Faculty Bibliography

Existing methods of screening for substance abuse (standardized questionnaires or clinician's simply asking) have proven difficult to initiate and maintain in primary care settings. This article reports on how predictive modeling can be used to screen for substance abuse using extant data in electronic health records (EHRs). We relied on data available through Veterans Affairs Informatics and Computing Infrastructure (VINCI) for the years 2006 through 2016. We focused on 4,681,809 veterans who had at least two primary care visits; 829,827 of whom had a hospitalization. Data included 699 million outpatient and 17 million inpatient records. The dependent variable was substance abuse as identified from 89 diagnostic codes using the Agency for Healthcare Quality and Research classification of diseases. In addition, we included the diagnostic codes used for identification of prescription abuse. The independent variables were 10,292 inpatient and 13,512 outpatient diagnoses, plus 71 dummy variables measuring age at different years between 20 and 90 years. A modified naive Bayes model was used to aggregate the risk across predictors. The accuracy of the predictions was examined using area under the receiver operating characteristic (AROC) curve in 20% of data, randomly set aside for the evaluation. Many physical/mental illnesses were associated with substance abuse. These associations supported findings reported in the literature regarding the impact of substance abuse on various diseases and vice versa. In randomly set-aside validation data, the model accurately predicted substance abuse for inpatient (AROC = 0.884), outpatient (AROC = 0.825), and combined inpatient and outpatient (AROC = 0.840) data. If one excludes information available after substance abuse is known, the cross-validated AROC remained high, 0.822 for inpatient and 0.817 for outpatient data. Data within EHRs can be used to detect existing or predict potential future substance abuse.

BACKGROUND:Type 2 diabetes mellitus (DM) affects 9.4% of US adults and children, while another 33.9% of Americans are at risk of DM. Health care institutions face many barriers to systematically delivering the preventive care needed to decrease DM incidence. Community health workers (CHWs) may, as frontline public health workers bridging clinic and community, help overcome these challenges. This paper presents the protocol for a pragmatic, cluster-randomized trial integrating CHWs into two primary care clinics to support DM prevention for at-risk patients. METHODS:The trial will randomize 15 care teams, stratified by practice site (Bellevue Hospital and Manhattan VA), totaling 56 primary care physicians. The study cohort will consist of ~ 2000 patients who are 18-75 years of age, actively enrolled in a primary care team, able to speak English or Spanish, and have at least one glycosylated hemoglobin (HbA1c) result in the prediabetic range (5.7-6.4%) since 2012. Those with a current DM diagnosis or DM medication prescription (other than metformin) are ineligible. The intervention consists of four core activities - setting health goals, health education, activation for doctor's appointments, and referrals to DM prevention programs - adjustable according to the patient's needs and readiness. The primary outcome is DM incidence. Secondary outcomes include weight loss, HbA1C, and self-reported health behaviors. Clinical variables and health behaviors will be obtained through electronic medical records and surveys, respectively. Implementation outcomes, namely implementation fidelity and physicians' perspectives about CHW integration into the clinic, will be assessed using interviews and CHW activity logs and analyzed for the influence of moderating organizational factors. DISCUSSION/CONCLUSIONS:This is the first rigorous, pragmatic trial to test the effectiveness of integrating CHWs into primary care for DM prevention reaching a population-based sample. Our study's limitations include language-based eligibility and the use of HbA1c as a measure of DM risk. It will measure both clinical and implementation outcomes and potentially broaden the evidence base for CHWs and patient-centered medical home implementation. Further, the intervention's unique features, notably patient-level personalization and referral to existing programs, may offer a scalable model to benefit patients at-risk of DM. TRIAL REGISTRATION/BACKGROUND:Clinicaltrials.gov NCT03006666 (Received 12/27/2016).

