Technology enables payers to balance provider cost, quality

October 1, 2007

What if MCO payers could measure providers' costs and outcomes in a single top-down program? What if they could standardize regulations, and immediately test their effectiveness? What if payers could actually help facilities and providers strike a balance between business efficiency and quality patient care-without shutting anyone down?

What if MCO payers could measure providers' costs and outcomes in a single top-down program? What if they could standardize regulations, and immediately test their effectiveness? What if payers could actually help facilities and providers strike a balance between business efficiency and quality patient care-without shutting anyone down?

These "what ifs" become reality when payers introduce decision support technology to providers for simulating costs and outcomes. Such in-depth predictive analysis helps payer and provider evaluate business performance, and set nationwide benchmarks.

In today's challenging healthcare environment, providers face various issues: increased emergency department (ED) volume, decreasing access points, diminishing hospital capacity, and population growth.

This sets the stage for the next electronic evolution phase: bringing that data into a modeling simulation program, where providers can get tomorrow's history today, and leverage predictive capabilities to make viable business decisions.

This entails inputting as much information as possible into the system to reflect the impact on patients, the cause of the diagnosis, the quality of healthcare delivered to patients, and various outcomes.

Though inputs vary based on providers' goals, some standard qualitative and quantitative inputs apply, including caseloads, on-time starts, turnover times, and milestones.

This detailed, in-depth process results in a comprehensive business overview, which can then be applied to facility design, department-specific productivity improvement, staff planning, emergency preparedness, bed capacity management, and admissions processes.

Consider one example of simulation technology in action: A post-anesthesia care unit (PACU) wants to deploy new technology, and is deciding between wireless and wired monitoring. It captures the original process in a flowchart, covering patient flow and quantitative cycle times of each task for a patient going through that flow.

These variables are plugged into the decision support program and then the MCO runs one example with a fixed number of beds in the PACU (for the wired scenario), and another with a flexible number of beds (for the wireless).

The result is a direct comparison of the two options that help administrators determine which option delivers the highest ROI, and which is smartest to implement.

On a higher level, payers can use the technology to evaluate their providers, and find a standard process that optimizes all inputs. The payer tests all possible processes to find the most balanced one, and implements it, which helps them reimburse on a standard cost-based level.

Simulation technology ultimately impacts the cost, quality, and risk of MCO processes in the following ways:

In short, simulation technology helps payers and providers shorten timelines and reduce resources to cut costs. Moreover, they can customize their systems around long-term financial plans, and develop growth strategies. MCO payers and providers can turn to simulation platforms for support, and in the process, transform "what if" into "what next" for their organizations.

Kurtis E. Shampine, is vice president and general manager ProModel Life Sciences Solutions and Dale Schroyer, project manager and sr. simulation consultant for ProModel, a leading simulation, business process optimization and decision support company.