Data Quality

Building PCOR Value and Integrity with Data Quality and Transparency Standards

BACKGROUND

EDM Forum previously supported initial conversations with a Data Quality Collaborative (DQC) project that focused on developing recommendations for standardized data quality assessment reporting. Results of that collaborative are under review for publications in eGEMs. The DQC work has now been expanded through a Patient-Centered Outcomes Research Institute (PCORI) funded project (Contract #ME-1303-5581). EDM Forum is providing continued support for this project.

The major aim of this project is to develop a comprehensive data quality assessment framework and guidelines for the CER community, including a framework to guide the development of new analytic and reporting methods specifically directed to data quality assessment and reporting for CER studies. This framework is necessary as data from clinical and patient-centered systems, research data warehouses, and large scale data networks begin to become established sources of observational data. It becomes more critical that consistent methods for assessing and reporting data quality are developed and adopted so that users of data and consumers of results understand the potential impact of data quality on study results.

This project seeks to develop a comprehensive data quality assessment and reporting framework that enables clinical investigators, patients, and policy makers to understand the strengths, weaknesses and limitations of observational data used to generate new clinical knowledge. While applicable to prospective data collection, our main focus is to develop methods for evaluating the quality of data that is not collected and maintained for the primary purpose of a specific research study.

REQUEST FOR INPUT (Deadline: Friday, August 15, 2014)

There are two requests for input. One is to provide comments on the draft data quality methods framework document that appears below and the second is a brief anonymous survey to collect your ideas about data quality assessment needs:

  1. We request feedback from the community on the draft data quality methods framework below. Comments are requested on:
    • General reactions to the framework;
    • Clarity of Section 1. Purpose and Section 2. Context and Scope;
    • Clarity of definitions of each data quality category (see Table 1);
    • Clarity of distinction of each data quality category (meaning, are the definitions of the categories clear enough that they are distinct from other categories?); and
    • Suggestions for other topics and issues that should be addressed specific to reporting on data quality issues.
  2. We request you provide additional input by completing a brief anonymous survey about data quality needs. Click here to complete the survey.

Please submit your comments and complete the survey by Friday, August 15, 2014. Again, please comment on specific sections of the paper where possible. As with a manuscript review, we ask that you refer to specific page and line numbers where relevant.

Please use the window below to view the paper. Alternatively, you can download a PDF of the manuscript here.