Risk of Potentially Preventable Hospitalizations After SARS-CoV-2 Infection.

Importance: Research demonstrates that SARS-CoV-2 infection is associated with increased risk of all-cause hospitalization. However, no prior studies have assessed the association between SARS-CoV-2 and potentially preventable hospitalizations-that is, hospitalizations for conditions that can usually be effectively managed in ambulatory care settings. Objective: To examine whether SARS-CoV-2 is associated with potentially preventable hospitalization in a nationwide cohort of US veterans. Design, Setting, and Participants: This cohort study used an emulated target randomized trial design with monthly sequential trials to compare risk of a potentially preventable hospitalization among veterans with SARS-CoV-2 and matched comparators without SARS-CoV-2. A total of 189 136 US veterans enrolled in the Veterans Health Administration (VHA) who were diagnosed with SARS-CoV-2 between March 1, 2020, and April 30, 2021, and 943 084 matched comparators were included in the analysis. Data were analyzed from May 10, 2023, to January 26, 2024. Exposure: SARS-CoV-2 infection. Main Outcomes and Measures: The primary outcome was a first potentially preventable hospitalization in VHA facilities, VHA-purchased community care, or Medicare fee-for-service care. Extended Cox models were used to examine adjusted hazard ratios (AHRs) of potentially preventable hospitalization among veterans with SARS-CoV-2 and comparators during follow-up periods of 0 to 30, 0 to 90, 0 to 180, and 0 to 365 days. The start of follow-up was defined as the date of each veteran's first positive SARS-CoV-2 diagnosis, with the same index date applied to their matched comparators. Results: The 1 132 220 participants were predominantly men (89.06%), with a mean (SD) age of 60.3 (16.4) years. Most veterans were of Black (23.44%) or White (69.37%) race. Veterans with SARS-CoV-2 and comparators were well-balanced (standardized mean differences, all <0.100) on observable baseline clinical and sociodemographic characteristics. Overall, 3.10% of veterans (3.81% of those with SARS-CoV-2 and 2.96% of comparators) had a potentially preventable hospitalization during 1-year follow-up. Risk of a potentially preventable hospitalization was greater among veterans with SARS-CoV-2 than comparators in 4 follow-up periods: 0- to 30-day AHR of 3.26 (95% CI, 3.06-3.46); 0- to 90-day AHR of 2.12 (95% CI, 2.03-2.21); 0- to 180-day AHR of 1.69 (95% CI, 1.63-1.75); and 0- to 365-day AHR of 1.44 (95% CI, 1.40-1.48). Conclusions and Relevance: In this cohort study, an increased risk of preventable hospitalization in veterans with SARS-CoV-2, which persisted for at least 1 year after initial infection, highlights the need for research on ways in which SARS-CoV-2 shapes postinfection care needs and engagement with the health system. Solutions are needed to mitigate preventable hospitalization after SARS-CoV-2.

Impact of SARS-CoV-2 Infection on Long-Term Depression Symptoms among Veterans.

BACKGROUND: Prior research demonstrates that SARS-COV-2 infection can be associated with a broad range of mental health outcomes including depression symptoms. Veterans, in particular, may be at elevated risk of increased depression following SARS-COV-2 infection given their high rates of pre-existing mental and physical health comorbidities. However, few studies have tried to isolate SARS-COV-2 infection associations with long term, patient-reported depression symptoms from other factors (e.g., physical health comorbidities, pandemic-related stress). OBJECTIVE: To evaluate the association between SARS-COV-2 infection and subsequent depression symptoms among United States Military Veterans. DESIGN: Survey-based non-randomized cohort study with matched comparators. PARTICIPANTS: A matched-dyadic sample from a larger, stratified random sample of participants with and without known to SARS-COV-2 infection were invited to participate in a survey evaluating mental health and wellness 18-months after their index infection date. Sampled participants were stratified by infection severity of the participant infected with SARS-COV-2 (hospitalized or not) and by month of index date. A total of 186 participants in each group agreed to participate in the survey and had sufficient data for inclusion in analyses. Those in the uninfected group who were later infected were excluded from analyses. MAIN MEASURES: Participants were administered the Patient Health Questionnaire-9 as part of a phone interview survey. Demographics, physical and mental health comorbidities were extracted from VHA administrative data. KEY RESULTS: Veterans infected with SARS-COV-2 had significantly higher depression symptoms scores compared with those uninfected. In particular, psychological symptoms (e.g., low mood, suicidal ideation) scores were elevated relative to the comparator group (MInfected = 3.16, 95%CI: 2.5, 3.8; MUninfected = 1.96, 95%CI: 1.4, 2.5). Findings were similar regardless of history of depression. CONCLUSION: SARS-COV-2 infection was associated with more depression symptoms among Veterans at 18-months post-infection. Routine evaluation of depression symptoms over time following SARS-COV-2 infection is important to facilitate adequate assessment and treatment.

Self-Reported Everyday Functioning After COVID-19 Infection.

