Featured Research

AHRQ-CMS CHIPRA Pediatric Quality Measurement Center and Testing Laboratory

Funded by the Agency for Healthcare Research and Quality and the Centers for Medicare and Medicaid Services
Principal Investigator: Jeffrey H. Silber, MD, PhD
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.  CHOP has formed an organizational architecture for a new CoE that builds on a strong, existing infrastructure already in place including investigators with breadth and depth in leadership and methodological expertise in quality and outcome assessment, unique data resources, and strategic partnerships. The CoE will include five methodological cores: (1) Quality Informatics-using the tools of informatics to adapt quality metrics to the electronic health record (EHR); (2)Multivariate Matching Laboratory--The lab will provide a unique analytic strength that will augment traditional analytic approaches to create scientifically rigorous pediatric risk adjustment models, produce better assessment of health and healthcare disparities, and improve validation of new quality measures; (3) Hospital Metrics-development of measures that focus on inpatient quality; (4) Medical Home-measurement of the performance of the medical home and community services that connect to it; and, (5) Health Plans-a special emphasis on measurement of plan enrollment duration and stability.
 

Impact of Obstetric Unit Closures on Pregancy Outcomes

Funded by the Agency for Healthcare Research and Quality
Principal Investigator: Scott A. Lorch, MD, MSCE
With over 4 million infants delivering in the United States every year, the provision of obstetric care is a critical part of the health care system of any locality. However, the reduction of obstetric services, especially through the closure of obstetric units, is a common occurrence. As with studies of hospital closures, the impact of obstetric unit closures on the health of the surrounding population is not well described.  Previous research investigated the case of Philadelphia, which experienced a 40% reduction in obstetric beds between 1997 and 2005. Compared to a pre-closure period of 1995-1996, it was found that these closures were associated with in an initial increase in neonatal mortality, a decline in the number of deliveries via Cesarean section, and a persistent increase in neonatal and maternal delivery complications. Although this single urban area experienced adverse effects from the closure of multiple obstetric units, it is not known whether similar results are possible in markets that experience the loss of fewer obstetric units; what the differential effects of an obstetric closure experienced by women in the same urban market; and how changes in the provision of obstetric care by the remaining obstetric units could modify these results.  Improved understanding of the impact of such service reductions in the obstetric market will result in more efficient use of health care services and optimize the value of health care dollars spent on obstetric care. 
 

Improving the Framework for Health Care Public Reporting

Funded by the Agency for Healthcare Research and Quality
Principal Investigator: Jeffrey H. Silber, MD, PhD
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.  Previous work has demonstrated that the Hospital Compare random effects mortality model provides predictions that may be misleading when evaluating small hospitals. This project aims to develop a more realistic approach to modeling hospital outcomes that is both more accurate (less misleading) than Hospital Compare, and more informative from the perspective of the individual patient seeking guidance on which hospital to choose for care. Furthermore, in order for the public to benefit, not only do the models need improvement, but the public will need to increase their use of these models. To accomplish this latter goal, this project will address barriers to the general use of these reports.  This project will develop models that are personalized to specific patient characteristics (making them more relevant for the individual patient), and, by making use of the Bayesian framework, will introduce new methods for presenting results that adapt to common mistakes surrounding the interpretation of probabilities. Thus, patient error in the interpretation of results will be both less likely to occur and less likely to lead to mistaken hospital selection.  Finally, as models will inevitably change and improve, this project also aims to develop a framework for future model comparisons, in order to assess whether new models should be adopted.     
 

Parental Trust and Racial Disparities in the Care of Discharged Premature Infants

Funded by the National Institute of Child Health and Human Development
Principal Investigator: Scott A. Lorch, MD, MSCE
Racial disparities continue to be a major impediment to the delivery of high quality health care to all patients.  This study is examining various underlying explanations for such disparities in the outcomes of care provided to premature infants in the first two years after discharge from the neonatal intensive care unit. By understanding these underlying explanations for the racial disparities in these outcomes, particularly families’ trust in the health care system, we can aid in the development of interventions to reduce these differences in care. 
 
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