Faculty Bibliography

While every disease could affect a patient's prognosis, published studies continue to use indices that include a selective list of diseases to predict prognosis, which may limit its accuracy. This paper compares 6-month mortality predicted by a multimorbidity index (MMI) that relies on all diagnoses to the Deyo version of the Charlson index (DCI), a popular index that utilizes a selective set of diagnoses. In this retrospective cohort study, we used data from the Veterans Administration Diabetes Risk national cohort that included 6,082,018 diabetes-free veterans receiving primary care from January 1, 2008 to December 31, 2016. For the MMI, 7805 diagnoses were assigned into 19 body systems, using the likelihood that the disease will increase risk of mortality. The DCI used 17 categories of diseases, classified by clinicians as severe diseases. In predicting 6-month mortality, the cross-validated area under the receiver operating curve for the MMI was 0.828 (95% confidence interval of 0.826-0.829) and for the DCI was 0.749 (95% confidence interval of 0.748-0.750). Using all available diagnoses (MMI) led to a large improvement in accuracy of predicting prognosis of patients than using a selected list of diagnosis (DCI).

BACKGROUND:While emerging studies suggest that the COVID-19 pandemic caused disruptions in routine healthcare utilization, the full impact of the pandemic on healthcare utilization among diverse group of patients with type 2 diabetes is unclear. The purpose of this study is to examine trends in healthcare utilization, including in-person and telehealth visits, among U.S. veterans with type 2 diabetes before, during and after the onset of the COVID-19 pandemic, by demographics, pre-pandemic glycemic control, and geographic region. METHODS:We longitudinally examined healthcare utilization in a large national cohort of veterans with new diabetes diagnoses between January 1, 2008 and December 31, 2018. The analytic sample was 733,006 veterans with recently-diagnosed diabetes, at least 1 encounter with veterans administration between March 2018-2020, and followed through March 2021. Monthly rates of glycohemoglobin (HbA1c) measurements, in-person and telehealth outpatient visits, and prescription fills for diabetes and hypertension medications were compared before and after March 2020 using interrupted time-series design. Log-linear regression model was used for statistical analysis. Secular trends were modeled with penalized cubic splines. RESULTS:In the initial 3 months after the pandemic onset, we observed large reductions in monthly rates of HbA1c measurements, from 130 (95%CI,110-140) to 50 (95%CI,30-80) per 1000 veterans, and in-person outpatient visits, from 1830 (95%CI,1640-2040) to 810 (95%CI,710-930) per 1000 veterans. However, monthly rates of telehealth visits doubled between March 2020-2021 from 330 (95%CI,310-350) to 770 (95%CI,720-820) per 1000 veterans. This pattern of increases in telehealth utilization varied by community type, with lowest increase in rural areas, and by race/ethnicity, with highest increase among non-hispanic Black veterans. Combined in-person and telehealth outpatient visits rebounded to pre-pandemic levels after 3 months. Despite notable changes in HbA1c measurements and visits during that initial window, we observed no changes in prescription fills rates. CONCLUSIONS:Healthcare utilization among veterans with diabetes was substantially disrupted at the onset of the pandemic, but rebounded after 3 months. There was disparity in uptake of telehealth visits by geography and race/ethnicity.

The objective of this study was to compare unannounced standardized patient (USP) and patient reports of care. Patient satisfaction surveys and USP checklist results collected at an urban, public hospital were compared to identify items included in both surveys. Qualitative commentary was reviewed to better understand USP and patient satisfaction survey data. Analyses included χ² and Mann-Whitney U test. Patients provided significantly higher ratings on 10 of the 11 items when compared to USPs. USPs may provide a more objective perspective on a clinical encounter than a real patient, reinforcing the notion that real patients skew overly positive or negative.

COVID-19 symptom definitions rarely include symptom severity. We collected daily nasal swabs and symptom diaries from contacts of SARS-CoV-2 cases. Requiring ≥1 moderate or severe symptom reduced sensitivity to predict SARS-CoV-2 shedding from 60.0% (CI: 52.9-66.7%) to 31.5% (CI: 25.7-38.0%), but increased specificity from 77.5% (CI:75.3-79.5%) to 93.8% (CI: 92.7-94.8%).