Importance: Changes in everyday functioning are crucial to assessing the long-term impact of COVID-19 infection. Objective: To examine the impact of COVID-19 infection on everyday functioning 18 months after infection among veterans with and without histories of COVID-19 infection. Design, Setting, and Participants: This cohort study used data from the US Veterans Affairs (VA) and included 186 veterans who had COVID-19 between October 2020 and April 2021 (ie, COVID-19 cohort) and 186 matched comparators who did not have documented COVID-19 infections (ie, control cohort). This match balanced the risk of COVID-19 based on 39 variables measured in the 24 months before infection or match, using principles of target trial emulation. Data were analyzed from December 2022 to December 2023. Exposure: First documented COVID-19. Main Outcome and Measures: The differences in self-reported everyday functioning 18 months after COVID-19 infection were estimated and compared with their matched comparators. Within-matched pair logistic and linear regressions assessed differences in outcomes and were weighted to account for sampling and nonresponse. Results: Among the 186 matched pairs of participants, their weighted mean age was 60.4 (95% CI, 57.5 to 63.2) years among veterans in the COVID-19 cohort (weighted sample, 91 459 of 101 133 [90.4%] male; 30 611 [30.3%] Black or African American veterans; 65 196 [64.4%] White veterans) and 61.1 (95% CI, 57.8 to 64.4) years among their comparators in the control cohort (91 459 [90.4%] male; 24 576 [24.3%] Black or African American veterans; 70 157 [69.4%] White veterans). A high proportion of veterans in the COVID-19 cohort (weighted percentage, 44.9% [95% CI, 34.2% to 56.2%]) reported that they could do less than what they felt they could do at the beginning of 2020 compared with the control cohort (weighted percentage, 35.3%; [95% CI, 25.6% to 46.4%]; within-matched pair adjusted odds ratio [OR], 1.52 [95% CI, 0.79 to 2.91]). There was no association of documented COVID-19 infection with fatigue, substantial pain, limitations in either activities of daily living and instrumental activities of daily living, severely curtailed life-space mobility, employment, or mean health-related quality of life on a utility scale. Conclusions and Relevance: In this cohort study of veterans with and without documented COVID-19, many reported a substantial loss of everyday functioning during the pandemic regardless of whether or not they had a documented infection with COVID-19. Future work with larger samples is needed to validate the estimated associations.

Lifetime non-fatal overdose experiences among at-risk adolescents and young adults in the emergency department with past-year opioid use in the USA.

BACKGROUND: Adolescents and young adults with risk factors for opioid misuse and opioid use disorder are at elevated risk for overdose. We examined prior non-fatal overdose experiences among at-risk adolescents/young adults to inform prevention efforts. METHODS: Adolescents/young adults (ages 16-30) in two US emergency departments self-reporting past year opioid misuse or opioid use plus a misuse risk factor completed a baseline survey as part of an ongoing randomised controlled trial. We describe baseline factors associated with (a) overall non-fatal overdose experiences and (b) groups based on substance(s) used during the worst overdose experience. RESULTS: Among 771 participants (27.9% male), 40.7% reported a non-fatal overdose experience. Compared with those without a prior overdose experience, those with prior overdose experience(s) were less likely to be heterosexual, and more likely to report a prior suicide attempt and greater peer substance misuse. Regarding the worst overdose experience, substance(s) included: 36.6% alcohol only, 28.0% alcohol and cannabis, 22.6% alcohol with other substance(s) and 12.7% other substance(s) only (eg, opioids). Compared with the alcohol only group, the alcohol and cannabis group were younger and less likely to be heterosexual; the alcohol with other substance(s) group were older and had greater peer substance misuse; and the other substance(s) only group were more likely to be male, receive public assistance, screen positive for anxiety and less likely to be heterosexual. CONCLUSIONS: Among at-risk adolescents/young adults, findings support the need for tailored overdose prevention efforts based on substance(s) used, with consideration of sexuality, mental health and peer substance use. TRIAL REGISTRATION NUMBER: NCT04550715.

Changes in Outpatient Health Care Use After COVID-19 Infection Among Veterans.

