Mocarski Michelle, Tian Ye, Smolarz B Gabriel, McAna John, Crawford Albert
1 Novo Nordisk, Inc. , Plainsboro, New Jersey.
2 College of Population Health, Thomas Jefferson University , Philadelphia, Pennsylvania.
Popul Health Manag. 2018 Jun;21(3):222-230. doi: 10.1089/pop.2017.0092. Epub 2017 Sep 26.
UNLABELLED: Obesity is a potentially modifiable risk factor for many diseases, and a better understanding of its impact on health care utilization, costs, and medical outcomes is needed. The ability to accurately evaluate obesity outcomes depends on a correct identification of the population with obesity. The primary objective of this study was to determine the prevalence and accuracy of International Classification of Diseases, Ninth Revision (ICD-9) coding for overweight and obesity within a US primary care electronic health record (EHR) database compared against actual body mass index (BMI) values from recorded clinical patient data; characteristics of patients with obesity who did or did not receive ICD-9 codes for overweight/obesity also were evaluated. The study sample included 5,512,285 patients in the database with any BMI value recorded between January 1, 2014, and June 30, 2014. Based on BMI, 74.6% of patients were categorized as being overweight or obese, but only 15.1% of patients had relevant ICD-9 codes. ICD-9 coding prevalence increased with increasing BMI category. Among patients with obesity (BMI ≥30 kg/m), those coded for obesity were younger, more often female, and had a greater comorbidity burden than those not coded; hypertension, dyslipidemia, type 2 diabetes mellitus, and gastroesophageal reflux disease were the most common comorbidities. KEY FINDINGS: US outpatients with overweight or obesity are not being reliably coded, making ICD-9 codes undependable sources for determining obesity prevalence and outcomes. BMI data available within EHR databases offer a more accurate and objective means of classifying overweight/obese status.
未标注:肥胖是许多疾病潜在的可改变风险因素,因此需要更好地了解其对医疗保健利用、成本和医疗结果的影响。准确评估肥胖结果的能力取决于对肥胖人群的正确识别。本研究的主要目的是确定美国基层医疗电子健康记录(EHR)数据库中,国际疾病分类第九版(ICD-9)对超重和肥胖编码的患病率及准确性,并与记录的临床患者数据中的实际体重指数(BMI)值进行比较;还评估了有或没有超重/肥胖ICD-9编码的肥胖患者的特征。研究样本包括数据库中在2014年1月1日至2014年6月30日期间记录有任何BMI值的5,512,285名患者。根据BMI,74.6%的患者被归类为超重或肥胖,但只有15.1%的患者有相关的ICD-9编码。ICD-9编码患病率随BMI类别增加而升高。在肥胖患者(BMI≥30 kg/m²)中,有肥胖编码的患者比没有编码的患者更年轻、女性更多,且合并症负担更重;高血压、血脂异常、2型糖尿病和胃食管反流病是最常见的合并症。 主要发现:美国超重或肥胖的门诊患者编码不可靠,使得ICD-9编码成为确定肥胖患病率和结果的不可靠来源。EHR数据库中的BMI数据提供了一种更准确、客观的超重/肥胖状态分类方法。
Pharmacoepidemiol Drug Saf. 2018-7-12
Diabetes Obes Metab. 2021-12
JAMA Ophthalmol. 2018-10-1
Mayo Clin Proc Innov Qual Outcomes. 2021-1-19
Diabetes Metab Syndr Obes. 2015-7-22
Pharmacoeconomics. 2015-7
Eval Health Prof. 2015-12
South Med J. 2014-6
BMC Health Serv Res. 2014-2-13
NCHS Data Brief. 2013-10