Faculty Bibliography

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

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.

OBJECTIVE: To explore and identify factors that influence physicians' decisions while monitoring patients with prostate cancer on active surveillance (AS). SUBJECTS AND METHODS: A purposive sampling strategy was used to identify physicians treating prostate cancer from diverse clinical backgrounds and geographic areas across the USA. We conducted 24 in-depth interviews from July to December 2015, until thematic saturation was reached. The Applied Thematic Analysis framework was used to guide data collection and analysis. Interview transcripts were reviewed and coded independently by two researchers. Matrix analysis and NVivo software were used for organization and further analysis. RESULTS: Eight key themes emerged to explain variation in AS monitoring: (i) physician comfort with AS; (ii) protocol selection; (iii) beliefs about the utility and quality of testing; (iv) years of experience and exposure to AS during training; (v) concerns about inflicting 'harm'; (vi) patient characteristics; (vii) patient preferences; and (viii) financial incentives. CONCLUSION: These qualitative data reveal which factors influence physicians who manage patients on AS. There is tension between providing standardized care while also considering individual patients' needs and health status. Additional education on AS is needed during urology training and continuing medical education. Future research is needed to empirically understand whether any specific protocol is superior to tailored, individualized care.

BACKGROUND: As healthcare moves towards technology-driven population health management, clinicians must adopt complex digital platforms to access health information and document care. OBJECTIVES: This study explored information literacy, a set of skills required to effectively navigate population health information systems, among primary care providers in one Veterans' Affairs (VA) medical center. METHODS: Information literacy was assessed during an 8-month randomized trial that tested a population health (panel) management intervention. Providers were asked about their use and comfort with two VA digital tools for panel management at baseline, 16 weeks, and post-intervention. An 8-item scale (range 0-40) was used to measure information literacy (Cronbach's alpha=0.84). Scores between study arms and provider types were compared using paired t-tests and ANOVAs. Associations between self-reported digital tool use and information literacy were measured via Pearson's correlations. RESULTS: Providers showed moderate levels of information literacy (M= 27.4, SD 6.5). There were no significant differences in mean information literacy between physicians (M=26.4, SD 6.7) and nurses (M=30.5, SD 5.2, p=0.57 for difference), or between intervention (M=28.4, SD 6.5) and control groups (M=25.1, SD 6.2, p=0.12 for difference). Information literacy was correlated with higher rates of self-reported information system usage (r=0.547, p=0.001). Clinicians identified data access, accuracy, and interpretability as potential information literacy barriers. CONCLUSIONS: While exploratory in nature, cautioning generalizability, the study suggests that measuring and improving clinicians' information literacy may play a significant role in the implementation and use of digital information tools, as these tools are rapidly being deployed to enhance communication among care teams, improve health care outcomes, and reduce overall costs.

PURPOSE: The authors performed a review of 30 Accelerating Change in Medical Education full grant submissions and an analysis of the health systems science (HSS)-related curricula at the 11 grant recipient schools to develop a potential comprehensive HSS curricular framework with domains and subcategories. METHOD: In phase 1, to identify domains, grant submissions were analyzed and coded using constant comparative analysis. In phase 2, a detailed review of all existing and planned syllabi and curriculum documents at the grantee schools was performed, and content in the core curricular domains was coded into subcategories. The lead investigators reviewed and discussed drafts of the categorization scheme, collapsed and combined domains and subcategories, and resolved disagreements via group discussion. RESULTS: Analysis yielded three types of domains: core, cross-cutting, and linking. Core domains included health care structures and processes; health care policy, economics, and management; clinical informatics and health information technology; population and public health; value-based care; and health system improvement. Cross-cutting domains included leadership and change agency; teamwork and interprofessional education; evidence-based medicine and practice; professionalism and ethics; and scholarship. One linking domain was identified: systems thinking. CONCLUSIONS: This broad framework aims to build on the traditional definition of systems-based practice and highlight the need for medical and other health professions schools to better align education programs with the anticipated needs of the systems in which students will practice. HSS will require a critical investigation into existing curricula to determine the most efficient methods for integration with the basic and clinical sciences.

The Minimizing Error, Maximizing Outcome (MEMO) study of clinics in New York City, Chicago, and Wisconsin linked primary care work experiences to physician stress. We analyzed MEMO data to determine how chaos in the clinic was associated with work conditions and quality of care measures. Surveys and medical record audits determined practice characteristics and medical errors, respectively. Physicians rated clinic atmosphere on a scale of 1 (calm) to 5 (chaotic). Chaotic clinics were defined as practices rated either 4 or 5 by greater than 50% of clinic physicians. Forty of 112 MEMO clinics (36%) were chaotic. Compared with nonchaotic practices, these clinics served more minority and Medicaid patients and had a greater likelihood of clinic bottlenecks such as phone access (both p < .01). Physicians in chaotic clinics reported lower work control and job satisfaction, less emphasis on teamwork and professionalism, more stress and burnout, and a higher likelihood of leaving the practice within 2 years (all p < .05). Chaotic clinics had higher rates of medical errors and more missed opportunities to provide preventative services (both p < .05). More research should examine the effectiveness of organizational interventions to decrease chaos in the clinic and to mitigate its effects on patient safety.