Importance: The association of COVID-19 infection with outpatient care utilization is unclear. Many studies reported population surveillance studies rather than comparing outpatient health care use between COVID-19-infected and uninfected cohorts. Objective: To compare outpatient health care use across 6 categories of care (primary care, specialty care, surgery care, mental health, emergency care, and diagnostic and/or other care) between veterans with or without COVID-19 infection. Design, Setting, and Participants: In a retrospective cohort study of Veterans Affairs primary care patients, veterans with COVID-19 infection were matched to a cohort of uninfected veterans. Data were obtained from the Veterans Affairs Corporate Data Warehouse and the Centers for Medicare & Medicaid Services Fee-for-Service Carrier/Physician Supplier file from January 2019 through December 2022. Data analysis was performed from September 2022 to April 2023. Exposure: COVID-19 infection. Main Outcomes and Measures: The primary outcome was the count of outpatient visits after COVID-19 infection. Negative binomial regression models compared outpatient use over a 1-year preinfection period, and peri-infection (0-30 days), intermediate (31-183 days), and long-term (184-365 days) postinfection periods. Results: The infected (202 803 veterans; mean [SD] age, 60.5 [16.2] years; 178 624 men [88.1%]) and uninfected (202 803 veterans; mean [SD] age, 60.4 [16.5] years; 178 624 men [88.1%]) cohorts were well matched across all covariates. Outpatient use in all categories (except surgical care) was significantly elevated during the peri-infection period for veterans with COVID-19 infection compared with the uninfected cohort, with an increase in all visits of 5.12 visits per 30 days (95% CI, 5.09-5.16 visits per 30 days), predominantly owing to primary care visits (increase of 1.86 visits per 30 days; 95% CI, 1.85-1.87 visits per 30 days). Differences in outpatient use attenuated over time but remained statistically significantly higher at 184 to 365 days after infection (increase of 0.25 visit per 30 days; 95% CI, 0.23-0.27 visit per 30 days). One-half of the increased outpatient visits were delivered via telehealth. The utilization increase was greatest for veterans aged 85 years and older (6.1 visits, 95% CI, 5.9-6.3 visits) vs those aged 20 to 44 years (4.8 visits, 95% CI, 4.7-4.8 visits) and unvaccinated veterans (4.5 visits, 95% CI, 4.3-4.6 visits) vs vaccinated veterans (3.2 visits; 95% CI, 3.4-4.8 visits). Conclusions and Relevance: This study found that outpatient use increased significantly in the month after infection, then attenuated but remained greater than the uninfected cohorts' use through 12 months, which suggests that there are sustained impacts of COVID-19 infection.

Rates of ICD-10 Code U09.9 Documentation and Clinical Characteristics of VA Patients With Post-COVID-19 Condition.

Importance: A significant proportion of SARS-CoV-2 infected individuals experience post-COVID-19 condition months after initial infection. Objective: To determine the rates, clinical setting, risk factors, and symptoms associated with the documentation of International Statistical Classification of Diseases Tenth Revision (ICD-10), code U09.9 for post-COVID-19 condition after acute infection. Design, Setting, and Participants: This retrospective cohort study was performed within the US Department of Veterans Affairs (VA) health care system. Veterans with a positive SARS-CoV-2 test result between October 1, 2021, the date ICD-10 code U09.9 was introduced, and January 31, 2023 (n = 388 980), and a randomly selected subsample of patients with the U09.9 code (n = 350) whose symptom prevalence was assessed by systematic medical record review, were included in the analysis. Exposure: Positive SARS-CoV-2 test result. Main Outcomes and Measures: Rates, clinical setting, risk factors, and symptoms associated with ICD-10 code U09.9 in the medical record. Results: Among the 388 980 persons with a positive SARS-CoV-2 test, the mean (SD) age was 61.4 (16.1) years; 87.3% were men. In terms of race and ethnicity, 0.8% were American Indian or Alaska Native, 1.4% were Asian, 20.7% were Black, 9.3% were Hispanic or Latino, 1.0% were Native Hawaiian or Other Pacific Islander; and 67.8% were White. Cumulative incidence of U09.9 documentation was 4.79% (95% CI, 4.73%-4.87%) at 6 months and 5.28% (95% CI, 5.21%-5.36%) at 12 months after infection. Factors independently associated with U09.9 documentation included older age, female sex, Hispanic or Latino ethnicity, comorbidity burden, and severe acute infection manifesting by symptoms, hospitalization, or ventilation. Primary vaccination (adjusted hazard ratio [AHR], 0.80 [95% CI, 0.78-0.83]) and booster vaccination (AHR, 0.66 [95% CI, 0.64-0.69]) were associated with a lower likelihood of U09.9 documentation. Marked differences by geographic region and facility in U09.9 code documentation may reflect local screening and care practices. Among the 350 patients undergoing systematic medical record review, the most common symptoms documented in the medical records among patients with the U09.9 code were shortness of breath (130 [37.1%]), fatigue or exhaustion (78 [22.3%]), cough (63 [18.0%]), reduced cognitive function or brain fog (22 [6.3%]), and change in smell and/or taste (20 [5.7%]). Conclusions and Relevance: In this cohort study of 388 980 veterans, documentation of ICD-10 code U09.9 had marked regional and facility-level variability. Strong risk factors for U09.9 documentation were identified, while vaccination appeared to be protective. Accurate and consistent documentation of U09.9 is needed to maximize its utility in tracking patients for clinical care and research. Future studies should examine the long-term trajectory of individuals with U09.9 documentation.

Variation by Institution in Sexual Harassment Experiences Among US Medical Interns.

This cross-sectional study investigates possible institutional and specialty variations in experiences of sexual harassment among US medical interns.

Prescriptions for Buprenorphine in Michigan Following an Education Intervention.

