Interactive visualization tool to understand and monitor health disparities in diabetes care and outcomes.

Objective: Type 2 diabetes (T2DM) poses a significant public health challenge, with pronounced disparities in control and outcomes. Social determinants of health (SDoH) significantly contribute to these disparities, affecting healthcare access, neighborhood environments, and social context. We discuss the design, development, and use of an innovative web-based application integrating real-world data (electronic health record and geospatial files), to enhance comprehension of the impact of SDoH on T2 DM health disparities. Methods: We identified a patient cohort with diabetes from the institutional Diabetes Registry (N = 67,699) within the Duke University Health System. Patient-level information (demographics, comorbidities, service utilization, laboratory results, and medications) was extracted to Tableau. Neighborhood-level socioeconomic status was assessed via the Area Deprivation Index (ADI), and geospatial files incorporated additional data related to points of interest (i.e., parks/green space). Interactive Tableau dashboards were developed to understand risk and contextual factors affecting diabetes management at the individual, group, neighborhood, and population levels. Results: The Tableau-powered digital health tool offers dynamic visualizations, identifying T2DM-related disparities. The dashboard allows for the exploration of contextual factors affecting diabetes management (e.g., food insecurity, built environment) and possesses capabilities to generate targeted patient lists for personalized diabetes care planning. Conclusion: As part of a broader health equity initiative, this application meets the needs of a diverse range of users. The interactive dashboard, incorporating clinical, sociodemographic, and environmental factors, enhances understanding at various levels and facilitates targeted interventions to address disparities in diabetes care and outcomes. Ultimately, this transformative approach aims to manage SDoH and improve patient care.

Addressing cost barriers to healthy eating with Eat Well, a prescription produce subsidy, for patients with diabetes and at risk for food insecurity: Study protocol for a type 1 hybrid effectiveness-implementation pragmatic randomized controlled trial.

BACKGROUND: Patients with diabetes at risk of food insecurity face cost barriers to healthy eating and, as a result, poor health outcomes. Population health management strategies are needed to improve food security in real-world health system settings. We seek to test the effect of a prescription produce program, 'Eat Well' on cardiometabolic health and healthcare utilization. We will also assess the implementation of an automated, affirmative outreach strategy. METHODS: We will recruit approximately 2400 patients from an integrated academic health system in the southeastern United States as part of a two-arm parallel hybrid type 1 pragmatic randomized controlled trial. Patients with diabetes, at risk for food insecurity, and a recent hemoglobin A1c reading will be eligible to participate. The intervention arm receives, 'Eat Well', which provides a debit card with $80 (added monthly) for 12 months valid for fresh, frozen, or canned fruits and vegetables across grocery retailers. The control arm does not. Both arms receive educational resources with diabetes nutrition and self-management materials, and information on existing care management resources. Using an intent-to-treat analysis, primary outcomes include hemoglobin A1C levels and emergency department visits in the 12 months following enrollment. Reach and fidelity data will be collected to assess implementation. DISCUSSION: Addressing food insecurity, particularly among those at heightened cardiometabolic risk, is critical to equitable and effective population health management. Pragmatic trials provide important insights into the effectiveness and implementation of 'Eat Well' and approaches like it in real-world settings. REGISTRATION: ClinicalTrials.gov Identifier: NCT05896644; Clinical Trial Registration Date: 2023-06-09.

Measures of Referral vs Receipt of Social Services Among Patients With Health-Related Social Needs.

This cohort study compares measures of referral vs receipt in evaluating social resource platform outcomes among patients with health-related social needs.

Improving glycemic control in diabetes through virtual interdisciplinary rounds.

