MAJOR NORTHEASTERN UNITED STATES HEALTHCARE SYSTEM
This nationally-acclaimed health system has 14+ hospitals and a physician network serving patients in a major northeastern city and its surrounding suburbs.
25,000 patients with congestive heart failure (CHF) who are re-admitted within 30 days
Improve predictability of the CHF 30-day readmission rate and improve quality of care based on the application of Social Determinants of Health (SDoH) as provided by the EIP
To quickly produce the applicable individualized SDoH data, Bellrock only needed the customer to provide the name of the patient, associated demographic data, and some specific clinical data. Armed with this information, Bellrock built a model via its EIP, based solely on SDoH, to predict 30-day CHF readmissions. The EIP predictive model can be reproduced for any disease sta
The EIP model was able to predict with 82% accuracy all 30-day CHF readmissions occurring over a five-year period. The potential savings for only 4 hospitals within the health system are $12 to $24 million, or 10% to 20% annually
Deploy the predictive model for current CHF-admitted patients before they are readmitted, and use EIP to develop predictive models for other disease states.
NATIONAL HEALTH INSURER
A leading health payer with more than 13 million members nationwide.
Respiratory disease in the insurer’s 110,000 members in South Carolina, with a focus on asthma.
Use Social Determinants of Health (SDoH) to identify those high-risk individuals likely to develop asthma (“Bloomers”). Improve disease management by deploying case managers for early intervention to reduce costs and admissions and improve health outcomes for members.
Bellrock combined SDoH data at an individual member level with client-supplied information and created a model using its exclusive Enterprise Intelligence Platform (EIP) to predict asthma admissions.
Bellrock’s EIP was able to predict with more than 80% accuracy the currently low-cost members who will have a high risk of asthma-related ER visits and inpatient admissions. Within the state of South Carolina, we estimate they should see a savings in the range of $4 to $6.5 million, or 30% to 50% annually.
Armed with this data on a near real-time basis, the health insurance company can deploy case managers to hospitals to collaborate with clinicians, addressing risk factors to decrease the likelihood of readmissions for asthma patients, thus reducing costs and improving outcomes.