Preparing Electronic Health Records Data for Comparative Effectiveness Studies

2012 ◽  
Author(s):  
Michael G. Kahn ◽  
Lisa M. Schilling ◽  
Bethany M. Kwan ◽  
Aidan Bunting ◽  
Chris Uhrich ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Comparative Effectiveness ◽  
Health Records ◽  
Electronic Health ◽  
Effectiveness Studies

Importance of Health Information Technology, Electronic Health Records, and Continuously Aggregating Data to Comparative Effectiveness Research and Learning Health Care

2012 ◽  
Vol 30 (34) ◽  
pp. 4243-4248 ◽  
Author(s):  
Benjamin J. Miriovsky ◽  
Lawrence N. Shulman ◽  
Amy P. Abernethy
Keyword(s):  
Electronic Health Records ◽  
Real Time ◽  
Comparative Effectiveness Research ◽  
Comparative Effectiveness ◽  
Clinical Care ◽  
Administrative Databases ◽  
Effectiveness Research ◽  
Health Records ◽  
Patient Level ◽  
Electronic Health

Rapidly accumulating clinical information can support cancer care and discovery. Future success depends on information management, access, use, and reuse. Electronic health records (EHRs) are highlighted as a critical component of evidence development and implementation, but to fully harness the potential of EHRs, they need to be more than electronic renderings of the traditional paper medical chart. Clinical informatics and structured accessible secure data captured through EHR systems provide mechanisms through which EHRs can facilitate comparative effectiveness research (CER). Use of large linked administrative databases to answer comparative questions is an early version of informatics-enabled CER familiar to oncologists. An updated version of informatics-enabled CER relies on EHR-derived structured data linked with supplemental information to provide patient-level information that can be aggregated and analyzed to support hypothesis generation, comparative assessment, and personalized care. As implementation of EHRs continues to expand, electronic databases containing information collected via EHRs will continuously aggregate; aggregating data enhanced with real-time analytics can provide point-of-care evidence to oncologists, tailored to patient-level characteristics. The system learns when clinical care informs research, and insights derived from research are reinvested in care. Challenges must be overcome, including interoperability, standardization, access, and development of real-time analytics.

Sign in / Sign up

Export Citation Format

Share Document