Background/UNASSIGNED:Active surveillance (AS) is the most rapidly expanding management option for favorable-risk prostate cancer (PCa). Early studies suggested substantial decrements in utility (quality of life weights) from disease-related anxiety. Our objective was to determine utilities for contemporary AS patients using different instruments. Methods/UNASSIGNED:We performed a systematic review of PubMed, PMC and OVID for utility measurements in modern AS patients. We then examined utilities among 37 men on AS participating in focus groups between 2015-2016 using the generic EurQol five dimensions questionnaire (EQ-5D-3L) and Patient Oriented Prostate Utility Scale (PORPUS), a PCa-specific instrument. Results/UNASSIGNED:The systematic review found previous studies with utilities for PCa treatment and historical watchful waiting populations, but none specifically in contemporary AS. In our AS population, the mean EQ-5D-3L score was 0.90±0.16 (median, 1.00; range, 0.21-1.00) and PORPUS was 0.98±0.03 (median, 0.99; range, 0.84-1.00). The Spearman correlation between the EQ-5D-3L and PORPUS was 0.87 (P<0.0001), and 38% of patients had a difference >0.1 between instruments. Conclusions/UNASSIGNED:Most contemporary AS patients had high utility scores suggesting that they perceive themselves in good health without a major decrement in quality of life from the disease. However, some patients had substantial differences in utility measured with generic versus disease-specific instruments. Further study is warranted into the optimal instrument for utility assessment in contemporary AS patients.

BACKGROUND: The Veterans Health Administration (VA) is investing considerable resources into providing remote management care to patients for disease prevention and management. Remote management includes online patient portals, e-mails between patients and providers, follow-up phone calls, and home health devices to monitor health status. However, little is known about patients' attitudes and preferences for this type of care. This qualitative study was conducted to better understand patient preferences for receiving remote care. METHODS: Ten focus groups were held comprising 77 patients with hypertension or tobacco use history at two VA medical centers. Discussion questions focused on experience with current VA remote management efforts and preferences for receiving additional care between outpatient visits. RESULTS: Most participants were receptive to remote management for referrals, appointment reminders, resource information, and motivational and emotional support between visits, but described challenges with some technological tools. Participants reported that remote management should be personalized and tailored to individual needs. They expressed preferences for frequency, scope, continuity of provider, and mode of communication between visits. Most participants were open to nonclinicians contacting them as long as they had direct connection to their medical team. Some participants expressed a preference for a licensed medical professional. All groups raised concerns around confidentiality and privacy of healthcare information. Female Veterans expressed a desire for gender-sensitive care and an interest in complementary and alternative medicine. CONCLUSIONS: The findings and specific recommendations from this study can improve existing remote management programs and inform the design of future efforts.

OBJECTIVE:To understand the informational needs during active surveillance (AS) for prostate cancer from the perspectives of patients and providers. METHODS:We conducted seven focus groups with 37 AS patients in two urban clinical settings, and 24 semi-structured interviews with a national sample of providers. Transcripts were analyzed using applied thematic analysis, and themes were organized using descriptive matrix analyses. RESULTS:We identified six themes related to informational needs during AS: 1) more information on prostate cancer (biopsy features, prognosis), 2) more information on active surveillance (difference from watchful waiting, testing protocol), 3) more information on alternative management options (complementary medicine, lifestyle modification), 4) greater variety of resources (multiple formats, targeting different audiences), 5) more social support and interaction, and 6) verified integrity of information (trusted, multidisciplinary and secure). CONCLUSIONS:Patients and providers described numerous drawbacks to existing prostate cancer resources and a variety of unmet needs including information on prognosis, AS testing protocols, and lifestyle modification. They also expressed a need for different types of resources, including interaction and unbiased information. PRACTICAL IMPLICATIONS/CONCLUSIONS:These results are useful to inform the design of future resources for men undergoing AS.

