Impact of Medical Training Programs on Time-to-Fill Physician Vacancies at the Veterans Health Administration.

BACKGROUND: The Department of Veterans Affairs (VA) provides the largest Graduate Medical Education (GME) training platform for health professionals in the United States. Studies on the impact of VA GME programs on physician recruitment were lacking. OBJECTIVES: To examine the impact of the size of residency training programs at a VA facility on the facility's time-to-fill physician vacancies, and whether the impact differs by the socioeconomic deprivation and public school quality of the geographic area. PROJECT DESIGN: We constructed an instrumental variable for training program size by interacting the facility clinicians share with the total training allocation nationally. SUBJECTS: Our evaluation used national data on filled physician vacancies in the VA that were posted between 2020 and 2021. MEASURES: The outcome evaluated was time-to-fill physician vacancies. Our explanatory variable was the facility-year level number of physician residency slots. RESULTS: For positions posted in 2020, an increase of one training slot was significantly associated with a decrease of 1.33 days to fill physician vacancies (95% CI, 0.38-2.28) in facilities in less deprived areas, a decrease of 1.50 days (95% CI, 0.75-2.25) in facilities with better public schools, a decrease of 3.30 days (95% CI, 0.85-5.76) in facilities in both less deprived areas and better public schools. We found similar results for positions posted in 2020 and 2021 when limiting time-to-fill to <500 days. CONCLUSIONS: We found that increasing the size of the residency program at a VA facility could decrease the facility's time-to-fill vacant physician positions in places with less socioeconomic deprivation or better public schools.

Impact of Nurse Residency Program on Time-to-Fill Nurse Vacancies at the Veterans Health Administration.

BACKGROUND: The Department of Veterans Affairs (VA) offers a 1-year Post-Baccalaureate-Registered Nurse Residency (PB-RNR) Program. The impact of the PB-RNR program on local RN recruitment was unknown. OBJECTIVES: We aimed to evaluate the effect of the size of the PB-RNR program at a VA facility on its time-to-fill RN vacancies. PROJECT DESIGN: We used an instrumental variable approach with a 2-stage residual inclusion specification. SUBJECTS: We included RN filled vacancies in the VA that were posted nationwide between 2020 and 2021. MEASURES: Our independent variable was the facility-year level number of PB-RNR program allocations. The 3 binary outcomes were whether the RN vacancy was filled within 90, 60, or 30 days. RESULTS: An increase of one training allocation was significantly associated with a 5.60 percentage point (PP) (95% CI: 2.74-8.46) higher likelihood of filling a vacancy within 90 days, 7.34 PP (95% CI: 4.66-10.03) higher likelihood of filling a vacancy within 60 days, and 5.32 PP (95% CI: 3.18-7.46) higher likelihood of filling a vacancy within 30 days. The impact was significant in both 2020 and 2021 positions, and in facilities located in areas with lower social deprivation scores, higher-quality public schools, or with either no or partial primary care physician shortages. CONCLUSIONS: We found favorable impacts of the size of the PB-RNR program at a VA facility on filling RN vacancies.

Costs and Productivity Benefits of the Department of Veterans Affairs Maintaining Internal Systems and Strengthening Integrated Outside Networks Act Scribes Trial.

OBJECTIVES: To improve access, the VA Maintaining Internal Systems and Strengthening Integrated Outside Networks (MISSION) Act of 2018 mandated a 2-year study of medical scribes in Veterans Health Administration specialty clinics and emergency departments. Medical scribes are employed in clinical settings with the goals of increasing provider productivity and satisfaction by minimizing physicians' documentation burden. Our objective is to quantify the economic outcomes of the MISSION Act scribes trial. METHODS: A cluster-randomized trial was designed with 12 Department of Veterans Affairs (VA) medical centers randomized into the intervention. We estimated the total cost of the trial, cost per scribe-year, and projected cost of hiring additional physicians to achieve the observed scribe productivity benefits in relative value units and visits per full-time-equivalent over the 2-year intervention period (June 30, 2020 to July 1, 2022). RESULTS: The estimated cost of the trial was $4.6 million, below the Congressional Budget Office estimate of $5 million. A full-time scribe-year cost approximately $74 600 through contracting and $62 900 through VA hiring. Randomization into the trial led to an approximate 30% increase in productivity in cardiology and 20% in orthopedics. The projected incremental cost of using additional physicians instead of scribes to achieve the same productivity benefits was nearly $1.7 million more, or 75% higher, than the observed cost of scribes in cardiology and orthopedics. CONCLUSIONS: As the largest randomized trial of scribes to date, the MISSION Act scribes trial provides important evidence on the costs and benefits of scribes. Improving productivity enhances access and scribes may give VA a new tool to improve productivity in specialty care at a lower cost than hiring additional providers.

