Predictive and Decision Analytics for Proactive Business Processes in Emergency Room and Outpatient Clinic Services

Overcrowding has been an issue in many outpatient clinics and emergency rooms of healthcare organizations. However, they are important departments that are required to efficiently serve the masses of patients from the general public.This workshop is created to understand the importance of evaluating...

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Main Authors: Kar Way TAN, GOTTIPATI, Swapna, KOH, Lian Chee
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Language:English
Published: Institutional Knowledge at Singapore Management University 2014
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Online Access:https://ink.library.smu.edu.sg/sis_research/2972
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spelling sg-smu-ink.sis_research-39722016-09-19T03:00:36Z Predictive and Decision Analytics for Proactive Business Processes in Emergency Room and Outpatient Clinic Services Kar Way TAN, GOTTIPATI, Swapna KOH, Lian Chee Overcrowding has been an issue in many outpatient clinics and emergency rooms of healthcare organizations. However, they are important departments that are required to efficiently serve the masses of patients from the general public.This workshop is created to understand the importance of evaluating the business processes in these departments and how data analytics can help to create insights and provides the opportunity for process and scheduling improvement, hence maximizing efficiency. A process view is important as it allows healthcare organization to stay focus on business needs and drive analytics initiatives. It also helps to leverage on economies of scales in applying techniques to multiple processes of similar nature. The workshop will also cover more advanced topics such as predictive and decision analytics, coupled with IT considerations to create decision-support strategies that enable proactive business processes. Proactive processes combine analytic tools with business process management technology in order to achieve continuous process improvements. Being proactive helps the healthcare organization prepare for likely scenarios. In the final part of the workshop, a case-study in the context of fulfilling service targets of a hospital’s emergency room will be used to show how use of data analytics, prediction analytics and decision analytics can empower decision-making and bring improvements to the ED process. The workshop will be conducted in seminar-styled, small-group coaching and small-group presentations. It is designed to be highly interactive to facilitate discussions and idea generations. 2014-07-01T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/2972 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Healthcare analytics Databases and Information Systems Medicine and Health Sciences Operations Research, Systems Engineering and Industrial Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Healthcare
analytics
Databases and Information Systems
Medicine and Health Sciences
Operations Research, Systems Engineering and Industrial Engineering
spellingShingle Healthcare
analytics
Databases and Information Systems
Medicine and Health Sciences
Operations Research, Systems Engineering and Industrial Engineering
Kar Way TAN,
GOTTIPATI, Swapna
KOH, Lian Chee
Predictive and Decision Analytics for Proactive Business Processes in Emergency Room and Outpatient Clinic Services
description Overcrowding has been an issue in many outpatient clinics and emergency rooms of healthcare organizations. However, they are important departments that are required to efficiently serve the masses of patients from the general public.This workshop is created to understand the importance of evaluating the business processes in these departments and how data analytics can help to create insights and provides the opportunity for process and scheduling improvement, hence maximizing efficiency. A process view is important as it allows healthcare organization to stay focus on business needs and drive analytics initiatives. It also helps to leverage on economies of scales in applying techniques to multiple processes of similar nature. The workshop will also cover more advanced topics such as predictive and decision analytics, coupled with IT considerations to create decision-support strategies that enable proactive business processes. Proactive processes combine analytic tools with business process management technology in order to achieve continuous process improvements. Being proactive helps the healthcare organization prepare for likely scenarios. In the final part of the workshop, a case-study in the context of fulfilling service targets of a hospital’s emergency room will be used to show how use of data analytics, prediction analytics and decision analytics can empower decision-making and bring improvements to the ED process. The workshop will be conducted in seminar-styled, small-group coaching and small-group presentations. It is designed to be highly interactive to facilitate discussions and idea generations.
format text
author Kar Way TAN,
GOTTIPATI, Swapna
KOH, Lian Chee
author_facet Kar Way TAN,
GOTTIPATI, Swapna
KOH, Lian Chee
author_sort Kar Way TAN,
title Predictive and Decision Analytics for Proactive Business Processes in Emergency Room and Outpatient Clinic Services
title_short Predictive and Decision Analytics for Proactive Business Processes in Emergency Room and Outpatient Clinic Services
title_full Predictive and Decision Analytics for Proactive Business Processes in Emergency Room and Outpatient Clinic Services
title_fullStr Predictive and Decision Analytics for Proactive Business Processes in Emergency Room and Outpatient Clinic Services
title_full_unstemmed Predictive and Decision Analytics for Proactive Business Processes in Emergency Room and Outpatient Clinic Services
title_sort predictive and decision analytics for proactive business processes in emergency room and outpatient clinic services
publisher Institutional Knowledge at Singapore Management University
publishDate 2014
url https://ink.library.smu.edu.sg/sis_research/2972
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