Incidental pulmonary nodules are an increasingly common consequence of routine medical care, with an incidence that is much greater than recognized previously. More frequent nodule identification has not been accompanied by increases in the diagnosis of cancerous nodules.

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.

Background Data on the epidemiology of herpes zoster (HZ), particularly in the unvaccinated immunocompetent population, are needed to assess disease burden and the potential impact of vaccination. Methods The study at a large health care organization comprised: (1) incidence estimated from immunocompetent adults aged ≥50 years unvaccinated with zoster vaccine live who had incident HZ in 2011–2015; (2) proportion of HZ-related nonpain complications assessed by double abstraction of electronic health records (EHRs) of 600 incident patients 2011–2015; (3) HZ-related hospitalizations among HZ patients diagnosed in 2015; (4) HZ-related death determined from automated data and EHRs; and (5) recurrent HZ identified from a cohort initially diagnosed with HZ in 2007–2008 and followed through 2016. Results HZ incidence rate was 9.92/1000 person-years (95% confidence interval [CI], 9.82–10.01). Proportions of cutaneous, neurologic, and other complications were 6.40% (95% CI,1.73%–11.07%), 0.77% (95% CI, .00%–2.36%), and 1.01% (95% CI, .00%–2.93%), respectively. Only 0.86% of patients had an HZ-related hospitalization. The case-fatality rate was 0.04%. Recurrence rate was 10.96/1000 person-years (95% CI, 10.18–11.79) with 10-year recurrence risk of 10.26% (95% CI, 9.36%–11.23%). Conclusions These recent HZ epidemiology data among an immunocompetent, unvaccinated population measure real-world disease burden.

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Introduction Lung nodules are commonly encountered in clinical practice, yet little is known about their management in community settings. An automated method for identifying patients with lung nodules would greatly facilitate research in this area. Methods Using members of a large, community-based health plan in 2006–2010, we developed a method to identify patients with lung nodules by combining five diagnostic codes, four procedural codes and a natural language processing (NLP) algorithm that performed free text searches of radiology transcripts. An experienced pulmonologist reviewed a random sample of 116 radiology transcripts, providing a reference standard for the NLP algorithm. Results We identified 7,112 unique members as having one or more incident lung nodules using an automated method. The mean age was 65 (SD 14) years. There were slightly more women (54%) than men, and Hispanics and non-whites comprised 45% of the lung nodule cohort. Thirty-six percent were never smokers while 11% were current smokers. Fourteen percent were subsequently diagnosed with lung cancer. The sensitivity and specificity of the NLP algorithm for identifying the presence of lung nodule(s) were 96% and 86%, respectively, compared with clinician review. Among the true positive transcripts in the validation sample, only 35% were solitary and unaccompanied by one or more associated findings and 56% measured 8–30 mm in diameter. Conclusions A combination of diagnostic codes, procedural codes and an NLP algorithm for free text searching of radiology reports can accurately and efficiently identify patients with incident lung nodules, many of whom are subsequently diagnosed with lung cancer.