ReviewObesity science & practice2020
Validated methods for identifying individuals with obesity in health care administrative databases: A systematic review.
Review in Obesity science & practice, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The validity of electronic health data for measuring smoking status: a systematic review and meta-analysis.BMC medical informatics and decision making · 2024Pooled it
- Article
- Same ICD-10 code, different estimands: four Polish National Health Fund obesity series, 2015-2025.Frontiers in public health · 2026Article
- Inequalities in Preterm Birth in England: A Retrospective National Cohort Study Focusing on Deprivation and Ethnicity, Using Routinely Collected Maternity Hospital Data.BJOG : an international journal of obstetrics and gynaecology · 2025Article
- Quantification of Information Gained by Linking Claims Data to an Electronic Health Record Cohort of Patients With Metastatic Breast Cancer.Pharmacoepidemiology and drug safety · 2025Article
- Factors Associated with Antiviral Drug Use Among Commercially Insured Children at High Risk for Complications of Influenza.The Journal of pediatrics · 2025Article
- Narcolepsy Is Associated With Subclinical Cardiovascular Disease as Early as Childhood: A Big Data Analysis.Journal of the American Heart Association · 2025Article
- Applying machine learning approaches for predicting obesity risk using US health administrative claims database.BMJ open diabetes research & care · 2024Observational
- Perinatal Outcomes Associated With Metformin Use During Pregnancy in Women With Pregestational Type 2 Diabetes Mellitus.Diabetes care · 2024Article
- Association of genetic risk, lifestyle, and their interaction with obesity and obesity-related morbidities.Cell metabolism · 2024Article
- Exploring of gut microbiota features in dyslipidemia and chronic coronary syndrome patients undergoing coronary angiography.Frontiers in microbiology · 2024Article
- Polypharmacy among medicaid-insured children with and without documented obesity.Pharmacotherapy · 2023Article
- Topiramate Utilization After Phentermine/Topiramate Approval for Obesity Management: Risk Minimization in the Era of Drug Repurposing.Drug safety · 2022Article
- Interconception Preventive Care and Recurrence of Pregnancy Complications for Medicaid-Insured Women.Journal of women's health (2002) · 2022Article
- Completeness and representativeness of body mass index in children's electronic general practice records: Linked cross-sectional study in an ethnically-diverse urban population in the United Kingdom.Pediatric obesity · 2021Article
- Detecting non-alcoholic fatty liver disease and risk factors in health databases: accuracy and limitations of the ICD-10-AM.BMJ open gastroenterology · 2021Article
- Validated methods for identifying individuals with obesity in health care administrative databases: A systematic review.Obesity science & practice · 2020Review
- Epidemiology of metabolic syndrome in patients with inflammatory bowel disease: a population-level cohort study from the United States.Annals of gastroenterologyArticle
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHealth care administrative databases are increasingly used for health studies and public health surveillance. Cases of individuals with obesity are selected using case-identification methods. However, the validity of these methods is fragmentary and particularly challenging for obesity case identification.
objectiveThe objectives of this systematic review are to (1) determine the case-identification methods used to identify individuals with obesity in health care administrative databases and (2) to summarize the validity of these case-identification methods when compared with a reference standard.
methodsA systematic literature search was conducted in six bibliographic databases for the period January 1980 to June 2019 for all studies evaluating obesity case-identification methods compared with a reference standard.
resultsSeventeen articles met the inclusion criteria. International Classification of Diseases (ICD) codes were the only case-identification method utilized in selected articles. The performance of obesity-identification methods varied widely across studies, with positive predictive value ranging from 19% to 100% while sensitivity ranged from 3% to 92%. The sensitivity of these methods was usually low while the specificity was higher.
conclusionWhen obesity is reported in health care administrative databases, it is usually correctly reported; however, obesity tends to be highly underreported in databases. Therefore, case-identification methods to monitor the prevalence and incidence of obesity within health care administrative databases are not reliable. In contrast, the use of these methods remains relevant for the selection of individuals with obesity for cohort studies, particularly when identifying cohorts of individuals with severe obesity or cohorts where obesity is associated with comorbidities.
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