Faculty Bibliography

PURPOSE/OBJECTIVE:The veterans administration diabetes risk (VADR) cohort facilitates studies on temporal and geographic patterns of pre-diabetes and diabetes, as well as targeted studies of their predictors. The cohort provides an infrastructure for examination of novel individual and community-level risk factors for diabetes and their consequences among veterans. This cohort also establishes a baseline against which to assess the impact of national or regional strategies to prevent diabetes in veterans. PARTICIPANTS/METHODS:The VADR cohort includes all 6 082 018 veterans in the USA enrolled in the veteran administration (VA) for primary care who were diabetes-free as of 1 January 2008 and who had at least two diabetes-free visits to a VA primary care service at least 30 days apart within any 5-year period since 1 January 2003, or veterans subsequently enrolled and were diabetes-free at cohort entry through 31 December 2016. Cohort subjects were followed from the date of cohort entry until censure defined as date of incident diabetes, loss to follow-up of 2 years, death or until 31 December 2018. FINDINGS TO DATE/UNASSIGNED:The incidence rate of type 2 diabetes in this cohort of over 6 million veterans followed for a median of 5.5 years (over 35 million person-years (PY)) was 26 per 1000 PY. During the study period, 8.5% of the cohort were lost to follow-up and 17.7% died. Many demographic, comorbidity and other clinical variables were more prevalent among patients with incident diabetes. FUTURE PLANS/UNASSIGNED:This cohort will be used to study community-level risk factors for diabetes, such as attributes of the food environment and neighbourhood socioeconomic status via geospatial linkage to residence address information.

Importance:The prevalence of leading risk factors for morbidity and mortality in the US significantly varies across regions, states, and neighborhoods, but the extent these differences are associated with a person's place of residence vs the characteristics of the people who live in different places remains unclear. Objective:To estimate the degree to which geographic differences in leading risk factors are associated with a person's place of residence by comparing trends in health outcomes among individuals who moved to different areas or did not move. Design, Setting, and Participants:This retrospective cohort study estimated the association between the differences in the prevalence of uncontrolled chronic conditions across movers' destination and origin zip codes and changes in individuals' likelihood of uncontrolled chronic conditions after moving, adjusting for person-specific fixed effects, the duration of time since the move, and secular trends among movers and those who did not move. Electronic health records from the Veterans Health Administration were analyzed. The primary analysis included 5 342 207 individuals with at least 1 Veterans Health Administration outpatient encounter between 2008 and 2018 who moved zip codes exactly once or never moved. Exposures:The difference in the prevalence of uncontrolled chronic conditions between a person's origin zip code and destination zip code (excluding the individual mover's outcomes). Main Outcomes and Measures:Prevalence of uncontrolled blood pressure (systolic blood pressure level >140 mm Hg or diastolic blood pressure level >90 mm Hg), uncontrolled diabetes (hemoglobin A1c level >8%), obesity (body mass index >30), and depressive symptoms (2-item Patient Health Questionnaire score ≥2) per quarter-year during the 3 years before and the 3 years after individuals moved. Results:The study population included 5 342 207 individuals (mean age, 57.6 [SD, 17.4] years, 93.9% men, 72.5% White individuals, and 12.7% Black individuals), of whom 1 095 608 moved exactly once and 4 246 599 never moved during the study period. Among the movers, the change after moving in the prevalence of uncontrolled blood pressure was 27.5% (95% CI, 23.8%-31.3%) of the between-area difference in the prevalence of uncontrolled blood pressure. Similarly, the change after moving in the prevalence of uncontrolled diabetes was 5.0% (95% CI, 2.7%-7.2%) of the between-area difference in the prevalence of uncontrolled diabetes; the change after moving in the prevalence of obesity was 3.1% (95% CI, 2.0%-4.2%) of the between-area difference in the prevalence of obesity; and the change after moving in the prevalence of depressive symptoms was 15.2% (95% CI, 13.1%-17.2%) of the between-area difference in the prevalence of depressive symptoms. Conclusions and Relevance:In this retrospective cohort study of individuals receiving care at Veterans Health Administration facilities, geographic differences in prevalence were associated with a substantial percentage of the change in individuals' likelihood of poor blood pressure control or depressive symptoms, and a smaller percentage of the change in individuals' likelihood of poor diabetes control and obesity. Further research is needed to understand the source of these associations with a person's place of residence.

