Geographic, Patient, and VA Medical Center Variation in the Receipt and Mode of Primary Care in a National Sample of Veterans with Diabetes during 2020.

While telemedicine infrastructure was in place within the Veterans Health Administration (VHA) healthcare system before the onset of the COVID-19 pandemic, geographically varying ordinances/closures disrupted vital care for chronic disease patients such as those with type 2 diabetes. We created a national cohort of 1,647,158 non-Hispanic White, non-Hispanic Black, and Hispanic veterans with diabetes including patients with at least one primary care visit and HbA1c lab result between 3.5% and 20% in the fiscal year (FY) 2018 or 2019. For each VAMC, the proportion of telehealth visits in FY 2019 was calculated. Two logistic Bayesian spatial models were employed for in-person primary care or telehealth primary care in the fourth quarter of the FY 2020, with spatial random effects incorporated at the VA medical center (MC) catchment area level. Finally, we computed and mapped the posterior probability of receipt of primary care for an "average" patient within each catchment area. Non-Hispanic Black veterans and Hispanic veterans were less likely to receive in-person primary care but more likely to receive tele-primary care than non-Hispanic white veterans during the study period. Veterans living in the most socially vulnerable areas were more likely to receive telehealth primary care in the fourth quarter of FY 2020 compared to the least socially vulnerable group but were less likely to receive in-person care. In summary, racial minorities and those in the most socially vulnerable areas were less likely to receive in-person primary care but more likely to receive telehealth primary care, potentially indicating a disparity in the impact of the pandemic across these groups.

Results of a multicenter cluster-randomized controlled clinical trial testing the effectiveness of a bioinformatics-enabled pharmacist intervention in transplant recipients.

An ambulatory medication safety dashboard was developed to identify missing labs, concerning labs, drug interactions, nonadherence, and transitions in care. This system was tested in a 2-year, prospective, cluster-randomized, controlled multicenter study. Pharmacists at 5 intervention sites used the dashboard to address medication safety issues, compared with usual care provided at 5 control sites. A total of 2196 transplant events were included (1300 intervention vs 896 control). During the 2-year study, the intervention arm had a 11.3% (95% confidence interval, 7.1%-15.5%) absolute risk reduction of having ≥1 emergency department (ED) visit (44.2% vs 55.5%, respectively; P < .001, respectively) and a 12.3% (95% confidence interval, 8.2%-16.4%) absolute risk reduction of having ≥1 hospitalization (30.1% vs 42.4%, respectively; P < .001). In those with ≥1 event, the median ED visit rate (2 [interquartile range (IQR) 1, 5] vs 2 [IQR 1, 4]; P = .510) and hospitalization rate (2 [IQR 1, 3] vs 2 [IQR 1, 3]; P = .380) were similar. Treatment effect varied by comorbidity burden, previous ED visits or hospitalizations, and heart or lung recipients. A bioinformatics dashboard-enabled, pharmacist-led intervention reduced the risk of having at least one ED visit or hospitalization, predominantly demonstrated in lower risk patients.

Evaluation of a non-pharmacological interdisciplinary pain rehabilitation and functional restoration program for chronic pain in veterans.

OBJECTIVE: To conduct a quality improvement evaluation of the Empower Veterans Program (EVP), an interdisciplinary pain rehabilitation/functional restoration program option for functional restoration for high-impact chronic pain, offered in a large metro-area Veterans Health Administration (VHA) system. DATA SOURCES: VHA Corporate Data Warehouse electronic medical record data for patients treated by EVP between 2015 and 2019. EVALUATION DESIGN: This retrospective design first compared EVP patients considered engaged or not engaged in completing treatment in terms of demographic characteristics and post-treatment changes in clinical measures related to opioid use and mental health. We then compared mortality risk between matched groups of treated and untreated patients with chronic pain and concurrent opioid prescriptions using propensity score matching and Cox proportional hazards methods. "Treated" in the matched groups was defined as any level of EVP participation (i.e., both engaged and not engaged). DATA COLLECTION/EXTRACTION METHODS: We first identified 1053 EVP patients with 1 year of pre-and post-treatment follow-time and determined their engagement level. From those with chronic pain and prescription opioids, we matched 237 EVP patients to 375 untreated patients. PRINCIPAL FINDINGS: Engaged patients (57.4% of treated patients), were somewhat older than the non-engaged (mean age 57.1 vs. 53.7, Cohen's D = 0.30), and achieved lower mean PHQ9 depression scores in the post-treatment year (9.2 vs. 10.6, Cohen's D = 0.20). Participation in EVP was associated with a 65% lower mortality risk among Veterans with chronic pain and opioid use when compared to the untreated patients: (HR: 0.35, 95% CI: 0.17, 0.75). CONCLUSIONS: EVP was associated with a large reduction in mortality risk for Veterans with both chronic pain and opioid use. This result could inform the decision process in a VA station or region when considering providing or expanding access to an interdisciplinary rehabilitation/functional restoration program for chronic pain.