OBJECTIVE: A team-based disease management approach that considers comorbid conditions, social drivers of health, and clinical guidelines improves diabetes care but can be costly and complex. Developing innovative models of care is crucial to improving diabetes outcomes. The objective of this analysis was to evaluate the efficacy of virtual interdisciplinary diabetes rounds in improving glycemic control. STUDY DESIGN: Retrospective cohort study using observational data from July 2018 to December 2021. METHODS: This study employed difference-in-differences analysis to compare change in hemoglobin A1c (HbA1c) in a group of patients whose providers received advice as part of virtual interdisciplinary rounds and a group of patients whose providers did not receive rounds advice. Patients with diabetes were identified for rounding (1) based on attribution to an accountable care organization along with an upcoming primary care appointment and an HbA1c between 8% and 9% or (2) via provider referral. RESULTS: The rounded group consisted of 481 patients and the comparison group included 1806 patients. There was a 0.3-point reduction in HbA1c (95% CI, 0.1-0.4) associated with rounds overall. In a subanalysis comparing provider adoption of recommendations among those rounded, provider adoption was associated with an HbA1c reduction of 0.5 points (95% CI, 0.1-0.9) at 6 months post rounds, although there was no significant difference in the full year post rounds. CONCLUSIONS: Interdisciplinary rounds can be an effective approach to proactively provide diabetes-focused recommendations. This modality allows for efficient, low-cost, and timely access to an endocrinologist and team to support primary care providers in diabetes management.

Leveraging Student Volunteers to Connect Patients with Social Risk to Resources On a Coordinated Care Platform: A Case Study with Two Endocrinology Clinics.

Introduction: Although unmet social needs can impact health outcomes, health systems often lack the capacity to fully address these needs. Our study describes a model that organized student volunteers as a community-based organisation (CBO) to serve as a social referral hub on a coordinated social care platform, NCCARE360. Description: Patients at two endocrinology clinics were systematically screened for social needs. Patients who screened positive and agreed to receive help were referred via NCCARE360 to student 'Help Desk' volunteers, who organised as a CBO. Trained student volunteers called patients to place referrals to resources and document them on the platform. The platform includes documentation at several levels, acting as a shared information source between healthcare providers, volunteer student patient navigators, and community resources. Navigators followed up with patients to problem-solve barriers and track referral outcomes on the platform, visible to all parties working with the patient. Discussion: Of the 44 patients who screened positive for social needs and were given referrals by Help Desk, 41 (93%) were reached for follow-up. Thirty-six patients (82%) connected to at least one resource. These results speak to the feasibility and utility of organising undergraduate student volunteers into a social referral hub to connect patients to resources on a coordinated care platform. Conclusion: Organising students as a CBO on a centralized social care platform can help bridge a critical gap between healthcare and social services, addressing health system capacity and ultimately improving patients' connections with resources.

Feasibility of Electronic Health Record Integration of a SMART Application to Facilitate Patient-Provider Communication for Medication Management.

Increased treatment complexity in patients with diabetes contributes to medication nonadherence. Patient portals that are accessible through electronic health records may offer improved patient-provider communication and better medication management in patients with diabetes and uncontrolled hypertension. We conducted a prospective, mixed-methods evaluation of the Duke PillBox application, a SMART-on-FHIR medication management application integrated into the electronic health record patient portal. Adults with active portal status, diabetes, and uncontrolled hypertension participated in a usability/feasibility survey and communicated with a pharmacist via the portal-based application who conducted medication reconciliation and discussed medication indications, side effects, and barriers to use with patients. Of the eligible patients (n = 285), 29 (10%) were interested, and 12 (8%) participated. Challenges to usability were due to the electronic health record-portal communication interface (91%), browser access and compatibility (55%), and persistent lists of unused medications in the electronic health record (27%). The findings of this study suggest that electronic health record-integrated medication applications are desirable as indicated in patient interactions at the outset and conclusion of the study. Persistent challenges included electronic health record integration, interoperability, user interface, and browser connectivity for both patients and providers.

General Behavioral Engagement and Changes in Clinical and Cognitive Outcomes of Patients with Type 2 Diabetes Using the Time2Focus Mobile App for Diabetes Education: Pilot Evaluation.

