title: Modelling elderly cardiac patients decision making using Cognitive Work Analysis: identifying requirements for patient decision aids.
abstract: BACKGROUND
  Patients make various healthcare decisions on a daily basis. Such day-to-day decision making can have significant consequences on their own health, treatment, care, and costs. While decision aids (DAs) provide effective support in enhancing patient's decision making, to date there have been few studies examining patient's decision making process or exploring how the understanding of such decision processes can aid in extracting requirements for the design of DAs.
  
  
  OBJECTIVE
  This paper applies Cognitive Work Analysis (CWA) to analyse patient's decision making in order to inform requirements for supporting self-care decision making.
  
  
  METHODS
  This study uses focus groups to elicit information from elderly cardiovascular disease (CVD) patients concerning a range of decision situations they face on a daily basis. Specifically, the focus groups addressed issues related to the decision making of CVD in terms of medication compliance, pain, diet and exercise.
  
  
  RESULTS
  The results of these focus groups are used to develop high level views using CWA. CWA framework decomposes the complex decision making problem to inform three approaches to DA design: one design based on high level requirements; one based on a normative model of decision-making for patients; and the third based on a range of heuristics that patients seem to use.
  
  
  CONCLUSIONS
  CWA helps in extracting and synthesising decision making from different perspectives: decision processes, work organisation, patient competencies and strategies used in decision making. As decision making can be influenced by human behaviour like skills, rules and knowledge, it is argued that patients require support to different types of decision making. This paper also provides insights for designers in using CWA framework for the design of effective DAs to support patients in self-management.
authors: School of Electronic, Electrical and Computer Engineering, University of Birmingham, United Kingdom. Electronic address: AVD016@bham.ac.uk.
authors: Anandhi Vivekanandan
authors: AV
authors: Dhukaram
authors: School of Electronic, Electrical and Computer Engineering, University of Birmingham, United Kingdom.
authors: Chris
authors: C
authors: Baber
mesh_terms: D000368:Aged; D002318:Cardiovascular Diseases / Q000628:therapy; D003657:Decision Making; D005260:Female; D017144:Focus Groups; D006801:Humans; D008297:Male; D008875:Middle Aged; D010358:Patient Participation; D036301:Qualitative Research; D012648:Self Care
keywords: Cognitive Work Analysis; DA requirements; Decision aids design; Patient decision making; Self-management