OBJECTIVE:This paper compares the accuracy of predicting suicide from Social Determinants of Health (SDoH) or history of illness. POPULATION STUDIED/METHODS:5 313 965 Veterans who at least had two primary care visits between 2008 and 2016. STUDY DESIGN/METHODS:The dependent variable was suicide or intentional self-injury. The independent variables were 10 495 International Classification of Disease (ICD) Version 9 codes, age, and gender. The ICD codes included 40 V-codes used for measuring SDoH, such as family disruption, family history of substance abuse, lack of education, legal impediments, social isolation, unemployment, and homelessness. The sample was randomly divided into training (90 percent) and validation (10 percent) sets. Area under the receiver operating characteristic (AROC) was used to measure accuracy of predictions in the validation set. PRINCIPAL FINDINGS/RESULTS:Separate analyses were done for inpatient and outpatient codes; the results were similar. In the hospitalized group, the mean age was 67.2 years, and 92.1 percent were male. The mean number of medical diagnostic codes during the study period was 37; and 12.9 percent had at least one SDoH V-code. At least one episode of suicide or intentional self-injury occurred in 1.89 percent of cases. SDoH V-codes, on average, elevated the risk of suicide or intentional self-injury by 24-fold (ranging from 4- to 86-fold). An index of 40 SDoH codes predicted suicide or intentional self-injury with an AROC of 0.64. An index of 10 445 medical diagnoses, without SDoH V-codes, had AROC of 0.77. The combined SDoH and medical diagnoses codes also had AROC of 0.77. CONCLUSION/CONCLUSIONS:In predicting suicide or intentional self-harm, SDoH V-codes add negligible information beyond what is already available in medical diagnosis codes. IMPLICATIONS FOR PRACTICE/CONCLUSIONS:Policies that affect SDoH (eg, housing policies, resilience training) may not have an impact on suicide rates, if they do not change the underlying medical causes of SDoH.

Collaboration among diverse stakeholders involved in the value transformation of health care requires consistent use of terminology. The objective of this study was to reach consensus definitions for the terms value-based care, value-based payment, and population health. A modified Delphi process was conducted from February 2017 to July 2017. An in-person panel meeting was followed by 3 rounds of surveys. Panelists anonymously rated individual components of definitions and full definitions on a 9-point Likert scale. Definitions were modified in an iterative process based on results of each survey round. Participants were a panel of 18 national leaders representing population health, health care delivery, academic medicine, payers, patient advocacy, and health care foundations. Main measures were survey ratings of definition components and definitions. At the conclusion of round 3, consensus was reached on the following definition for value-based payment, with 13 of 18 panelists (72.2%) assigning a high rating (7- 9) and 1 of 18 (5.6%) assigning a low rating (1-3): "Value-based payment aligns reimbursement with achievement of value-based care (health outcomes/cost) in a defined population with providers held accountable for achieving financial goals and health outcomes. Value-based payment encourages optimal care delivery, including coordination across healthcare disciplines and between the health care system and community resources, to improve health outcomes, for both individuals and populations." The iterative process elucidated specific areas of agreement and disagreement for value-based care and population health but did not reach consensus. Policy makers cannot assume uniform interpretation of other concepts underlying health care reform efforts.