BACKGROUND: Type 2 diabetes affects 30 million Americans, representing a significant cause of morbidity and mortality. Self-management support is an important component of chronic illness care and is a key pillar of the chronic care model. Face-to-face teaching and patient education materials suffer from being static or incompatible with mobile lifestyles. Digital apps provide a self-management support alternative that is convenient and scalable. OBJECTIVE: This pilot study tested the real-world deployment of a self-guided mobile app for diabetes education (Time2Focus app; MicroMass Communications Inc, Cary, NC), which utilizes evidence-based content and gamification to deliver an interactive learning experience. METHODS: Primary care providers were approached for permission to invite their patients to participate. Eligible patients were 18 to 89 years of age, had a diagnosis of type 2 diabetes, hemoglobin A1c (HbA1c) ≥8% and <12% in the past 3 months, an active online patient portal account (tied to the electronic health record), and access to an iOS or Android smartphone. Interested patients were emailed a baseline survey, and once this was completed, were sent instructions for downloading the Time2Focus app. After completing all 12 levels, participants were sent a follow-up survey. The primary outcome was the change in HbA1c. Secondary outcomes included medication adherence, self-care activities, self-reporting of physical activities, diabetes self-efficacy, illness perceptions, diabetes distress scale, and users' engagement with and rating of the app. RESULTS: Of 1355 potentially eligible patients screened, 201 were consented. Of these 201 patients, 101 (50.2%) did not download the app. Of the 100 participants (49.8%) who downloaded the app, 16 (16.0%) completed 0 levels, 26 (26.0%) completed 1 to 4 levels, 10 (10.0%) completed 5 to 11 levels, and 48 (48.0%) completed all 12 levels of the app and the follow-up survey. Those completing one or more levels had a mean pre/post-HbA1c change of -0.41% (compared to -0.32% among those who completed zero levels); however, the unadjusted two-tailed t test indicated no significant difference between the two groups (P=.73). Diabetes self-efficacy showed a large and significant increase during app usage for completers (mean change 1.28, P<.001, d=.83). Severity of illness perceptions showed a small but significant decrease during app usage for completers (mean change -0.51, P=.004, d=.43). Diabetes distress showed a small but significant decrease during app usage for completers (mean change -0.45, P=.006, d=.41). The net promoter score was 62.5, indicating that those who completed all levels of the app rated it highly and would recommend it to others. CONCLUSIONS: Participants who engaged in all 12 levels of the Time2Focus mobile app showed an improvement in diabetes self-efficacy and a decrease in severity of illness perceptions. The decrease in HbA1c observed in app users relative to nonusers during this limited pilot study was not statistically significant. However, uptake and application of lessons learned from self-management support may be delayed. Further research is needed to address how to increase engagement through self-management support and to investigate if follow up over a longer period demonstrates a significant change in outcomes such as HbA1c.

Painful diabetic peripheral neuropathy: Health care costs and complications from 2010 to 2015.

