Final Research Report

View this project's final research report.

Peer-Review Summary

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 lauded the researchers’ work to better predict patient diagnoses and other traits to account for missing information in the electronic health record. The reviewers asked that the researchers provide more information about the reasoning behind the Bayesian approaches developed in this study. The researchers responded by adding results of several comparable methods to their report to demonstrate the superiority of the Bayesian methods.
  • The reviewers asked how useful this work would be for clinical research. The researchers responded that the results of this study and their use of simulation studies like the work completed in this research have the potential to be very useful for clinical research. However, their approach must first be compared to a gold standard, even though they also note that one does not currently exist.

Conflict of Interest Disclosures

Project Information

Rebecca Hubbard, PhD
University of Pennsylvania
$1,059,240
10.25302/03.2021.ME.151132666
Statistical Methods for Phenotype Estimation and Analysis Using Electronic Health Records

Key Dates

July 2016
July 2021
2016
2021

Study Registration Information

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Last updated: March 4, 2022