ArticleCurrent epidemiology reports2014
Misclassification in administrative claims data: quantifying the impact on treatment effect estimates.
Article in Current epidemiology reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 105 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
105 citing papers in PubMed, 2 syntheses or guidelines pooled it.
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- Association of Immunodeficiency and HIV Viremia With Cervical Precancer and Cancer Risk Among Women With HIV in South Africa.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2026Article
- Association of pharmacotherapy with all-cause mortality among patients with irritable bowel syndrome.Communications medicine · 2026Article
- A Latent Variable Approach for Causal Effect Estimation Under Misclassified Treatment Assignment.Statistics in medicine · 2026Article
- Patient and public involvement and engagement in target trial emulation framework: a scoping review protocol.BMJ open · 2026Article
- The association between midlife neighbourhood walkability and Alzheimer's disease in women: a prospective nested case-control study.Age and ageing · 2026Article
- Validation of algorithms for identifying people living with HIV in French medico-administrative databases: implications for HIV surveillance.BMC medical research methodology · 2026Article
- Genomics of drug target prioritization for complex diseases.Nature reviews. Genetics · 2026Review
- Ensuring Reliability of Curated Electronic Health Record-Derived Data: The Validation of Accuracy for Large Language Model-/Machine Learning-Extracted Information and Data (VALID) Framework.JCO clinical cancer informatics · 2026Article
- Use of Clinical Notes to Assess Neuropsychiatric Events After Montelukast Initiation.JAMA network open · 2026Article
- Colchicine in Coronary Artery Disease: Comparative Review of CLEAR SYNERGY, LoDoCo2 and COLCOT.Current atherosclerosis reports · 2026Review
- Real-world adherence, healthcare resource utilization, and costs following a transition to aripiprazole once every 2 months among patients diagnosed with bipolar I disorder in the United States.Frontiers in psychiatry · 2026Article
- Outcomes and Management of Pregnancies Screening Positive for Microdeletions 22q11.2, 15q11.2, 1p36, 4p, or 5p: A Retrospective Cohort Study.The application of clinical genetics · 2026Article
- Adjusting for selection bias due to missing eligibility criteria in emulated target trials.American journal of epidemiology · 2025Article
- Addressing bias due to measurement error of an outcome with unknown sensitivity in database epidemiologic studies. A contribution from the ConcePTION project.American journal of epidemiology · 2025Article
- Health Care Setting and Minimally Adequate Depression Treatment Among Publicly Insured Children.JAMA network open · 2025Article
- Considerations for Data Accuracy in Assessing Pulmonary Arterial Hypertension Care Delivery.American journal of respiratory and critical care medicine · 2025Article
45 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Misclassification is present in nearly every epidemiologic study, yet is rarely quantified in analysis in favor of a focus on random error. In this review, we discuss past and present wisdom on misclassification and what measures should be taken to quantify this influential bias, with a focus on bias in pharmacoepidemiologic studies. To date, pharmacoepidemiology primarily utilizes data obtained from administrative claims, a rich source of prescription data but susceptible to bias from unobservable factors including medication sample use, medications filled but not taken, health conditions that are not reported in the administrative billing data, and inadequate capture of confounders. Due to the increasing focus on comparative effectiveness research, we provide a discussion of misclassification in the context of an active comparator, including a demonstration of treatment effects biased away from the null in the presence of nondifferential misclassification. Finally, we highlight recently developed methods to quantify bias and offer these methods as potential options for strengthening the validity and quantifying uncertainty of results obtained from pharmacoepidemiologic research.
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