Importance: Buprenorphine is an underused treatment for opioid use disorder (OUD) that can be prescribed in general medical settings. Founded in 2017, the Michigan Opioid Collaborative (MOC) is an outreach and educational program that aims to address clinician and community barriers to buprenorphine access; however, the association between the MOC and buprenorphine treatment is unknown. Objective: To evaluate the association between MOC service use and county-level temporal trends of density of buprenorphine prescribers and patients receiving buprenorphine. Design, Setting, and Participants: This cohort study exploited staggered implementation of MOC services across all Michigan counties. Difference-in-difference analyses were conducted by applying linear fixed-effects regression across all counties to estimate the overall association of MOC engagement with outcomes and linear regression for each MOC-engaged county separately to infer county-specific results using data from May 2015 to August 2020. Analyses were conducted from September 2021 to November 2023. Exposures: MOC engagement. Main Outcomes and Measures: County-level monthly numbers of buprenorphine prescribers and patients receiving buprenorphine (per 100 000 population). Results: Among 83 total counties, 57 counties (68.7%) in Michigan were engaged by MOC by 2020, with 3 (3.6%) initiating engagement in 2017, 19 (22.9%) in 2018, 27 (32.5%) in 2019, and 8 (9.6%) in 2020. Michigan is made up of 83 counties with a total population size of 9 990 000. A total of 5 070 000 (50.8%) were female, 1 410 000 (14.1%) were African American or Black, 530 000 (5.3%) were Hispanic or Latino, and 7 470 000 (74.7%) were non-Hispanic White. The mean (SD) value of median age across counties was 44.8 (6.4). The monthly increases in buprenorphine prescriber numbers in the preengagement (including all time points for nonengaged counties) and postengagement periods were 0.07 and 0.39 per 100 000 population, respectively, with the absolute difference being 0.33 (95% CI, 0.12-0.53) prescribers per 100 000 population (P = .002). The numbers of patients receiving buprenorphine increased by an average of 0.6 and 7.15 per 100 000 population per month in preengagement and postengagement periods, respectively, indicating an estimated additional 6.56 (95% CI, 2.09-11.02) patients receiving buprenorphine per 100 000 population (P = .004) monthly increase after engagement compared with before. Conclusions and Relevance: In this cohort study measuring buprenorphine prescriptions in Michigan over time, counties' engagement in OUD-focused outreach and clinician education services delivered by a multidisciplinary team was associated with a temporal increase in buprenorphine prescribers and patients receiving buprenorphine.

Benzodiazepine Discontinuation and Mortality Among Patients Receiving Long-Term Benzodiazepine Therapy.

Importance: There is interest in reducing long-term benzodiazepine prescribing given harms associated with use, but the cumulative risks or benefits of discontinuation are unknown. Objective: To identify the association of benzodiazepine discontinuation with mortality and other adverse events among patients prescribed stable long-term benzodiazepine therapy, stratified by baseline opioid exposure. Design, Setting, and Participants: This comparative effectiveness study with a trial emulation approach included data from a US commercial insurance database between January 1, 2013, and December 31, 2017. Eligible participants were adults with stable long-term benzodiazepine prescription treatment. Data were analyzed between December 2022 and November 2023. Exposure: Benzodiazepine discontinuation, defined as no benzodiazepine prescription coverage for 31 consecutive days identified during a 6-month grace period after baseline. Main Outcome and Measures: Mortality during 12 months of follow-up; secondary outcomes included nonfatal overdose, suicide attempt or self-inflicted injury, suicidal ideation, and emergency department use, identified in medical claims. Inverse probability weighting was used to adjust for baseline confounders that potentially affected treatment assignment and censoring due to death or disenrollment. Primary analysis used an intention-to-treat approach; a secondary per-protocol analysis estimated associations after accounting for nonadherence. Analyses were stratified by opioid use. Results: The study included 213 011 (136 609 female [64.1%]; mean [SD] age, 62.2 [14.9] years; 2953 Asian [1.4%], 18 926 Black [8.9%], 22 734 Hispanic [10.7%], and 168 398 White [60.2%]) and 140 565 (91 811 female [65.3%]; mean [SD] age, 61.1 [13.2] years; 1319 Asian [0.9%], 15 945 Black [11.3%], 11 989 Hispanic [8.5%], and 111 312 White [79.2%]) patients with stable long-term benzodiazepine use without and with opioid exposure, respectively. Among the nonopioid exposed, the adjusted cumulative incidence of death after 1 year was 5.5% (95% CI, 5.4%-5.8%) for discontinuers, an absolute risk difference of 2.1 percentage points (95% CI, 1.9-2.3 percentage points) higher than for nondiscontinuers. The mortality risk was 1.6 (95% CI, 1.6-1.7) times that of nondiscontinuers. Among those with opioid exposure, the adjusted cumulative incidence of death was 6.3% (95% CI, 6.0%-6.6%) for discontinuers, an absolute risk difference of 2.4 percentage points (95% CI, 2.2-2.7 percentage points) higher than for nondiscontinuers and a mortality risk 1.6 (95% CI, 1.5-1.7) times that of nondiscontinuers. Cumulative incidence of secondary outcomes was also higher among discontinuers. Conclusions and Relevance: This study identifies small absolute increases in risk of harms among patients with stable long-term prescription benzodiazepine treatment who appear to discontinue relative to continuing treatment, including those with and without recent prescription opioid exposure. Policy broadly promoting benzodiazepine discontinuation may have unintended risks.

Risk of Suicide-Related Outcomes After SARS-COV-2 Infection: Results from a Nationwide Observational Matched Cohort of US Veterans.

