Literature DB >> 25380698

Validity of a Claims-Based Diagnosis of Obesity Among Medicare Beneficiaries.

Jennifer T Lloyd1, Steve A Blackwell2, Iris I Wei2, Benjamin L Howell2, William H Shrank3.   

Abstract

Population-level data on obesity are difficult to obtain. Claims-based data sets are useful for studying public health at a population level but lack physical measurements. The objective of this study was to determine the validity of a claims-based measure of obesity compared to obesity diagnosed with clinical data as well as the validity among older adults who suffer from chronic disease. This study used data from the National Health and Nutrition Examination Survey 1999-2004 for adults aged ≥ 65 successfully linked to 1999-2007 Medicare claims (N = 3,554). Sensitivity, specificity, positive and negative predictive values, κ statistics as well as logistic regression analyses were computed for the claims-based diagnosis of obesity versus obesity diagnosed with body mass index. The claims-based diagnosis of obesity underestimates the true prevalence in the older Medicare population with a low sensitivity (18.4%). However, this method has a high specificity (97.3%) and is accurate when it is present. Sensitivity was improved when comparing the claim-based diagnosis to Class II obesity (34.2%) and when used in combination with chronic conditions such as diabetes, congestive heart failure, chronic obstructive pulmonary disease, or depression. Understanding the validity of a claims-based obesity diagnosis could aid researchers in understanding the feasibility of conducting research on obesity using claims data.
© The Author(s) 2014.

Entities:  

Keywords:  Medicare; NHANES; aging; body mass index; epidemiology

Mesh:

Year:  2014        PMID: 25380698     DOI: 10.1177/0163278714553661

Source DB:  PubMed          Journal:  Eval Health Prof        ISSN: 0163-2787            Impact factor:   2.651


  16 in total

1.  Association Between Prediabetes/Diabetes and Asthma Exacerbations in a Claims-Based Obese Asthma Cohort.

Authors:  Tianshi David Wu; Emily P Brigham; Corinne A Keet; Todd T Brown; Nadia N Hansel; Meredith C McCormack
Journal:  J Allergy Clin Immunol Pract       Date:  2019-03-08

2.  Body Mass Index, Diabetes and Intrahepatic Cholangiocarcinoma Risk: The Liver Cancer Pooling Project and Meta-analysis.

Authors:  Jessica L Petrick; Jake E Thistle; Anne Zeleniuch-Jacquotte; Xuehong Zhang; Jean Wactawski-Wende; Alison L Van Dyke; Meir J Stampfer; Rashmi Sinha; Howard D Sesso; Catherine Schairer; Lynn Rosenberg; Thomas E Rohan; Kim Robien; Mark P Purdue; Jenny N Poynter; Julie R Palmer; Christina C Newton; Martha S Linet; Linda M Liao; I-Min Lee; Jill Koshiol; Cari M Kitahara; Jonathan N Hofmann; Barry I Graubard; Edward Giovannucci; Michael J Gaziano; Susan M Gapstur; Neal D Freedman; Dawn Q Chong; Andrew T Chan; Julie E Buring; Laura Beane E Freeman; Peter T Campbell; Katherine A McGlynn
Journal:  Am J Gastroenterol       Date:  2018-09-03       Impact factor: 10.864

3.  Incidence of Proliferative Diabetic Retinopathy and Other Neovascular Sequelae at 5 Years Following Diagnosis of Type 2 Diabetes.

Authors:  William S Gange; Jennifer Lopez; Benjamin Y Xu; Khristina Lung; Seth A Seabury; Brian C Toy
Journal:  Diabetes Care       Date:  2021-09-02       Impact factor: 19.112

4.  Single-arm Trials With External Comparators and Confounder Misclassification: How Adjustment Can Fail.

Authors:  Michael Webster-Clark; Michele Jonsson Funk; Til Stürmer
Journal:  Med Care       Date:  2020-12       Impact factor: 3.178

5.  Use of International Classification of Diseases, Ninth Revision Codes for Obesity: Trends in the United States from an Electronic Health Record-Derived Database.

Authors:  Michelle Mocarski; Ye Tian; B Gabriel Smolarz; John McAna; Albert Crawford
Journal:  Popul Health Manag       Date:  2017-09-26       Impact factor: 2.459

6.  New diagnosis of cancer and the risk of subsequent cerebrovascular events.

Authors:  Babak B Navi; George Howard; Virginia J Howard; Hong Zhao; Suzanne E Judd; Mitchell S V Elkind; Costantino Iadecola; Lisa M DeAngelis; Hooman Kamel; Peter M Okin; Susan Gilchrist; Elsayed Z Soliman; Mary Cushman; Paul Muntner
Journal:  Neurology       Date:  2018-05-04       Impact factor: 9.910

7.  Validation of obesity-related diagnosis codes in claims data.

Authors:  Karine Suissa; Sebastian Schneeweiss; Kueiyu Joshua Lin; Gregory Brill; Seoyoung C Kim; Elisabetta Patorno
Journal:  Diabetes Obes Metab       Date:  2021-08-18       Impact factor: 6.577

8.  Comparative Effectiveness and Safety of Rivaroxaban and Warfarin Among Nonvalvular Atrial Fibrillation (NVAF) Patients with Obesity and Polypharmacy in the United States (US).

Authors:  Jeffrey S Berger; François Laliberté; Akshay Kharat; Dominique Lejeune; Kenneth Todd Moore; Young Jung; Patrick Lefebvre; Veronica Ashton
Journal:  Adv Ther       Date:  2021-05-25       Impact factor: 3.845

9.  International Classification of Diseases (ICD)-coded obesity predicts risk of incident osteoporotic fracture.

Authors:  Shuman Yang; Lisa M Lix; Lin Yan; Aynslie M Hinds; William D Leslie
Journal:  PLoS One       Date:  2017-12-07       Impact factor: 3.240

10.  Suitability of administrative claims databases for bariatric surgery research - is the glass half-full or half-empty?

Authors:  Xiaojuan Li; Kristina H Lewis; Katherine Callaway; J Frank Wharam; Sengwee Toh
Journal:  BMC Med Res Methodol       Date:  2020-09-07       Impact factor: 4.615

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