title: What is needed to implement a computer-assisted health risk assessment tool? An exploratory concept mapping study.
abstract: BACKGROUND
  Emerging eHealth tools could facilitate the delivery of comprehensive care in time-constrained clinical settings. One such tool is interactive computer-assisted health-risk assessments (HRA), which may improve provider-patient communication at the point of care, particularly for psychosocial health concerns, which remain under-detected in clinical encounters. The research team explored the perspectives of healthcare providers representing a variety of disciplines (physicians, nurses, social workers, allied staff) regarding the factors required for implementation of an interactive HRA on psychosocial health.
  
  
  METHODS
  The research team employed a semi-qualitative participatory method known as Concept Mapping, which involved three distinct phases. First, in face-to-face and online brainstorming sessions, participants responded to an open-ended central question: "What factors should be in place within your clinical setting to support an effective computer-assisted screening tool for psychosocial risks?" The brainstormed items were consolidated by the research team. Then, in face-to-face and online sorting sessions, participants grouped the items thematically as 'it made sense to them'. Participants also rated each item on a 5-point scale for its 'importance' and 'action feasibility' over the ensuing six month period. The sorted and rated data was analyzed using multidimensional scaling and hierarchical cluster analyses which produced visual maps. In the third and final phase, the face-to-face Interpretation sessions, the concept maps were discussed and illuminated by participants collectively.
  
  
  RESULTS
  Overall, 54 providers participated (emergency care 48%; primary care 52%). Participants brainstormed 196 items thought to be necessary for the implementation of an interactive HRA emphasizing psychosocial health. These were consolidated by the research team into 85 items. After sorting and rating, cluster analysis revealed a concept map with a seven-cluster solution: 1) the HRA's equitable availability; 2) the HRA's ease of use and appropriateness; 3) the content of the HRA survey; 4) patient confidentiality and choice; 5) patient comfort through humanistic touch; 6) professional development, care and workload; and 7) clinical management protocol. Drawing insight from the theoretical lens of Sociotechnical theory, the seven clusters of factors required for HRA implementation could be read as belonging to three overarching aspects : Technical (cluster 1, 2 and 3), Social-Patient (cluster 4 and 5), and Social-Provider (cluster 6 and 7). Participants rated every one of the clusters as important, with mean scores from 4.0 to 4.5. Their scores for feasibility were somewhat lower, ranging from 3.4 to. 4.3. Comparing the scores for importance and feasibility, a significant difference was found for one cluster from each region (cluster 2, 5, 6). The cluster on professional development, care and workload was perceived as especially challenging in emergency department settings, and possible reasons were discussed in the interpretation sessions.
  
  
  CONCLUSIONS
  A number of intertwined multilevel factors emerged as important for the implementation of a computer-assisted, interactive HRA with a focus on psychosocial health. Future developments in this area could benefit from systems thinking and insights from theoretical perspectives, such as sociotechnical system theory for joint optimization and responsible autonomy, with emphasis on both the technical and social aspects of HRA implementation.
authors.affiliation: School of Health Policy and Management, York University, 4700 Keele Street, HNES Building, 4th Floor, Toronto, ON, M3J 1P3, Canada. farahmad@yorku.ca
authors.forename: Farah
authors.initials: F
authors.lastname: Ahmad
authors.forename: Cameron
authors.initials: C
authors.lastname: Norman
authors.forename: Patricia
authors.initials: P
authors.lastname: O'Campo
mesh_terms: D002170:Canada; D016000:Cluster Analysis; D003210:Concept Formation; D020000:Decision Support Systems, Clinical; D006126:Group Processes; D006801:Humans; D020407:Internet; D008507:Medically Underserved Area; D001523:Mental Disorders / Q000175:diagnosis; D016730:Program Development; D036301:Qualitative Research; D018570:Risk Assessment / Q000379:methods; D014584:User-Computer Interface