Accelerate value‑based reimbursement scalability

Enable automation and stakeholder visibility to scale VBR initiatives.

Population Payment Management

Most healthcare entities face great challenges bringing their value-based initiatives to fruition outside of a small number of limited-scope pilot programs. This is due, in large part, to a lack of automation, modeling and a meaningful ability to project realistic opportunities, or losses, for a given arrangement. Scaling and optimizing value-based reimbursement programs (such as shared savings, bundles, episodes and P4P) requires integrated modeling and “what-if” analyses, a detailed understanding of member populations and the ability to continuously monitor program performance in a highly transparent manner for all stakeholders.

Our Approach

Edifecs Population Payment Management delivers a scalable platform complete with capabilities that enhance a healthcare entity’s ability to target, design, administer and optimize their value-based initiatives. It models and analyzes impact of value-based reimbursement models; health plans and ACOs of all types can perform "what-if" analyses of future medical costs and gain enhanced intelligence into the risk of their member populations. Flexible templates reduce program design complexity and impactful analytics improve performance for all stakeholders while enhancing provider buy-in.


Drive program success via targeted alignment

Deftly target specific provider networks and member populations.

  • Identify, attribute and maintain the alignment of specific providers and networks to select member populations.
  • Identify high-risk populations and high-cost utilizers based on a variety of population health factors.
  • Determine program rosters based upon both financial and clinical indicators (e.g., highest performing – cost & quality - post-acute care partners for an episode of care arrangement).
  • Perform targeted budget calculations for each provider based upon risk and inflation adjusted profiles.

Fluidly design program and financial parameters

Model and analyze financial arrangements. Leverage program templates.

  • Perform "what-if" and ROI analyses on budget calculations, risk adjustment methodology and member attribution.
  • Seamlessly leverage the results of analyses/modeling to generate custom program designs.
  • Leverage out-of-the-box program templates based on MSSP, CJR, BPCI and commercial health plan templates to streamline program set up and improve scalability.
  • Enhance the ability to predict future costs, from service utilization to individual members based upon risk profiles.

Insightfully manage program performance through stakeholder visibility

Ensure complete and timely financial and population health transparency.

  • Support extensible payment workflows including interim and final settlement mechanisms.
  • Timely, actionable reports and dashboards highlighting KPIs, metrics and budget/savings calculations.
  • Enable “at-a-glance” review of the program performance of all alternative payment initiatives.
  • Leverage Edifecs "big data" platform to streamline data connectivity and insights for all program stakeholders.

Scale program initiatives through automation and transparency

Automate  all design and contracting processes, including attribution, risk adjustment, calculation of savings payments, and application of quality measures to program payments.

  • Intelligently optimize program operations and drive value-based care and reimbursement initiative scalability.
  • Identify and facilitate program design changes (such as moving to a two-sided risk model earlier) based upon provider performance.
  • Enable decision support for use by health plans during program renewal with providers. Provides dashboards and reports for health plan sales and marketing teams to effectively communicate program benefits to employers and plan sponsors
  • Deliver a robust and highly scalable platform which enables bringing pilot projects to enterprise and community level.
  • Reduce data latency due to disconnected systems and improve the usability and impact of real-time intelligence.