Impact of Pharmacist-Driven Transitions of Care Interventions on Post-hospital Outcomes Among Patients With Coronary Artery Disease: A Systematic Review.

Background: Transitions of care (ToC) aim to provide continuity while preventing loss of information that may result in poor outcomes such as hospital readmission. Readmissions not only burden patients, they also increase costs. Given the high prevalence of coronary artery diseases (CAD) in the United States (US), patients with CAD often make up a significant portion of hospital readmissions. Objective: To conduct a systematic review evaluating the impact of pharmacist-driven ToC interventions on post-hospital outcomes for patients with CAD. Methods: MEDLINE, Scopus, and CINAHL were searched from database inception through 03/2020 using key words for CAD and pharmacists. Studies were included if they: (1) identified adults with CAD at US hospitals, (2) evaluated pharmacist-driven ToC interventions, and (3) assessed post-discharge outcomes. Outcomes were summarized qualitatively. Results: Of the 1612 citations identified, 11 met criteria for inclusion. Pharmacist-driven ToC interventions were multifaceted and frequently included medication reconciliation, medication counseling, post-discharge follow-up and initiatives to improve medication adherence. Hospital readmission and emergency room visits were numerically lower among patients receiving vs not receiving pharmacist-driven interventions, with statistically significant differences observed in 1 study. Secondary prevention measures and adherence tended to be more favorable in the pharmacist-driven intervention groups. Conclusion: Eleven studies of multifaceted, ToC interventions led by pharmacists were identified. Readmissions were numerically lower and secondary prevention measures and adherence were more favorable among patients receiving pharmacist-driven interventions. However, sufficiently powered studies are still required to confirm these benefits.

Effectiveness of a substance use treatment program for veterans with chronic pain and opioid use disorder.

OBJECTIVE: Veterans suffer disproportionately from the combined adverse health impacts of chronic pain and hazardous opioid use. This evaluation involved a substance use treatment program that included medication for opioid use disorder (SATP-MOUD) in a large metro-area Veterans Health Administration (VHA). This form of treatment has become increasingly important during the opioid crisis and is among several important Department of Veteran's Affairs (VA) initiatives to improve treatment for opioid use disorder (OUD), for which chronic pain is often a comorbid condition. METHODS: We compared clinical measures related to substance use and mental health between groups who were considered either engaged or not engaged in completing treatment. The study used propensity score matching methods and Cox proportional hazards models to compare the mortality risk for treated and untreated veterans who had chronic pain with concurrent opioid use. RESULTS: We identified 1559 SATP-MOUD patients with 1 year of pre- and post-treatment follow-time. From those with chronic pain and concurrent opioid use, we matched 478 SATP-MOUD patients to 647 untreated patients. Engaged patients (at least 4 visits in the first 8 weeks of treatment) had significant improvements in Brief Addiction Monitor (BAM) scores and in PHQ-9 depression screening scores compared to those who started treatment but did not meet the engagement threshold. In Cox proportional hazards analysis, participation in SATP-MOUD was associated with a 38% lower mortality risk among veterans with chronic pain and opioid use when compared to the untreated group: (HR: 0.62, 95% CI: 0.47, 0.82). CONCLUSIONS: SATP-MOUD, as delivered in actual practice, was associated with significant improvements in depression and addiction severity scores, and was associated with reduced mortality risk for veterans with chronic pain and OUD.