OBJECTIVE: To quantify health care resource utilization and risk of complications in painful diabetic peripheral neuropathy (pDPN). METHODS: Adult patients diagnosed with diabetes mellitus or diabetic peripheral neuropathy (DPN) were identified in MarketScan from January 2010 to December 2015. Subgroups (pDPN and nonpainful DPN) were based on the use of pain medications 6 months before a new indexed diagnosis and 1 year thereafter. Health care costs were collected for up to 5 years, and complications charted for those with at least 1 and 2 years of follow-up. Complication comparisons were made using χ2 or Fisher exact tests, and a multivariable regression cost model was fit with log link function using generalized estimating equations. RESULTS: Among 360,559 patients with diabetes (62 ± 14 years; 54.3% female), 84,069 (23.3%) developed pDPN, 17,267 (4.8%) experienced nonpainful DPN, and the majority (259,223, 71.9%) were controls with diabetes without neuropathy. At baseline, costs associated with pDPN patients were 20% higher than diabetic controls (95% confidence interval [CI] [1.19, 1.21], p < 0.001), which increased to 31% in the 5th year (95% CI [1.27, 1.34], p < 0.001). Patients with pDPN had 200%, 356%, and 224% of the odds of using opioids, anticonvulsants, and antidepressants, respectively, compared with diabetic controls. The amputation risk in the pDPN subgroup was 16.24 times that of diabetic controls (95% CI [2.15, 122.72], p = 0.0003), and 87% more patients with pDPN experienced lower extremity infections (95% CI [1.43, 2.46], p < 0.0001) within a year. Within 2 years, 2.2% of patients with pDPN had falls and fall-related injuries compared with 1.1% of diabetic controls (p < 0.0001). CONCLUSIONS: Our study characterizes a substantial pDPN cohort in the United States, demonstrating considerable morbidity and economic costs.

Research use of electronic health records: patients' perspectives on contact by researchers.

Objective: The use of electronic health records (EHRs) for research has the potential to improve the diagnosis and treatment of disease, yet contact with patients based on results of EHR phenotyping has received little attention. Researchers will almost certainly discover discrepancies in EHRs that call for resolution and, in some cases, raise the ethical dilemma of whether to contact patients about a potentially undiagnosed or untreated health concern. The objective of this study was to explore patients' attitudes and opinions about potential contact by researchers who have had access to their EHRs. Materials and methods: We conducted 15 focus groups in four diverse counties in the southeastern United States. We designed vignettes to describe different situations in which researchers conducting a hypothetical study might have reason to consider contact with patients. Results: Many patients believed it was important for researchers to take action if they discovered information suggesting a current serious health concern. Relaying the information through patients' physicians was considered the most appropriate course of action. Across vignettes, there were significant differences between urban and rural sites. Discussion and conclusions: Researchers may increasingly encounter situations involving contact with patients following EHR phenotyping. They should carefully consider the possibility of such contact when planning their studies, including the time and expertise needed to adjudicate potentially serious discrepancies. Our focus group results are one source of input for the development of ethical approaches to the research use of EHRs.

Medicare utilization, screening, and costs among participants in the Southeastern Diabetes Initiative: A population-based evaluation.

AIMS: Type 2 diabetes mellitus imposes significant burdens on patients and health care systems. Population-level interventions are being implemented to reach large numbers of patients at risk of or diagnosed with diabetes. We describe a population-based evaluation of the Southeastern Diabetes Initiative (SEDI) from the perspective of a payer, the Centers for Medicare & Medicaid Services (CMS). The purpose of this paper is to describe the population-based evaluation approach of the SEDI intervention from a Medicare utilization and cost perspective. METHODS: We measured associations between the SEDI intervention and receipt of diabetes screening (i.e., HbA1c test, eye exam, lipid profile), health care resource use, and costs among intervention enrollees, compared with a control cohort of Medicare beneficiaries in geographically adjacent counties. RESULTS: The intervention cohort had slightly lower 1-year screening in 2 of 3 domains (4% for HbA1c; 9% for lipid profiles) in the post-intervention period, compared with the control cohort. The SEDI intervention cohort did not have different Medicare utilization or total Medicare costs in the post-intervention period from surrounding control counties. CONCLUSIONS: Our analytic approach may be useful to others evaluating CMS demonstration projects in which population-level health is targeted for improvement in a well-defined clinical population.

Assessing electronic health record phenotypes against gold-standard diagnostic criteria for diabetes mellitus.

