Quadrant,Statement ID,Statement Text,Importance,Feasibility
High-High,1,Human oversight during implementation in early days,4.25,3.42
High-High,89,Allow clinicians to focus on tasks requiring their expertise,4.17,4.0
High-High,100,Automation of routine tasks,4.0,4.08
High-High,9,Ensuring accountability and oversight of AI,4.0,3.58
High-High,8,Minimizing bias and increasing performance and accuracy,4.0,3.33
High-High,69,Reduce admin burden,3.92,4.17
High-High,59,Prediction/prognosis/treatment recommendations,3.92,3.58
High-High,30,"Savings in time, can integrate different information and improve in treatment especially when there is less number of human specialist",3.83,3.67
High-High,39,Educating end-users about properly navigating AI,3.83,3.58
High-High,98,Lists possible outcome and risks for the patient,3.83,3.58
High-High,23,AI allows access vast information very quickly to help diagnosis,3.75,4.0
High-High,18,AI could free up time for pt care,3.75,3.67
High-High,2,Concerns with confidentiality,3.75,3.25
High-High,84,Live translation and/or transcription of conversations,3.73,4.08
High-High,50,Increases digestibility/highlighting key points,3.67,4.33
High-High,76,Triage diagnostic results for clinicians,3.67,3.67
High-High,42,Improve access to services,3.67,3.58
High-High,4,Efficiency improved for documentation,3.58,4.17
High-High,11,"Better detection (of moles, cancer lumps)",3.58,3.75
High-High,44,AI could help improve accuracy,3.58,3.75
High-High,53,Pooling large volume of data can improve accuracy of AI system and allow for more timely diagnosis and treatment recommendation,3.58,3.75
High-High,58,Noticing patterns and new things humans haven't noticed,3.58,3.5
High-High,64,Personalization of AI support tools for patients,3.58,3.33
High-High,79,AI could help address the human health resources issue,3.58,3.25
High-High,72,Ability to make text/conversation more digestable for patients (less technical),3.5,3.83
High-High,43,Ensuring accessibility and translation,3.5,3.67
High-High,80,Faster assessments to inform decision-making,3.5,3.58
High-High,19,Developing a rigorous privacy and quality assurance framework,3.5,3.42
High-High,73,Ensuring clinical validation of AI tools,3.5,3.42
High-High,57,"24/7 availability, AI doesn't get tired or brain fog",3.42,4.25
High-High,70,Potential in navigation and directing to self-management resources,3.42,3.67
High-High,15,AI could decrease false positives,3.42,3.42
High-High,88,Ensuring interpretability of AI tools,3.42,3.33
High-High,12,Diversification of AI training data and sources,3.33,3.33
High-High,7,AI could perpetuate existing biases,3.33,3.25
High-High,24,Benefits in early distress screening,3.33,3.25
Low-High,51,Collate large databases,3.25,4.17
Low-High,22,Benefits with accessibility & communication (translating languages lay terms),3.25,3.58
Low-High,27,Benefits with patient access to accurate information,3.25,3.55
Low-High,37,Consultation recording and transcription,3.17,4.18
Low-High,68,Phased roll-out,3.17,4.08
Low-High,56,Multidisciplinary collaboration and training in developing AI models,3.17,3.25
Low-High,86,Lack of training/knowledge for those using the AI tool in the real world,3.17,3.25
Low-High,41,Facilitation of clinical research,3.08,3.42
Low-High,90,"Identifying and focusing on high-priority areas, such as prevention",3.08,3.42
Low-High,97,"Potential for widening differential diagnosis, widening perspective of patient",3.0,3.33
Low-High,62,Increased opportunities for innovation,2.92,3.58
Low-High,34,Knowledge repositing for learning and research,2.92,3.5
Low-High,45,Embed research / quality improvement into all areas,2.92,3.25
