Population Analytics with Predictive Models
Demonstrate Impact through Population Analytics with Predictive Models
All data captured in P-CIS, ingested from an EHR/EMR, data warehouse, or collected on any type of assessment or form, funnels directly into SF-AI powered dashboards with predictive analytics. This allows Supervisors, Managers and Administrators to use filters to drill into insights for specific care populations. The dashboards continuously learn about the care organizations, their care models, their staff, and their service populations. Then it updates insights based on who is served and what works for whom.
P-CIS securely and directly connects a care organization’s data to predictive analytics models for pattern recognition, including but not limited to regression, latent class analysis, random forest, spatial geographic mapping, and neural networks — directly in P-CIS. There is no longer any need to export data into a CSV file and import it into another statistical processing application for higher level insights. P-CIS automates analysis directly from data, minutes after data are captured. Providing boundless options for visualization, P-CIS supports filtering and drilling for real-time discovery. Dynamic visualizations with deep learning models are directly available and distributable to staff.
Population Health Dashboard: Dashboards monitor population needs and care system impact on needs in real time
Predictive Models: ML/AI identifies patterns of success across service populations to prioritize areas of care focus that have the most impact on the overall health and wellbeing for subpopulations with shared circumstances
Custom Dashboards and Analytics: Custom designed dashboards monitor any patient/client related data in real-time, including care quality, care outcomes, and value-based care metrics
The Benefit. P-CIS provides transparency across the entire care organizations’ impact on its service populations. The outcomes presented deliver insights for model adjustments supporting continuous quality improvements (CQI), so that organizations can evidence their value with more efficient and effective care.
Standard Population Health Dashboard
Standard population health dashboard allows users to drill into subpopulations to see their level of success in care according to user-defined parameters
Predictive Models
Predictive models can identify which populations are responding well to which services
