne index and patients with a weighted score of ≥ 2 were defined as high comorbidity. We applied interrupted time-series models to estimate marginal changes in PCP visits attributable to PCMH implementation. Differences in marginal changes were calculated across comorbidity groups (high vs. low). Analyses were stratified by age group to account for Medicare eligibility. KEY RESULTS: Among age 65+ patients, PCMH was associated with greater PCP visits starting four and ten quarters following implementation for high- and low-comorbidity patients, respectively. Changes were larger for high-comorbidity patients (eight to 11 greater visits per 1000 patients per quarter). Among patients age < 65, PCMH was associated with greater visits for high-comorbidity patients starting eight quarters following implementation, but fewer visits for low-comorbidity patients in all quarters. The difference in visit changes across groups ranged from 18 to 67 visits per 1000 patients per quarter. CONCLUSIONS: Increases in PCP visits attributable to PCMH were greater among patients with higher comorbidity. Health systems implementing PCMH should account for population-level comorbidity burden when planning for PCMH-related changes in PCP utilization.

The experience of Patient Aligned Care Team (PACT) members.

BACKGROUND: In April 2010, the Veterans Health Administration (VHA) launched the Patient Aligned Care Team (PACT) initiative to implement a patient-centered medical home (PCMH) model. Few evaluations have addressed the effects of PCMH on health care professionals' experiences. PURPOSES: The aim of this study was to contribute to evaluation of the PACT initiative and the broader literature on PCMH by assessing respondents' experiences of implementing a PCMH model and becoming a teamlet. METHODOLOGY/APPROACH: A retrospective qualitative analysis of open-text responses in a survey fielded to all VHA Primary Care personnel (VHA Primary Care physicians, nurse practitioners, physician assistants, nurse care managers, clinical associates, and administrative clerks) in May and June 2012 (approximately 2 years into the 5-year planned implementation of PACT) using deductive and inductive content analysis. The main measures were two open-response fields: "Is there anything else you would like us to relay to the VA leadership in Central Office?" and "Do you have any other comments or feedback on PACT?" The data consisted of free text responses of 3,868 survey participants who provided text for one or both of the open-response fields. FINDINGS: Although respondents viewed PACT positively as a model and reported it improved relationships with patients and increased patient satisfaction, they described multiple barriers to achieving functioning teamlets and unintended consequences, including reduced time with patients, increased participant burnout, and decreased team efficacy because of low-performing team members. A central theme related to staffing being insufficient for the new model. PRACTICE IMPLICATIONS: Insufficient staffing of PCMH teams is a critical barrier to realizing the benefits of the new model. Frontline staff have concrete recommendations for other problems, such as using back-up teams to cover during absences, but that will require providing more opportunities for feedback from staff to be heard.

Using a single item to measure burnout in primary care staff: a psychometric evaluation.

BACKGROUND: Burnout affects nearly half of all U.S. nurses and physicians, and has been linked to poor outcomes such as worse patient safety. The most common measure of burnout is the well-validated Maslach Burnout Inventory (MBI). However, the MBI is proprietary and carries licensing fees, posing challenges to routine or repeated assessment. OBJECTIVE: To compare a non-proprietary, single-item burnout measure to a single item from the MBI Emotional Exhaustion (MBI:EE) subscale that has been validated as a standalone burnout measure. DESIGN: Cross-sectional online survey. PARTICIPANTS: A sample of primary care providers (PCPs), registered nurses, clinical associates (e.g., licensed practical nurses (LPNs), medical technicians), and administrative clerks in the Veterans Health Administration surveyed in 2012. MAIN METHODS: We compared a validated one-item version of the MBI:EE and a non-proprietary single-item burnout measure used in the Physician Work Life Study. We calculated kappa statistics, sensitivity and specificity, positive predictive (PPV) and negative predictive values (NPV), and area under the receiver operator curve (AUC). We conducted analyses stratified by occupation to determine the stability of the correlation between the two measures. KEY RESULTS: We analyzed responses from 5,404 participants, including 1,769 providers and 1,380 registered nurses. The prevalence of burnout was 36.7% as measured on the single MBI:EE item and 38.5% as measured on the non-proprietary single-item measure. Relative to the MBI:EE, the non-proprietary single-item measure had a correlation of 0.79, sensitivity of 83.2%, specificity of 87.4%, and AUC of 0.93 (se = 0.004). Results were similar when stratified by respondent occupation. CONCLUSIONS: A non-proprietary single-item measure served as a reliable substitute for the MBI:EE across occupations. Because it is non-proprietary and easy to interpret, it has logistical advantages over the one-item MBI.

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.