- •Foreword
- •Contents
- •Contributor Current and Past Positions: Association for Academic Surgery
- •Contributors
- •Academic Surgeons as Bridge-Tenders
- •Types of Surgical Research
- •Going Forward
- •Selected Readings
- •Introduction
- •Preparation Phase
- •Assistant Professor
- •Job Search
- •The First Three Years
- •Career Development Awards (CDAs)
- •Contemplating a Mid-Career Move?
- •Approaching Promotion
- •Associate Professor and Transition to Full Professor
- •Conclusion
- •Selected Readings
- •Introduction
- •Reviewing the Literature
- •Developing a Hypothesis
- •Study Design
- •Selected Readings
- •Introduction
- •The Dual Loyalties of the Surgeon-Scientist
- •Human Subjects Research
- •Informed Consent
- •Surgical Innovation and Surgical Research
- •Conflict of Interest
- •Publication and Authorship
- •Conclusion
- •References
- •Sources of Error in Medical Research
- •Study Design
- •Inferential Statistics
- •Types of Variables
- •Measures of Central Tendency and Spread
- •Measures of Spread
- •Comparison of Numeric Variables
- •Comparison of Categorical Values
- •Outcomes/Health Services Research
- •Steps in Outcomes Research
- •The Basics of Advanced Statistical Analysis
- •Multivariate Analysis
- •Time-to-Event Analysis
- •Advanced Methods for Controlling for Selection Bias
- •Propensity Score Analysis
- •Instrumental Variable (IV) Analysis
- •Summary
- •Selected Readings
- •Transgenic Models
- •Xenograft Models
- •Noncancer Models
- •Alternative Vertebrate Models
- •Selected Readings
- •Overview
- •Intellectual Disciplines and Research Tools
- •Comparative Effectiveness Research
- •Patient-Centered Outcomes Research
- •Data Synthesis
- •Overview
- •Intellectual Disciplines and Research Tools
- •Disparities
- •Quality Measurement
- •Implementation Science
- •Patient Safety
- •Optimizing the Health Care Delivery System
- •Overview
- •Intellectual Disciplines and Research Tools
- •Policy Evaluation
- •Surgical Workforce
- •Conclusion
- •References
- •Introduction
- •What Is Evidence-Based Medicine?
- •Evidence-Based Educational Research
- •Forums for Surgical Education Research
- •Conducting Surgical Education Research
- •Developing Good Research Questions
- •Beginning the Study Design Process
- •Developing a Research Team
- •Pilot Testing
- •Demonstrating Reliability and Validity
- •Developing a Study Design
- •Data Collection and Analysis
- •Surveys
- •Ethics
- •Funding
- •Conclusions
- •Selected Readings
- •Genomics
- •Gene-Expression Profiling
- •Proteomics
- •Metabolomics
- •Conclusions
- •References
- •Selected Readings
- •Introduction
- •Why Write
- •Getting Started
- •Where and When to Write
- •Choosing the Journal
- •Instructions to Authors
- •Writing
- •Manuscript Writing Order
- •Figures and Tables
- •Methods
- •Results
- •Figure Legends
- •Introduction
- •Discussion
- •Acknowledgments
- •Abstract
- •Title
- •Authorship
- •Revising Before Submission
- •Responding to Reviewer Comments
- •References
- •Selected Readings
- •Introduction
- •Origins of the Term
- •Modern Definition and Primer
- •Transition from Mentee to Colleague
- •Mentoring Risks
- •Conclusion
- •References
- •Selected Readings
- •The Career Development Plan
- •Choosing the Mentor
- •Writing the Career Development Plan
- •The Candidate
- •Research Plan
- •Final Finishing Points About the Research Plan
- •Summary
- •References
- •Introduction
- •Decisions, Decisions!
- •Mission Impossible: Defining a Laboratory Mission or Vision
- •Project Planning
- •Saving Money
- •Seek Help
- •People
- •Who Should I Hire?
