ArticleJournal of clinical & translational endocrinology2015
Methods and initial findings from the Durham Diabetes Coalition: Integrating geospatial health technology and community interventions to reduce death and disability.
Article in Journal of clinical & translational endocrinology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
18 citing papers in PubMed, 26 citations in OpenAlex.
- Automated Type 2 Diabetes Case and Control Identification from the MIMIC-IV Database.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023Article
- Association between Gentrification and Health and Healthcare Utilization.Journal of urban health : bulletin of the New York Academy of Medicine · 2022Article
- Democratizing health system data to impact social and environmental health contexts: a novel collaborative community data-sharing model.Journal of public health (Oxford, England) · 2020Article
- Promoting equity at the population level: Putting the foundational principles into practice through disability advocacy.Rehabilitation psychology · 2020Review
- The Rate Stabilizing Tool: Generating Stable Local-Level Measures of Chronic Disease.Preventing chronic disease · 2019Article
- Geographic surveillance of community associated MRSA infections in children using electronic health record data.BMC infectious diseases · 2019Article
- Iranian healthcare professionals' perspectives about factors influencing the use of telemedicine in diabetes management.World journal of diabetes · 2018Article
- Substance use disorders and medical comorbidities among high-need, high-risk patients with diabetes.Drug and alcohol dependence · 2018Article
- Development and validation of an electronic medical record (EMR)-based computed phenotype of HIV-1 infection.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- Illustrating Informed Presence Bias in Electronic Health Records Data: How Patient Interactions with a Health System Can Impact Inference.EGEMS (Washington, DC) · 2017Article
- Automated Diabetes Case Identification Using Electronic Health Record Data at a Tertiary Care Facility.Mayo Clinic proceedings. Innovations, quality & outcomes · 2017Article
- Assessing electronic health record phenotypes against gold-standard diagnostic criteria for diabetes mellitus.Journal of the American Medical Informatics Association : JAMIA · 2017Article
- Big Data Science: Opportunities and Challenges to Address Minority Health and Health Disparities in the 21st Century.Ethnicity & disease · 2017Review
- Controlling for Informed Presence Bias Due to the Number of Health Encounters in an Electronic Health Record.American journal of epidemiology · 2016Article
- The agreement of patient-reported versus observed medication adherence in type 2 diabetes mellitus (T2DM).BMJ open diabetes research & care · 2016Article
- 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.Contemporary clinical trials · 2016Article
- Substance use and mental diagnoses among adults with and without type 2 diabetes: Results from electronic health records data.Drug and alcohol dependence · 2015Article
- Qualitative Exploration of Geospatially Identified Bright Spots and Priority Areas to Improve Diabetes Management.Journal of primary care & community healthArticle
Corrections and comments
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Authors and funding
15 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe 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
methodsA 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.
resultsThe 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.
conclusionsTo 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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.