DOI: 10.3886/icpsr39476
title: Improving the Use of Patient Registries for Comparative Effectiveness [Methods Study], Boston, Massachusetts, 2013-2018
title: Archival Version

description: Researchers can use data from patient registries to look at which medicines or other treatments work best. Registries store data about people with a specific health problem. The data may include the health care and medicines patients receive over time and patient reports of their health status.
To find out patients' health status, registries ask patients to fill out surveys at different times during treatment. Researchers can compare survey results from when patients first take the survey with results from surveys taken after treatment. They can then find out how well a medicine works. But patients may not always take the first survey before they start a new medicine. Sometimes, they don't take the first survey until after starting treatment. When this happens, it is hard to know how well the medicine works.
In this study, the research team looked at different ways to use data from patient surveys in registries. The team wanted to learn which way would give the most accurate understanding of the effects of a new medicine. The study also looked at patients' views on taking part in registries.
description: To determine the least-biased methods for estimating sparsely measured PROs in registry analyses. The study aims were the following: 

To identify and test the best methods for incorporating potential confounders of patient-reported outcomes that researchers did not measure at the same time as treatment initiation into the analysis of clinical registry data; 
To assess patient preferences regarding clinical registry participation
description: This simulation study compared the ability of computational methods to incorporate patient-reported outcomes as confounders into the analysis of comparative drug safety research. The research team then applied these adjustment methods to rheumatoid arthritis (RA) patient registry data to validate results. The simulation study compared 13 confounder adjustment methods to model the total comparative effect of drug treatments on risk ratios for infection. The adjustment methods included, for example, using the most recent measurement prior to treatment initiation and using the arithmetic mean of the two nearest measurements. Simulation scenarios assumed a 5,000-patient sample, used different distributions of patient global assessment scores, and employed varying time intervals between patient global assessment measurement and treatment initiation.
The team empirically validated the tested confounder adjustment methods using data from 294 eligible patients with RA who began treatment with a tumor necrosis factor-alpha inhibitor or other medicine. Researchers assessed comparative safety based on infection risk following treatment.
To obtain patient preferences for participating in registry research, the research team conducted focus groups and administered surveys to 150 patients with RA and 169 patients with inflammatory bowel disease (IBD). In each survey group, 95% of respondents were non-Hispanic white. The mean age was 62 for the RA respondents and 43 for the IBD respondents, and 83% of RA respondents and 62% of IBD respondents were women.
Patients, clinicians, and patient registry researchers helped develop focus group questions and study design elements.
description: Datasets: 
DS1: Improving the Use of Patient Registries for Comparative Effectiveness [Methods Study], Boston, Massachusetts, 2013-2018
description: Rheumatoid Arthritis patients and Bowel Disease patients from Brigham and Women's hospital.