Assessment of cardiometabolic risk factors in a national primary care electronic health record database

被引:22
|
作者
Brixner, Diana
Said, Qayyim
Kirkness, Carmen
Oberg, Brian
Ben-Joseph, Rami
Oderda, Gary
机构
[1] Univ Utah, Coll Pharm, Pharmacotherapy Outcomes Res Ctr, Salt Lake City, UT 84112 USA
[2] Sanofi Aventis Outcomes, Bridgewater, NJ USA
关键词
cardiometabolic risk; electronic health records; metabolic syndrome; prevalence; primary care;
D O I
10.1111/j.1524-4733.2006.00152.x
中图分类号
F [经济];
学科分类号
02 ;
摘要
Objective: This Study examines the prevalence of various cardiometabolic risk (CMR) factors that may contribute to metabolic syndrome in a primary care setting. These risk factors were accessed with use of a national electronic health record database. Methods: In the database, from January 1, 2003 to December 3 1, 2004, patients aged 18 to 64 years with information regarding CMR factors were identified by clinical (biometrics), diagnosis (TCD-9 codes) or treatment (prescriptions) information. Results: The study population consisted of 475,651 patients with information on indicators of CMR, excluding patients with bariatric Surgery or a body mass index (BMI) >= 35 kg/m(2). Of these, 72,593 (!5.3%) and 55,928 (11.8%) had metabolic syndrome according to the National Cholesterol Education Program (NCEP) and International Diabetes Federation (IDF) criteria, respectively. In addition, 162,521 (34.2%) had BMI (>= 27 kg/m(2)) as a risk factor. High blood pressure was identified as a risk factor in 266,371 patients (56.0%). High triglycerides were identified as a risk factor in 10.7%) of the population, low high-density lipoprotein in 16.0%), impaired-fasting glucose in 8.8%, diabetes in 7.2%, and metabolic syndrome (diagnosis) in 0.1%. A total of 178,055 (37.4%) of the study population) subjects had positive indicators of CMR as defined by the NCEP and IDE, Results indicated that obesity is the most prevalent CMR factor representing 90.6% of this at-risk population. Conclusions: The distribution of CMR factors in a primary care database is similar to that established by prospective national health surveys. A key source of identification of risk factors are clinical outcomes including BMI and lab values. Future studies on metabolic syndrome need to link clinically based information with more readily available treatment and diagnosis information.
引用
收藏
页码:S29 / S36
页数:8
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