OBJECTIVE: We assessed the sensitivity and specificity of 8 electronic health record (EHR)-based phenotypes for diabetes mellitus against gold-standard American Diabetes Association (ADA) diagnostic criteria via chart review by clinical experts. MATERIALS AND METHODS: We identified EHR-based diabetes phenotype definitions that were developed for various purposes by a variety of users, including academic medical centers, Medicare, the New York City Health Department, and pharmacy benefit managers. We applied these definitions to a sample of 173 503 patients with records in the Duke Health System Enterprise Data Warehouse and at least 1 visit over a 5-year period (2007-2011). Of these patients, 22 679 (13%) met the criteria of 1 or more of the selected diabetes phenotype definitions. A statistically balanced sample of these patients was selected for chart review by clinical experts to determine the presence or absence of type 2 diabetes in the sample. RESULTS: The sensitivity (62-94%) and specificity (95-99%) of EHR-based type 2 diabetes phenotypes (compared with the gold standard ADA criteria via chart review) varied depending on the component criteria and timing of observations and measurements. DISCUSSION AND CONCLUSIONS: Researchers using EHR-based phenotype definitions should clearly specify the characteristics that comprise the definition, variations of ADA criteria, and how different phenotype definitions and components impact the patient populations retrieved and the intended application. Careful attention to phenotype definitions is critical if the promise of leveraging EHR data to improve individual and population health is to be fulfilled.

The agreement of patient-reported versus observed medication adherence in type 2 diabetes mellitus (T2DM).

OBJECTIVE: Medication adherence in type 2 diabetes mellitus (T2DM) improves glycemic control and is associated with reduced adverse clinical events, and accurately assessing adherence assessment is important. We aimed to determine agreement between two commonly used adherence measures-the self-reported Morisky Medication Adherence Scale (MMAS) and direct observation of medication use by nurse practitioners (NPs) during home visits-and determine the relationship between each measure and glycated hemoglobin (HbA1c). RESEARCH DESIGN AND METHODS: We evaluated agreement between adherence measures in the Southeastern Diabetes Initiative (SEDI) prospective clinical intervention home visit cohort, which included high-risk patients (n=430) in 4 SEDI-participating counties. The mean age was 58.7 (SD 11.6) years. The majority were white (n=210, 48.8%), female (n=236, 54.9%), living with a partner (n=316, 74.5%), and insured by Medicare/Medicaid (n=361, 84.0%). Medication adherence was dichotomized to 'adherent' or 'not adherent' using established cut-points. Inter-rater agreement was evaluated using Cohen's κ coefficient. Relationships among adherence measures and HbA1c were evaluated using the Wilcoxon rank-sum test and c-statistics. RESULTS: Fewer patients (n=261, 61%) were considered adherent by self-reported MMAS score versus the NP-observed score (n=338; 79%). Inter-rater agreement between the two adherence measures was fair (κ=0.24; 95% CI 0.15 to 0.33; p<0.0001). Higher adherence was significantly associated with lower HbA1c levels for both measures, yet discrimination was weak (c-statistic=0.6). CONCLUSIONS: Agreement between self-reported versus directly observed medication adherence was lower than expected. Though scores for both adherence measures were significantly associated with HbA1c, neither discriminated well for discrete levels of HbA1c.

Using electronic health record data for substance use Screening, Brief Intervention, and Referral to Treatment among adults with type 2 diabetes: Design of a National Drug Abuse Treatment Clinical Trials Network study.

BACKGROUND: The Affordable Care Act encourages healthcare systems to integrate behavioral and medical healthcare, as well as to employ electronic health records (EHRs) for health information exchange and quality improvement. Pragmatic research paradigms that employ EHRs in research are needed to produce clinical evidence in real-world medical settings for informing learning healthcare systems. Adults with comorbid diabetes and substance use disorders (SUDs) tend to use costly inpatient treatments; however, there is a lack of empirical data on implementing behavioral healthcare to reduce health risk in adults with high-risk diabetes. Given the complexity of high-risk patients' medical problems and the cost of conducting randomized trials, a feasibility project is warranted to guide practical study designs. METHODS: We describe the study design, which explores the feasibility of implementing substance use Screening, Brief Intervention, and Referral to Treatment (SBIRT) among adults with high-risk type 2 diabetes mellitus (T2DM) within a home-based primary care setting. Our study includes the development of an integrated EHR datamart to identify eligible patients and collect diabetes healthcare data, and the use of a geographic health information system to understand the social context in patients' communities. Analysis will examine recruitment, proportion of patients receiving brief intervention and/or referrals, substance use, SUD treatment use, diabetes outcomes, and retention. DISCUSSION: By capitalizing on an existing T2DM project that uses home-based primary care, our study results will provide timely clinical information to inform the designs and implementation of future SBIRT studies among adults with multiple medical conditions.