Advanced models for improved prediction of opioid-related overdose and suicide events among Veterans using administrative healthcare data.

Veterans suffer disproportionate health impacts from the opioid epidemic, including overdose, suicide, and death. Prediction models based on electronic medical record data can be powerful tools for identifying patients at greatest risk of such outcomes. The Veterans Health Administration implemented the Stratification Tool for Opioid Risk Mitigation (STORM) in 2018. In this study we propose changes to the original STORM model and propose alternative models that improve risk prediction performance. The best of these proposed models uses a multivariate generalized linear mixed modeling (mGLMM) approach to produce separate predictions for overdose and suicide-related events (SRE) rather than a single prediction for combined outcomes. Further improvements include incorporation of additional data sources and new predictor variables in a longitudinal setting. Compared to a modified version of the STORM model with the same outcome, predictor and interaction terms, our proposed model has a significantly better prediction performance in terms of AUC (84% vs. 77%) and sensitivity (71% vs. 66%). The mGLMM performed particularly well in identifying patients at risk for SREs, where 72% of actual events were accurately predicted among patients with the 100,000 highest risk scores compared with 49.7% for the modified STORM model. The mGLMM's strong performance in identifying true cases (sensitivity) among this highest risk group was the most important improvement given the model's primary purpose for accurately identifying patients at most risk for adverse outcomes such that they are prioritized to receive risk mitigation interventions. Some predictors in the proposed model have markedly different associations with overdose and suicide risks, which will allow clinicians to better target interventions to the most relevant risks. Supplementary Information: The online version contains supplementary material available at 10.1007/s10742-021-00263-7.

Approaches for missing covariate data in logistic regression with MNAR sensitivity analyses.

Data with missing covariate values but fully observed binary outcomes are an important subset of the missing data challenge. Common approaches are complete case analysis (CCA) and multiple imputation (MI). While CCA relies on missing completely at random (MCAR), MI usually relies on a missing at random (MAR) assumption to produce unbiased results. For MI involving logistic regression models, it is also important to consider several missing not at random (MNAR) conditions under which CCA is asymptotically unbiased and, as we show, MI is also valid in some cases. We use a data application and simulation study to compare the performance of several machine learning and parametric MI methods under a fully conditional specification framework (MI-FCS). Our simulation includes five scenarios involving MCAR, MAR, and MNAR under predictable and nonpredictable conditions, where "predictable" indicates missingness is not associated with the outcome. We build on previous results in the literature to show MI and CCA can both produce unbiased results under more conditions than some analysts may realize. When both approaches were valid, we found that MI-FCS was at least as good as CCA in terms of estimated bias and coverage, and was superior when missingness involved a categorical covariate. We also demonstrate how MNAR sensitivity analysis can build confidence that unbiased results were obtained, including under MNAR-predictable, when CCA and MI are both valid. Since the missingness mechanism cannot be identified from observed data, investigators should compare results from MI and CCA when both are plausibly valid, followed by MNAR sensitivity analysis.

Racial-Geographic Disparity in Lipid Management in Veterans with Type 2 Diabetes: A 10-Year Retrospective Cohort Study.

Purpose: The prevalence of diabetes in U.S. veterans (20.5%) is nearly three times that of the general population. Minority veterans have higher rates of diabetes compared with their counterparts and urban/rural residence is also associated with uncontrolled cholesterol. However, the interplay between urban/rural residence and race/ethnicity on cholesterol control is unclear. Methods: Veterans Health Administration Corporate Data Warehouse and Centers for Medicare and Medicaid data were used to create unique dataset and perform longitudinal study of veterans with type 2 diabetes from 2006 to 2016. Logistic regression was used to model the association between low-density lipoprotein (LDL) control and the primary exposures (race/ethnicity and location of residence) after adjusting for all measured covariates, including the interaction between location of residence and race/ethnicity. Results: There was a significant interaction between race/ethnicity and rural residence. Rural non-Hispanic Black (NHB) veterans had higher odds for LDL >100 mg/dL (odds ratio [OR]=1.70, 95% confidence interval [CI] 1.50-1.60) and for LDL >70 mg/dL (OR=1.59, 95% CI 1.53-1.64) compared with urban non-Hispanic White (NHW) veterans. Similarly, compared with urban NHW, urban NHB veterans had higher odds of LDL >100 mg/dL (OR=1.45, 95% CI 1.43-1.47) and LDL >70 mg/dL (OR=1.36, 95% CI 1.34-1.38). Conclusion: This study highlights health disparities for veterans with type 2 diabetes. Future research is needed to evaluate interventions for mitigating these disparities in cholesterol management among veterans with diabetes.

