TY - GEN
T1 - Health Service Decision Toolbox (HSDT)
T2 - 15th International Conference on Service Systems and Service Management, ICSSSM 2018
AU - Xu, Guoquan
AU - Yu, Zhongyuan
AU - Pennock, Michael J.
AU - Rouse, William B.
AU - Naylor, Mary D.
AU - Paul, Mark V.
AU - Hirschman, Karen B.
AU - Pepe, Kara
AU - Xie, Huaqing
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/9/13
Y1 - 2018/9/13
N2 - The amount of data being digitally collected and stored by health information technology (health IT) is vast and expanding rapidly. How to convert this huge amount of resources into knowledge that can facilitate delivering the right intervention to the right patient, or how to bridge the gap between prevention research and practice, remain unclear. The objective of this study is to develop a Health Service Decision Toolbox (HSDT) that enables healthcare providers to integrate vast data sources collected by Health IT to improve confidence in decisions of whether or not to adopt an evidence-based intervention. HSDT can guide users through feeding massive health related data into several major input groups, such as healthcare providers, patient population, and intervention procedures. With the HSDT, we can successfully project specific impacts, because of additional tailoring to fit each organization/patient population's unique circumstances. When such tailoring combined with an interactive visualization environment, it would further increase decision makers' confidence. We illustrate the use of HSDT with a case study of delivering Transitional Care Model (TCM) to the most needed hospitals. TCM is a proven care management approach that is designed and tested by University of Pennsylvania via multiple NIH funded clinical trials.
AB - The amount of data being digitally collected and stored by health information technology (health IT) is vast and expanding rapidly. How to convert this huge amount of resources into knowledge that can facilitate delivering the right intervention to the right patient, or how to bridge the gap between prevention research and practice, remain unclear. The objective of this study is to develop a Health Service Decision Toolbox (HSDT) that enables healthcare providers to integrate vast data sources collected by Health IT to improve confidence in decisions of whether or not to adopt an evidence-based intervention. HSDT can guide users through feeding massive health related data into several major input groups, such as healthcare providers, patient population, and intervention procedures. With the HSDT, we can successfully project specific impacts, because of additional tailoring to fit each organization/patient population's unique circumstances. When such tailoring combined with an interactive visualization environment, it would further increase decision makers' confidence. We illustrate the use of HSDT with a case study of delivering Transitional Care Model (TCM) to the most needed hospitals. TCM is a proven care management approach that is designed and tested by University of Pennsylvania via multiple NIH funded clinical trials.
KW - Evidence-based Practice
KW - Health Data Analytics
KW - Health Information Technology
KW - Health Policy
UR - http://www.scopus.com/inward/record.url?scp=85054352462&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85054352462&partnerID=8YFLogxK
U2 - 10.1109/ICSSSM.2018.8465110
DO - 10.1109/ICSSSM.2018.8465110
M3 - Conference contribution
AN - SCOPUS:85054352462
SN - 9781538651780
T3 - 2018 15th International Conference on Service Systems and Service Management, ICSSSM 2018
BT - 2018 15th International Conference on Service Systems and Service Management, ICSSSM 2018
Y2 - 21 July 2018 through 22 July 2018
ER -