Methods and initial findings from the Durham Diabetes Coalition: Integrating geospatial health technology and community interventions to reduce death and disability.

OBJECTIVE: The Durham Diabetes Coalition (DDC) was established in response to escalating rates of disability and death related to type 2 diabetes mellitus, particularly among racial/ethnic minorities and persons of low socioeconomic status in Durham County, North Carolina. We describe a community-based demonstration project, informed by a geographic health information system (GHIS), that aims to improve health and healthcare delivery for Durham County residents with diabetes. MATERIALS AND METHODS: A prospective, population-based study is assessing a community intervention that leverages a GHIS to inform community-based diabetes care programs. The GHIS integrates clinical, social, and environmental data to identify, stratify by risk, and assist selection of interventions at the individual, neighborhood, and population levels. RESULTS: The DDC is using a multifaceted approach facilitated by GHIS to identify the specific risk profiles of patients and neighborhoods across Durham County. A total of 22,982 patients with diabetes in Durham County were identified using a computable phenotype. These patients tended to be older, female, African American, and not covered by private health insurance, compared with the 166,041 persons without diabetes. Predictive models inform decision-making to facilitate care and track outcomes. Interventions include: 1) neighborhood interventions to improve the context of care; 2) intensive team-based care for persons in the top decile of risk for death or hospitalization within the coming year; 3) low-intensity telephone coaching to improve adherence to evidence-based treatments; 4) county-wide communication strategies; and 5) systematic quality improvement in clinical care. CONCLUSIONS: To improve health outcomes and reduce costs associated with type 2 diabetes, the DDC is matching resources with the specific needs of individuals and communities based on their risk characteristics.

Barriers to care for patients with diabetes in Durham, North Carolina, why are we withholding life-sustaining medications from the patients who need them the most?

The diabetes epidemic and its complications disproportionately affect minorities and the poor. Medical treatments that can prevent or delay diabetes complications are widely available but poverty underlies much of why there are disparities in diabetes care and outcomes. Lack of access to care, food insecurity and inability to pay for medications prevents adherence to a medication and lifestyle regimen that can be life-sustaining. At the very least, US policies should be changed to provide life-sustaining medications that prevent costly complications to patients who cannot afford them. Adopting value-based insurance design would benefit patients with diabetes who cannot afford to pay for medications but would also reduce healthcare costs in the long run.

The implementation and evaluation of an evidence-based protocol to treat diabetic ketoacidosis: a quality improvement study.

This retrospective observational quality improvement study was conducted to determine whether an evidence-based protocol for the treatment of diabetic ketoacidosis improved patient outcomes in our academic medical center. This study evaluated fidelity of providers to the protocol, as well as time to resolution of diabetic ketoacidosis as measured by closure of the anion gap (AG). Other secondary outcomes included time to intravenous fluids, time to potassium replacement, and rates of hypoglycemia and hypokalemia.Two cohorts including historical (N = 41) and current (N = 37) were compared to evaluate the effectiveness of the protocol. There were no differences between group demographics at baseline. After implementation of the protocol, 43.2% of patients were treated using full protocol fidelity, 21.6% were treated with partial fidelity, and 35.1% were not treated using the protocol. Although none of the outcomes reached statistical significance, patients in the current group who were treated with full protocol fidelity had an average time to AG closure that was 3 hr less than those who were not treated according to the protocol, and an average time to potassium replacement that was 2 hr less. When comparing the historical cohort with the patients treated with full protocol fidelity, there was improvement in protocol-treated patients in time to AG closure (2 hr), time to dextrose replacement (1.7 hr), and time to potassium replacement (2 hr). The rates of hypokalemia were improved with protocol treatment; 37.5% of protocol-treated patients had hypokalemia as opposed to 63.4% of those not treated according to protocol.Overall, despite the low fidelity in our institution, the protocol promoted evidence-based practice and patients treated according to the protocol had decreased time to treatment outcomes including quicker AG closure, improved intravenous fluids resuscitation, and more accurate and timely electrolyte correction.

