Criteria for developing clinical decision support systems

The use of archived information and knowledge derived from data-driven system, both at the point of care and retrospectively, is critical to improving the balance between healthcare expenditure and healthcare quality. Data-driven clinical decision support, augmented by performance feedback and education, is a logical addition to consensus- and evidence-based approaches on the path to widespread use of intelligent search agents, expert recognition and warning systems. We believe that these initial applications should (a) capture and archive, with identifiable end-points, complete episode-of-care information for high-complexity, high-cost illnesses, and (b) utilize large numbers of these cases to drive risk-adjusted “individualized” probabilities for patients requiring care at the time of intervention