- •Advertising
- •References
- •Interviews
- •Conduct a Structured Interview
- •Probation Period
- •Trainees
- •Trainee Funding
- •Time Is on Your Mind
- •Research Techniques
- •Program Leadership
- •Summary
- •Selected Readings
- •Introduction
- •Direct Evidence
- •Indirect Evidence
- •Burnout
- •Prevention of and Recovery from Work–Life Imbalance
- •Action Plan for Finding Balance: Personal Level
- •Action Plan for Finding Balance: Professional Level
- •Conclusion
- •References
- •Introduction
- •Time Management Strategies
- •Planning and Prioritizing
- •Delegating and Saying “No”
- •Action Plans
- •Activity Logs
- •Scheduling Protected Time
- •Eliminating Distractions
- •Buffer Time
- •Goal Setting
- •Completing Large Tasks
- •Maximizing Efficiency
- •Get Organized
- •Multitasking
- •Think Positive
- •Summary
- •References
- •Selected Readings
- •Index
72 T.S. Riall
are used to compare proportions for categorical or ordinal values with two or more independent groups. In the case of more than two groups, the resulting P-value indicates an overall difference between the groups but does not provide pairwise comparisons. When expected cell frequencies are less than five, Fisher exact tests should be used. For matched samples, the McNemar test is used for two variables and the Cochran Q test for three or more.
Outcomes/Health Services Research
Health services or outcomes research often involves second- ary data analysis of large administrative datasets that were not initially collected for research purposes.These datasets include Medicare data, Surveillance, Epidemiology, and End Results (SEER) tumor registry data, hospital discharge data, tumor registries,the National Cancer Data Bank,and the Nationwide Inpatient Sample. The use of such data is complex and poses many analytical difficulties. It is absolutely critical to under- stand if the particular dataset can actually answer your ques- tion.For example,you might want to use SEER tumor registry data to evaluate several published algorithms for predicting additional axillary node positivity in patients with a positive sentinel lymph node biopsy. You need to carefully look through the documentation. SEER collected information on sentinel lymph node biopsy after 2002. However, they give only the final nodal status of the axilla, and you are unable to separate the status of the sentinel nodes from the status of the remainder of the axilla, so you cannot do the study.
In addition, the coding in administrative datasets changes over time. For example, new diagnosis and procedure codes are added and staging schemes are altered, and it is easy to make errors. Therefore, you must thoroughly understand the dataset. I recommend working with someone who has used the dataset before. Download all the relevant coding manuals and information from associated websites and be sure you understand changes in coding schemes over time. Finally, the
Chapter 5. Analyzing Your Data |
73 |
manipulation of these datasets requires significant expertise in data management and should not be performed without the help of an experienced data manager/biostatistician.
Administrative data are observational. As such, they are susceptible to significant confounding and selection bias.This often requires advanced statistical techniques to decrease the inherent selection bias, and there may be situations in which we cannot overcome this bias at all. For example, in a 2008 study by Giordano et al.(see selected references),the authors used SEER data to compare outcomes in 43,847 men receiv- ing or not receiving active treatment for lowand intermedi- ate-risk prostate cancer. A previous study using SEER data showed that active treatment was associated with improved survival.This study showed that the observed association was likely the result of selection bias by evaluating cancer mortal- ity and non-cancer mortality in the two groups. Patients who received active treatment also had significantly lower noncancer mortality,suggesting significant selection bias in which patients receive therapy and which do not.
Steps in Outcomes Research
There are generally six steps in developing an outcomes research project. You must identify a researchable question, develop a conceptual model, identify the primary outcome (and secondary outcomes if desired), identify critical inde- pendent variables (predictors and potential confounders), identify appropriate measures of each variable, and develop an analysis plan.
For example, we wanted to use Medicare claims data to evaluate current cholecystectomy rates in Medicare benefi- ciaries presenting with gallstone pancreatitis. We wanted to evaluate factors that predicted cholecystectomy on initial hospitalization. We then wanted to look at gallstone-related readmission rates in patients who did or did not undergo cholecystectomy.We developed the conceptual model shown in Fig. 5.3. We hypothesized that admitting service, hospital