DocumentCode :
3089299
Title :
Taming complex healthcare data models with dictionary tooling
Author :
Timm, John T. E. ; Hui, John ; Knoop, Sarah ; Schwarz, P.
Author_Institution :
IBM Almaden Res. Center, San Jose, CA, USA
fYear :
2013
fDate :
20-21 May 2013
Firstpage :
35
Lastpage :
38
Abstract :
Information models used in the healthcare domain tend to be complex, in part because they were designed to be as flexible and generic as possible. This complexity presents a steep learning curve for implementers, which can lead to partial or poorly-implemented solutions. In this paper, we present a tool that facilitates the creation of sets of modular and composable clinical data abstractions. Using these, implementers can produce and consume standards-compliant clinical data correctly and efficiently without being experts in the underlying information models or the medical terminologies they reference.
Keywords :
data structures; dictionaries; health care; learning (artificial intelligence); medical information systems; complex healthcare data model taming; composable clinical data abstractions; dictionary tooling; healthcare domain; information models; medical terminologies; modular clinical data abstractions; partial-implemented solutions; poorly-implemented solutions; standards-compliant clinical data; steep learning curve; Blood pressure; Complexity theory; Dictionaries; Medical services; Pressure measurement; Standards; XML; Clinical data abstractions; interoperability; standards;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering in Health Care (SEHC), 2013 5th International Workshop on
Conference_Location :
San Francisco, CA
Type :
conf
DOI :
10.1109/SEHC.2013.6602475
Filename :
6602475
Link To Document :
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