Outcome Measures Framework: Information Model Report
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Authors
Richard E. Gliklich, M.D. (OM1)
Kristen Bibeau, Ph.D., M.S.P.H. (QuintilesIMS)
Floyd Eisenberg, M.D., M.P.H. (iParsimony LLC)
Jannette Hanna, M.B.A., P.M.P. (QuintilesIMS)
Michelle B. Leavy, M.P.H. (OM1)
Daniel Campion, M.B.A. (QuintilesIMS)
Jennifer B. Christian, Pharm.D., M.P.H., Ph.D., FISPE (QuintilesIMS)
Kristen Bibeau, Ph.D., M.S.P.H. (QuintilesIMS)
Floyd Eisenberg, M.D., M.P.H. (iParsimony LLC)
Jannette Hanna, M.B.A., P.M.P. (QuintilesIMS)
Michelle B. Leavy, M.P.H. (OM1)
Daniel Campion, M.B.A. (QuintilesIMS)
Jennifer B. Christian, Pharm.D., M.P.H., Ph.D., FISPE (QuintilesIMS)
Structured Abstract
Objectives. This report details the research undertaken to understand registries listed on clinicaltrials.gov, as well the burden required to record some of the most intricate, necessary data so that it is available to all other registries and viewers. The published Outcome Measures Framework (OMF) was used to evaluate the completeness of entries.
Data Sources. We searched the records for patient registries posted in the ClinicalTrials.gov database. For both the quantitative and qualitative studies, all records on ClinicalTrials.gov on June 23, 2015 that were defined as Patient Registries in the 'Study Type' field were downloaded for inclusion in the analyses.
Review Methods. A literature review, quantitative analysis, and qualitative analysis were undertaken to understand all facets of registration of patient registries. The report provides information on what fields within clinicaltrials.gov are populated most frequently, whether those fields were required or not, and explains how more complete data on the study population could be elicited and validated. It also describes how dominant definitions will be chosen as well as process measures such as treatments or procedures, and the associated outcome of the patients or participants involved.
A qualitative analysis on four condition areas was conducted to measure the degree to which outcome data, as entered in clinicaltrials.gov, mapped to the framework developed in the OMF. The conditions examined were depression, asthma, rheumatoid arthritis, and cardiac surgery. Two of these conditions, cardiac surgery and rheumatoid arthritis, were considered "deeper dives" and examined more in-depth detail on the level of data available in clinicaltrials.gov or other registry-run Web sites, as applicable.
Results. These research approaches were conducted with the intent to inform researchers on the development of an Internet-based database intended to house a fully functional system to clearly define, and eventually harmonize, outcome measures. This system has been termed the Outcome Measures Repository (OMR). The information model and governance structure is described in this report.
Conclusions. The intent of this report and the resulting OMR is to capture that data elements and sub-elements with the utmost attention to detail to ensure the optimal amount of information is captured while also avoiding undue burden on behalf of the registry steward responsible for entering the data into the OMR.
Suggested citation
Gliklich RE, Bibeau K, Eisenberg F, Hanna J, Leavy MB, Campion D, Christian JB. Registry of Patient Registries Outcome Measures Framework: Information Model Report. Methods Research Report. (Prepared by L&M Policy Research, LLC, under Contract No. 290-2014-00004-C.) AHRQ Publication No. 17(18)-EHC012-EF. Rockville, MD: Agency for Healthcare Research and Quality; February 2018. www.effectivehealthcare.ahrq.gov/reports/final/cfm. DOI: https://doi.org/10.23970/AHRQROPRMETHODS.
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