Missing signposts on the roadmap to quality: a call to improve medication adherence indicators in data collection for population research.

PURPOSE: Poor adherence to prescribed medicines is associated with increased rates of poor outcomes, including hospitalization, serious adverse events, and death, and is also associated with increased healthcare costs. However, current approaches to evaluation of medication adherence using real-world electronic health records (EHRs) or claims data may miss critical opportunities for data capture and fall short in modeling and representing the full complexity of the healthcare environment. We sought to explore a framework for understanding and improving data capture for medication adherence in a population-based intervention in four U.S. counties. APPROACH: We posited that application of a data model and a process matrix when designing data collection for medication adherence would improve identification of variables and data accessibility, and could support future research on medication-taking behaviors. We then constructed a use case in which data related to medication adherence would be leveraged to support improved healthcare quality, clinical outcomes, and efficiency of healthcare delivery in a population-based intervention for persons with diabetes. Because EHRs in use at participating sites were deemed incapable of supplying the needed data, we applied a taxonomic approach to identify and define variables of interest. We then applied a process matrix methodology, in which we identified key research goals and chose optimal data domains and their respective data elements, to instantiate the resulting data model. CONCLUSIONS: Combining a taxonomic approach with a process matrix methodology may afford significant benefits when designing data collection for clinical and population-based research in the arena of medication adherence. Such an approach can effectively depict complex real-world concepts and domains by "mapping" the relationships between disparate contributors to medication adherence and describing their relative contributions to the shared goals of improved healthcare quality, outcomes, and cost.

A comparison of phenotype definitions for diabetes mellitus.

OBJECTIVE: This study compares the yield and characteristics of diabetes cohorts identified using heterogeneous phenotype definitions. MATERIALS AND METHODS: Inclusion criteria from seven diabetes phenotype definitions were translated into query algorithms and applied to a population (n=173 503) of adult patients from Duke University Health System. The numbers of patients meeting criteria for each definition and component (diagnosis, diabetes-associated medications, and laboratory results) were compared. RESULTS: Three phenotype definitions based heavily on ICD-9-CM codes identified 9-11% of the patient population. A broad definition for the Durham Diabetes Coalition included additional criteria and identified 13%. The electronic medical records and genomics, NYC A1c Registry, and diabetes-associated medications definitions, which have restricted or no ICD-9-CM criteria, identified the smallest proportions of patients (7%). The demographic characteristics for all seven phenotype definitions were similar (56-57% women, mean age range 56-57 years).The NYC A1c Registry definition had higher average patient encounters (54) than the other definitions (range 44-48) and the reference population (20) over the 5-year observation period. The concordance between populations returned by different phenotype definitions ranged from 50 to 86%. Overall, more patients met ICD-9-CM and laboratory criteria than medication criteria, but the number of patients that met abnormal laboratory criteria exclusively was greater than the numbers meeting diagnostic or medication data exclusively. DISCUSSION: Differences across phenotype definitions can potentially affect their application in healthcare organizations and the subsequent interpretation of data. CONCLUSIONS: Further research focused on defining the clinical characteristics of standard diabetes cohorts is important to identify appropriate phenotype definitions for health, policy, and research.