Investigating the Potential for Bias When Using a Widely Accepted Medication Adherence Measure to Predict Mortality.

STUDY OBJECTIVE: Summary measures of medication adherence, such as the proportion of days covered (PDC), are often used to analyze the association between medication adherence and various health outcomes. We hypothesized that PDC and similar measures may lead to biased results in some situations when used to estimate the association between adherence and the outcome event (e.g., mortality). Thus, the objective was to determine the conditions under which PDC and similar measures might produce biased estimates of the association between adherence and mortality and to review methods to avoid such bias. DESIGN: Simulation study and analysis of data from a large retrospective cohort study. MEASUREMENTS AND MAIN RESULTS: We conducted a comprehensive simulation to compare how adherence estimates varied-using prescription-based (end point was final date that medications were on hand or date of death) and interval-based (end point based on fixed calendar interval or date of death) PDC denominators-when deaths occurred either during or after the adherence exposure period. We then made similar comparisons using data from a retrospective study that included comprehensive measures of medication refill activity and clinical outcomes of 207,841 patients with diabetes mellitus who were prescribed one or more oral antidiabetic medications. When deaths occurred within the adherence exposure period, substantial bias in adherence estimates was possible regardless of the PDC denominator type. CONCLUSION: Investigators using PDC or similar proxy measures should carefully consider the temporal relationship between adherence exposure and clinical outcomes when the outcome event affects the adherence measurement.

The interaction between rural/urban status and dual use status among veterans with heart failure.

INTRODUCTION: Dual healthcare system use is associated with higher rates of healthcare utilization, but the influence of rurality on this phenomenon is unclear. This study aimed to determine the extent to which rurality in the USA modifies the likelihood for acute healthcare use among veterans with heart failure (HF). METHODS: Using merged Veterans Affairs (VA), Medicare, and state-level administrative data, a retrospective cohort study of 4985 veterans with HF was performed. Negative binomial regression with interaction term for dual use and geographic location was used to estimate and compare the associations between dual use (as compared to VA-only use) and emergency department (ED) visits, hospitalizations, and 30-day hospital readmissions in rural/highly rural veterans versus urban veterans. RESULTS: The association between dual use compared to VA-only use and ED visits was stronger in rural/highly rural veterans (RR=1.28 (95%CI: 1.21,1.35)) than in urban veterans (rate ratio (RR)=1.17 (95% confidence interval (CI): 1.11,1.22)) (interaction p-value=0.0109), while the association between dual use and all-cause hospitalizations was similar in rural/highly rural veterans (RR=2.00 (95%CI: 1.87, 2.14)) and in urban veterans (RR=1.87 (95%CI: 1.77,1.98)). The association between dual use and all-cause 30-day hospital readmission was also similar in rural/highly rural versus urban veterans. CONCLUSION: Rurality significantly modifies the likelihood of ED visits for HF, although this effect was not observed for hospitalizations or hospital readmissions. While other patient- or system-level factors may more heavily influence hospitalization and readmission in this population, dual use appears to be a marker for higher healthcare utilization and worse outcomes for both urban and rural veterans.

Differences in Hospital Readmission Risk across All Payer Groups in South Carolina.