Differences in adverse outcomes across race and ethnicity among Veterans with similar predicted risks of an overdose or suicide-related event.

OBJECTIVE: To evaluate the degree to which differences in incidence of mortality and serious adverse events exist across patient race and ethnicity among Veterans Health Administration (VHA) patients receiving outpatient opioid prescriptions and who have similar predicted risks of adverse outcomes. Patients were assigned scores via the VHA Stratification Tool for Opioid Risk Mitigation (STORM), a model used to predict the risk of experiencing overdose- or suicide-related health care events or death. Individuals with the highest STORM risk scores are targeted for case review. DESIGN: Retrospective cohort study of high-risk veterans who received an outpatient prescription opioid between 4/2018-3/2019. SETTING: All VHA medical centers. PARTICIPANTS: In total, 84 473 patients whose estimated risk scores were between 0.0420 and 0.0609, the risk scores associated with the top 5%-10% of risk in the STORM development sample. METHODS: We examined the expected probability of mortality and serious adverse events (SAEs; overdose or suicide-related events) given a patient's risk score and race. RESULTS: Given a similar risk score, Black patients were less likely than White patients to have a recorded SAE within 6 months of risk score calculation. Black, Hispanic, and Asian patients were less likely than White patients with similar risk scores to die within 6 months of risk score calculation. Some of the mortality differences were driven by age differences in the composition of racial and ethnic groups in our sample. CONCLUSIONS: Our results suggest that relying on the STORM model to identify patients who may benefit from an interdisciplinary case review may identify patients with clinically meaningful differences in outcome risk across race and ethnicity.

Effect of the Maintaining Internal Systems and Strengthening Integrated Outside Networks (MISSION) Act Scribes Trial on Emergency Department Provider Productivity and Patient Throughput Times.

BACKGROUND: To help improve access to care, section 507 of the VA MISSION (Maintaining Internal Systems and Strengthening Integrated Outside Networks) Act of 2018 mandated a 2-year trial of medical scribes in the Veterans Health Administration (VHA). OBJECTIVE: The impact of scribes on provider productivity and patient throughput time in VHA emergency departments (EDs) was evaluated. METHODS: A clustered randomized trial was designed using intent-to-treat difference-in-differences analysis. The intervention period was from June 30, 2020 to July 1, 2022. The trial included six intervention and six comparison ED clinics. Two ED providers who volunteered to participate in the trial were assigned two scribes each. Scribes assisted providers with documentation and visit-related activities. The outcomes were provider productivity and patient throughput time per clinic-pay period. RESULTS: Randomization to intervention resulted in decreased provider productivity and increased patient throughput time. In adjusted regression models, randomization to scribes was associated with a decrease of 8.4 visits per full-time equivalent (95% confidence interval [CI] 12.4-4.3; p < 0.001) and 0.5 patients per day per provider (95% CI 0.8-0.3; p < 0.001). Intervention was associated with increases in length of stay of 29.1 min (95% CI 21.2-36.9 min; p < 0.001), 6.3 min in door to doctor (95% CI 2.9-9.6 min; p < 0.001), 19.5 min in door to disposition (95% CI 13.2-25.9 min; p < 0.001), and 13.7 min in doctor to disposition (95% CI 8.8-18.6 min; p < 0.001). CONCLUSIONS: Scribes were associated with decreased provider productivity and increased patient throughput time in VHA EDs. Although scribes may have contributed to improvements in other dimensions of quality, further examination of the ways in which scribes were used is advisable before widespread adoption in VHA EDs.

Excess Mortality at Veterans Health Administration Facilities During the COVID-19 Pandemic.

