IntroductionElectronic health record (EHR) data enhance opportunities for conducting surveillance of diabetes. The objective of this study was to identify the number of people with diabetes from a diabetes DataLink developed as part of the SUPREME-DM (SUrveillance, PREvention, and ManagEment of Diabetes Mellitus) project, a consortium of 11 integrated health systems that use comprehensive EHR data for research.MethodsWe identified all members of 11 health care systems who had any enrollment from January 2005 through December 2009. For these members, we searched inpatient and outpatient diagnosis codes, laboratory test results, and pharmaceutical dispensings from January 2000 through December 2009 to create indicator variables that could potentially identify a person with diabetes. Using this information, we estimated the number of people with diabetes and among them, the number of incident cases, defined as indication of diabetes after at least 2 years of continuous health system enrollment.ResultsThe 11 health systems contributed 15,765,529 unique members, of whom 1,085,947 (6.9%) met 1 or more study criteria for diabetes. The nonstandardized proportion meeting study criteria for diabetes ranged from 4.2% to 12.4% across sites. Most members with diabetes (88%) met multiple criteria. Of the members with diabetes, 428,349 (39.4%) were incident cases.ConclusionThe SUPREME-DM DataLink is a unique resource that provides an opportunity to conduct comparative effectiveness research, epidemiologic surveillance including longitudinal analyses, and population-based care management studies of people with diabetes. It also provides a useful data source for pragmatic clinical trials of prevention or treatment interventions.

Objective Little is known about how patient-clinician communication leads to better outcomes. Among patients with diabetes, we describe patient-reported use of collaborative goal setting and evaluate whether perceived competency and physician trust mediate the association between collaborative goal setting and glycemic control. Methods Data from a patient survey administered in 2008 to a cohort of insured patients aged 18+ years with diabetes who initiated oral mono-therapy between 2000–2005 were joined with pharmaceutical claims data for the prior 12 months and laboratory data for the prior and subsequent 12 months (N=1,065). A structural equation model (SEM) was used to test mediation models controlling for baseline HbA1c. Results The hypothesized mediation model was supported. Patient-reported use of more collaborative goal setting was associated with greater perceived self-management competency and increased level of trust in the physician (p<0.05). In turn, both greater perceived competence and increased trust were associated with increased control (p< 0.05). Conclusions Findings indicate that engaging patients in collaborative goal setting during clinic encounters has potential to foster a trusting patient-clinician relationship as well as enhance patient perceived competence, thereby improving clinical control. Practice Implications Fostering collaborative goal setting may yield payoffs in improved clinical outcomes among patients with diabetes.

Background Patients hospitalized for COVID-19 may experience complications following hospitalization and require readmission. This analysis estimates the rate and risk factors associated with COVID-19-related readmission and inpatient mortality. Methods This is a retrospective cohort study utilizing deidentified chargemaster data from 297 hospitals across 40 US states on patients hospitalized with COVID-19 February 15-June 09, 2020. Demographics, comorbidities, acute conditions, and clinical characteristics of first hospitalization are summarized. Mulitvariable logistic regression was used to measure risk factor associations with 30-day readmission and in-hospital mortality. Results Among 29,659 patients, 1,070 (3.6%) were readmitted. Readmitted patients were more likely to have diabetes, hypertension, cardiovascular disease (CVD), chronic kidney disease (CKD) vs those not readmitted (p&lt;0.0001) and to present on first admission with acute kidney injury (15.6% vs. 9.2%), congestive heart failure (6.4% vs. 2.4%), and cardiomyopathy (2.1% vs. 0.8%) (p&lt;0.0001). Higher odds of readmission were observed in patients age &gt;60 vs. 1840 (odds ratio [OR]=1.92, 95% confidence interval [CI]=1.48, 2.50), and admitted in the Northeast vs. West (OR=1.43, 95% CI=1.14, 1.79) or South (OR=1.28, 95% CI=1.11, 1.49). Comorbidities including diabetes (OR=1.34, 95% CI=1.12, 1.60), CVD (OR=1.46, 95% CI=1.23, 1.72), CKD stage 1-5 (OR=1.51, 95% CI=1.25,1.81) and stage 5 (OR=2.27, 95% CI=1.81, 2.86) were associated with higher odds of readmission. 12.3% of readmitted patients died during second hospitalization. Conclusions Among this large US population of patients hospitalized with COVID-19, readmission was associated with certain comorbidities and acute conditions during first hospitalization. These findings may inform strategies to mitigate risks of readmission due to COVID-19 complications.

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