INTRODUCTION/BACKGROUND:The aim of this research was to assess the association between inflammation and oral health and diabetes, as well as the mediating role of oral hygiene practice in this association. METHODS:Data were from the 2009-2010 National Health and Nutrition Examination Survey. The analytical sample consisted of 2,191 respondents aged 50 and older. Poor oral health was clinically defined by significant tooth loss (STL) and periodontal disease (PD). Diabetes mellitus (DM) was determined by glycemic levels. The outcome variable was serum C-reactive protein (CRP) level, dichotomised as ≥1 mg/dL (elevated CRP) vs <1 mg/dL (not elevated CRP). Two path models, one using STL and DM as the independent variable, the other using PD and DM as the independent variable, were estimated to assess the direct effects of having poor oral health and DM on elevated CRP and the mediating effects of dental flossing. RESULTS:In path model 1, individuals having both STL and DM (adjusted odds ratio [AOR], 1.92; 95% confidence interval [CI], 1.30-2.82) or having STL alone (AOR, 2.30; 95% CI, 1.68-3.15) were more likely to have elevated CRP than those with neither STL nor DM; dental flossing (AOR, 0.92, 95% CI, 0.88-0.96) was associated with lower risk of elevated CRP. In path model 2, no significant association was found between having both PD and DM and elevated CRP; dental flossing (AOR, 0.91; 95% CI:, 0.86-0.94) was associated with lower risk of elevated CRP. CONCLUSIONS:Findings from this study highlight the importance of improving oral health and oral hygiene practice to mitigate inflammation. Further research is needed to assess the longer-term effects of reducing inflammation.

BACKGROUND:Large-scale longitudinal studies evaluating influences of the built environment on risk for type 2 diabetes (T2D) are scarce, and findings have been inconsistent. OBJECTIVE:To evaluate whether land use environment (LUE), a proxy of neighborhood walkability, is associated with T2D risk across different US community types, and to assess whether the association is modified by food environment. METHODS:The Veteran's Administration Diabetes Risk (VADR) study is a retrospective cohort of diabetes-free US veteran patients enrolled in VA primary care facilities nationwide from January 1, 2008, to December 31, 2016, and followed longitudinally through December 31, 2018. A total of 4,096,629 patients had baseline addresses available in electronic health records that were geocoded and assigned a census tract-level LUE score. LUE scores were divided into quartiles, where a higher score indicated higher neighborhood walkability levels. New diagnoses for T2D were identified using a published computable phenotype. Adjusted time-to-event analyses using piecewise exponential models were fit within four strata of community types (higher-density urban, lower-density urban, suburban/small town, and rural). We also evaluated effect modification by tract-level food environment measures within each stratum. RESULTS:In adjusted analyses, higher LUE had a protective effect on T2D risk in rural and suburban/small town communities (linear quartile trend test p-value <0.001). However, in lower density urban communities, higher LUE increased T2D risk (linear quartile trend test p-value <0.001) and no association was found in higher density urban communities (linear quartile trend test p-value = 0.317). Particularly strong protective effects were observed for veterans living in suburban/small towns with more supermarkets and more walkable spaces (p-interaction = 0.001). CONCLUSION/CONCLUSIONS:Among veterans, LUE may influence T2D risk, particularly in rural and suburban communities. Food environment may modify the association between LUE and T2D.

INTRODUCTION/BACKGROUND:Early or mid-career physicians have few opportunities to participate in career development programs in health policy and advocacy with experiential and mentored training that can be incorporated into their busy lives. AIM/OBJECTIVE:The Society of General Internal Medicine (SGIM) created the Leadership in Health Policy (LEAHP) program, a year-long career development program, to prepare participants with a sufficient depth of knowledge, skills, attitudes, and behaviors to continue to build mastery and effectiveness as leaders, advocates, and educators in health policy. We sought to evaluate the program's impact on participants' self-efficacy in the core skills targeted in the curriculum. SETTING/PARTICIPANTS/METHODS:Fifty-five junior faculty and trainees across three scholar cohorts from 2017 to 2021. PROGRAM DESCRIPTION/METHODS:Activities included workshops and exercises at an annual meeting, one-on-one mentorship, monthly webinars and journal clubs, interaction with policy makers, and completion of capstone projects. PROGRAM EVALUATION/RESULTS:Self-administered, electronic surveys conducted before and following the year-long program showed a significant improvement in mean self-efficacy scores for the total score and for each of the six domains in general knowledge, teaching, research, and advocacy in health policy. Compared to the baseline scores, after the program the total mean score increased from 3.1 to 4.1, an increase of 1.1 points on a 5-point Likert scale (95% CI: 0.9-1.3; Cohen's D: 1.7), with 61.4% of respondents increasing their mean score by at least 1 point. Responses to open-ended questions indicated that the program met scholars' stated needs to improve their knowledge base in health policy and advocacy skills. DISCUSSION/CONCLUSIONS:The LEAHP program provides an opportunity for mentored, experiential training in health policy and advocacy, can build the knowledge and amplify the scale of physicians engaged in health policy, and help move physicians from individual patient advocacy in the clinic to that of populations.

