Download PCORI Methodology Standards: Academic Curriculum

PCORI Methodology Standards:
Academic Curriculum
© 2016 Patient-Centered Outcomes Research Institute. All Rights Reserved.
Module 8: Using Existing Registries
Category 6: Data Registries
Prepared and presented by Alison Klein, PhD, MHS
Considerations When Selecting an Existing Registry for a
Patient-Centered Outcomes Research (PCOR) Question
 Study purpose:
 Were the objectives/hypotheses predefined or post hoc?
 Study design:
 What is the appropriate study design to address my research question using the
registry data?
 Patient population:
 Who was studied?
 Data quality:
 How were the data collected, reviewed, and verified?
 Data completeness:
 How were missing data handled?
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How Do the Goals of the Registry Synergize With the Research Question?
 Registry goals range from simple, testable hypotheses to primarily descriptive (not all
registries have specific, testable, or simple hypotheses)
 Does your research question clearly match with the design of the registry?
• For example, examining effectiveness of screening in a familial colon cancer
registry
 Is your research developed ancillary to the registry goals?
• For example, strategies to overcome disparities in access to screening
 Although patient registries can be established with a very specific research question of
interest, often they are established to meet a very broad area of research
 If registry is transparent in its methods, this can allow for potential users of the
registry to determine if their specific research question can be addressed
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Cohort Studies Within a Registry Framework
 Cohort:
 A study in which a group of individuals, typically with a common characteristic, are
followed longitudinally and the occurrence of health-related events is ascertained
 Example:
• Cystic Fibrosis registry
 Impact of household income on death
 Causes of death among patients with cystic fibrosis
• Melanoma Family Registry
 Risk of pancreatic cancer among families with CDKN2A variants
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Case–Control Studies Within a Registry Framework
 Case–control study:
 Individuals with and without a given disease or condition are identified at a given
point of time from a population
 Example:
• Cancer registries
 Predictors of intensive care unit admissions
 Characteristics of long-term survivors
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Registry Patient
Population:
Determination of
Whether the
Study Population
Meets the Goals
of the Research
Question
Target population
The population to which the study findings are meant to apply
Accessible population
Subset of the target population who are specifically defined and available for study
Intended population
Members of the accessible population who are sampled according to the registry design
Actual population
People who actually participate in registry
Adapted from: Gliklich, R., Dreyer, N., Leavy, M., eds.
(2014). Registries for Evaluating Patient Outcomes: A
User’s Guide. Third edition. AHRQ Publication No.
13(14)-EHC111. Rockville, MD: Agency for Healthcare
Research and Quality. Figure 13. Available at:
http://www.effectivehealthcare.ahrq.gov/ehc/produc
ts/420/1897/registries-guide-3rd-edition-vol-1140430.pdf. Accessed September 10, 2015.
Analytic population
People who meet the criteria for analysis
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Data Quality: How Were the Data Collected, Reviewed, and Verified?
 Evaluation of the study protocol
 Does the protocol allow you to address your research question of interest?
 Is the data collection appropriate for your research question?
 Will the data collection methods limit your study questions or conclusion?
 Access to the data dictionary needed
 Were valid instruments used?
 How were data coded?
 Evaluate data assurance processes
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Data Completeness
 What was the response rate?
 Were there differential responses by key study parameters that could introduce
selection biases?
 Was the data capture complete?
 What are missing rates of key variables of interest?
 What was follow-up rate?
 How were losses to follow-up tracked?
 What steps were taken to minimize losses to follow-up?
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Data Analysis
 Observational study methods
 Missing data
 Control for confounding by observed covariates
• Matching, restriction, stratification, standardization
 Regression analysis
 Causal inference
 Propensity score
 Instrumental variables
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Summary
 Registry can allow for great flexibility in research questions
 Variety of study designs can be implemented
 Efficient for rare disease or rare exposures
 Careful consideration is necessary to determine whether registry data are compatible
with the research question
 Are data of high enough quality to address research question?
 Are biases and limitations present in data?
• Are these concerns great enough to suggest the study is not appropriate?
 Analytical methods and challenges common to observational studies apply
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