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What is Healthcare Process Simulation?

Healthcare Process Simulation: A Primer

Process Simulations are dynamic computer software tools that enable hospitals to conduct accurate, objective predictive analyses of the effects of process improvements, facilities changes, and new designs prior to implementation. Process Simulation essentially allows you to “tear the roof off the building”, examine the working environment, and “reach down and turn the dials” on the processes to see the effects of change, so as to fully understand the effects on the entire system prior to implementation. Since often no single solution is adequate to solve complex issues, Process Simulation allows you to fully understand the full effects of multiple, complex changes before they are implemented.

We know from experience that “Best Practices” don’t always equal “Best results” because the upstream and downstream effects of the changes have not been fully accounted for, measured, and anticipated. Therefore, the results of Best Practices are sometimes stunted by upstream and downstream process barriers. Even worse, when making complex changes and multiple implementations, the results are often impossible to predict accurately using conventional tools such as spreadsheets and flowcharts, making consensus on improvements ideas difficult to attain.

Process Simulation tools allow for unprecedented predictive analysis and a complete understanding of the effects of even the most complex process changes. Thus the technology allows the user to:

1. Simplify even the most complex problems,
2. See key issues and results of change more clearly, and
3. Make better and more objective decisions.

Attributes of Simulation for Analytics

In general, the benefits of using process simulation as a predictive analysis tool in healthcare lies in its ability to deal effectively with four key concepts:

1) Variability in and between processes. All human activity is variable. That is, no two iterations of a process performed by humans are exactly the same…there is always some degree of variability in process time. Variability within a series of processes has the effect of compounding. That is, the variability of one process directly affects the next process, and the next, and the next. This variability can severely alter total system process times and flow. (For instance, there is no single LOS for patients in an ED…all LOS’s are different). Thus, it is necessary to account for this variability in order to accurately examine process parameters such as patient flow, throughput, process times, wait times, staffing requirements, etc. Average numbers commonly used in process analysis fail to account for process variability, resulting in what is called the “error of averages”, which can lead to misleading results, bad decisions, poor financial performance, and poor patient experiences. Because spreadsheets and flowcharts that utilize averages do not account for this important variability, they can yield misleading conclusions.

Simulation takes variability into account, thus allowing a much more realistic depiction of real-life processes, and more accurate predictions of throughput, process times, and other key factors. ProModel’s health care-specific softwares, such as MedModel, ED Simulator, and Process Simulator, use distributions (or data curves) that accurately represent the processes and its inherent variability to derive their results, thus replicating reality. Because simulations account for this variability, they are inherently more accurate that static analysis tools such as spreadsheets and flowcharts.

2) Interdependencies. Because hospital processes are interrelated, changing one affects the others in the system. Coupled with the inherent and often drastic variability within processes, these interdependencies make process analysis particularly complex. Simulations take the interdependencies of processes and resources into account, thus allowing the user to see how changes to one process can affect others both upstream and downstream. Without this capability, examination of system-wide processes and changes becomes extremely difficult, particularly in cases of complex systems such as Emergency Departments.

3) Time. Processes take place over time. Furthermore, everything from patient acuities to volumes to technologies can impact processes over a day, week, or year. Thus, in order to properly account for the effects of change to processes, particularly subtle change, one must be able to evaluate changes over a span of time. ProModel simulations can run for days, weeks, months, even years, in order to determine the true long term effects of changes to a system. This allows the user to see how changes, combinations of changes, and even subtle changes, will affect the overall system over the course of extended time periods.

4) What-If’s. Because simulations account for variability, the interdependencies within a system, and the effects of time, they are accurate representations of even the most complex real-life systems. Because of this inherent accuracy and the structure of a model, simulations allow the user to test the effects of proposed changes on the system. By testing possible solutions to problems, the model becomes a risk-free environment for the evaluation of ideas and potential solutions. Combinations of complex solutions can be tried in minutes using a model that might take months to implement and analyze of the hospital floor. Thus, simulations serve as an easier, more effective predictive analysis tool for decision-making.

Accuracy

By taking into account variability and interdependencies of processes, the complexity of multiple inter-related processes, and the effects of change over time, ProModel Healthcare simulation are very accurate and objective. They are so accurate (documented accuracy versus real-life as high as 99%) that they become highly functional and reliable predictive analysis and ongoing CPI (continuous process improvement) tools.
Complexity

Because of the robustness of the technology, simulations can account for many variables and processes simultaneously, enabling a customer to build the complexity of their scenario(s) into a useable format for decision-making. ProModel simulations have replicated systems containing thousands of concurrent variables. Thus the technology allows the user to:

1) Simplify even the most complex problems,
2) See key issues and results of change more clearly, and
3) Make better and more objective decisions.

Decision Support

Simulations are accurate and objective predictive analysis tools. And since they allow you to get to answers you might otherwise not attain, they become valuable decision support tools for management. By analyzing everything from patient flow to wait times to staff utilization, simulations allow management a better overall view of systems and operations. Their objectivity allows for solid decision-making with objective criteria.

• Patient flow
• Patient wait-times
• Staff utilization
• Process flow and bottlenecks
• Patient access
• Complex solutions to multiple issues
• Staffing mix analysis
• Patient acuity studies
• Cost and revenue enhancement

• Emergency Departments
• Bed Management
• Labs
• Radiology
• Patient Transfers
• Outpatient clinics
• LDR/LDRP
• Process and paperwork flow
• Conceptual design of new facilities
• Facility expansion (which ones and where)
• Overall system staffing requirements
• Overall system patient flow
• Cost and revenue analysis

Project value is greatly enhanced when the developed simulation is used beyond the initial project by the hospital staff to evaluate scenarios and make continuous process improvement. Local understanding and involvement greatly facilitates change management and the probability that project recommendations will be successfully implemented and real value obtained.

The value created with an effective Process Simulation engagement can typically be in the millions of dollars and the benefits may include:

• Decreased LOS and wait times by as much as 40% - from at least 20 minutes up to hours savings
• Decreased LWOT’s by 5% to 30%
• Increased throughput capacity of existing facility by over 15,000 patient annually while maintaining existing staff levels and LOS
• Decreased Radiology turn-around time by nearly 40%
• Decreased lab turn-around time
• Improved design and process flow before plans were finalized

For a typical model and implementation, the simulation efforts frequently uncover the following:

• Hidden process issues and problems
• Staffing inefficiencies
• Non-value-added and redundant processes
• Room and resource allocation problems
• Bottlenecks and capacity constraints
• Under- and over-utilized resources, rooms, and staff
• Ancillary issues such as issues with radiology, lab or transfers