IMPORTANCE: The COVID-19 pandemic resulted in excess mortality among the general US population and at Veterans Health Administration (VHA) facilities. It is critical to understand the characteristics of facilities that experienced the highest and lowest pandemic-related mortality to inform future mitigation efforts. OBJECTIVE: To identify facility-level excess mortality during the pandemic and to correlate these estimates with facility characteristics and community-wide rates of COVID-19 burden. DESIGN: We used pre-pandemic data to estimate mortality risk prediction models using 5-fold cross-validation and Poisson quasi-likelihood regression. We then estimated excess mortality and observed versus expected (O/E) mortality ratios by the VHA facility from March to December 2020. We examined facility-level characteristics by excess mortality quartile. PARTICIPANTS: Overall, there were 11.4 million VHA enrollees during 2016 and 2020. MAIN MEASURES: Facility-level O/E mortality ratios and excess all-cause mortality. RESULT: VHA-enrolled veterans experienced 52,038 excess deaths from March to December 2020, equating to 16.8% excess mortality. Facility-specific rates ranged from -5.5% to +63.7%. Facilities in the lowest quartile for excess mortality experienced fewer COVID-19 deaths (0.7-1.51, P <0.001) and cases (52.0-63.0, P =0.002) per 1,000 population compared with the highest quartile. The highest quartile facilities had more hospital beds (276.7-187.6, P =0.024) and a higher percent change in the share of visits conducted via telehealth from 2019 to 2020 (183%-133%, P <0.008). CONCLUSIONS: There was a large variation in mortality across VHA facilities during the pandemic, which was only partially explained by the local COVID-19 burden. Our work provides a framework for large health care systems to identify changes in facility-level mortality during a public health emergency.

Effect of a National VHA Medical Scribe Pilot on Provider Productivity, Wait Times, and Patient Satisfaction in Cardiology and Orthopedics.

BACKGROUND: Section 507 of the VA MISSION Act of 2018 mandated a 2-year pilot study of medical scribes in the Veterans Health Administration (VHA), with 12 VA Medical Centers randomly selected to receive scribes in their emergency departments or high wait time specialty clinics (cardiology and orthopedics). The pilot began on June 30, 2020, and ended on July 1, 2022. OBJECTIVE: Our objective was to evaluate the impact of medical scribes on provider productivity, wait times, and patient satisfaction in cardiology and orthopedics, as mandated by the MISSION Act. DESIGN: Cluster randomized trial, with intent-to-treat analysis using difference-in-differences regression. PATIENTS: Veterans using 18 included VA Medical Centers (12 intervention and 6 comparison sites). INTERVENTION: Randomization into MISSION 507 medical scribe pilot. MAIN MEASURES: Provider productivity, wait times, and patient satisfaction per clinic-pay period. KEY RESULTS: Randomization into the scribe pilot was associated with increases of 25.2 relative value units (RVUs) per full-time equivalent (FTE) (p < 0.001) and 8.5 visits per FTE (p = 0.002) in cardiology and increases of 17.3 RVUs per FTE (p = 0.001) and 12.5 visits per FTE (p = 0.001) in orthopedics. We found that the scribe pilot was associated with a decrease of 8.5 days in request to appointment day wait times (p < 0.001) in orthopedics, driven by a 5.7-day decrease in appointment made to appointment day wait times (p < 0.001), and observed no change in wait times in cardiology. We also observed no declines in patient satisfaction with randomization into the scribe pilot. CONCLUSIONS: Given the potential improvements in productivity and wait times with no change in patient satisfaction, our results suggest that scribes may be a useful tool to improve access to VHA care. However, participation in the pilot by sites and providers was voluntary, which could have implications for scalability and what effects could be expected if scribes were introduced to the care process without buy-in. Cost was not considered in this analysis but is an important factor for future implementation. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04154462.

Effect of a Predictive Analytics-Targeted Program in Patients on Opioids: a Stepped-Wedge Cluster Randomized Controlled Trial.

