TY - GEN
T1 - Using Prevalence Patterns to Discover Un-mapped Flowsheet Data in an Electronic Health Record Data Warehouse
AU - Bokov, Alex F.
AU - Bos, Angela B.
AU - Manuel, Laura S.
AU - Tirado-Ramos, Alfredo
AU - Kittrell, Pamela
AU - Jackson, Carlayne
AU - Olin, Gail P.
N1 - Funding Information:
This work was supported by PCORI grants CDRN-1306- 04631 and CDRN-1501-26643NIH
Publisher Copyright:
© 2017 IEEE.
PY - 2017/11/10
Y1 - 2017/11/10
N2 - We have developed a data summarization tool called Chi2notype which leverages the star schema of the Integrating Informatics from Bench to Bedside (i2b2) vendor-neutral data-warehouse platform to characterize a patient-cohort of interest. Chi2notype calculates a chi-squared statistic for every one of the hundreds of thousands of variables in an Electronic Medical Record (EMR) system and uses it to rank them from most over-represented in the cohort to most under-represented. This can be used for many purposes, including detection of adverse events, studies of socioeconomic disparities in health outcomes, and quality control. Here we demonstrate the use of Chi2notype to find un-mapped elements from nursing flowsheets used for monitoring the progress of ALS patients, thus making it possible to link them to their respective parent flowsheets in the i2b2 ontology. This, in turn, makes these flowsheets accessible to researchers performing eligibility queries or retrospective analysis on de-identified electronic health record (EHR) data.
AB - We have developed a data summarization tool called Chi2notype which leverages the star schema of the Integrating Informatics from Bench to Bedside (i2b2) vendor-neutral data-warehouse platform to characterize a patient-cohort of interest. Chi2notype calculates a chi-squared statistic for every one of the hundreds of thousands of variables in an Electronic Medical Record (EMR) system and uses it to rank them from most over-represented in the cohort to most under-represented. This can be used for many purposes, including detection of adverse events, studies of socioeconomic disparities in health outcomes, and quality control. Here we demonstrate the use of Chi2notype to find un-mapped elements from nursing flowsheets used for monitoring the progress of ALS patients, thus making it possible to link them to their respective parent flowsheets in the i2b2 ontology. This, in turn, makes these flowsheets accessible to researchers performing eligibility queries or retrospective analysis on de-identified electronic health record (EHR) data.
UR - http://www.scopus.com/inward/record.url?scp=85040345251&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85040345251&partnerID=8YFLogxK
U2 - 10.1109/CBMS.2017.122
DO - 10.1109/CBMS.2017.122
M3 - Conference contribution
AN - SCOPUS:85040345251
T3 - Proceedings - IEEE Symposium on Computer-Based Medical Systems
SP - 324
EP - 327
BT - Proceedings - 2017 IEEE 30th International Symposium on Computer-Based Medical Systems, CBMS 2017
A2 - Bamidis, Panagiotis D.
A2 - Konstantinidis, Stathis Th.
A2 - Rodrigues, Pedro Pereira
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 30th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2017
Y2 - 22 June 2017 through 24 June 2017
ER -