SCIO's Prospective Cost of Care Model was one of only four models evaluated in the report that combines diagnosis, pharmacy and prior cost data in predicting risk. The paper is the first the Society has issued since 2007, which pre-dates the changes to healthcare brought on by the Affordable Care Act (ACA), and marks the first time SCIO has been included.
"While risk scoring has always been an important factor in healthcare, the changes brought on by the ACA make it even more critical to get it right," said Lalithya Yerramilli, vice president analytics at SCIO Health Analytics. "Payers and providers both want to control costs and apply their limited resources where they will deliver the greatest ROI, in patient health as well as financially. The rigorous evaluation performed by the Society of Actuaries demonstrates the value SCIO brings as well as the comprehensiveness of our approach. We are proud to have merited this impartial validation of the effectiveness of our risk scoring model."
SCIO's Prospective Cost of Care Model was evaluated as a prospective model, i.e., one that uses data from one year to predict medical expenditures for the following year. The SCIO model aims to predict the total costs and financial risk per member using their healthcare utilization, prior year's total health expenditures and demographic details. The inclusion of behavioral, demographic and attitudinal data as a standard part of its analytics solutions enables SCIO to deliver a 360 degree view of individuals. This view not only reflects the cost that will be accrued by individuals if they continue on their current health trajectory, but also helps payer and providers make decisions around how effective more care will be (impactability) and how willing individuals are to follow plans of care (intervenability).
SCIO was one of four vendors reviewed that follow the prospective model, which incorporates diagnosis (medical) data, pharmacy data and data on prior costs. While accepted as being less accurate overall than the concurrent model of using information from one year to explain medical expenditures in that same year, the prospective model is highly valued for its ability to guide future behaviors and actions to improve outcomes.
The study reviewed data from a broad cross-section of patients, beginning with children less than one year old and including males and females in tightly defined age groups up to 64 years of age. Adults older than 64 were eliminated as it is expected most will use Medicare rather than commercial health plans. The study design also looked at individuals in specific disease categories, including heart disease, mental illness, diabetes, low back pain, asthma and arthritis.
"Although there is a lot of uncertainty regarding the direction of healthcare at the moment, it is highly likely that the industry will continue to transition from fee for service to value-based care. That factor alone underscores the growing need to be able to predict risk with greater accuracy," said Yerramilli. "As this study demonstrates, SCIO has the analytics capabilities and expertise to help payer, provider and life sciences organizations manage risk more effectively."
Based in West Hartford, Connecticut, SCIO Health Analytics is a leading health analytics solution and services company. It serves healthcare organizations across the continuum including over 20 provider groups and 30 health plans representing more than 90 million members, four of the top six PBMs, and clients in 30 countries for 8 of the top 15 global pharmaceutical companies. SCIO provides predictive analytic solutions and services that transform data into actionable insights, helping healthcare organizations create the understanding that drives change through care, network and reimbursement optimization as well as commercial effectiveness. SCIO's insights as a service approach supports the shift to value-based care, solving healthcare problems simply and efficiently. Visit SCIO's new website for up to date information on their product and solution offerings: www.sciohealthanalytics.com