Low-High,21,Helps with generation of ideas can act as a sounding board,2.83,3.58
Low-High,74,"Concerns with maintaining up to date information, sources and programming",2.83,3.42
Low-High,28,Concerns about personalizing care,2.83,3.25
High-Low,3,Concerns with patient acceptability,4.08,3.17
High-Low,94,Patient/parent/caregiver/provider acceptability,3.92,2.92
High-Low,38,Ensuring cybersecurity of AI tools,3.75,3.17
High-Low,46,"Data that the AI model is trained on must be good, clean, large and diverse",3.58,2.83
High-Low,85,"Establishing guidelines for ""best practices"" for training AI + clinical validation",3.5,3.17
High-Low,40,Concerns with protection of personal health identifiers,3.42,3.0
High-Low,63,Distress is nuanced and often detected in the unsaid of human communication and in a trusting therapeutic relationship,3.42,2.5
High-Low,82,AI could make mistakes,3.33,3.0
High-Low,17,Benefits in equitable access,3.33,2.92
High-Low,14,Concerns with liability,3.33,2.83
High-Low,75,Data privacy concerns,3.33,2.83
High-Low,49,Loss of human connection/interactions,3.33,2.75
High-Low,5,False confidence,3.33,2.73
Low-Low,66,Concerns with consent of patient,3.25,3.17
Low-Low,6,AI could provide alternate perspectives,3.17,3.17
Low-Low,16,Proactive preventative care,3.17,3.0
Low-Low,54,Concerns with responsibility accountability of AI recommendations,3.17,3.0
Low-Low,55,AI hallucinations,3.17,2.83
Low-Low,92,Maintaining competency with changing best practices and approved standards,3.17,2.83
Low-Low,20,AI could be misused,3.17,2.75
Low-Low,31,AI could remove human bias,3.17,2.75
Low-Low,36,AI could be of concern to patient privacy,3.08,3.08
Low-Low,60,"Concerns with standards for quality, accuracy, etc.",3.08,2.92
Low-Low,48,Preservation of human touch,3.08,2.83
Low-Low,10,Concerns with digital literacy and digital divide barriers,3.08,2.75
Low-Low,81,Concerns with transparency,3.08,2.75
Low-Low,67,Racism bias through research (history of medical research),3.08,2.5
Low-Low,35,AI could be of concern regarding its ongoing validation,3.0,3.09
Low-Low,25,Establishing proper consent,3.0,3.08
Low-Low,13,Too much bureaucracy slowing progress,3.0,3.0
Low-Low,93,Minority groups being marginalized,3.0,2.92
Low-Low,96,Possibility of data breaches / data leaks,3.0,2.83
Low-Low,65,Concerns with difficulty to know older data for training and missing new breakthrough information,2.92,2.92
Low-Low,29,Data governance policies and regulations to enhance data quality and accountability,2.92,2.58
Low-Low,91,Concerns that data is held by private companies,2.92,2.42
Low-Low,95,Data ownership and standards and guidelines on AI developed are not established,2.83,2.92
Low-Low,32,Regulation framework and a good understanding of the medico-legal implications,2.83,2.25
Low-Low,52,AI could engender issues with trust,2.75,2.67
Low-Low,78,Control of data by corporations,2.75,2.5
Low-Low,83,"Concerns with stability of the system (during virus attack, power outage, system interruption)",2.75,2.42
Low-Low,99,Cybersecurity concerns,2.75,2.42
Low-Low,71,Over reliance by physicians and reduced problem solving skills,2.67,2.75
Low-Low,47,Concerns with attrition of skills in healthcare providers,2.58,2.58
Low-Low,33,"AI could lead to excessive human delegation, assuming that AI will take care of it!",2.58,2.5
Low-Low,26,Concerns with job security,2.42,2.25
Low-Low,77,Concerns with going too far and can't come back,2.33,2.5
Low-Low,87,Can existing healthcare servers support the use of AI?,2.17,3.08
Low-Low,61,Concerns with power outages and down time procedures,2.17,2.58