BACKGROUND: Risk of overdose, suicide, and other adverse outcomes are elevated among sub-populations prescribed opioid analgesics. To address this, the Veterans Health Administration (VHA) developed the Stratification Tool for Opioid Risk Mitigation (STORM)-a provider-facing dashboard that utilizes predictive analytics to stratify patients prescribed opioids based on risk for overdose/suicide. OBJECTIVE: To evaluate the impact of the case review mandate on serious adverse events (SAEs) and all-cause mortality among high-risk Veterans. DESIGN: A 23-month stepped-wedge cluster randomized controlled trial in all 140 VHA medical centers between 2018 and 2020. PARTICIPANTS: A total of 44,042 patients actively prescribed opioid analgesics with high STORM risk scores (i.e., percentiles 1% to 5%) for an overdose or suicide-related event. INTERVENTION: A mandate requiring providers to perform case reviews on opioid analgesic-prescribed patients at high risk of overdose/suicide. MAIN MEASURES: Nine serious adverse events (SAEs), case review completion, number of risk mitigation strategies, and all-cause mortality. KEY RESULTS: Mandated review inclusion was associated with a significant decrease in all-cause mortality within 4 months of inclusion (OR: 0.78; 95% CI: 0.65-0.94). There was no detectable effect on SAEs. Stepped-wedge analyses found that mandated review patients were five times more likely to receive a case review than non-mandated patients with similar risk (OR: 5.1; 95% CI: 3.64-7.23) and received more risk mitigation strategies than non-mandated patients (0.498; CI: 0.39-0.61). CONCLUSIONS: Among VHA patients prescribed opioid analgesics, identifying high risk patients and mandating they receive an interdisciplinary case review was associated with a decrease in all-cause mortality. Results suggest that providers can leverage predictive analytic-targeted population health approaches and interdisciplinary collaboration to improve patient outcomes. TRIAL REGISTRATION: ISRCTN16012111.

Developing and evaluating a pediatric asthma severity computable phenotype derived from electronic health records.

BACKGROUND: Extensive data available in electronic health records (EHRs) have the potential to improve asthma care and understanding of factors influencing asthma outcomes. However, this work can be accomplished only when the EHR data allow for accurate measures of severity, which at present are complex and inconsistent. OBJECTIVE: Our aims were to create and evaluate a standardized pediatric asthma severity phenotype based in clinical asthma guidelines for use in EHR-based health initiatives and studies and also to examine the presence and absence of these data in relation to patient characteristics. METHODS: We developed an asthma severity computable phenotype and compared the concordance of different severity components contributing to the phenotype to trends in the literature. We used multivariable logistic regression to assess the presence of EHR data relevant to asthma severity. RESULTS: The asthma severity computable phenotype performs as expected in comparison with national statistics and the literature. Severity classification for a child is maximized when based on the long-term medication regimen component and minimized when based only on the symptom data component. Use of the severity phenotype results in better, clinically grounded classification. Children for whom severity could be ascertained from these EHR data were more likely to be seen for asthma in the outpatient setting and less likely to be older or Hispanic. Black children were less likely to have lung function testing data present. CONCLUSION: We developed a pragmatic computable phenotype for pediatric asthma severity that is transportable to other EHRs.

Priority access to health care: Evidence from an exogenous policy shock.

Access to care is an important issue in public health care systems. Unlike private systems, in which price equilibrates supply and demand, public systems often ration medical services through wait times. Access that is given on a first come, first served basis might not yield an allocation of resources that maximizes the health of a population, potentially creating suboptimal heterogeneity in wait times. In this study, we examine an access disparity between two groups of patients-established patients and new patients. We exploit an exogenous policy change-implemented by the U.S. Veterans Health Administration-that removed the disparity and homogenized the wait time. We find strong evidence that without such a policy, established patients have priority access over new patients. We discuss whether this is a suboptimal allocation of resources. We additionally find that established patient priority access is an important determinant of access for new patients; accounting for it increased the explanatory power of our statistical model of new patient wait times by a factor of five. The findings imply that policy and management decisions may be more effective in achieving the optimal distribution of access if access heterogeneity is recognized and accounted for explicitly.

Exploring Opportunities for Household-Level Chronic Care Management Using Linked Electronic Health Records of Adults and Children: A Retrospective Cohort Study.

OBJECTIVE: Linking electronic health records (EHR) of pediatric and adult patients living in the same household has the potential to improve chronic care management efficiencies by facilitating the delivery of services to multiple household members at once. However, little is known about relationship between the chronic medical (CM) and behavioral health (CBH) of adults and children living in common households. METHODS: EHR data for children were linked to the EHR data of adults living at the same address during the same time in a retrospective cohort study from 2006 to 2014 to evaluate associations between adult and child CM and CBH conditions within a Boston safety-net primary care patient sample. RESULTS: Of the 13,845 included children, 61.6% lived with at least one adult with ≥ 1 CM or CBH condition. Compared to children living with an adult(s) without a chronic condition, children living with an adult with a CM or CBH condition had a respective 16.2% and 18.1% increased likelihood of having a chronic condition themselves, with multiple adult chronic conditions in adults increasing children's likelihood. CONCLUSIONS FOR PRACTICE: We found a positive association between the chronic diseases of adult and child household members. Given the clustering of child and adult chronic disease within households, using EHR data to support the care management needs of multiple members of households may be a promising approach to improving child and adult health in safety-net settings.