BACKGROUND: Negative mental health-related effects of SARS-COV-2 infection are increasingly evident. However, the impact on suicide-related outcomes is poorly understood, especially among populations at elevated risk. OBJECTIVE: To determine risk of suicide attempts and other self-directed violence (SDV) after SARS-COV-2 infection in a high-risk population. DESIGN: We employed an observational design supported by comprehensive electronic health records from the Veterans Health Administration (VHA) to examine the association of SARS-COV-2 infection with suicide attempts and other SDV within one year of infection. Veterans with SARS-COV-2 infections were matched 1:5 with non-infected comparators each month. Three periods after index were evaluated: days 1-30, days 31-365, and days 1-365. PARTICIPANTS: VHA patients infected with SARS-COV-2 between March 1, 2020 and March 31, 2021 and matched non-infected Veteran comparators. MAIN MEASURES: Suicide attempt and other SDV events for the COVID-19 and non-infected comparator groups were analyzed using incidence rates per 100,000 person years and hazard ratios from Cox regressions modeling time from matched index date to first event. Subgroups were also examined. KEY RESULTS: 198,938 veterans with SARS-COV-2 (COVID-19 group) and 992,036 comparators were included. Unadjusted one-year incidence per 100,000 for suicide attempt and other SDV was higher among the COVID-19 group: 355 vs 250 and 327 vs 235, respectively. The COVID-19 group had higher risk than comparators for suicide attempts: days 1-30 hazard ratio (HR) = 2.54 (CI:2.05, 3.15), days 31-365 HR = 1.30 (CI:1.19, 1.43) and days 1-365 HR = 1.41 (CI:1.30, 1.54), and for other SDV: days 1-30 HR = 1.94 (CI:1.51, 2.49), days 31-365 HR = 1.32 (CI:1.20, 1.45) and days 1-365 HR = 1.38 (CI:1.26, 1.51). CONCLUSIONS: COVID-19 patients had higher risks of both suicide attempts and other forms of SDV compared to uninfected comparators, which persisted for at least one year after infection. Results support suicide risk screening of those infected with SARS-COV-2 to identify opportunities to prevent self-harm.

State-to-State Variation in Opioid Dispensing Changes Following the Release of the 2016 CDC Guideline for Prescribing Opioids for Chronic Pain.

Importance: Evidence suggests that opioid prescribing was reduced nationally following the 2016 release of the Guideline for Prescribing Opioids for Chronic Pain by the US Centers for Diseases Control and Prevention (CDC). State-to-state variability in postguideline changes has not been quantified and could point to further avenues for reducing opioid-related harms. Objective: To estimate state-level changes in opioid dispensing following the 2016 CDC Guideline release and explore state-to-state heterogeneity in those changes. Design, Setting, and Participants: This cross-sectional study included information on opioid prescriptions for US individuals between 2012 and 2018 from an administrative database. Serial cross-sections of monthly opioid dispensing trajectories in each US state and the District of Columbia were analyzed using segmented regression to characterize preguideline dispensing trajectories and to estimate how those trajectories changed following the 2016 guideline release. Data were analyzed January to March 2023. Exposure: The March 2016 CDC Guideline for Prescribing Opioids for Chronic Pain. Main Outcomes and Measures: Four measures of opioid dispensing: opioid dispensing rate per 100 000 persons, long-acting opioid dispensing rate per 100 000 persons, high-dose (90 or more morphine milligram equivalents [MME] per day) dispensing rate per 100 000 persons, and average per capita MME. All measures were calculated monthly, from January 2012 through December 2018. Results: Data from approximately 58 900 retail pharmacies were included in analysis, representing approximately 92% of US retail prescriptions. The overall monthly dispensing rate in the US in early 2012 was approximately 7000 per 100 000 population. Following the 2016 guideline release, the already-decreasing slope accelerated nationally for the overall dispensing rate (preguideline slope, -23.19; postguideline slope, -48.97; change in slope, 25.97 [95% CI, 18.67-32.95]), long-acting dispensing rate (preguideline slope, -1.03; postguideline slope, -5.94; change in slope, 4.90 [95% CI, 4.26-5.55]), high-dose dispensing (preguideline slope, -3.52; postguideline slope, -7.63; change in slope, 4.11 [95% CI, 3.49-4.73]), and per-capita MME (preguideline slope, -0.22; postguideline slope, -0.58; change in slope, 0.36 [95% CI, 0.30-0.42]). For all outcomes, nearly all states showed analogous acceleration of an already-decreasing slope, but there was substantial state-to-state heterogeneity. Slope changes (preguideline - postguideline slope) ranged from 9.15 (Massachusetts) to 74.75 (Mississippi) for overall dispensing, 1.88 (Rhode Island) to 13.41 (Maine) for long-acting dispensing, 0.71 (District of Columbia) to 13.68 (Maine) for high-dose dispensing, and 0.06 (Hawaii) to 0.91 (Arkansas) for per capita MME. Conclusions and Relevance: The 2016 CDC Guideline release was associated with broad reductions in prescription opioid dispensing, and those changes showed substantial geographic variability. Determining the factors associated with these state-level differences may inform further improvements to ensure safe prescribing practices.

Late Mortality After COVID-19 Infection Among US Veterans vs Risk-Matched Comparators: A 2-Year Cohort Analysis.

