AI Healthcare Research: Directions and Strategies
Several directions and strategies for AI research in healthcare are suggested as follows: First, AI researchers in healthcare should utilize the results from predictive modeling of determinants of
personal health or outcomes. Predictive analytics should not just to rely on a single criterion. By identifying a few parameters parsimoniously, we would be able to optimize the performance and outcomes. In other words, the future is to look beyond the scope of design and process that will be directly influenced by the context or ecology of medical care. We should focus on outcomes and performance as well. This systems approach to healthcare also refers to the context-design-process-outcomes framework guiding the development of AI research.
Second, the convergence in systems science needs to employ causal inquiry approaches via the establishment of theoretical models containing the context-design-process-performance-outcome components of the healthcare system. This causal framework specifies that under specific contexts, a good design leads to a good process, good process leads to good performance, and then good performance helps achieve better patient care outcomes. This is an expanded model of the structural-process-outcome framework specified by Donabedian (1966) for quality improvement.
Third, a multi-tiered approach to healing environment design is suggested. Figure 2 displays a complex causal model of the determinants of health care outcomes. The endpoint is a holistic state of physical and mental wellbeing achievable through improving the healthcare delivery system and its performance. With adequate levels of inputs and outputs used in the healthcare system, the patient-centered care modality is integrated into the design. Evidence-based design in healing environments can exert important positive effects, including the reduction of stress and risk, improvement of patient safety, reduction of airborne
6 Thomas T.H. Wan. / Convergence of Artificial Intelligence Research in Healthcare: Trends and Approaches
pathogens and hospital acquired infections, avoidance of transfer patients induced errors, and enhancement of staff satisfaction and productivity (Ulrich et al., 2004; Douglas and Douglas, 2005; and Huisman et al, 2012). Furthermore, the systematic design has to consider the context or environment in which patient care is affected by cultural, political, social and physical environmental factors. The appropriate designs and processes of care management or population health management enable to maximize or optimize performance of a healthcare system.