Back to search

Article

Utility of Automated Data-adaptive Propensity Score Method for Confounding by Indication in Comparative Effectiveness Study in Real World Medicare and Registry Data

2021-04-09

Abstract excerpt

<h4>ABSTRACT</h4> <h4>Background</h4> Confounding by indication is a serious threat to comparative studies using real world data. We assessed the utility of automated data-adaptive analytic approach for confounding adjustment when both claims and clinical registry data are available. <h4>Methods</h4> We used a comparative study example of carotid artery stenting (CAS) vs. carotid endarterectomy (CEA) in 2005-2008...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
7c2aada2-8805-5418-9f6d-d492a5ca5396
DOI
10.1101/2021.04.06.21254887
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Utility of Automated Data-adaptive Propensity Score Method for Confounding by Indication in Comparative Effectiveness Study in Real World Medicare and Registry DataDOI 10.1101/2021.04.06.21254887
A plasmode simulation-based bias analysis for residual confounding by unmeasured variables leveraging information-rich subsetsSemantic proximity
Design Matters in Patient-Level Prediction: Evaluation of a Cohort vs. Case-Control Design When Developing Predictive Models in Observational Healthcare DatasetsSemantic proximity
Impact of Physician Experience on Stroke or Death Rates in Transfemoral Carotid Artery Stenting: Insights from the Vascular Quality InitiativeSemantic proximity
Evaluating algorithmic fairness in the presence of clinical guidelines: the case of atherosclerotic cardiovascular disease risk estimationSemantic proximity
The GRACE Treatment-Selection Paradox in Real-World Non-ST- Elevation Acute Coronary Syndrome: Comorbidity Burden, Invasive Management, and Medication PersistenceSemantic proximity
Assessment of sex and racial biases in electronic health records of emergency department patients with acute coronary syndromeSemantic proximity
Causal Forests versus Inverse Probability of Treatment Weighting to adjust for Cluster-Level Confounding: A Parametric and Plasmode Simulation Study based on US Hosptial Electronic Health Record DataSemantic proximity
Stage-wise algorithmic bias, its reporting, and relation to classical systematic review biases in AI-based automated screening in health sciences: A structured literature reviewSemantic proximity
Benchmarking commercial healthcare claims dataSemantic proximity
Quantitative bias analysis methods for summary level epidemiologic data in the peer-reviewed literature: a systematic reviewSemantic proximity
Data reuse enables cost-efficient randomized trials of medical AI modelsSemantic proximity
Bias and Variance of Adjusting for InstrumentsSemantic proximity
Select a neighboring publication to make it the new centre.