Importance:Racial and ethnic diversity among study participants is associated with improved generalizability of clinical trial results and may address inequities in evidence that informs public health strategies. Novel strategies are needed for equitable access and recruitment of diverse clinical trial populations. Objective:To investigate demographic and geographical location data for participants in 2 remote COVID-19 clinical trials with online recruitment and compare with those of a contemporaneous clinic-based COVID-19 study. Design, Setting, and Participants:This cohort study was conducted using data from 3 completed, prospective randomized clinical trials conducted at the same time: 2 remotely conducted studies (the Early Treatment Study and Hydroxychloroquine COVID-19 Postexposure Prophylaxis [PEP] Study) and 1 clinic-based study of convalescent plasma (the Expanded Access to Convalescent Plasma for the Treatment of Patients With COVID-19 study). Data were collected from March to August 2020 with 1 to 28 days of participant follow-up. All studies had clinical sites in Seattle, Washington; the 2 remote trials also had collaborating sites in New York, New York; Syracuse, New York; Baltimore, Maryland; Boston, Massachusetts; Chicago, Illinois; New Orleans, Louisiana; and Los Angeles, California. Two remote trials with inclusive social media strategies enrolled 929 participants with recent SARS-CoV-2 exposure (Hydroxychloroquine COVID-19 PEP Trial) and 231 participants with COVID-19 infection (Early Treatment Study); the clinic-based Expanded Access to Convalescent Plasma for the Treatment of Patients With COVID-19 study enrolled 250 participants with recent COVID-19 infection. Data were analyzed from April to August 2021. Interventions:Remote trials used inclusive social media strategies and clinician referral for recruitment and telehealth, courier deliveries, and self-collected nasal swabs for remotely conducted study visits. For the clinic-based study, participants were recruited via clinician referral and attended in-person visits. Main Outcomes and Measures:Google Analytics data were used to measure online participant engagement and recruitment. Participant demographics and geographical location data from remote trials were pooled and compared with those of the clinic-based study. Statistical comparison of demographic data was limited to participants with COVID infections (ie, those in the remotely conducted Early Treatment Study vs those in the clinic-based study) to improve accuracy of comparison given that the Hydroxychloroquine COVID-19 PEP Trial enrolled participants with COVID-19 exposures and thus had different enrollment criteria. Results:A total of 1410 participants were included. Among 1160 participants in remote trials and 250 participants in the clinic-based trial, the mean (range) age of participants was 39 (18-80) years vs 50 (19-79) years and 676 individuals (58.3%) vs 131 individuals (52.4%) reported female sex. The Early Treatment Study with inclusive social media strategies enrolled 231 participants in 41 US states with increased rates of racial, ethnic, and geographic diversity compared with participants in the clinic-based study. Among 228 participants in the remotely conducted Early Treatment Study with race data vs participants in the clinic-based study, 39 individuals (17.1%) vs 1 individual (0.4%) identified as Alaska Native or American Indian, 11 individuals (4.8%) vs 22 individuals (8.8%) identified as Asian, 26 individuals (11.4%) vs 4 individuals (1.6%) identified as Black, 3 individuals (1.3%) vs 1 individual identified as Native Hawaiian or Pacific Islander, 117 individuals (51.3%) vs 214 individuals (85.6%) identified as White, and 32 individuals (14.0%) vs 8 individuals (3.2%) identified as other race (P < .001). Among 230 individuals in the Early Treatment Study vs 236 individuals in the clinic-based trial with ethnicity data, 71 individuals (30.9%) vs 11 individuals (4.7%) identified as Hispanic or Latinx (P<.001). There were 29 individuals in the Early Treatment Study with nonurban residences (ie, rural, small town, or peri-urban; 12.6%) vs 6 of 248 individuals in the clinic-based trial with residence data (2.4%) (P < .001). In remote trial online recruitment, the highest engagement was with advertisements on social media platforms; among 125 147 unique users with age demographics who clicked on online recruitment advertisements, 84 188 individuals (67.3%) engaged via Facebook. Conclusions and Relevance:These findings suggest that remote clinical trials with online advertising may be considered as a strategy to improve diversity among clinical trial participants.

Socioeconomic status-related (SES-related) health disparities are worsening across resource-rich environments, despite increased knowledge about health determinants and inducements for healthful behavior change. We ask whether insights from addiction science and evolutionary biology may assist understanding and counteracting SES-related health disparities. It is known that a mismatch between evolved traits and behaviors that conserve energy drives many health deficits. We posit that this energy mismatch is one manifestation of a more expansive mismatch in levels of reward activation, between environments more versus less manipulated by human activity. This larger mismatch explains why SES-related health disparities arise not only from overeating and excessive sedentism, but also from alcohol, nicotine, other substances, and mood disorders. Lower SES persons are more likely to have lower baseline reward activation, which leads to higher prioritization of reward elevating activities, and at the same time are less likely to act on knowledge about unhealthfulness of behaviors.