Effect on VA Patient Satisfaction of Provider's Use of an Integrated Viewer of Multiple Electronic Health Records.

PURPOSE: To examine associations between patient perceptions that their provider was knowledgeable of their medical history and clinicians' early adoption of an application that presents providers with an integrated longitudinal view of a patient's electronic health records (EHR) from multiple healthcare systems. METHOD: This retrospective analysis utilizes provider audit logs from the Veterans Health Administration Joint Legacy Viewer (JLV) and patient responses to the Survey of Patient Healthcare Experiences Patient-Centered Medical Home (SHEP/PCMH) patient satisfaction survey (FY2016) to assess the relationship between the primary care provider being an early adopter of JLV and patient perception of the provider's knowledge of their medical history. Multivariate logistic regression models were used to control for patient age, race, sex education, health status, duration of patient-provider relationship, and provider characteristics. RESULTS: The study used responses from 203,903 patients to the SHEP-PCMH survey in FY2016 who received outpatient primary care services from 11,421 unique providers. Most (91%) clinicians had no JLV utilization in the 6 months prior to the studied patient visit. Controlling for patient demographics, length of the patient-provider relationship, and provider and facility characteristics, being an early adopter of the JLV system was associated with a 14% (adj OR 1.14, p < 0.000) increased odds that patients felt their provider was knowledgeable about their medical history. When evaluating the interaction between duration of patient-provider relationship and being an early adopter of JLV, a greater effect was seen with patient-provider relationships that were greater than 3 years (adj OR 1.23, p < 0.000), compared to those less than 3 years. CONCLUSIONS: Increasing the interoperability of medical information systems has the potential to improve both patient care and patient experience of care. This study demonstrates that early adopters of an integrated view of electronic health records from multiple delivery systems are more likely to have their patients report that their clinician was knowledgeable of their medical history. With provider payments often linked to patient satisfaction performance metrics, investments in interoperability may be worthwhile.

Clinical Operations Variables are Associated With Blood Pressure Outcomes.

BACKGROUND: Uncontrolled blood pressure (BP), among patients diagnosed and treated for the condition, remains an important clinical challenge; aspects of clinical operations could potentially be adjusted if they were associated with better outcomes. OBJECTIVES: To assess clinical operations factors' effects on normalization of uncontrolled BP. RESEARCH DESIGN: Observational cohort study. SUBJECTS: Patients diagnosed with hypertension from a large urban clinical practice (2005-2009). MEASURES: We obtained clinical data on BP, organized by person-month, and administrative data on primary care provider (PCP) staffing. We assessed the resolution of an episode of uncontrolled BP as a function of time-varying covariates including practice-level appointment volume, individual clinicians' appointment volume, overall practice-level PCP staffing, and number of unique PCPs. RESULTS: Among the 7409 unique patients representing 50,403 person-months, normalization was less likely for the patients in whom the episode starts during months when the number of unique PCPs were high [the top quintile of unique PCPs was associated with a 9 percentage point lower probability of normalization (P<0.01) than the lowest quintile]. Practice appointment volume negatively affected the likelihood of normalization [episodes starting in months with the most appointments were associated with a 6 percentage point reduction in the probability of normalization (P=0.01)]. Neither clinician appointment volume nor practice clinician staffing levels were significantly associated with the probability of normalization. CONCLUSIONS: Findings suggest that clinical operations factors can affect clinical outcomes like BP normalization, and point to the importance of considering outcome effects when organizing clinical care.

Trends in Male and Female Genital Warts Among Adolescents in a Safety-Net Health Care System 2004-2013: Correlation With Introduction of Female and Male Human Papillomavirus Vaccination.