BACKGROUND:Evidence shows community health workers (CHWs) can effectively deliver proven behavior-change strategies to prevent type 2 diabetes mellitus (diabetes) and enhance preventive care efforts in primary care for minority and low-income populations. However, operational details to integrate CHWs into primary care practice remain less well known. OBJECTIVE:To examine clinicians' perceptions about working with CHWs for diabetes prevention in safety-net primary care. SETTING/METHODS:Clinicians are primary care physicians and nurses at two New York City safety-net hospitals participating in CHORD (Community Health Outreach to Reduce Diabetes). CHORD is a cluster-randomized trial testing a CHW intervention to prevent diabetes. DESIGN/METHODS:Guided by the Consolidated Framework for Implementation Research, we studied how features of the CHW model and organizational context of the primary care practices influenced clinicians' perspectives about the acceptability, appropriateness, and feasibility of a diabetes-prevention CHW program. Data were collected pre-intervention using semi-structured interviews (n = 18) and a 20-item survey (n = 54). APPROACH/METHODS:Both survey and interview questions covered clinicians' perspectives on diabetes prevention, attitudes and beliefs about CHWs' role, expectations in working with CHWs, and use of clinic- and community-based diabetes- prevention resources. Survey responses were descriptively analyzed. Interviews were coded using a mix of deductive and inductive approaches for thematic analysis. KEY RESULTS/RESULTS:Eighty-seven percent of survey respondents agreed CHWs could help in preventing diabetes; 83% reported interest in working with CHWs. Ninety-one percent were aware of clinic-based prevention resources; only 11% were aware of community resources. Clinicians supported CHWs' cultural competency and neighborhood reach, but expressed concerns about the adequacy of CHWs' training; public and professional emphasis on diabetes treatment over prevention; and added workload and communication with CHWs. CONCLUSIONS:Clinicians found CHWs appropriate for diabetes prevention in safety-net settings. However, disseminating high-quality evidence about CHWs' effectiveness and operations is needed to overcome concerns about integrating CHWs in primary care.

Importance/UNASSIGNED:Temporary disruptions in health care access are common, but their associations with chronic disease control remain unknown. Objective/UNASSIGNED:To evaluate whether long-term changes in chronic disease control were associated with a temporary 6-month decrease in access to health care services. Design, Setting, and Participants/UNASSIGNED:This cohort study examined the long-term changes in chronic disease control associated with the 6-month closure of the Manhattan facility of the Veterans Affairs (VA) New York Harbor Healthcare System after superstorm Sandy, which caused a significant disruption in health care access for veterans in the region. Electronic health records from the VA Healthcare System between October 29, 2010, and October 29, 2014, were used to identify a total of 81 544 veterans who were and were not exposed to the 6-month closure of the VA Manhattan Medical Center after superstorm Sandy. Of those, 19 207 veterans were included in the exposed cohort and 62 337 were included in the nonexposed control cohort, which included veterans who were equally exposed to the storm but who retained regular access to health care from 3 VA medical centers (Brooklyn and the Bronx in New York and New Haven in Connecticut) during and after the storm. A difference-in-differences analysis was used to assess within-patient changes in chronic disease control over time between a cohort that was exposed to decreased health care access compared with a similar cohort that was not exposed to decreased access. All analyses adjusted for individual demographic and socioeconomic characteristics, between-zip code differences, and common time trends. Data analyses were conducted between February 1, 2016, and September 30, 2019. Exposure/UNASSIGNED:The 6-month closure of the VA Manhattan Medical Center after superstorm Sandy on October 29, 2012. Main Outcomes and Measures/UNASSIGNED:The outcomes measured were uncontrolled blood pressure (defined as mean blood pressure per patient per quarter >140/90 mm Hg), uncontrolled diabetes (defined as mean hemoglobin A1c per patient per quarter >8%), uncontrolled cholesterol (defined as mean low density lipoprotein per patient per quarter >140 mg/dL), and patient weight. Results/UNASSIGNED:Among the 81 544 veterans included in the study, the mean (SD) age was 62.1 (17.6) years, and 93.6% were men, 62.7% were white, and 31.8% were black. At the 3-month midpoint of the 6-month facility closure of the VA Manhattan Medical Center, an absolute decrease of 24.8% (95% CI, -26.5% to -23.0%; P < .001) was observed in the percentage of veterans who had any VA primary care visit per quarter compared with a baseline of 47.8% before the closure (relative decrease, 51.9%; 95% CI, -55.4% to -48.1%; P < .001). One year after the facility reopened, no differential change was observed in the percentage of patients with a primary care visit between the exposed vs nonexposed cohorts (absolute decrease, -0.1%; 95% CI, -1.5% to 1.4%; P = .94); however, patients in the exposed cohort were 25.9% more likely to have uncontrolled blood pressure than patients in the nonexposed cohort (unadjusted increase, 5.5% in the exposed cohort vs 1.3% in the nonexposed cohort; adjusted absolute increase, 5.0%; 95% CI, 3.5%-6.0%; P < .001). Two years after superstorm Sandy, patients in the exposed cohort were 10.9% more likely to experience uncontrolled blood pressure than those in the nonexposed cohort (unadjusted increase, 5.2% in the exposed cohort vs 3.5% in the nonexposed cohort; adjusted absolute increase, 2.1%; 95% CI, 0.5%-3.6%; P < .001). Compared with the nonexposed cohort, the exposed cohort also experienced a decrease in filled medication prescriptions per patient per quarter of 6.9% during the facility closure (absolute decrease, -0.7 prescriptions filled per patient per quarter; 95% CI, -0.9 to -0.5; P < .001) and of 2.2% a year after the facility reopened (absolute decrease, -0.2 prescriptions filled per patient per quarter; 95% CI, -0.4 to -0.1; P = .04). No differential changes were observed in uncontrolled diabetes, uncontrolled cholesterol, or patient weight. Conclusions and Relevance/UNASSIGNED:In this study, a temporary period of decreased access to health care services was associated with increased rates of uncontrolled hypertension, but not with increased rates of uncontrolled diabetes or hyperlipidemia, more than 1 year after the Manhattan VA facility reopened. Temporary gaps in access to health care may be associated with long-term increases in uncontrolled blood pressure among patients with hypertension.

