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

ABSTRACT: 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.

SUBMITTER: Holt TA

PROVIDER: S-EPMC4251506 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature

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

Holt Tim A TA Gunnarsson Candace L CL Cload Paul A PA Ross Susan D SD

CMAJ open 20141001 4

<h4>Background</h4>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.<h4>Methods</h4>We conducted a cross-sectional study and retrospective observational cohort analysis of prima ...[more]

PMID: 25485250

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Project description:IntroductionThe extent of preventable medication-related hospital admissions and medication-related issues in primary care is significant enough to justify developing decision support systems for medication safety surveillance. The prerequisite for such systems is defining a relevant set of medication safety-related indicators and understanding the influence of both patient and general practice characteristics on medication prescribing and monitoring.ObjectiveThe aim of the study was to investigate the feasibility of linked primary and secondary care electronic health record data for surveillance of medication safety, examining not only prescribing but also monitoring, and associations with patient- and general practice-level characteristics.MethodsA cross-sectional study was conducted using linked records of patients served by one hospital and over 50 general practices in Salford, UK. Statistical analysis consisted of mixed-effects logistic models, relating prescribing safety indicators to potential determinants.ResultsThe overall prevalence (proportion of patients with at least one medication safety hazard) was 5.45 % for prescribing indicators and 7.65 % for monitoring indicators. Older patients and those on multiple medications were at higher risk of prescribing hazards, but at lower risk of missed monitoring. The odds of missed monitoring among all patients were 25 % less for males, 50 % less for patients in practices that provide general practitioner training, and threefold higher in practices serving the most deprived compared with the least deprived areas. Practices with more prescribing hazards did not tend to show more monitoring issues.ConclusionsSystematic collection, collation, and analysis of linked primary and secondary care records produce plausible and useful information about medication safety for a health system. Medication safety surveillance systems should pay close attention to patient age and polypharmacy with respect to both prescribing and monitoring failures; treat prescribing and monitoring as different statistical processes, rather than a combined measure of prescribing safety; and audit the socio-economic equity of missed monitoring.

Project description:Physicians can receive federal payments for meaningful use of complete certified electronic health records (EHRs). Evidence is limited on how EHR use affects clinical care and outcomes.To examine the association between use of a commercially available certified EHR and clinical care processes and disease control in patients with diabetes.Quasi-experimental design with outpatient EHR implementation sequentially across 17 medical centers. Multivariate analyses adjusted for patient characteristics, medical center, time trends, and facility-level clustering.Kaiser Permanente Northern California, an integrated delivery system.169 711 patients with diabetes mellitus.Use of a commercially available certified EHR.Drug treatment intensification and hemoglobin A(1c) (HbA(1c)) and low-density lipoprotein cholesterol (LDL-C) testing and values.Use of an EHR was associated with statistically significant improvements in treatment intensification after HbA(1c) values of 9% or greater (odds ratio, 1.10 [95% CI, 1.05 to 1.15]) or LDL-C values of 2.6 to 3.3 mmol/L (100 to 129 mg/dL) (odds ratio, 1.06 [CI, 1.00 to 1.12]); increases in 1-year retesting for HbA(1c) and LDL-C levels among all patients, with the most dramatic change among patients with the worst disease control (HbA(1c) levels ?9% or LDL-C levels ?3.4 mmol/L [?130 mg/dL]); and decreased 90-day retesting among patients with HbA(1c) levels less than 7% or LDL-C levels less than 2.6 mmol/L (<100 mg/dL). The EHR was also associated with statistically significant reductions in HbA(1c) and LDL-C levels, with the largest reductions among patients with the worst control (0.06-mmol/L [2.19-mg/dL] reduction among patients with baseline LDL-C levels ?3.4 mmol/L [?130 mg/dL]; P < 0.001).The EHR was implemented in a setting with strong baseline performance on cardiovascular care quality measures.Use of a commercially available certified EHR was associated with improved drug treatment intensification, monitoring, and physiologic control among patients with diabetes, with greater improvements among patients with worse control and less testing in patients already meeting guideline-recommended glycemic and lipid targets.National Institute of Diabetes and Digestive and Kidney Diseases.

Project description:BACKGROUND:Influenza causes an estimated 3000 to 50,000 deaths per year in the United States of America (US). Timely and representative data can help local, state, and national public health officials monitor and respond to outbreaks of seasonal influenza. Data from cloud-based electronic health records (EHR) and crowd-sourced influenza surveillance systems have the potential to provide complementary, near real-time estimates of influenza activity. The objectives of this paper are to compare two novel influenza-tracking systems with three traditional healthcare-based influenza surveillance systems at four spatial resolutions: national, regional, state, and city, and to determine the minimum number of participants in these systems required to produce influenza activity estimates that resemble the historical trends recorded by traditional surveillance systems. METHODS:We compared influenza activity estimates from five influenza surveillance systems: 1) patient visits for influenza-like illness (ILI) from the US Outpatient ILI Surveillance Network (ILINet), 2) virologic data from World Health Organization (WHO) Collaborating and National Respiratory and Enteric Virus Surveillance System (NREVSS) Laboratories, 3) Emergency Department (ED) syndromic surveillance from Boston, Massachusetts, 4) patient visits for ILI from EHR, and 5) reports of ILI from the crowd-sourced system, Flu Near You (FNY), by calculating correlations between these systems across four influenza seasons, 2012-16, at four different spatial resolutions in the US. For the crowd-sourced system, we also used a bootstrapping statistical approach to estimate the minimum number of reports necessary to produce a meaningful signal at a given spatial resolution. RESULTS:In general, as the spatial resolution increased, correlation values between all influenza surveillance systems decreased. Influenza-like Illness rates in geographic areas with more than 250 crowd-sourced participants or with more than 20,000 visit counts for EHR tracked government-lead estimates of influenza activity. CONCLUSIONS:With a sufficient number of reports, data from novel influenza surveillance systems can complement traditional healthcare-based systems at multiple spatial resolutions.

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

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

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