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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.
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
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