TY - JOUR

T1 - Electronic medical record

T2 - data collection and reporting for spinal cord injury

AU - Biering-Sørensen, Fin

AU - Cohen, Stacey

AU - Rodriguez, Gianna Maria

AU - Tausk, Kelly

AU - Martin, Josh

PY - 2018

Y1 - 2018

N2 - Study design: Presentation of implementation of International Spinal Cord Injury (SCI) Data Sets, International Standards for Neurological Classification of SCI (ISNCSCI), and other structured SCI tools in to the Electronic Medical Record (EMR) Epic.Objectives: To describe the implementation of SCI tools in Epic at Rigshospitalet, University of Hospital, Capital Region of Denmark, and the ambitions for the future development of SCI related structured data and their reporting in the Epic EMR to be able to standardize data collection to facilitate research within institutions and collaboratively with other institutions locally and globally.Setting: Denmark and United States of America.Methods: The general content of the EMR Epic and the SCI-specific structured data implemented are described as well as the tools for reporting.Results: The ISNCSCI is made available via access to http://isncscialgorithm.azurewebsites.net/. After filling in the test data on the website, one can save the completed form as an image within the patient's chart. The International SCI Core Data Set and 13 International SCI Basic Data Sets (Table 1) are nearly completely implemented in the Danish version of Epic as SmartForms. In addition, 14 functional measures, including the Spinal Cord Independence Measure III, are implemented as flowsheets (Table 2).Conclusions: The possibility of entering international recognized structured data into the EMR gives better possibility for data sharing across SCI centers worldwide.Sponsorship: Gianna Maria Rodriguez, Stacey Cohen, and Fin Biering-Sørensen are users of Epic, but have no economic relationship with Epic. Kelly Tausk and Josh Martin are employees of Epic.

AB - Study design: Presentation of implementation of International Spinal Cord Injury (SCI) Data Sets, International Standards for Neurological Classification of SCI (ISNCSCI), and other structured SCI tools in to the Electronic Medical Record (EMR) Epic.Objectives: To describe the implementation of SCI tools in Epic at Rigshospitalet, University of Hospital, Capital Region of Denmark, and the ambitions for the future development of SCI related structured data and their reporting in the Epic EMR to be able to standardize data collection to facilitate research within institutions and collaboratively with other institutions locally and globally.Setting: Denmark and United States of America.Methods: The general content of the EMR Epic and the SCI-specific structured data implemented are described as well as the tools for reporting.Results: The ISNCSCI is made available via access to http://isncscialgorithm.azurewebsites.net/. After filling in the test data on the website, one can save the completed form as an image within the patient's chart. The International SCI Core Data Set and 13 International SCI Basic Data Sets (Table 1) are nearly completely implemented in the Danish version of Epic as SmartForms. In addition, 14 functional measures, including the Spinal Cord Independence Measure III, are implemented as flowsheets (Table 2).Conclusions: The possibility of entering international recognized structured data into the EMR gives better possibility for data sharing across SCI centers worldwide.Sponsorship: Gianna Maria Rodriguez, Stacey Cohen, and Fin Biering-Sørensen are users of Epic, but have no economic relationship with Epic. Kelly Tausk and Josh Martin are employees of Epic.

U2 - 10.1038/s41394-018-0106-3

DO - 10.1038/s41394-018-0106-3

M3 - Journal article

C2 - 30109135

VL - 4

JO - Spinal cord series and cases

JF - Spinal cord series and cases

SN - 2058-6124

M1 - 70

ER -