TY - GEN
T1 - Medical concept intersection between outside medical records and consultant notes
T2 - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
AU - Moon, Sungrim
AU - Liu, Sijia
AU - Kingsbury, Paul
AU - Chen, David
AU - Wang, Yanshan
AU - Shen, Feichen
AU - Chaudhry, Rajeev
AU - Liu, Hongfang
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/15
Y1 - 2017/12/15
N2 - One of the promises of "meaningful use" of Electronic Health Records (EHRs) is to facilitate digital information exchange between healthcare providers through continuity of care documents. Despite such promise, outside medical records (OMRs) of referral patients including clinical notes, lab test results or diagnostic test reports are frequently provided through fax or print out. Moreover, it is not clear how much information in those OMRs is utilized when providing care at the early stage. In this study, we collected clinical concepts automatically from OMRs through optical character recognition (OCR) technology and then performed a quantitative analysis of concepts presented in OMRs and concepts captured in clinical notes at Mayo Clinic. We also investigated information from OMRs not captured in initial consultant notes but presented over subsequent consultant notes. We identified 12.93% of concepts from OMRs were identified in clinical documents within three months. Among those overlapping concepts, 26.74% of them were not captured in initial consultant notes. Our study presents that clinical information from OMRs is important for patient care. Also, the delayed presence of information in clinical notes may indicate important information from OMRs is not fully utilized earlier in the care.
AB - One of the promises of "meaningful use" of Electronic Health Records (EHRs) is to facilitate digital information exchange between healthcare providers through continuity of care documents. Despite such promise, outside medical records (OMRs) of referral patients including clinical notes, lab test results or diagnostic test reports are frequently provided through fax or print out. Moreover, it is not clear how much information in those OMRs is utilized when providing care at the early stage. In this study, we collected clinical concepts automatically from OMRs through optical character recognition (OCR) technology and then performed a quantitative analysis of concepts presented in OMRs and concepts captured in clinical notes at Mayo Clinic. We also investigated information from OMRs not captured in initial consultant notes but presented over subsequent consultant notes. We identified 12.93% of concepts from OMRs were identified in clinical documents within three months. Among those overlapping concepts, 26.74% of them were not captured in initial consultant notes. Our study presents that clinical information from OMRs is important for patient care. Also, the delayed presence of information in clinical notes may indicate important information from OMRs is not fully utilized earlier in the care.
KW - Electronic health record
KW - Medical concept matching
KW - Natural language processing
KW - Optical character recognition
KW - Outside medical records
UR - http://www.scopus.com/inward/record.url?scp=85046014959&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85046014959&partnerID=8YFLogxK
U2 - 10.1109/BIBM.2017.8217883
DO - 10.1109/BIBM.2017.8217883
M3 - Conference contribution
AN - SCOPUS:85046014959
T3 - Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
SP - 1495
EP - 1500
BT - Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
A2 - Yoo, Illhoi
A2 - Zheng, Jane Huiru
A2 - Gong, Yang
A2 - Hu, Xiaohua Tony
A2 - Shyu, Chi-Ren
A2 - Bromberg, Yana
A2 - Gao, Jean
A2 - Korkin, Dmitry
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 13 November 2017 through 16 November 2017
ER -