Importance: Despite growing evidence of persistent problems after acute COVID-19, how long the excess mortality risk associated with COVID-19 persists is unknown. Objective: To measure the time course of differential mortality among Veterans who had a first-documented COVID-19 infection by separately assessing acute mortality from later mortality among matched groups with infected and uninfected individuals who survived and were uncensored at the start of each period. Design, Settings, and Participants: This retrospective cohort study used prospectively collected health record data from Veterans Affairs hospitals across the US on Veterans who had COVID-19 between March 2020 and April 2021. Each individual was matched with up to 5 comparators who had not been infected with COVID-19 at the time of matching. This match balanced, on a month-by-month basis, the risk of developing COVID-19 using 37 variables measured in the 24 months before the date of the infection or match. A primary analysis censored comparators when they developed COVID-19 with inverse probability of censoring weighting in Cox regression. A secondary analysis did not censor. Data analyses were performed from April 2021 through June 2023. Exposure: First-documented case of COVID-19 (SARS-CoV-2) infection. Main Outcome Measures: Hazard ratios for all-cause mortality at clinically meaningful intervals after infection: 0 to 90, 91 to 180, 181 to 365, and 366 to 730 days. Results: The study sample comprised 208 061 Veterans with first-documented COVID-19 infection (mean [SD] age, 60.5 (16.2) years; 21 936 (10.5) women; 47 645 [22.9] Black and 139 604 [67.1] White individuals) and 1 037 423 matched uninfected comparators with similar characteristics. Veterans with COVID-19 had an unadjusted mortality rate of 8.7% during the 2-year period after the initial infection compared with 4.1% among uninfected comparators, with censoring if the comparator later developed COVID-19-an adjusted hazard ratio (aHR) of 2.01 (95% CI, 1.98-2.04). The risk of excess death varied, being highest during days 0 to 90 after infection (aHR, 6.36; 95% CI, 6.20-6.51) and still elevated during days 91 to 180 (aHR, 1.18; 95% CI, 1.12-1.23). Those who survived COVID-19 had decreased mortality on days 181 to 365 (aHR, 0.92; 95% CI, 0.89-0.95) and 366 to 730 (aHR, 0.89; 95% CI, 0.85-0.92). These patterns were consistent across sensitivity analyses. Conclusion and Relevance: The findings of this retrospective cohort study indicate that although overall 2-year mortality risk was worse among those infected with COVID-19, by day 180 after infection they had no excess mortality during the next 1.5 years.

An Automatically Adaptive Digital Health Intervention to Decrease Opioid-Related Risk While Conserving Counselor Time: Quantitative Analysis of Treatment Decisions Based on Artificial Intelligence and Patient-Reported Risk Measures.

BACKGROUND: Some patients prescribed opioid analgesic (OA) medications for pain experience serious side effects, including dependence, sedation, and overdose. As most patients are at low risk for OA-related harms, risk reduction interventions requiring multiple counseling sessions are impractical on a large scale. OBJECTIVE: This study evaluates whether an intervention based on reinforcement learning (RL), a field of artificial intelligence, learned through experience to personalize interactions with patients with pain discharged from the emergency department (ED) and decreased self-reported OA misuse behaviors while conserving counselors' time. METHODS: We used data representing 2439 weekly interactions between a digital health intervention ("Prescription Opioid Wellness and Engagement Research in the ED" [PowerED]) and 228 patients with pain discharged from 2 EDs who reported recent opioid misuse. During each patient's 12 weeks of intervention, PowerED used RL to select from 3 treatment options: a brief motivational message delivered via an interactive voice response (IVR) call, a longer motivational IVR call, or a live call from a counselor. The algorithm selected session types for each patient each week, with the goal of minimizing OA risk, defined in terms of a dynamic score reflecting patient reports during IVR monitoring calls. When a live counseling call was predicted to have a similar impact on future risk as an IVR message, the algorithm favored IVR to conserve counselor time. We used logit models to estimate changes in the relative frequency of each session type as PowerED gained experience. Poisson regression was used to examine the changes in self-reported OA risk scores over calendar time, controlling for the ordinal session number (1st to 12th). RESULTS: Participants on average were 40 (SD 12.7) years of age; 66.7% (152/228) were women and 51.3% (117/228) were unemployed. Most participants (175/228, 76.8%) reported chronic pain, and 46.2% (104/225) had moderate to severe depressive symptoms. As PowerED gained experience through interactions over a period of 142 weeks, it delivered fewer live counseling sessions than brief IVR sessions (P=.006) and extended IVR sessions (P<.001). Live counseling sessions were selected 33.5% of the time in the first 5 weeks of interactions (95% CI 27.4%-39.7%) but only for 16.4% of sessions (95% CI 12.7%-20%) after 125 weeks. Controlling for each patient's changes during the course of treatment, this adaptation of treatment-type allocation led to progressively greater improvements in self-reported OA risk scores (P<.001) over calendar time, as measured by the number of weeks since enrollment began. Improvement in risk behaviors over time was especially pronounced among patients with the highest risk at baseline (P=.02). CONCLUSIONS: The RL-supported program learned which treatment modalities worked best to improve self-reported OA risk behaviors while conserving counselors' time. RL-supported interventions represent a scalable solution for patients with pain receiving OA prescriptions. TRIAL REGISTRATION: Clinicaltrials.gov NCT02990377; https://classic.clinicaltrials.gov/ct2/show/NCT02990377.