BACKGROUND:Exposure to antibiotics may increase the risk of type 2 diabetes. Veterans are at increased risk for diabetes and for exposure to antibiotics. OBJECTIVE:To determine the impact of antibiotic exposure for risk of diabetes. DESIGN/METHODS:Retrospective cohort study. PARTICIPANTS/METHODS:Veterans at the New York Harbor Healthcare System enrolled in primary care, 2004-2014, with ≥2 glycosylated hemoglobin test results <6.5%. MAIN MEASURES/METHODS:The primary exposure was any antimicrobial prescribed >6 months prior to the date of diabetes diagnosis, loss to follow-up, death, or the end of the study, measured as the number of courses of antimicrobial prescriptions filled and the mean daily dose (MDD). The primary outcome was incident diagnosis of diabetes through 2014, defined ≥2 ICD-9 codes for diabetes or ≥2 prescriptions of diabetes medications, other than metformin. Cox proportional hazards regression was used to model antimicrobial medications, demographic and anthropometric measures, and comorbid cardiovascular conditions to incident diabetes. Models incorporated time varying covariates of antimicrobial medication and MDD to analyze associations by antimicrobial class. KEY RESULTS/RESULTS:Among 14,361 Veterans, 9922 (69.1%) were prescribed any antimicrobial medication during the study period. 1413 (9.8%) individuals developed type 2 diabetes. Increased risk of diabetes was associated with >1 prescription (HR 1.13 [1.01-1.26]) compared to none. Time varying analysis of the total number of cumulative courses prescribed showed increased diabetes risk for cephalosporin (HR 1.17 [1.04-1.31]), macrolide (HR 1.08 [1.03-1.13]) and penicillin (HR 1.05 [1.02-1.07]). MDD showed increased risk per 100-unit (mg) increase in antibiotic exposure from (HR 1.05 [1.02-1.08]) for sulfonamide to (HR 1.70 [1.51-1.92]) for cephalosporin. CONCLUSION/CONCLUSIONS:Any and repeated exposure to certain antibiotics may increase diabetes risk among Veterans. Results from this study add to the growing evidence suggesting that antibiotic exposure increases risk for diabetes. Antibiotic stewardship may be enhanced by better understanding this risk, and may lower the incidence of diabetes in populations at risk.