BACKGROUND: Human papillomavirus (HPV) vaccination remains underused in the United States, and few population-level studies on effectiveness exist. METHODS: We examined trends in rates of genital warts diagnoses and HPV vaccination rates (defined as receipt of 1 or more vaccine doses) among low-income and minority adolescents between 2004 and 2013. Data were obtained from a database containing de-identified medical record information including all outpatient visits to an urban medical center and 6 affiliated community health centers. International Classification of Diseases, Ninth Revision codes were used to determine genital warts diagnoses. We estimated annual rates of genital warts for each period for females and males using an interrupted time-series Poisson regression model. RESULTS: As HPV vaccination rates in low-income, minority adolescents rose from 0% to 59% (females) and 0 to 41% (males) between 2004 and 2013, genital warts rates decreased from 3.5% (females) and 3.6% (males) to 1.5% (females) and 2.9% (males). Rates of genital warts decreased significantly for both females and males from the prevaccination to the postvaccination periods (P < 0.05 for both comparisons). Genital warts rates for males began to decrease after the introduction of female vaccination and continued to decrease after male vaccination was introduced. CONCLUSIONS: Introduction of HPV vaccination correlated with lower rates of genital warts among a cohort of low-income and minority adolescents. Rates of genital warts began to decrease in females and males following the introduction of female vaccination and continued to fall after the introduction of male vaccination, indicating that male vaccination may confer additional benefit to both males and females over herd immunity alone, especially when vaccination rates are suboptimal.

Medical training program size and clinical staff productivity and turnover.

OBJECTIVE: The objective of this analysis was to evaluate the effect of resident program training size on clinician productivity and turnover in the Veterans Health Administration (VHA), the largest education and training platform for medical professionals in the United States. DATA SOURCES: We retrieved administrative data on training programs and training facilities from the VA Office of Academic Affiliations and the VHA Corporate Data Warehouse. Data on primary care physician shortage areas were retrieved from the Health Resources and Services Administration. STUDY DESIGN: We used a quasi-experimental instrumental variables 2SLS design and constructed an exogenous predicted training allocation treatment variable as a function of the total national training program allocation. The outcome was clinical staff productivity and turnover. Secondary analyses stratified results using Health Professional Shortage Areas data (HPSA). DATA COLLECTION/EXTRACTION METHODS: Data were obtained for a national dataset of 141 VHA medical facilities and 26 specialties that hosted training programs across 11 years from 2011 to 2021 (N = 132,177). PRINCIPAL FINDINGS: Instrumental variables results showed that on average, an increase of one training slot in a specialty leads to a decrease of 0.039 visits per standardized clinic day (p < 0.001) and a 0.02 percentage point increase in turnover (p < 0.001). The direction of this association varied by specialty: while psychiatry and psychology specialties saw a decline in productivity, fields such as primary care and cardiology experienced an increase in productivity. HPSA stratified results indicate that negative effects on productivity and turnover are driven by areas with little to no primary care physician shortage, whereas shortage areas experienced a small increase in productivity and no effect on turnover. CONCLUSIONS: This quasi-experimental evaluation indicates that resident training program size is associated with reduced productivity and increased turnover in specialties such as psychiatry and in facilities with high baseline productivity. However, in specialties like primary care and cardiology, as well as areas with shortages of primary care, larger training programs are associated with increased productivity.

Caring Letters Sent by a Clinician or Peer to At-Risk Veterans: A Randomized Clinical Trial.

Importance: Caring letters is an evidence-based suicide prevention intervention in acute care settings, but its outcomes among individuals who contact a national crisis line have not previously been evaluated. Objective: To examine the outcomes of the Veterans Crisis Line (VCL) caring letters intervention and determine whether there are differences in outcomes by signatory. Design, Setting, and Participants: This parallel randomized clinical trial compared signatories of caring letters and used an observational design to compare no receipt of caring letters with any caring letters receipt. Participants included veterans who contacted the VCL. Enrollment occurred between June 11, 2020, and June 10, 2021, with 1 year of follow-up. Analyses were completed between July 2022 and August 2023. Intervention: Veterans were randomized to receive 9 caring letters for 1 year from either a clinician or peer veteran signatory. Main Outcomes and Measures: The primary outcome measure was suicide attempt incidence in the 12 months following the index VCL contact. Incidence of Veterans Health Administration (VHA) inpatient, outpatient, and emergency health care use were secondary outcomes. All-cause mortality was an exploratory outcome. Wilcoxon rank-sum tests and χ2 tests were used to assess the differences in outcomes among the treatment and comparison groups. Results: A total of 102 709 veterans (86 942 males [84.65%]; 15 737 females [15.32%]; mean [SD] age, 53.82 [17.35] years) contacted the VCL and were randomized. No association was found among signatory and suicide attempts, secondary outcomes, or all-cause mortality. In the analysis of any receipt of caring letters, there was no evidence of an association between caring letters receipt and suicide attempt incidence. Caring letters receipt was associated with increased VHA health care use (any outpatient: hazard ratio [HR], 1.10; 95% CI, 1.08-1.13; outpatient mental health: HR, 1.19; 95% CI, 1.17-1.22; any inpatient: HR, 1.13; 95% CI, 1.08-1.18; inpatient mental health: HR, 1.14; 95% CI, 1.07-1.21). Caring letters receipt was not associated with all-cause mortality. Conclusions and Relevance: Among VHA patients who contacted the VCL, caring letters were not associated with suicide attempts, but were associated with a higher probability of health care use. No differences in outcomes were identified by signatory. Trial Registration: isrctn.org Identifier: ISRCTN27551361.

