Personalized Process and Decision Support in Emergency Care by Mining Electronic Health Records and Sensor Data
Pages 415 - 418
Abstract
Physicians are constantly confronted with decisions on what should be done next during the diagnosis and treatment of patients. Non-routine medical treatment processes, for example in emergency care, are the most extreme group of such processes due to the large and diverse set of options at each decision point. Such decision making can be very demanding and even overwhelming, especially for less experienced medical personnel. The current IT infrastructure in healthcare remains lacking in support for decision making. In this research project, we lay the foundation process & decision support system that externalizes the knowledge and experience from historic data to offer personalized and process-aware decision support to physicians. The systems uses two separate but complementary components: a process engine and a prediction generator.
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Index Terms
- Personalized Process and Decision Support in Emergency Care by Mining Electronic Health Records and Sensor Data
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Published In
May 2020
446 pages
ISBN:9781450375320
DOI:10.1145/3421937
- Editors:
- Sean A. Munson,
- Stephen M. Schueller,
- General Chair:
- Rosa Arriaga
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Association for Computing Machinery
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Published: 02 February 2021
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PervasiveHealth '20
PervasiveHealth '20: 14th EAI International Conference on Pervasive Computing Technologies for Healthcare
May 18 - 20, 2020
GA, Atlanta, USA
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PervasiveHealth '20 Paper Acceptance Rate 55 of 116 submissions, 47%;
Overall Acceptance Rate 55 of 116 submissions, 47%
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