Known and unknown requirements in healthcare

Alistair Sutcliffe; Peter Sawyer; Gemma Stringer; Samuel Couth; Laura J.E. Brown; Ann Gledson; Christopher Bull; Paul Rayson; John Keane; Xiao jun Zeng; Iracema Leroi

doi:10.1007/s00766-018-0301-6

Known and unknown requirements in healthcare

Alistair Sutcliffe^*, Peter Sawyer, Gemma Stringer, Samuel Couth, Laura J.E. Brown, Ann Gledson, Christopher Bull, Paul Rayson, John Keane, Xiao jun Zeng, Iracema Leroi

^*Corresponding author for this work

Engineering & Applied Science

Research output: Contribution to journal › Article › peer-review

Abstract

We report experience in requirements elicitation of domain knowledge from experts in clinical and cognitive neurosciences. The elicitation target was a causal model for early signs of dementia indicated by changes in user behaviour and errors apparent in logs of computer activity. A Delphi-style process consisting of workshops with experts followed by a questionnaire was adopted. The paper describes how the elicitation process had to be adapted to deal with problems encountered in terminology and limited consensus among the experts. In spite of the difficulties encountered, a partial causal model of user behavioural pathologies and errors was elicited. This informed requirements for configuring data- and text-mining tools to search for the specific data patterns. Lessons learned for elicitation from experts are presented, and the implications for requirements are discussed as “unknown unknowns”, as well as configuration requirements for directing data-/text-mining tools towards refining awareness requirements in healthcare applications.

Original language	English
Number of pages	20
Journal	Requirements engineering
Early online date	30 Jul 2018
DOIs	https://doi.org/10.1007/s00766-018-0301-6
Publication status	E-pub ahead of print - 30 Jul 2018

Bibliographical note

This article is published under an open access license. Please check the 'Copyright Information' section for details of this license and what re-use is permitted. If your intended use exceeds what is permitted by the license or if you are unable to locate the licence and re-use information, please contact the Rights and Permissions team.

Keywords

Causal models
Data mining
Domain knowledge
Experts
Medical informatics
Requirements elicitation

Access to Document

10.1007/s00766-018-0301-6Licence: CC BY

Known and unknown requirements in healthcare
This article is published under an open access license. Please check the 'Copyright Information' section for details of this license and what re-use is permitted. If your intended use exceeds what is permitted by the license or if you are unable to locate the licence and re-use information, please contact the Rights and Permissions team.
Final published version, 1.1 MBLicence: CC BY

Fingerprint Dive into the research topics of 'Known and unknown requirements in healthcare'. Together they form a unique fingerprint.

Peter Sawyer
- Engineering & Applied Science
- Computer Science - Professor in Computer Science
- Aston Institute of Urban Technology and the Environment (ASTUTE)
Person: Academic

Cite this

@article{955be84a663f40169b68b71a8c0d1561,

title = "Known and unknown requirements in healthcare",

abstract = "We report experience in requirements elicitation of domain knowledge from experts in clinical and cognitive neurosciences. The elicitation target was a causal model for early signs of dementia indicated by changes in user behaviour and errors apparent in logs of computer activity. A Delphi-style process consisting of workshops with experts followed by a questionnaire was adopted. The paper describes how the elicitation process had to be adapted to deal with problems encountered in terminology and limited consensus among the experts. In spite of the difficulties encountered, a partial causal model of user behavioural pathologies and errors was elicited. This informed requirements for configuring data- and text-mining tools to search for the specific data patterns. Lessons learned for elicitation from experts are presented, and the implications for requirements are discussed as “unknown unknowns”, as well as configuration requirements for directing data-/text-mining tools towards refining awareness requirements in healthcare applications.",

keywords = "Causal models, Data mining, Domain knowledge, Experts, Medical informatics, Requirements elicitation",

author = "Alistair Sutcliffe and Peter Sawyer and Gemma Stringer and Samuel Couth and Brown, {Laura J.E.} and Ann Gledson and Christopher Bull and Paul Rayson and John Keane and Zeng, {Xiao jun} and Iracema Leroi",

note = "This article is published under an open access license. Please check the 'Copyright Information' section for details of this license and what re-use is permitted. If your intended use exceeds what is permitted by the license or if you are unable to locate the licence and re-use information, please contact the Rights and Permissions team.",

year = "2018",

month = jul,

day = "30",

doi = "10.1007/s00766-018-0301-6",

language = "English",

journal = "Requirements engineering",

issn = "0947-3602",

publisher = "Springer",

}

TY - JOUR

T1 - Known and unknown requirements in healthcare

AU - Sutcliffe, Alistair

AU - Sawyer, Peter

AU - Stringer, Gemma

AU - Couth, Samuel

AU - Brown, Laura J.E.

AU - Gledson, Ann

AU - Bull, Christopher

AU - Rayson, Paul

AU - Keane, John

AU - Zeng, Xiao jun

AU - Leroi, Iracema

N1 - This article is published under an open access license. Please check the 'Copyright Information' section for details of this license and what re-use is permitted. If your intended use exceeds what is permitted by the license or if you are unable to locate the licence and re-use information, please contact the Rights and Permissions team.

PY - 2018/7/30

Y1 - 2018/7/30

N2 - We report experience in requirements elicitation of domain knowledge from experts in clinical and cognitive neurosciences. The elicitation target was a causal model for early signs of dementia indicated by changes in user behaviour and errors apparent in logs of computer activity. A Delphi-style process consisting of workshops with experts followed by a questionnaire was adopted. The paper describes how the elicitation process had to be adapted to deal with problems encountered in terminology and limited consensus among the experts. In spite of the difficulties encountered, a partial causal model of user behavioural pathologies and errors was elicited. This informed requirements for configuring data- and text-mining tools to search for the specific data patterns. Lessons learned for elicitation from experts are presented, and the implications for requirements are discussed as “unknown unknowns”, as well as configuration requirements for directing data-/text-mining tools towards refining awareness requirements in healthcare applications.

AB - We report experience in requirements elicitation of domain knowledge from experts in clinical and cognitive neurosciences. The elicitation target was a causal model for early signs of dementia indicated by changes in user behaviour and errors apparent in logs of computer activity. A Delphi-style process consisting of workshops with experts followed by a questionnaire was adopted. The paper describes how the elicitation process had to be adapted to deal with problems encountered in terminology and limited consensus among the experts. In spite of the difficulties encountered, a partial causal model of user behavioural pathologies and errors was elicited. This informed requirements for configuring data- and text-mining tools to search for the specific data patterns. Lessons learned for elicitation from experts are presented, and the implications for requirements are discussed as “unknown unknowns”, as well as configuration requirements for directing data-/text-mining tools towards refining awareness requirements in healthcare applications.

KW - Causal models

KW - Data mining

KW - Domain knowledge

KW - Experts

KW - Medical informatics

KW - Requirements elicitation

UR - http://www.scopus.com/inward/record.url?scp=85050971357&partnerID=8YFLogxK

UR - https://link.springer.com/article/10.1007%2Fs00766-018-0301-6

U2 - 10.1007/s00766-018-0301-6

DO - 10.1007/s00766-018-0301-6

M3 - Article

AN - SCOPUS:85050971357

JO - Requirements engineering

JF - Requirements engineering

SN - 0947-3602

ER -