Prevalence of obesity, type II diabetes mellitus, hyperlipidemia, and hypertension in the United States: findings from the GE Centricity Electronic Medical Record database.

This study analyzed GE Centricity Electronic Medical Record (EMR) data to examine the effects of body mass index (BMI) and obesity, key risk factor components of metabolic syndrome, on the prevalence of 3 chronic diseases: type II diabetes mellitus, hyperlipidemia, and hypertension. These chronic diseases occur with high prevalence and impose high disease burdens. The rationale for using Centricity EMR data is 2-fold. First, EMRs may be a good source of BMI/obesity data, which are often underreported in surveys and administrative databases. Second, EMRs provide an ideal means to track variables over time and, thus, allow longitudinal analyses of relationships between risk factors and disease prevalence and progression. Analysis of Centricity EMR data showed associations of age, sex, race/ethnicity, and BMI with diagnosed prevalence of the 3 conditions. Results include uniform direct correlations between age and BMI and prevalence of each disease; uniformly greater disease prevalence for males than females; varying differences by race/ethnicity (ie, African Americans have the highest prevalence of diagnosed type II diabetes and hypertension, while whites have the highest prevalence of diagnosed hypertension); and adverse effects of comorbidities. The direct associations between BMI and disease prevalence are consistent for males and females and across all racial/ethnic groups. The results reported herein contribute to the growing literature about the adverse effects of obesity on chronic disease prevalence and about the potential value of EMR data to elucidate trends in disease prevalence and facilitate longitudinal analyses.

Comparison of GE Centricity Electronic Medical Record database and National Ambulatory Medical Care Survey findings on the prevalence of major conditions in the United States.

The study objective was to facilitate investigations by assessing the external validity and generalizability of the Centricity Electronic Medical Record (EMR) database and analytical results to the US population using the National Ambulatory Medical Care Survey (NAMCS) data and results as an appropriate validation resource. Demographic and diagnostic data from the NAMCS were compared to similar data from the Centricity EMR database, and the impact of the different methods of data collection was analyzed. Compared to NAMCS survey data on visits, Centricity EMR data shows higher proportions of visits by younger patients and by females. Other comparisons suggest more acute visits in Centricity and more chronic visits in NAMCS. The key finding from the Centricity EMR is more visits for the 13 chronic conditions highlighted in the NAMCS survey, with virtually all comparisons showing higher proportions in Centricity. Although data and results from Centricity and NAMCS are not perfectly comparable, once techniques are employed to deal with limitations, Centricity data appear more sensitive in capturing diagnoses, especially chronic diagnoses. Likely explanations include differences in data collection using the EMR versus the survey, particularly more comprehensive medical documentation requirements for the Centricity EMR and its inclusion of laboratory results and medication data collected over time, compared to the survey, which focused on the primary reason for that visit. It is likely that Centricity data reflect medical problems more accurately and provide a more accurate estimate of the distribution of diagnoses in ambulatory visits in the United States. Further research should address potential methodological approaches to maximize the validity and utility of EMR databases.