Identification of undiagnosed diabetes and quality of diabetes care in the United States: cross-sectional study of 11.5 million primary care electronic records.

BACKGROUND: Electronic diabetes registers promote structured care and enable identification of undiagnosed diabetes, but they require consistent coding of the diagnosis in electronic medical records. We investigated the potential of electronic medical records to identify undiagnosed diabetes and to support diabetes management in a large primary care population in the United States. METHODS: We conducted a cross-sectional study and retrospective observational cohort analysis of primary care electronic medical records from a nationally representative US database (GE Centricity). We tested the feasibility of identifying patients with undiagnosed diabetes by applying simple algorithms to the electronic medical record data. We compared the quality of care provided to patients in the United States who had diabetes (coded and uncoded) for at least 15 months with the quality of care provided in England using a set of 16 indicators. RESULTS: We included 11 540 454 electronic medical records from more than 9000 primary care clinics across the United States. Of the 1 110 398 records indicating diagnosed diabetes, only 61.9% contained a diagnostic code. Of the 10 430 056 records for nondiabetic patients, 0.4% (n = 40 359) had at least 2 abnormal fasting or random blood glucose values, and 0.2% (n = 23 261) of the remaining records had at least 1 documented glycated hemoglobin (HbA1c) value of 6.5% or higher. Among the 622 260 patients for whom information on quality-of-care indicators was available, those with a coded diagnosis of diabetes had a significantly higher level of quality of care than those with uncoded diabetes (p < 0.01); however, the quality of care was generally lower than that indicated in England. INTERPRETATION: We were able to identify a substantial number of patients with uncoded diabetes and probable undiagnosed diabetes using simple algorithms applied to the primary care electronic records. Electronic coding of the diagnosis was associated with improved quality of care. Electronic diabetes registers are underused in US primary care and provide opportunities to facilitate the systematic, structured approach that is established in England.

Risk of stroke and oral anticoagulant use in atrial fibrillation: a cross-sectional survey.

BACKGROUND: Oral anticoagulants substantially reduce the risk of stroke in atrial fibrillation but are underutilised in current practice. AIM: To measure the distribution of stroke risk in patients with atrial fibrillation (using the CHADS(2) and CHA(2)DS(2)-VASc scores) and changes in oral anticoagulant use during 2007-2010. DESIGN AND SETTING: Longitudinal series of cross-sectional survey in 583 UK practices linked to the QResearch(®) database providing 99 351 anonymised electronic records from people with atrial fibrillation. METHOD: The proportion of patients in each CHADS(2) and CHA(2)DS(2)-VASc risk band in 2010 was calculated; for each of the years 2007-2010, the proportions with risk scores ≥2 that were using anticoagulants or antiplatelet agents were estimated. The proportions identified at high risk were re-estimated using alternative definitions of hypertension based on coded data. Finally, the prevalence of comorbid conditions in treated and untreated high-risk (CHADS(2) ≥2) groups was derived. RESULTS: The proportion at high risk of stroke in 2010 was 56.9% according to the CHADS(2) ≥2 threshold, and 84.5% according to CHA(2)DS(2)-VASc ≥2 threshold. The proportions of these groups receiving anticoagulants were 53.0% and 50.7% respectively and increased during 2007-2010. The means of identifying the population of individuals with hypertension significantly influenced the estimated proportion at high risk. Comorbid conditions associated with avoidance of anticoagulants included history of falls, use of nonsteroidal anti-inflammatory drugs, and dementia. CONCLUSION: Oral anticoagulant use in atrial fibrillation has increased in UK practice since 2007, but remains suboptimal. Improved coding of hypertension is required to support systematic identification of individuals at high risk of stroke and could be assisted by practice-based software.

Statins and risk of cancer: a retrospective cohort analysis of 45,857 matched pairs from an electronic medical records database of 11 million adult Americans.

OBJECTIVES: The purpose of this study was to determine whether cancer can be attributed to statin use among a general population of older adults in the United States with at least 3 years of follow-up. BACKGROUND: Statins are widely prescribed drugs in the United States for the management of dyslipidemia, atherosclerosis, and cardiovascular event risk reduction. Unsettled scientific debate about the association of statins with cancer continues, with high-profile studies showing conflicting results. METHODS: A retrospective cohort analysis of the incidence of cancer in older adults who have and who have not used statins was performed. More than 11 million analyzable patient records from January 1990 through February 2009 were drawn from the General Electric Centricity electronic medical records database. Propensity matching found pairs of patients receiving and not receiving statin therapy who shared similar propensities for statin use. RESULTS: Propensity score methods matched 45,857 comparison pairs of patients taking a statin and patients not taking a statin. The average time in the database was 8 years, with pairs being followed for an average of 4.6 and 4.7 years. After matching, the incidence of cancer in patients taking a statin was 11.37% compared with 11.11% in matched patients not taking a statin. Multivariate-matched Cox regression analysis showed a nonsignificant hazard ratio of 1.04 (95% confidence interval: 0.99 to 1.09). Kaplan-Meier curves for diagnosis of any cancer up to 10 years also showed no difference for patients taking a statin and those not taking a statin. CONCLUSIONS: This retrospective analysis of nearly 46,000 propensity-matched pairs demonstrated no statistically significant increased risk of cancer associated with statins.