Comparing Outcomes and Costs at Teaching and non-Teaching Hospitals, A Multivariate Matching Analysis
The overall goal of this study is to compare the costs and quality of similar Medicare patients admitted to teaching and non-teaching hospitals. There are three main aims: (I) develop matched pairs of patients that are treated at teaching and non-teaching hospitals across major medical conditions and surgical procedures. Assess the quality of matches based on the standardized differences in variables across comparison groups. (2) Analyze cost and quality differences across matched pairs. (3) Analyze outcome synergy (an interaction between risk and treatment location) inside each major clinical group (CHF, AMI, Pneumonia, General Surgery, Orthopedic Surgery, and Vascular Surgery). The intent is to determine whether subsets of patients inside each major clinical group have better outcomes at either teaching or non-teaching hospitals.
Understanding Multimorbidity through Multivariate Template Matching
Older adults with multimorbidity (MM) have greatly increased risk for death, complications, and readmissions after being admitted to the hospital for medical conditions or surgical procedures. This proposal proposes a better way to define MM, relying on large samples to identify the correct MM clusters that most influence outcomes, and applies novel techniques to produce vital information that will allow patients and hospitals to better identify those hospitals that are best and worst at caring for such patients.
The theory and outcome measure Failure-to-Rescue (FTR) was developed to assess hospital quality of care for surgical patients. FTR measures the ability ofOlder adults with multimorbidity (MM) have greatly increased risk for death, complications, and readmissions after being admitted to the hospital for medical conditions or surgical procedures. This proposal proposes a better way to define MM, relying on large samples to identify the correct MM clusters that most influence outcomes, and applies novel techniques to produce vital information that will allow patients and hospitals to better identify those hospitals that are best and worst at caring for such patients caregivers to manage a patient who becomes complicated and keep them from dying. This study seeks to extend FTR to the analysis of medical conditions.
Understanding Racial Disparities in Surgical Outcomes
Many studies have documented important racial disparities in surgical outcomes, but their etiologies are not clear. While we generally find better surgical outcomes (lower mortality) at teaching hospitals and a higher rate of minority patients at these hospitals, the survival benefit at teaching hospitals does not seem to equally apply to white and black patients. This study is exploring why we observe disparities in three common surgical specialties with respect to procedure time, a classic measure of surgical practice.
Improving the Framework for Health Care Public Reporting
Any effort to improve the science of public reporting must include an approach that ensures that guidance provided to the public is accurate, informative, relevant and understandable. Through the use of Bayesian models (a form of statistical modeling that is ideally suited to compare risks), this project aims to develop a better method to present information to the public about hospital quality, a better model for predicting and comparing outcomes across hospitals, and better methods to select and improve future models that may be used to aid the public in hospital selection.
Recently Completed Projects
AHRQ-CMS CHIPRA Pediatric Quality Measurement Center and Testing Laboratory
The AHRQ-CMS CHIPRA Laboratory at the Children’s Hospital of Philadelphia (CHOP) is one of seven Centers of Excellence (CoE) for the national Pediatric Quality Measures Program. This program was established by the Children’s Health Insurance Program Reauthorization Act to foster the development of evidence-based pediatric quality measures, which have lagged significantly behind adult quality measures. The CHOP CoE is currently focusing on studies related to continuity of insurance coverage, risk adjustment methodology in Medicaid and the Children’s Health Insurance Program, and patient reported outcomes.
Improving Process Measurement
This project seeks to improve process measurement by (1) testing whether unadjusted process measures are biased because patient factors are associated with process adherence; and (2) developing a new methodology, “Multivariate Template Matching,” for more efficiently selecting patient charts in which to follow and compare process adherence. If successful, results from this proposal could be utilized to implement template matching when assessing process compliance for Hospital Compare and other programs which study process as a quality of care indicator.
Describing and Understanding Racial Disparities
This project explores “Tapered Multivariate Matching,” a new theory and conceptual framework for examining racial disparities and quality of care. The aims of the study are to apply the tapered multivariate matching framework to breast and colorectal cancer using the national Medicare-SEER database to identify specific aspects of patient care that lead to quality differences by race and to demonstrate how tapered multivariate matching results can be conveyed in a clear and understandable report to policy analysts and the public.
Obesity and Surgical Outcomes
Obesity has been implicated in predisposing patients to worse surgical outcomes (death and complications). However, the etiology of these outcome differences is not well understood or well defined. Developing approaches to improving outcomes in this population is therefore challenging. The aim of this study was to examine, using an efficient design that incorporated a 3 state, 50-hospital Medicare augmented claims database and nested, detailed chart abstraction using a matched cohort design, the differences in outcomes and treatments between obese and normal weight patients who underwent general, orthopedic, vascular or urological surgery.
Development of a Risk Adjusted Aggregated Complication Measure
The study examined mortality, average lengths of hospitalization, length of stay outlier rates and ratings, readmission rates for any reason and for complication/infection and regionally adjusted average hospital charges. A method to aggregate across complications was developed in order to produce more stable measures of outcome.
Investigating the Relationship Between Measures of Hospital Occupancy and Length of Stay
Using detailed data on neonatal patients treated at Kaiser Permanente hospitals, this project obtained unbiased measures of the relationship between occupancy and length of stay by including information on daily staffing and severity of illness at discharge not available in most administrative datasets and using various methods to account for simultaneity including time-varying models, instrumental variables, and proxy measures for length of stay.
Improving Pediatric Severity Adjustment for Measuring Quality of Care
This project utilized the internal data generated by The Children's Hospital of Philadelphia and its satellite practices to develop a minimum, uniform pediatric research database.