Evaluating Quality of Clinical Data for Use in Healthcare Research

The presentation will offer a detailed case study of recent efforts at HealthCore, a healthcare research company, to evaluate the usefulness of clinical data, with lessons learned about:

Planning data quality assessment in stages
Prioritizing investigations based on research needs
Identifying assumptions and confirming them
Exposing potential bias in the record
Evaluating changes in the data over time
Surfacing data gaps and nuances that would affect research
Communicating and tracking potential issues with stakeholders

The HealthCore scientists who study the "real world" safety and effectiveness of drugs, medical devices and care management interventions are increasingly looking to use electronic medical records and other clinical datasets to answer important research questions. But each new clinical dataset that might be usable for research comes with a new set of unknowns to be explored and understood. This case study will describe an approach for addressing the list of unknowns in order to make researchable data available at the pace of research.

Christiana Boehmer, MS, CDMP has over 20 years of experience in senior IT roles with responsibilities for data modeling, data integration, data quality, and analytics. She is currently Sr. Technical Data Analyst for Arcadia Healthcare Solutions in Burlington, MA. She previously was team lead for data quality investigations at HealthCore, a healthcare research organization. In that role, Chris led a team of research stakeholders to articulate the critical data quality criteria relevant to research usage of clinical data, and used that roadmap to drive data quality assessments. She is a Certified Data Management Professional (CDMP) at the mastery level with specialty in data and information quality.