TY - JOUR
T1 - Electronic medical record integration with a database for adult congenital heart disease
T2 - Early experience and progress in automating multicenter data collection
AU - Broberg, Craig S.
AU - Mitchell, Julie
AU - Rehel, Silven
AU - Grant, Andrew
AU - Gianola, Ann
AU - Beninato, Peter
AU - Winter, Christiane
AU - Verstappen, Amy
AU - Valente, Anne Marie
AU - Weiss, Joseph
AU - Zaidi, Ali
AU - Earing, Michael G.
AU - Cook, Stephen
AU - Daniels, Curt
AU - Webb, Gary
AU - Khairy, Paul
AU - Marelli, Ariane
AU - Gurvitz, Michelle Z.
AU - Sahn, David J.
N1 - Publisher Copyright:
© 2015 Elsevier Ireland Ltd. All rights reserved.
PY - 2015/7/23
Y1 - 2015/7/23
N2 - Background The adoption of electronic health records (EHR) has created an opportunity for multicenter data collection, yet the feasibility and reliability of this methodology is unknown. The aim of this study was to integrate EHR data into a homogeneous central repository specifically addressing the field of adult congenital heart disease (ACHD). Methods Target data variables were proposed and prioritized by consensus of investigators at five target ACHD programs. Database analysts determined which variables were available within their institutions' EHR and stratified their accessibility, and results were compared between centers. Data for patients seen in a single calendar year were extracted to a uniform database and subsequently consolidated. Results From 415 proposed target variables, only 28 were available in discrete formats at all centers. For variables of highest priority, 16/28 (57%) were available at all four sites, but only 11% for those of high priority. Integration was neither simple nor straightforward. Coding schemes in use for congenital heart diagnoses varied and would require additional user input for accurate mapping. There was considerable variability in procedure reporting formats and medication schemes, often with center-specific modifications. Despite the challenges, the final acquisition included limited data on 2161 patients, and allowed for population analysis of race/ethnicity, defect complexity, and body morphometrics. Conclusion Large-scale multicenter automated data acquisition from EHRs is feasible yet challenging. Obstacles stem from variability in data formats, coding schemes, and adoption of non-standard lists within each EHR. The success of large-scale multicenter ACHD research will require institution-specific data integration efforts.
AB - Background The adoption of electronic health records (EHR) has created an opportunity for multicenter data collection, yet the feasibility and reliability of this methodology is unknown. The aim of this study was to integrate EHR data into a homogeneous central repository specifically addressing the field of adult congenital heart disease (ACHD). Methods Target data variables were proposed and prioritized by consensus of investigators at five target ACHD programs. Database analysts determined which variables were available within their institutions' EHR and stratified their accessibility, and results were compared between centers. Data for patients seen in a single calendar year were extracted to a uniform database and subsequently consolidated. Results From 415 proposed target variables, only 28 were available in discrete formats at all centers. For variables of highest priority, 16/28 (57%) were available at all four sites, but only 11% for those of high priority. Integration was neither simple nor straightforward. Coding schemes in use for congenital heart diagnoses varied and would require additional user input for accurate mapping. There was considerable variability in procedure reporting formats and medication schemes, often with center-specific modifications. Despite the challenges, the final acquisition included limited data on 2161 patients, and allowed for population analysis of race/ethnicity, defect complexity, and body morphometrics. Conclusion Large-scale multicenter automated data acquisition from EHRs is feasible yet challenging. Obstacles stem from variability in data formats, coding schemes, and adoption of non-standard lists within each EHR. The success of large-scale multicenter ACHD research will require institution-specific data integration efforts.
KW - Congenital heart disease
KW - Electronic health records
KW - Healthcare information systems
KW - Multicenter data collection
UR - http://www.scopus.com/inward/record.url?scp=84937418300&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84937418300&partnerID=8YFLogxK
U2 - 10.1016/j.ijcard.2015.05.140
DO - 10.1016/j.ijcard.2015.05.140
M3 - Article
C2 - 26142077
AN - SCOPUS:84937418300
SN - 0167-5273
VL - 196
SP - 178
EP - 182
JO - International Journal of Cardiology
JF - International Journal of Cardiology
ER -