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Objectives. To assess linkages of patient data from a health care system in the southeastern United States to microdata from the American Community Survey (ACS) with the goal of better understanding health disparities and social determinants of health in the population. Methods. Once a data use agreement was in place, a stratified random sample of approximately 200 000 was drawn of patients aged 25 to 74 years with at least 2 visits between January 1, 2016, and December 31, 2019. Information from the sampled electronic health records (EHRs) was transferred securely to the Census Bureau, put through the Census Person Identification Validation System to assign Protected Identification Keys (PIKs) as unique identifiers wherever possible. EHRs with PIKs assigned were then linked to 2001–2017 ACS records with a PIK. Results. PIKs were assigned to 94% of the sampled patients. Of patients with PIKs, 15.5% matched to persons sampled in the ACS. Conclusions. Linking data from EHRs to ACS records is feasible and, with adjustments for differential coverage, will advance understanding of social determinants and enhance the ability of integrated delivery systems to reflect and affect the health of the populations served. (Am J Public Health. 2022;112(6):923–930. https://doi.org/10.2105/AJPH.2022.306783) [ABSTRACT FROM AUTHOR]

We used electronic medical record (EMR) data in the National Patient-Centered Clinical Research Network (PCORnet) to characterize “real-world” prescription patterns of Type 2 diabetes (T2D) medications. We identified a retrospective cohort of 613,203 adult patients with T2D from 33 datamarts (median patient number: 12,711) from 2012 through 2017 using a validated computable phenotype. We characterized outpatient T2D prescriptions for each patient in the 90 days before and after cohort entry, as well as demographics, comorbidities, non-T2D prescriptions, and clinical and laboratory variables in the 730 days prior to cohort entry. Approximately half of the individuals in the cohort were females and 20% Black. Hypertension (60.3%) and hyperlipidemia (50.5%) were highly prevalent. Most patients were prescribed either a single T2D drug class (42.2%) or had no evidence of a T2D prescription in the EMR (42.4%). A smaller percentage was prescribed multiple T2D drug types (15.4%). Among patients prescribed a single T2D drug type, metformin was the most common (42.6%), followed by insulin (18.2%) and sulfonylureas (13.9%). Newer classes represented approximately 13% of single T2D drug type prescriptions (dipeptidyl peptidase-4 inhibitors [6.6%], glucagon-like peptide-1 receptor agonists [2.5%], thiazolidinediones [2.0%], and sodium-glucose cotransporter-2 inhibitors [1.6%]). Among patients prescribed multiple T2D drug types, the most common combination was metformin and sulfonylureas (63.5%). Metformin-based regimens were highly prevalent in PCORnet's T2D population, whereas newer agents were prescribed less frequently. PCORnet is a novel source for the potential conduct of observational studies among patients with T2D. [ABSTRACT FROM AUTHOR]

Background: Understanding the long-term cardiovascular safety of type 2 diabetes (T2D) medications is a high-priority research area. We used electronic medical record (EMR) data in the National Patient Centered Clinical Research Network (PCORnet) to characterize "real-world" use of T2D medications. Methods and Results: We identified a retrospective cohort of patients with T2D using a validated computable phenotype. We queried 4 unique PCORnet sites for data regarding T2D medication use in the 90 days before and after cohort entry. We described patient demographics, comorbidities, non-T2D medication use, and clinical variables in the 730 days prior to cohort entry. We identified 49,654 patients with T2D across the 4 sites (range: 2,276-20,322). Use of T2D medications, characterized by pharmacologic class, and selected characteristics are presented in Table. Among patients prescribed a single class of T2D medication, metformin was the most common (52.5%). Among patients prescribed multiple classes of T2D agents, the most common combination was metformin and sulfonylureas (49%). Conclusions: Across 4 PCORnet sites, metformin-based regimens were very prevalent, and approximately 10% of regimens included newer agents. PCORnet will be a valuable resource for future observational studies of T2D medications and long-term cardiovascular outcomes in "real-world" populations. Disclosure: K.N. Bachmann: Stock/Shareholder; Self; Medtronic. C. Roumie: None. A.D. Wiese: None. C.G. Grijalva: None. J.B. Buse: Consultant; Self; Neurimmune AG. Research Support; Self; AstraZeneca, National Center for Advancing Translational Sciences, National Institute of Diabetes and Digestive and Kidney Diseases, Novo Nordisk A/S, Sanofi, vTv Therapeutics. Stock/Shareholder; Self; Mellitus Health, PhaseBio Pharmaceuticals, Inc., Stability Health. Other Relationship; Self; ADOCIA, AstraZeneca, Dance Biopharm Holdings Inc., Eli Lilly and Company, MannKind Corporation, NovaTarg, Novo Nordisk A/S, Senseonics, vTv Therapeutics, Zafgen, Inc. R. Bradford: None. E.O. Zalimeni: None. P. Knoepp: None. H.L. Morris: None. W.T. Donahoo: None. N. Fanous: None. V. Fonseca: Board Member; Self; American Association of Clinical Endocrinologists. Consultant; Self; Abbott, Asahi Kasei Corporation, Novo Nordisk Inc., Sanofi US, Takeda Pharmaceutical Company Limited. Research Support; Self; Bayer US. Stock/Shareholder; Self; Amgen Inc., BRAVO4HEALTH, Mellitus Health. B. Katalenich: None. M.M. Cook: None. R.L. Rothman: Consultant; Self; Abbott, edlogics. R.J. Chakkalakal: None. Funding: National Institutes of Health (UL1TR002489, UL1TR002489); U.S. Department of Veterans Affairs (IK2CX001678); Patient-Centered Outcomes Research Institute (CDRN-1306-04869) [ABSTRACT FROM AUTHOR]