Improving Access to Care for Patients Taking Opioids for Chronic Pain: Recommendations from a Modified Delphi Panel in Michigan.

Purpose: About 5-8 million US patients take long-term opioid therapy for chronic pain. In the context of policies and guidelines instituted to reduce inappropriate opioid prescribing, abrupt discontinuations in opioid prescriptions have increased and many primary care clinics will not prescribe opioids for new patients, reducing access to care. This may result in uncontrolled pain and other negative outcomes, such as transition to illicit opioids. The objective of this study was to generate policy, intervention, and research recommendations to improve access to care for these patients. Participants and Methods: We conducted a RAND/UCLA Modified Delphi, consisting of workshops, background videos and reading materials, and moderated web-based panel discussions held September 2020-January 2021. The panel consisted of 24 individuals from across Michigan, identified via expert nomination and snowball recruitment, including clinical providers, health science researchers, state-level policymakers and regulators, care coordination experts, patient advocates, payor representatives, and community and public health experts. The panel proposed intervention, policy, and research recommendations, scored the feasibility, impact, and importance of each on a 9-point scale, and ranked all recommendations by implementation priority. Results: The panel produced 11 final recommendations across three themes: reimbursement reform, provider education, and reducing racial inequities in care. The 3 reimbursement-focused recommendations were highest ranked (theme average = 4.2/11), including the two top-ranked recommendations: increasing reimbursement for time needed to treat complex chronic pain (ranked #1/11) and bundling payment for multimodal pain care (#2/11). Four provider education recommendations ranked slightly lower (theme average = 6.2/11) and included clarifying the spectrum of opioid dependence and training providers on multimodal treatments. Four recommendations addressed racial inequities (theme average = 7.2/11), such as standardizing pain management protocols to reduce treatment disparities. Conclusion: Panelists indicated reimbursement should incentivize traditionally lower-paying evidence-based pain care, but multiple strategies may be needed to meaningfully expand access.

Mental health care utilization among men with castration-resistant prostate cancer receiving abiraterone or enzalutamide.

BACKGROUND: Abiraterone and enzalutamide are castration-resistant prostate cancer (CRPC) therapies with potentially distinct associations with mental health symptoms given their differing antiandrogen targets. METHODS: We used national Veterans Health Administration data to identify patients with CRPC who received first-line abiraterone or enzalutamide from 2010 to 2017. Using Poisson regression, we compared outpatient mental health encounters per 100 patient-months on drug between the abiraterone and enzalutamide cohorts adjusting for patient factors (e.g., age). We compared mental health encounters in the year before versus after starting therapy using the McNemar test. RESULTS: We identified 2902 CRPC patients who received abiraterone (n = 1992) or enzalutamide (n = 910). We found no difference in outpatient mental health encounters between the two groups (adjusted incident rate ratio [aIRR] 1.04, 95% confidence interval [CI] 0.95-1.15). However, men with preexisting mental health diagnoses received 81.3% of the outpatient mental health encounters and had higher rates of these encounters with enzalutamide (aIRR 1.21, 95% CI 1.09-1.34). Among patients with ≥1 year of enrollment before and after starting abiraterone (n = 1139) or enzalutamide (n = 446), there was no difference in mental health care utilization before versus after starting treatment (17.0% of patients vs. 17.6%, p = 0.60, abiraterone; 16.4% vs. 18.4%, p = 0.26, enzalutamide). CONCLUSION: We found no overall differences in mental health care utilization between CRPC patients who received first-line abiraterone versus enzalutamide. However, men with preexisting mental health diagnoses received the majority of mental health care and had more mental health visits with enzalutamide.

Prescription characteristics associated with drug overdose risk among adults prescribed benzodiazepines: a cohort study.

