Dataset Information

Assessing Hospital Performance After Percutaneous Coronary Intervention Using Big Data.

ABSTRACT: 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 30-day excess mortality risk among 8952 adults undergoing percutaneous coronary intervention between October 1, 2011, and September 30, 2012, in 24 Massachusetts hospitals using clinical registry data linked with billing data. We compared conventional logistic regression models with augmented inverse probability weighted estimators and targeted maximum likelihood estimators to generate more efficient and unbiased estimates of hospital effects. We also compared a clinically informed and a machine-learning approach to confounder selection, using elastic net penalized regression in the latter case. Hospital excess risk estimates range from -1.4% to 2.0% across methods and confounder sets. Some hospitals were consistently classified as low or as high excess mortality outliers; others changed classification depending on the method and confounder set used. Switching from the clinically selected list of 11 confounders to a full set of 225 confounders increased the estimation uncertainty by an average of 62% across methods as measured by confidence interval length. Agreement among methods ranged from fair, with a ? statistic of 0.39 (SE: 0.16), to perfect, with a ? of 1 (SE: 0.0).Modern causal inference techniques should be more frequently adopted to leverage big data while minimizing bias in hospital performance assessments.

SUBMITTER: Spertus JV

PROVIDER: S-EPMC5341139 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Assessing Hospital Performance After Percutaneous Coronary Intervention Using Big Data.

Spertus Jacob V JV T Normand Sharon-Lise SL Wolf Robert R Cioffi Matt M Lovett Ann A Rose Sherri S

Circulation. Cardiovascular quality and outcomes 20161108 6

<h4>Background</h4>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.<h4>Methods and results</h4>We assessed hospital all-cause 30-day excess mortality risk among 8952 adults undergoing percutaneous coronary intervention between October 1, 2011, and September 30, 2012, in 24 Massac ...[more]

PMID: 28263941

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Project description:ImportanceDiagnostic coronary angiography in asymptomatic patients may lead to inappropriate percutaneous coronary intervention (PCI) due to a diagnostic-therapeutic cascade. Understanding the association between patient selection for coronary angiography and PCI appropriateness may inform strategies to minimize inappropriate procedures.ObjectiveTo determine if hospitals that frequently perform coronary angiography in asymptomatic patients, a clinical scenario in which the benefit of angiography is less clear, are more likely to perform inappropriate PCI.Design, setting, and participantsMulticenter observational study of 544 hospitals participating in the CathPCI Registry between July 1, 2009, and September 30, 2013.Main outcomes and measuresHospital proportion of asymptomatic patients at diagnostic coronary angiography and hospital rate of inappropriate PCI as defined by 2012 appropriate use criteria for coronary revascularization.ResultsOf 1 225 562 patients who underwent elective coronary angiography, 308 083 (25.1%) were asymptomatic. The hospital proportion of angiography among asymptomatic patients ranged from 1.0% to 73.6% (median, 24.7%; interquartile range, 15.9%-35.9%). By hospital quartile of asymptomatic patients at angiography, hospitals with higher rates of asymptomatic patients at angiography had higher median rates of inappropriate PCI (14.8% vs 20.2% vs 24.0 vs 29.4% from lowest to highest quartile, P < .001 for trend). This outcome was attributable to more frequent use of inappropriate PCI in asymptomatic patients at hospitals with higher rates of angiography in asymptomatic patients (5.4% vs 9.9% vs 14.7% vs 21.6% from lowest to highest quartile, P < .001 for trend). Hospitals with higher rates of asymptomatic patients at angiography also had lower rates of appropriate PCI (38.7% vs 33.0% vs 32.3% vs 32.9% from lowest to highest quartile, P < .001 for trend).Conclusions and relevanceIn a national sample of hospitals, performance of coronary angiography in asymptomatic patients was associated with higher rates of inappropriate PCI and lower rates of appropriate PCI. Improving preprocedural risk stratification and thresholds for coronary angiography may be one strategy to improve the appropriateness of PCI.

