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.
Example of Simulation Usage:
• 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
Areas where simulation has been used:
• 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.
Value of the Use of Simulation Solutions
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