Racial and ethnic disparities in excess mortality among U.S. veterans during the COVID-19 pandemic.

OBJECTIVE: The COVID-19 pandemic disproportionately affected racial and ethnic minorities among the general population in the United States; however, little is known regarding its impact on U.S. military Veterans. In this study, our objectives were to identify the extent to which Veterans experienced increased all-cause mortality during the COVID-19 pandemic, stratified by race and ethnicity. DATA SOURCES: Administrative data from the Veterans Health Administration's Corporate Data Warehouse. STUDY DESIGN: We use pre-pandemic data to estimate mortality risk models using five-fold cross-validation and quasi-Poisson regression. Models were stratified by a combined race-ethnicity variable and included controls for major comorbidities, demographic characteristics, and county fixed effects. DATA COLLECTION: We queried data for all Veterans residing in the 50 states plus Washington D.C. during 2016-2020. Veterans were excluded from analyses if they were missing county of residence or race-ethnicity data. Data were then aggregated to the county-year level and stratified by race-ethnicity. PRINCIPAL FINDINGS: Overall, Veterans' mortality rates were 16% above normal during March-December 2020 which equates to 42,348 excess deaths. However, there was substantial variation by racial and ethnic group. Non-Hispanic White Veterans experienced the smallest relative increase in mortality (17%, 95% CI 11%-24%), while Native American Veterans had the highest increase (40%, 95% CI 17%-73%). Black Veterans (32%, 95% CI 27%-39%) and Hispanic Veterans (26%, 95% CI 17%-36%) had somewhat lower excess mortality, although these changes were significantly higher compared to White Veterans. Disparities were smaller than in the general population. CONCLUSIONS: Minoritized Veterans experienced higher rates excess of mortality during the COVID-19 pandemic compared to White Veterans, though with smaller differences than the general population. This is likely due in part to the long-standing history of structural racism in the United States that has negatively affected the health of minoritized communities via several pathways including health care access, economic, and occupational inequities.

Likelihood of COVID-19 reinfection in an urban community cohort in Massachusetts.

Background: Understanding the association of prior SARS-CoV-2 infection with subsequent reinfection has public health relevance. Objective: To explore COVID-19 severity and SARS-CoV-2 infection and reinfection rates. Design: Retrospective cohort study. Setting: Boston, Massachusetts, during the first COVID-19 surge (01/01/2020-05/31/2020; Period-1) and after the first surge (06/01/2020-02/28/2021; Period-2); Period-2 included the second surge (11/01/2020-02/28/2021). Participants: Patients in an academic medical center and six community health centers who received a clinical diagnosis of COVID-19 between 01/01/2020 and 05/31/2020 or SARS-CoV-2 testing between 01/01/2020 and 02/28/2021. Measurements: COVID-19 severity was compared between Period-1 and Period-2. Poisson regression models adjusted for demographic variables, medical comorbidities, and census tract were used to assess reinfection risk among patients with COVID-19 diagnoses or SARS-CoV-2 testing during Period-1 and additional SARS-CoV-2 testing during Period-2. Results: Among 142,047 individuals receiving SARS-CoV-2 testing or clinical diagnoses during the study period, 15.8% were infected. Among COVID-19 patients, 22.5% visited the emergency department, 13% were hospitalized, and 4% received critical care. Healthcare utilization was higher during Period-1 than Period-2 (22.9% vs. 18.9% emergency department use, 14.7% vs. 9.9% hospitalization, 5.5% vs. 2.5% critical care; p < 0.001). Reinfection was assessed among 8961 patients with a SARS-CoV-2 test or COVID-19 diagnosis in Period-1 who underwent additional testing in Period-2. A total of 2.7% (n = 65/2431) with SARS-CoV-2 in Period-1 tested positive in Period-2, compared with 12.6% (n = 821/6530) of those who initially tested negative (IRR of reinfection = 0.19, 95% CI: 0.15-0.25). Conclusions: Prior SARS-CoV-2 infection among this observational cohort was associated with an 81% lower reinfection rate.

