Forecasted to expand at a compound annual growth rate of 9.3%, with revenues topping $6.47 billion USD by 2024, CDS systems are poised to become the user interface of choice for clinical interaction within healthcare information technology, according to Frost and Sullivan. Industry experts believe CDS systems could even supersede electronic health records as the primary health IT point of interface for clinicians.
But in a world where CDS systems are being more frequently consulted and relied upon to optimize healthcare, they must be held to a high standard when informing the clinical decision-making that impacts patient care and outcomes.
In its recent “Best Practices for World-Class Performance” review of CDS systems, Frost & Sullivan noted certain key factors that denote “pioneering” solutions in the CDS space:
- Grading Quality of Evidence: The volume of clinical research produced makes it difficult for care teams to keep up with the latest healthcare best practices and clinical guidance, especially in the wake of a global pandemic. Because no clinician can distill the massive volume of new data regularly, clinicians need to understand how experts evaluate data and arrive at a recommendation. CDS systems that grade clinical recommendations by the quality of evidence instill confidence levels that guide decision-making, even when the evidence is weak or unclear.
- Aligning Care Team Decisions: For each patient, clinical decisions consider a complex range of variables, such as the patient's background and preferences, the latest medical evidence, and what is discovered by the provider during the clinical encounter. As care teams have expanded, clinical decisions are being made across an even more significant number of roles, introducing the risk of misaligned decisions. Given that care teams use their CDS solutions consistently every day, aligned content and communication across solutions can help to standardize care and improve outcomes.
- Avoiding Typical CDS Pitfalls: Traditional CDS systems come with disadvantages – like alert fatigue, diagnostic errors, and disrupted workflows – that make advanced systems that incorporate greater precision and fewer manual inputs a better choice for clinicians.