Variation in care is a major factor influencing increased population healthcare costs. While some variation in care is expected and appropriate for certain cohorts, variation can be a sign of decreased access for patients, inappropriate treatment, poor access to treatment alternatives, and reimbursements based ...
Variation in care is a major factor influencing increased population healthcare costs. While some variation in care is expected and appropriate for certain cohorts, variation can be a sign of decreased access for patients, inappropriate treatment, poor access to treatment alternatives, and reimbursements based on volume and increased treatment costs.
Executives and physicians face the menacing task of controlling care variation to control spending in healthcare organizations. Due to the multiple complicating factors contributing to this cost and quality driver, sophisticated prediction to proactively manage costs related to unstandardized care is an immediate need.
Length of Stay Predictions
The KenSci Hospital Length of Stay Solution provides a view into how healthcare facilities can use information such as patient’s vitals, their history, and current symptoms and accurately predict how long they need to be treated and what type of care they need during their stay by applying machine learning.
The KenSci solution identifies patients at risk for a preventable readmission with 71% accuracy using a weighted classifier to strengthen predictability among large sets of inpatient data real- time. This machine learning approach increases the reliability to answer the question of who might return to the hospital within thirty days of discharge.
Discharge Disposition Predictions
With the help of the accurate estimation of the stay of patients, the hospital can plan for more efficient patient discharge. Predicting the probable discharge dates can help to determine available bed hours that results in higher average occupancy and less waste of resources in the hospital.
Singular insight dashboard
An interactive dashboard provides patient risk scores serving as an at-a-glance clinical tool for ease of identification for patients at- risk for readmission.