Paper Info
Title
Requirements Engineering for Health Data Analytics: Challenges and Possible Directions
Abstract
We are witnessing a radical change of attitude towards health information management - the adoption of data analytics to help people monitor and predict health conditions proactively. Most hospitals are aggregating data to provide some sort of analytics as part of their daily practices. Many medical doctors start developing data repositories of their own specialty so that evidence-based clinical decisions can be made, and data of research value can be obtained and exploited efficiently. Health analytics projects need to have software requirements defined for them. These projects must deal with the data itself, the operations performed on the data, and the formatting and distribution of the data for use. The end products of requirements process for a health analytics project will be a set of business and user requirements (both functional, and nonfunctional). It reveals stakeholder needs of analytics results, in terms of how quickly, how often and in what format. This paper shares our observations on the status quo in this area, present the problems and challenges encountered, report the experience and findings in real world projects, and discuss some possible future directions in this area.
Year
DOI
Venue
2016
10.1109/RE.2016.48
2016 IEEE 24th International Requirements Engineering Conference (RE)
Keywords
Field
DocType
healthcare,data analytics,domain knowledge,information model,function and non-functional requirements
Data science,Business analytics,Software analytics,Web analytics,Computer science,Requirements engineering,Analytics,Business intelligence,User requirements document,Software requirements
Conference
ISSN
ISBN
Citations 
2332-6441
978-1-5090-4122-0
4
PageRank 
References 
Authors
0.44
8
4
Name
Order
Citations
PageRank
Lin Liu11128115.75
Letong Feng261.49
Zhanqiang Cao350.80
Jingdong Li464.19