Project description:Patients with ST elevation myocardial infarction (STEMI) require rapid identification and triage to initiate reperfusion therapy. Walk-in STEMI patients have longer treatment times compared to emergency medical service (EMS) transported patients. While effective triage of large numbers of critically ill patients in the emergency department is often cited as the reason for treatment delays, additional factors have not been explored. The purpose of this study was to evaluate baseline demographic and clinical differences between walk-in and EMS-transported STEMI patients and identify factors associated with prolonged door to balloon (D2B) time in walk-in STEMI patients.We performed a retrospective review of 136 STEMI patients presenting to an urban academic teaching center from January 2009 through December 2010. Baseline demographics, mode of hospital entry (walk-in versus EMS transport), treatment times, angiographic findings, procedures performed and in-hospital clinical events were collected. We compared walk-in and EMS-transported STEMI patients and identified independent factors of prolonged D2B time for walk-in patients using stepwise logistic regression analysis.Walk-in patients (n=51) were more likely to be Latino and presented with a higher heart rate, higher systolic blood pressure, prior history of diabetes mellitus and were more likely to have an elevated initial troponin value, compared to EMS-transported patients. EMS-transported patients (n=64) were more likely to be white and had a higher prevalence of left main coronary artery disease, compared to walk-in patients. Door to electrocardiogram (ECG), ECG to catheterization laboratory (CL) activation and D2B times were significantly longer for walk-in patients. Walk-in patients were more likely to have D2B time >90 minutes, compared to EMS- transported patients; odds ratio 3.53 (95% CI 1.03, 12.07), p=0.04. Stepwise logistic regression identified hospital entry mode as the only independent predictor for prolonged D2B time.Baseline differences exist between walk-in and EMS-transported STEMI patients undergoing primary percutaneous coronary intervention (PCI). Hospital entry mode was the most important predictor for prolonged treatment times for primary PCI, independent of age, Latino ethnicity, heart rate, systolic blood pressure and initial troponin value. Prolonged door to ECG and ECG to CL activation times are modifiable factors associated with prolonged treatment times in walk-in STEMI patients. In addition to promoting the use of EMS transport, efforts are needed to rapidly identify and expedite the triage of walk-in STEMI patients.

Project description:Importance:Multiple states publicly report a hospital's risk-adjusted mortality rate for percutaneous coronary intervention (PCI) as a quality measure. However, whether reported annual PCI mortality is associated with a hospital's future performance is unclear. Objective:To evaluate the association between reported risk-adjusted hospital PCI-related mortality and a hospital's future PCI-related mortality. Design, Setting, and Participants:This study used data from the New York Percutaneous Intervention Reporting System from January 1, 1998, to December 31, 2016, to assess hospitals that perform PCI. Exposures:Public-reported, risk-adjusted, 30-day mortality after PCI. Main Outcomes and Measures:The primary analysis evaluated the association between a hospital's reported risk-adjusted PCI-related mortality and future PCI-related mortality. The correlation between a hospital's observed to expected (O/E) PCI-related mortality rates each year and future O/E mortality ratios was assessed. Multivariable linear regression was used to examine the association between index year O/E mortality and O/E mortality in subsequent years while adjusting for PCI volume and patient severity. Results:This study included 67 New York hospitals and 960 hospital-years. Hospitals with low PCI-related mortality (O/E mortality ratio, ?1) and high mortality (O/E mortality ratio, >1) had inverse associations between their O/E mortality ratio in the index year and the subsequent change in the ratio (hospitals with low mortality, r?=?-0.45; hospitals with high mortality, r?=?-0.60). Little of the variation in risk-adjusted mortality was explained by prior performance. An increase in the O/E mortality ratio from 1.0 to 2.0 in the index year was associated with a higher O/E mortality ratio of only 0.15 (95% CI, 0.02-0.27) in the following year. Conclusions and Relevance:At hospitals with high or low PCI-related mortality rates, the rates largely regressed to the mean the following year. A hospital's risk-adjusted mortality rate was poorly associated with its future mortality. The annual hospital PCI-related mortality may not be a reliable factor associated with hospital quality to consider in a practice change or when helping patients select high-quality hospitals.

Dataset Information

Assessing Hospital Performance After Percutaneous Coronary Intervention Using Big Data.

Publications

Assessing Hospital Performance After Percutaneous Coronary Intervention Using Big Data.

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