OBJECTIVE: To evaluate differences in hospital readmission risk across all payers in South Carolina (SC). DATA SOURCES/STUDY SETTING: South Carolina Revenue and Fiscal Affairs Office (SCRFA) statewide all payer claims database including 2,476,431 hospitalizations in SC acute care hospitals between 2008 and 2014. STUDY DESIGN: We compared the odds of unplanned all-cause 30-day readmission for private insurance, Medicare, Medicaid, uninsured, and other payers and examined interaction effects between payer and index admission characteristics using generalized estimating equations. DATA COLLECTION: SCRFA receives claims and administrative health care data from all SC health care facilities in accordance with SC state law. PRINCIPAL FINDINGS: Odds of readmission were lower for females compared to males in private, Medicare, and Medicaid payers. African Americans had higher odds of readmission compared to whites across private insurance, Medicare, and Medicaid, but they had lower odds among the uninsured. Longer length of stay had the strongest association with readmission for private and other payers, whereas an increased number of comorbidities related to the highest readmission odds within Medicaid. CONCLUSIONS: Associations between index admission characteristics and readmission likelihood varied significantly with payer. Findings should guide the development of payer-specific quality improvement programs.

Comorbid depression is differentially associated with longitudinal medication nonadherence by race/ethnicity in patients with type 2 diabetes.

The aim of the study was to examine whether depression impacts medication nonadherence (MNA) over time and determine if race has a differential impact on MNA in patients with type 2 diabetes and comorbid depression.Generalized estimating equations were used with a longitudinal national cohort of 740,197 veterans with type 2 diabetes. MNA was the main outcome defined by <80% medication possession ratio for diabetes medications. The primary independent variable was comorbid depression. Analyses were adjusted for the longitudinal nature of the data and covariates including age, sex, marital status, and rural/urban residence.In adjusted models, MNA was higher in non-Hispanic blacks (NHBs) (odds ratio [OR] 1.58 [95% confidence interval-CI: 1.57, 1.59]), Hispanics (OR 1.34 [95% CI: 1.32, 1.35]), and the other/missing racial/ethnic group (OR 1.37 [95% CI: 1.36, 1.38]) than in non-Hispanic whites (NHWs). In stratified analyses, the odds of MNA associated with depression were highest in NHWs (OR 1.14 [95% CI: 1.12, 1.15]) and were significantly associated in the other 3 minority racial/ethnic groups. MNA was lower in rural than urban NHWs (OR 0.91 [95% CI: 0.90, 0.92]), NHBs (OR 0.92 [95% CI: 0.91, 0.94]), and the other/unknown racial/ethnic group (OR 0.89 [95% CI: 0.88, 0.90]), but higher in rural Hispanic patients (OR 1.12 [95% CI: 1.09, 1.14]).Depression was associated with increased odds of MNA in NHWs, as well as in minority groups, although associations were weaker in minority groups, perhaps as a result of the high baseline levels of MNA in minority groups. There were also differences by race/ethnicity in MNA in rural versus urban subjects.

Attitudes and practices of resident physicians regarding hypertension in the inpatient setting.

Hypertension is prevalent in the population at large and among hospitalized patients. Little has been reported regarding the attitudes and patterns of care of physicians managing nonemergent elevated blood pressure (BP) among inpatients. Resident physicians in internal medicine (IM), family medicine (FM), and surgery were surveyed regarding inpatient BP management. One hundred eighty-one questionnaires were completed across 3 sites. Respondents generally considered inpatient BP control a high priority. A majority of IM and FM residents indicated following the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC 7) consensus guidelines for inpatients compared to 20% of surgery residents (P<.001). While trainees did not appear to strictly follow JNC 7 guidelines for goal BP of 140/90 mm Hg, they did report making frequent BP medication changes (∼51% reported changing regimens for >50% of hypertensive patients). Overall ∼90% indicated that discharging a hypertensive patient on a drug regimen established during hospitalization is preferable to reverting to the regimen in place at the time of admission. Resident physicians regard elevated BP inpatient management as important, but attitudes and practice vary between specialties. JNC 7 guidelines may not be appropriate for inpatient use. Future research should focus on developing functional diagnostic criteria for hypertension in the inpatient setting and determining best practices inpatient BP management.