Assessing Hospital Performance After Percutaneous Coronary Intervention Using Big Data

Although risk adjustment remains a cornerstone for comparing outcomes across hospitals, optimal strategies continue to evolve in the presence of many confounders. We compared conventional regression-based model to approaches particularly suited to leveraging big data. We assessed hospital all-cause...

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Veröffentlicht in:	Circulation Cardiovascular quality and outcomes 2016-11, Vol.9 (6), p.659-669
Hauptverfasser:	Spertus, Jacob V, T Normand, Sharon-Lise, Wolf, Robert, Cioffi, Matt, Lovett, Ann, Rose, Sherri
Format:	Artikel
Sprache:	eng
Schlagworte:	Aged Aged, 80 and over Algorithms Cause of Death Data Mining - methods Databases, Factual Female Hospital Mortality Hospitals - standards Humans Likelihood Functions Logistic Models Machine Learning Male Massachusetts Middle Aged Multivariate Analysis Percutaneous Coronary Intervention - adverse effects Percutaneous Coronary Intervention - mortality Percutaneous Coronary Intervention - standards Process Assessment (Health Care) - standards Propensity Score Quality Indicators, Health Care - standards Registries Risk Factors Time Factors Treatment Outcome
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