Metformin prescription for U.S. veterans with prediabetes, 2010-2019.

Affecting an estimated 88 million Americans, prediabetes increases the risk for developing type 2 diabetes mellitus (T2DM), and independently, cardiovascular disease, retinopathy, nephropathy, and neuropathy. Nevertheless, little is known about the use of metformin for diabetes prevention among patients in the Veterans Health Administration, the largest integrated healthcare system in the U.S. This is a retrospective observational cohort study of the proportion of Veterans with incident prediabetes who were prescribed metformin at the Veterans Health Administration from October 2010 to September 2019. Among 1,059,605 Veterans with incident prediabetes, 12,009 (1.1%) were prescribed metformin during an average 3.4 years of observation after diagnosis. Metformin prescribing was marginally higher (1.6%) among those with body mass index (BMI) ≥35 kg/m2, age <60 years, HbA1c≥6.0%, or those with a history of gestational diabetes, all subgroups at a higher risk for progression to T2DM. In a multivariable model, metformin was more likely to be prescribed for those with BMI ≥35 kg/m2 incidence rate ratio [IRR] 2.6 [95% confidence intervals (CI): 2.1-3.3], female sex IRR, 2.4 [95% CI: 1.8-3.3], HbA1c≥6% IRR, 1.93 [95% CI: 1.5-2.4], age <60 years IRR, 1.7 [95% CI: 1.3-2.3], hypertriglyceridemia IRR, 1.5 [95% CI: 1.2-1.9], hypertension IRR, 1.5 [95% CI: 1.1-2.1], Major Depressive Disorder IRR, 1.5 [95% CI: 1.1-2.0], or schizophrenia IRR, 2.1 [95% CI: 1.2-3.8]. Over 20% of Veterans with prediabetes attended a comprehensive structured lifestyle modification clinic or program. Among Veterans with prediabetes, metformin was prescribed to 1.1% overall, a proportion that marginally increased to 1.6% in the subset of individuals at highest risk for progression to T2DM.

Characteristics of Chiropractic Patients in the Veterans Health Administration During the COVID-19 Pandemic: A Cross-Sectional Analysis.

OBJECTIVE: The purpose of this study was to determine whether patient characteristics were associated with face-to-face (F2F) and telehealth visits for those receiving chiropractic care for musculoskeletal conditions in the US Veterans Health Administration (VHA) during the COVID-19 pandemic. METHODS: A retrospective cross-sectional analysis of all patients (veterans, dependents, and spouses) who received chiropractic care nationwide at the VHA from March 1, 2020, to February 28, 2021, was performed. Patients were allocated into 1 of the following 3 groups: only telehealth visits, only F2F visits, and combined F2F and telehealth visits. Patient characteristics included age, sex, race, ethnicity, marital status, and Charlson Comorbidity Index. Multinomial logistic regression estimated associations of these variables with visit type. RESULTS: The total number of unique patients seen by chiropractors between March 2020 and February 2021 was 62 658. Key findings were that patients of non-White race and Hispanic or Latino ethnicity were more likely to attend telehealth-only visits (Black [odds ratio 1.20, 95% confidence interval {1.10-1.31}], other races [1.36 {1.16-1.59}], and Hispanic or Latino [1.35 {1.20-1.52}]) and combination telehealth and F2F care (Black [1.32 {1.25-1.40}], other races [1.37 {1.23-1.52}], and Hispanic or Latino [1.63 {1.51-1.76}]). Patients younger than 40 years of age were more likely to choose telehealth visits ([1.13 {1.02-1.26}], 66-75 years [1.17 {1.01-1.35}], and >75 years [1.26 {1.06-1.51}] vs those 40-55 years of age). Sex, visit frequency, and Charlson Comorbidity Index showed significant relationships as well, while marital status did not. CONCLUSION: During the COVID-19 pandemic, VHA patients with musculoskeletal complaints using chiropractic telehealth were more ethnically and racially diverse than those using F2F care alone.

Measuring coordination of epilepsy care: A mixed methods evaluation of social network analysis versus relational coordination.

OBJECTIVES: Coordination of multidisciplinary care is critical to address the complex needs of people with neurological disorders; however, quality improvement and research tools to measure coordination of neurological care are not well-developed. This study explored and compared the value of social network analysis (SNA) and relational coordination (RC) in measuring coordination of care in a neurology setting. The Department of Veterans Affairs Healthcare System (VA) established an Epilepsy Centers of Excellence (ECOE) hub and spoke model of care, which provides a setting to measure coordination of care across networks of providers. METHODS: In a parallel mixed methods approach, we compared coordination of care of VA providers who formally engage the ECOE system to VA providers outside the ECOE system using SNA and RC. Coordination of care scores were compiled from provider teams across 66 VA facilities, and key informant interviews of 80 epilepsy care team members were conducted concurrently to describe the quality of epilepsy care coordinating in the VA healthcare system. RESULTS: On average, members of healthcare teams affiliated with the ECOE program rated quality of communication and respect higher than non-ECOE physicians. Connectivity between neurologist and primary care providers as well as between neurologists and mental health providers were higher within ECOE hub facilities compared to spoke referring facilities. Key informant interviews reported the important role of formal and informal programming, social support and social capital, and social influence on epilepsy care networks. CONCLUSION: For quality improvement and research purposes, SNA and RC can be used to measure coordination of neurological care; RC provides a detailed assessment of the quality of communication within and across healthcare teams but is difficult to administer and analyze; SNA provides large scale coordination of care maps and metrics to compare across large healthcare systems. The two measures provide complimentary coordination of care data at a local as well as population level. Interviews describe the mechanisms of developing and sustaining health professional networks that are not captured in either SNA or RC measures.