Final Research Report
View this project's final research report.
Results of This Project
Related Journal Citations
Peer review of PCORI-funded research helps make sure the report presents complete, balanced, and useful information about the research. It also assesses how the project addressed PCORI’s Methodology Standards. During peer review, experts read a draft report of the research and provide comments about the report. These experts may include a scientist focused on the research topic, a specialist in research methods, a patient or caregiver, and a healthcare professional. These reviewers cannot have conflicts of interest with the study.
The peer reviewers point out where the draft report may need revision. For example, they may suggest ways to improve descriptions of the conduct of the study or to clarify the connection between results and conclusions. Sometimes, awardees revise their draft reports twice or more to address all of the reviewers’ comments.
Peer reviewers commented and the researchers made changes or provided responses. Those comments and responses included the following:
- The reviewers commented that the simulation study is not representative of many electronic medical record (EMR) studies because of the low number of cases and co-occurring variables. They asked that this be noted as a limitation of the study. The researchers explained that they designed their simulation to meet several statistical goals and that most of their simulations came from existing literature. The researchers agreed that their simulation was relatively small in its number of observations and covariates, given the usual scale of comparative effectiveness research (CER) with EMRs. The researchers explained that they did not use larger simulated data sets because of limited time and the small size of their juvenile idiopathic arthritis CER study. However, the researchers noted their GPMatch method ranked second in a comparison of 19 causal inference methods. This comparison used many more cases and covariates than they used in the current project. The researchers felt that this demonstrated the strong performance of GPMatch, even with a larger dataset with more covariates.
- The reviewers asked if the concept of adaptive treatment strategies described in the report was the same as the concept of a dynamic treatment regime. The reviewers asked for clarification on terms and goals. The researchers said the dynamic treatment regime approach tends to focus on trying to find an optimal set of decision rules that leads to a desired final outcome using reinforcement learning, but the approach does not fit well with research that is interested in optimizing results at intermediate time points. The researchers explained they used the term adaptive treatment strategies to distinguish the approach in GPMatch from methods that rely on reinforcement learning, but acknowledged that adaptive treatment strategies and dynamic treatment regime are often used interchangeably in the literature.
Conflict of Interest Disclosures
- Has Results