
ISPOR PATIENT REGISTRY SPECIAL INTEREST GROUP (PR) |
| Patient Registry Analysis Working Group |
Co-Chairs: Maria Malmenäs MSc, Manager Biostatistics, Outcome Surveys, Global Medical Affairs, Shire Human Genetic Therapies, Danderyd, Sweden
Mike Novotny MBA, MA, CEO, Medrio, San Francisco, CA, USA |
Members: Lusine Abrahamyan MD, MPH, PhD(c); Nancy Dreyer PhD, MPH; Claudio Faria PharmD, MPH; Rebecca Gruhlkey MBA; Margaret Hux MSc; Nandan Kenkeremath JD, BS; Isabelle Morin MSc; Peggy Schrammel; Steven Takemoto PhD; Michelle Prichard Turner MS, BS; Jaro Wex PhD, MD, BA |
| Goal: to establish good research practices on the analysis and interpretation of patient registry data to meet the registry sponsor’s desired goal(s), domestically and internationally. |
| 14th Annual International Meeting Presentation |
Background:
Observational registries of specific patient groups offer an attractive opportunity to evaluate real-world effectiveness and cost-effectiveness of treatments. Good research practices for data analysis and interpretation will increase our ability to conduct comparative research within patient registries. Background continued…
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I. Good Research Practices for Cost-effectiveness Analysis of Patient Registry Data
(Chair: Marg Hux)
Provide practical recommendations on suitable statistical approaches to registry data with a focus on estimating the cost-effectiveness of treatment methods. These recommendations will focus on how to present value for money to support purchase and use of a product compared to treatment alternatives that would be used for patients in real world practice. The effectiveness will be described in terms of clinical benefit of importance to patients. For example, rather than laboratory results, measures of importance can include such methods as events of illness averted, clinical remission. Value clinical benefit will include different health effects using quality adjusted life years (QALY).
II. Good Research Practices for Analysis of Effectiveness in Registry Data
(Chair: Maria Malmenäs)
Provide recommendations on suitable statistical approaches to registry data with a particular focus on estimating the effectiveness of treatment methods. This task force will focus on statistical methods for controlling bias due to lack of randomization to treatment, including (1) covariate adjustments, (2) matching, and (3) propensity scoring, while noting several other methods available. The importance of correct handling of missing data will be emphasized and several imputation techniques discussed.
III. Good Research Practices for Reporting Results from Registry Data for Publications
(Chair: Lusine Abrahamyan)
Develop a plan for reporting results from registry data for publications and evaluate the STROBE guideline for its appropriateness for patient registries. This project team will develop a checklist for best practices on reporting results from registry data and a point by point list analyzing the STROBE guideline for relevance to registries. |
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