ACO Risk Model
A Web-based modeling, planning and collaboration tool that provides you with a well informed view of the future of Accountable Care.
In addition to the traditional ‘insurance risks’ providers are being asked to take on, the increasing complexity of medical sciences and the rapid emergence of powerful new diagnostic and therapeutic tools are driving a new risk: capital-intensive ‘procedure lock-in.’ While these new technologies offer enormous potential benefits, they often require large up-front investments in facilities, equipment and qualified personnel. A thorough understanding of the current and future characteristics of the local and regional markets enables providers to more properly assess the risks inherent in these investments and ensure the existence of a significant, stable patient base.
Helping providers meet these challenges is the latest offering from PotentiaMED: PMED analytics ACO risk modeler. Drawing on highly detailed demographics, epidemiological and clinical data sources, the PMED ACO risk modeler provides an intuitive, graphical environment in which executives can explore local, regional and national markets, how these markets are expected to evolve, and the effects these changes will have on their individual organizations.
Incorporating tools from IBM’s world-class analytics platform including Cognos TM1 and SPSS packages, PMED analytics ACO risk modeler enables decision-makers to bring analytical insights directly into the planning process. By grounding the long-term planning process in a reliable, data-driven model of current and future market conditions, PMED ACO risk modeler helps organizations make superior decisions about resource allocation, training and recruitment efforts, negotiations and relationships with payers and providers, and long-term growth strategies.
PMED analytics ACO risk modeler leverages the PMED proprietary databases, including demographic and outcome data in implementing PMED analytics to:
- Understand population health data
- Develop accurate cardiac risk models
- Identify referral pattern populations
- Enable multivariable testing & scenario analysis
- Forecast utilization, and understand capacity requirements
- Recognize patients at higher risk for complications, and develop interventions
- Define recovery times for patients with multiple co-morbidities
- Shorten patients’ length of stay and reduce costs of treatment
- Determine KPI's to enable prioritization of future initiatives
- Define strategy based on an informed view of the future
