Observational studyHealth services research2018
Stratifying Patients with Diabetes into Clinically Relevant Groups by Combination of Chronic Conditions to Identify Gaps in Quality of Care.
Observational study in Health services research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed.
- Association rule analysis of physical activity and multimorbidity in middle-aged Korean adults with diabetes: an evidence to promote active lifestyles.BMC public health · 2026Article
- Demographic Mix of Care Homes and Personalised Use of SGLT-2 Inhibitors and GLP-1RAs in Residents with Type 2 Diabetes Mellitus.Journal of personalized medicine · 2026Review
- Association between Geriatric Nutrition Risk Index and depression in older hemodialysis patients with and without type 2 diabetes mellitus: a multicenter cross-sectional study.Frontiers in endocrinology · 2025Article
- Multimorbidity and Functional Disability among Older Adults: The Role of Inflammation and Glycemic Status - An Observational Longitudinal Study.Gerontology · 2023Observational
- Development and validation of novel multimorbidity indices for older adults.Journal of the American Geriatrics Society · 2023Article
- Multimorbidity, Frailty and Diabetes in Older People-Identifying Interrelationships and Outcomes.Journal of personalized medicine · 2022Review
- Real-world risk factors of confirmed or probable COVID-19 in Americans with diabetes: A prospective, community-based study (iNPHORM).Endocrinology, diabetes & metabolism · 2022Article
- Risk from delayed or missed care and non-COVID-19 outcomes for older patients with chronic conditions during the pandemic.Journal of the American Geriatrics Society · 2022Article
- Health information technology to improve care for people with multiple chronic conditions.Health services research · 2021Review
- Multimorbidity and achievement of treatment goals among patients with type 2 diabetes: a primary care, real-world study.BMC health services research · 2021Article
- Reducing Fall-related Revisits for Elderly Diabetes Patients in Emergency Departments: A Transition Flow Model.IEEE robotics and automation letters · 2021Article
- Are Disability Rates among People with Diabetes Increasing in Germany? A Decomposition Analysis of Temporal Change between 2004 and 2015.Journal of aging and health · 2021Article
- Diabetes-Multimorbidity Combinations and Disability Among Middle-aged and Older Adults.Journal of general internal medicine · 2019Article
- Optimal information networks: Application for data-driven integrated health in populations.Science advances · 2018Article
- Predicting onset of complications from diabetes: a graph based approach.Applied network science · 2018Article
- Longitudinal trends and predictors of statin use among patients with diabetes.Journal of diabetes and its complications · 2018Article
- Diabetes multimorbidity combinations and disability in the Mexican Health and Aging Study, 2012-2015.Archives of gerontology and geriatricsArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
objectiveTo find clinically relevant combinations of chronic conditions among patients with diabetes and to examine their relationships with six diabetes quality metrics. DATA SOURCES/STUDY
settingTwenty-nine thousand five hundred and sixty-two adult patients with diabetes seen at eight Midwestern U.S. health systems during 2010-2011. STUDY
designWe retrospectively evaluated the relationship between six diabetes quality metrics and patients' combinations of chronic conditions. We analyzed 12 conditions that were concordant with diabetes care to define five mutually exclusive combinations of conditions ("classes") based on condition co-occurrence. We used logistic regression to quantify the relationship between condition classes and quality metrics, adjusted for patient demographics and utilization. DATA COLLECTION: We extracted electronic health record data using a standardized algorithm. PRINCIPAL
findingsWe found the following condition classes: severe cardiac, cardiac, noncardiac vascular, risk factors, and no concordant comorbidities. Adjusted odds ratios and 95 percent confidence intervals for glycemic control were, respectively, 1.95 (1.7-2.2), 1.6 (1.4-1.9), 1.3 (1.2-1.5), and 1.3 (1.2-1.4) compared to the class with no comorbidities. Results showed similar patterns for other metrics.
conclusionsPatients had distinct quality metric achievement by condition class, and those in less severe classes were less likely to achieve diabetes metrics.
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