Advanced clinical analytics tools provide healthcare systems with insight into clinician behavior and potential knowledge gaps, to meaningfully shape education, quality, and population health programming.
Importance of healthcare analytics for health system administrators
Clinical decision support (CDS) tools are vital for modern healthcare systems. As medical knowledge expands and clinicians are increasingly time-constrained, care teams need a reliable evidence-based solution that helps them answer questions at the point of care.
But healthcare system administrators, care team leaders and academic personnel require different actionable insights from their CDS solution. For them, the value lies within CDS analytics.
In the past, CDS analytics have mostly been confined to generic, high-level utilization reports that give administrators a retrospective snapshot of the overall level of usage of the solution, explains Julie Frey, Head of Provider Product for Wolters Kluwer, Health. However, it is more important and more valuable for administrators to proactively access actionable insights on what is top of mind for different members of the care team, including advanced practice providers and registered nurses, she says. “From those insights, administrators can take targeted and impactful remediation steps to close knowledge and care gaps that ultimately improve not only provider performance but also patient outcomes. That’s the path of evolution that decision support is currently on.”
Application of analytics: Contribution to care team education and performance
CDS-based clinical analytics have the power to identify and demonstrate key priorities and knowledge gaps to focus on for care team development, and that is beneficial for a health system’s overall practice.
The administrators who serve as the bridge between clinicians and IT tend to be the most engaged in analytics, along with those who have an education responsibility. Together, these leaders are finding great value in having insight into providers' point-of-care behavior for a variety of use cases, including:
- Enabling data-driven and specific professional education campaigns.
- Supporting clinical quality initiatives and uncovering potentially costly care variations.
- Managing emerging community health trends.