Outcomes Research

Center for Perioperative Outcomes Research

The Center for Perioperative Outcomes Research (CPOR) focuses on the use of innovative data sources and analytical tools to advance the science of perioperative clinical care. The use of large observational data sets provides valuable insight into the risk and benefit of classical treatment regimens in perioperative medicine, such as beta blockade in non-cardiac surgery and aprotinin in cardiac surgery. By combining administrative, clinical and registry data, outcomes research using observational data sets is complementary to traditional small, randomized controlled trials. 

The CPOR is composed of clinical researchers, statistical analysis experts, database architects and administrative support staff. We have created an infrastructure to enable a broad array of clinicians and non-clinician scientists to conduct outcomes research. In addition, CPOR is acquiring and developing large observational data sets that enable outcomes research without repetitive data cleaning. We are also member to the Multicenter Perioperative Outcomes Group (MPOG).

CPOR has developed an educational curriculum that cultivates future outcomes research faculty. The traditional medical school and residency research training curriculum does not provide the basic information to consume or produce outcomes research using large observational data sets. As a result, CPOR provides a foundation of knowledge to help investigators with the basics of observational data set research, including:

1. The advantages and disadvantages of various national observational data sets, including:

• National Surgical Quality Improvement Program
• Nationwide Inpatient Sample
• National Hospital Discharge Survey
• Social Security Death Master File
• Medicare Identifiable, Limited Data Set, and De-identified Data Set

2. Data quality in specific hospital clinical information systems, including:

• Anesthesia Information System
• Critical Care Nursing Record
• Pharmacy
• Blood bank
• Radiology

3. Types of research questions that can be addressed using observational data sets

4. Basic statistical technique training (for non-statisticians)

5. Responsible reporting and manuscript preparation

Finally, we build relationships with external quality improvement, outcomes research, epidemiology and statistical analysis organizations.

CPOR Lecture Series

• Lecture one: Outcomes Research Overview
• Lecture two: Data Sources Available for Observational Research
• Lecture three: How to Design an Answerable Question
• Lecture four: Basic Statistics for Non-Statisticians - Descriptive and Univariate Techniques
• Lecture five: Evaluation and Development of a Testable Research Hypothesis
• Lecture six: Privacy, Security, IRB and Access
• Lecture seven: More Basic Statistics for Non-Statisticians - Multivariate Techniques
• Lecture eight: Writing an Observational Manuscript