BACKGROUND: Drug overdose (OD) deaths in the U.S. continue to rise. After opioids, benzodiazepines (BZD) are the medication most commonly involved in prescription overdoses, yet OD risk factors among those prescribed BZD are not well understood. Our objective was to examine characteristics of BZD, opioid, and other psychotropic prescriptions associated with increased drug OD risk following a BZD prescription. METHODS: We completed a retrospective cohort study using a 20% sample of Medicare beneficiaries with prescription drug coverage. We identified patients with a BZD prescription ("index") claim between 1 April 2016 and 31 December 2017. In the 6 months pre-index, those without and with BZD claims comprised incident and continuing cohorts, which were split by age (incident < 65 [n = 105,737], 65 + [n = 385,951]; continuing < 65 [n = 240,358], 65 + [n = 508,230]). Exposures of interest were: average daily dose and days prescribed of the index BZD; baseline BZD medication possession ratio (MPR) for the continuing cohort; co-prescribed opioids and psychotropics. Our primary outcome was a treated drug OD event (including accidental, intentional, undetermined, or adverse effect) within 30 days of the index BZD, examined using Cox proportional hazards. RESULTS: Among incident and continuing BZD cohorts, 0.78% and 0.56% experienced an OD event. Compared to 14-30 days, a < 14-day fill corresponded to higher OD risk in incident (< 65 adjusted hazard ratio [aHR] 1.16 [95% CI 1.03-1.31]; 65 + : aHR 1.21 [CI 1.13-1.30]) and continuing (< 65: aHR 1.33 [CI 1.15-1.53]; 65 + : aHR 1.43 [CI 1.30-1.57]) cohorts. Among continuing users, lower baseline exposure (i.e., MPR < 0.5) was associated with increased OD risk for those < 65 (aHR 1.20 [CI 1.06-1.36]); 65 + (aHR 1.12 [CI 1.01-1.24]). Along with opioids, concurrent antipsychotic use and antiepileptic use were associated with elevated risk of OD in all 4 cohorts (e.g., aHRs for the continuing 65 + cohort: opioid, 1.73 [CI 1.58-1.90]; antipsychotic, 1.33 [CI 1.18-1.50]; antiepileptic, 1.18 [1.08-1.30]). CONCLUSIONS: In both the incident and continuing cohorts, patients dispensed fewer days' supply were at increased OD risk; those in the continuing cohort with more limited baseline BZD exposure were also at elevated risk. Concurrent medication exposures including opioids, antipsychotics, and antiepileptics were associated with short-term elevated OD risk.

Design and analysis of outcomes following SARS-CoV-2 infection in veterans.

BACKGROUND: Understanding how SARS-CoV-2 infection impacts long-term patient outcomes requires identification of comparable persons with and without infection. We report the design and implementation of a matching strategy employed by the Department of Veterans Affairs' (VA) COVID-19 Observational Research Collaboratory (CORC) to develop comparable cohorts of SARS-CoV-2 infected and uninfected persons for the purpose of inferring potential causative long-term adverse effects of SARS-CoV-2 infection in the Veteran population. METHODS: In a retrospective cohort study, we identified VA health care system patients who were and were not infected with SARS-CoV-2 on a rolling monthly basis. We generated matched cohorts within each month utilizing a combination of exact and time-varying propensity score matching based on electronic health record (EHR)-derived covariates that can be confounders or risk factors across a range of outcomes. RESULTS: From an initial pool of 126,689,864 person-months of observation, we generated final matched cohorts of 208,536 Veterans infected between March 2020-April 2021 and 3,014,091 uninfected Veterans. Matched cohorts were well-balanced on all 39 covariates used in matching after excluding patients for: no VA health care utilization; implausible age, weight, or height; living outside of the 50 states or Washington, D.C.; prior SARS-CoV-2 diagnosis per Medicare claims; or lack of a suitable match. Most Veterans in the matched cohort were male (88.3%), non-Hispanic (87.1%), white (67.2%), and living in urban areas (71.5%), with a mean age of 60.6, BMI of 31.3, Gagne comorbidity score of 1.4 and a mean of 2.3 CDC high-risk conditions. The most common diagnoses were hypertension (61.4%), diabetes (34.3%), major depression (32.2%), coronary heart disease (28.5%), PTSD (25.5%), anxiety (22.5%), and chronic kidney disease (22.5%). CONCLUSION: This successful creation of matched SARS-CoV-2 infected and uninfected patient cohorts from the largest integrated health system in the United States will support cohort studies of outcomes derived from EHRs and sample selection for qualitative interviews and patient surveys. These studies will increase our understanding of the long-term outcomes of Veterans who were infected with SARS-CoV-2.

Polygenic Risk and Social Support in Predicting Depression Under Stress.

OBJECTIVE: Despite substantial progress in identifying genomic variation associated with major depression, the mechanisms by which genomic and environmental factors jointly influence depression risk remain unclear. Genomically conferred sensitivity to the social environment may be one mechanism linking genomic variation and depressive symptoms. The authors assessed whether social support affects the likelihood of depression development differently across the spectrum of genomic risk in two samples that experienced substantial life stress: 1,011 first-year training physicians (interns) in the Intern Health Study (IHS) and 435 recently widowed Health and Retirement Study (HRS) participants. METHODS: Participants' depressive symptoms and social support were assessed with questionnaires that were administered before and after the life stressor. Polygenic risk scores (PRSs) for major depressive disorder were calculated for both samples. RESULTS: Depressive symptom scores increased by 126% after the start of internship in the IHS sample and by 34% after widowing in the HRS sample. There was an interaction between depression PRS and change in social support in the prediction of depressive symptoms in both the IHS sample (incidence rate ratio [IRR]=0.96, 95% CI=0.93, 0.98) and the HRS sample (IRR=0.78, 95% CI=0.66, 0.92), with higher depression PRS associated with greater sensitivity to changes in social support. Johnson-Neyman intervals indicated a crossover effect, with losses and gains in social support moderating the effect of PRS on depressive symptoms. (Johnson-Neyman interval in the IHS sample, -0.02, 0.71; in the HRS sample, -0.49, 1.92). CONCLUSIONS: The study findings suggest that individuals with high genomic risk for developing increased depressive symptoms under adverse social conditions also benefit more from nurturing social environments.