United States Veterans are at excess risk for type 2 diabetes, but population differentials in risk have not been characterized. We determined risk of type 2 diabetes in relation to prediabetes and dyslipidemic profiles in Veterans at the VA New York Harbor (VA NYHHS) during 2004-2014. Prediabetes was based on American Diabetes Association hemoglobin A1c (HbA1c) testing cut-points, one of several possible criteria used to define prediabetes. We evaluated transition to type 2 diabetes in 4,297 normoglycemic Veterans and 7,060 Veterans with prediabetes. Cox proportional hazards regression was used to relate HbA1c levels, lipid profiles, demographic, anthropometric and comorbid cardiovascular factors to incident diabetes (Hazard Ratio [HR] and 95% confidence intervals). Compared to normoglycemic Veterans (HbA1c: 5.0-5.6%; 31-38 mmol/mol), risks for diabetes were >2-fold in the moderate prediabetes risk group (HbA1c: 5.7-5.9%; 39-41 mmol/mol) (HR 2.37 [1.98-2.85]) and >5-fold in the high risk prediabetes group (HbA1c: 6.0-6.4%; 42-46 mmol/mol) (HR 5.59 [4.75-6.58]). Risks for diabetes were increased with elevated VLDL (≥40mg/dl; HR 1.31 [1.09-1.58]) and TG/HDL (≥1.5mg/dl; HR 1.34 [1.12-1.59]), and decreased with elevated HDL (≥35mg/dl; HR 0.80 [0.67-0.96]). Transition to diabetes in Veterans was related in age-stratified risk score analyses to HbA1c, VLDL, HDL and TG/HDL, BMI, hypertension and race, with 5-year risk differentials of 62% for the lowest (5-year risk, 13.5%) vs. the highest quartile (5-year risk, 21.9%) of the risk score. This investigation identified substantial differentials in risk of diabetes in Veterans, based on a readily-derived risk score suitable for risk stratification for type 2 diabetes prevention.

Background: 84 million Americans have pre-diabetes, but few are aware of their risk of diabetes, and building primary care (PC) systems to identify and engage this population in effective lifestyle modification is a challenge. Community health workers (CHWs) can assist patients with such changes to reduce this risk. However, it remains uncertain how best to integrate CHWs into PC practice. As part of the Community Health Outreach to Reduce Diabetes (CHORD) study, a randomized trial testing the efficacy of integrating CHWs into PC teams to prevent diabetes, the present study assessed PC clinic staff's baseline readiness to integrate CHWs into their practice. Methods: In this mixed methods study, we surveyed providers in the PC clinics at Bellevue Hospital and VA NY Harbor. Surveys used a 1-5 Likert scale for 20 questions in 4 domains: self-efficacy in preventing diabetes, beliefs about CHWs' role, expectations in working with CHWs, and use of diabetes prevention resources. We calculated the proportion of respondents agreeing with items (4 or 5), averaged for each domain. We also conducted semi-structured interviews with 9 PC staff at each site using guides with core questions about diabetes prevention practices, knowledge and attitudes regarding CHWs, and expectations and concerns about working with CHWs. Interviews were recorded, transcribed, and independently coded using the constant comparison method to develop core themes. Results: Of the 54 of 56 providers responding (96%), 33 at Bellevue and 21 at VA, 63% were female, with an average of 14 years in the practice. 62% agreed that they felt effective in preventing diabetes, 87% agreed that CHWs would be helpful in preventing diabetes, and 83% reported interest in working with CHWs. While 91% were aware of diabetes prevention resources in clinic and 54% agreed that they routinely refer to these resources, only 11% were aware of such resources in the community and only 2% routinely refer. Interviewed staff expressed low self-efficacy in diabetes prevention, limited by time, knowledge of patients' communities, and patient social barriers. They expected that patient contact with CHWs will offer benefits, but were concerned about fitting CHWs into clinic workflow and added communication burden, which they suggested may be minimized by using existing lines of communication among clinic staff. Conclusions: PC staff believed that CHWs can help improve preventive care for pre-diabetic patients. Most lack knowledge about community-based resources, and were ready to work with CHWs on diabetes prevention, who may expand access and engagement in such behavior change resources, such as the diabetes prevention program, sources of healthy food, and opportunities for exercise. By using PC staff's insights for implementing CHW interventions, a more seamless integration into clinical practice may be achieved