County-Level Impact of the COVID-19 Pandemic on Excess Mortality Among U.S. Veterans: A Population-Based Study.

BACKGROUND: As the novel coronavirus (COVID-19) continues to impact the world at large, Veterans of the US Armed Forces are experiencing increases in both COVID-19 and non-COVID-19 mortality. Veterans may be more susceptible to the pandemic than the general population due to their higher comorbidity burdens and older age, but no research has examined if trends in excess mortality differ between these groups. Additionally, individual-level data on demographics, comorbidities, and deaths are provided in near-real time for all enrolees of the Veterans Health Administration (VHA). These data provide a unique opportunity to identify excess mortality throughout 2020 at a subnational level, and to validate these estimates against local COVID-19 burden. METHODS: We queried VHA administrative data on demographics and comorbidities for 11.4 million enrolees during 2016-2020. Pre-pandemic data was used to develop and cross-validate eight mortality prediction models at the county-level including Poisson, Poisson quasi-likelihood, negative binomial, and generalized estimating equations. We then estimated county-level excess Veteran mortality during 2020 and correlated these estimates with local rates of COVID-19 confirmed cases and deaths. FINDINGS: All models demonstrated excellent agreement between observed and predicted mortality during 2016-2019; a Poisson quasi-likelihood with county fixed effects minimized median squared error with a calibration slope of 1.00. Veterans of the U.S. Armed Forces faced an excess mortality rate of 13% in 2020, which corresponds to 50,299 excess deaths. County-level estimates of excess mortality were correlated with both COVID-19 cases (R2=0.77) and deaths per 1,000 population (R2=0.59). INTERPRETATION: We developed sub-national estimates of excess mortality associated with the pandemic and shared our data as a resource for researchers and data journalists. Despite Veterans' greater likelihood of risk factors associated with severe COVID-19 illness, their excess mortality rate was slightly lower than the general population. Consistent access to health care and the rapid expansion of VHA telemedicine during the pandemic may explain this divergence. FUNDING: This work was supported by grants from the Department of Veterans Affairs Quality Enhancement Research Initiative [PEC 16-001]. Dr. Griffith's effort was supported in part by the Agency for Healthcare Research & Quality [K12 HS026395].

In-home environmental exposures predicted from geospatial characteristics of the built environment and electronic health records of children with asthma.

PURPOSE: Children may be exposed to numerous in-home environmental exposures (IHEE) that trigger asthma exacerbations. Spatially linking social and environmental exposures to electronic health records (EHR) can aid exposure assessment, epidemiology, and clinical treatment, but EHR data on exposures are missing for many children with asthma. To address the issue, we predicted presence of indoor asthma trigger allergens, and estimated effects of their key geospatial predictors. METHODS: Our study samples were comprised of children with asthma who provided self-reported IHEE data in EHR at a safety-net hospital in New England during 2004-2015. We used an ensemble machine learning algorithm and 86 multilevel features (e.g., individual, housing, neighborhood) to predict presence of cockroaches, rodents (mice or rats), mold, and bedroom carpeting/rugs in homes. We reduced dimensionality via elastic net regression and estimated effects by the G-computation causal inference method. RESULTS: Our models reasonably predicted presence of cockroaches (area under receiver operating curves [AUC] = 0.65), rodents (AUC = 0.64), and bedroom carpeting/rugs (AUC = 0.64), but not mold (AUC = 0.54). In models adjusted for confounders, higher average household sizes in census tracts were associated with more reports of pests (cockroaches and rodents). Tax-exempt parcels were associated with more reports of cockroaches in homes. Living in a White-segregated neighborhood was linked with lower reported rodent presence, and mixed residential/commercial housing and newer buildings were associated with more reports of bedroom carpeting/rugs in bedrooms. CONCLUSIONS: We innovatively applied a machine learning and causal inference mixture methodology to detail IHEE among children with asthma using EHR and geospatial data, which could have wide applicability and utility.