Successful Risk Stratification Models of managed populations is a key requirement for success in any Value-Based Care initiative. Over the years the industry has advanced through 3 generations of risk models.
First-generation models rely primarily on claims data and include the HCC and ACG (Johns Hopkins) models. These models tend to have some limited success in predicting costs but cannot deal with clinical and Social Determinants of Health (SDoH) data.
The 2nd generation of models brings clinically and claims data together or are based on SDoH. These include models such as the Soliton Suggested Risk (SSR) score and the AAFP risk model. The SDoH models focus exclusively on socio-economic data and ignore clinically and claims-based information. These 2nd generation models tend to have better predictability than the 1st gen models but are still limited.
The 3rd generation of risk stratification models uses AI to merge the 1st and 2nd gen models to produce layered results and composite scores that have much-improved predictability.
CareSpace® provides the industry’s first 3rd generation risk algorithm based on four advanced risk models to give providers the maximum flexibility in managing their at-risk populations. These capabilities eclipse those of our competitors by a wide margin
Multilayer risk stratification capabilities that allow you to:
Identify patients who need immediate attention
Reduce Unnecessary Utilization of resources
Improve Health Outcomes
Lower health costs
CareSpace® equips you with three predefined risk models and a customizable risk model.
Predefined Risk Models
CMS Hierarchical Condition Categories code (HCC)
The HCC module uses components from the Clinical Decision Support and the analytics from the clinical data to provide real-time alerts to ensure that patient care meets the standards set out by CMS in the HCC model.
Social Determinants of Health (SDoH) risk score
The SDoH risk score takes into account 258 publicly available socio-economic data sources. It provides a deeper view of patients and their likelihood of having adverse events by differentiating between patients with similar clinical profiles but different behavioral and socio-economic factors.
Soliton Suggested Risk Score (SSR)
This AI engine generated risk score takes various clinical triggers, labs, procedures, admissions and discharge and other data to provide a high, medium or low risk score for each patient.
Customizable Risk Stratification Models
Clinical Risk Score
The clinical risk score allows providers to enter their perceived risk for each individual patient based on their expertise and intimate knowledge of their patients.
This model also allows providers to use the Soliton AI engine to create configurable event triggers to assign risk levels to patients.
Contact us for more information on how we can better help you navigate the Value Based Care world through optimal risk stratification.