KenSci's risk prediction platform helps health systems identify population health risk, optimize clinical outcomes and operational efficiency across the care continuum.
With a machine learning library of over 150+ prebuilt models and modular solutions for clinical and operational risk prediction KenSci's average deployment takes 10 weeks and ROI visibility in 90 days.
Who might get sick? How sick would they get? How can we co-ordinate their care better? How can we optimize care for outcomes AND cost?
Sepsis accounts for considerably more hospital readmissions and associated costs than any of the four medical conditions tracked by the federal government to measure quality of care and guide pay-for-performance reimbursements, per an analysis led by the University of Pittsburgh School of Medicine and VA Pittsburgh Healthcare System.
KenSci's Clinical Analytics solution helps CFOs and CMOs reduce the total cost impact of Sepsis and HAC by helping to identify patterns and predict patients who are at high risk. Enabling care managers to engage and modify their risk helping to prevent infection, readmission and mortality.