HEALTHCARE PROCESS IMPROVEMENT USING
SIMULATION
Nadja Damij and Talib Damij
Faculty of information studies, Novi trg 5, SI-8000 Novo mesto, Slovenia
Faculty of economics, University of Ljubljana, Kardeljeva ploščad 17, SI-1000 Ljubljana, Slovenia
Keywords: Healthcare process, Activity table, Simulation.
Abstract: This study is concerned with business process modelling and improvement as an essential work in creating a
successful and competitive enterprise. To achieve this goal, we use a technique called the Activity Table to
develop an as-is process model. When the process model is created, it must be checked and validate to find
out if it reflects the real process. Then the model is analysed carefully using different "what-if" questions.
Scenarios of process behaviour are then simulated to find out their impact on process performance and to
compare them in order to choose the best solution. The business process ‘‘Surgery” is used as an example to
demonstrate the implementation of the methodology.
1 INTRODUCTION
In recent years process improvement has become a
very important way of ensuring changes in an
organization’s structure and functioning to create a
better, more competitive and successful enterprise.
The purpose of this study is to present the
utilization of a simulation technique in the field of
business process improvement, which is invaluable
in developing an efficient, competitive and
successful organization.
In addition to the introduction, the paper has four
other sections. In Section 2, we introduce business
processes and the problem of business process
modelling using the Activity Table modelling
technique.
In Section 3, we discuss simulation as an
imitation of the functioning of a real-world process
over time. The functioning of the process is
observed in order for it to be completely understood.
Understanding the behaviour of a process over then
time enables us to develop a model and create one or
more simulation scenarios that are then tested by
running the simulation software.
In Section 4, process improvement is presented
as a method to improve the organization’s processes
by carrying out changes in their functioning
necessary to make them more effective, with a high
quality level, without duplication of procedures and
activities, and with reduced costs, in order to achieve
greater customer satisfaction. A process called
"Surgery" is used to demonstrate the simulation
technique in process improvement. In Section 5,
some useful remarks and conclusions are presented.
2 PROCESS MODELLING
The functioning of any enterprise may be
represented by a number of processes, called
business processes. Most of the problems faced by
enterprises concern are internal business procedures
that are neither well defined nor particularly efficient
(Hales, 1993).
A business process is defined by (Hammer et al.,
1993) as a collection of activities that takes one or
more kinds of input and creates an output that is of a
value to the customer.
A business process is defined as a structured,
measured set of activities designed to produce a
specified output for a particular customer or market
(Davenport, 1993).
Business processes are horizontal processes that
link together the various functional activities that
deliver the output of the enterprise. They consist of
functional work processes that either produce or
provide support services for those work processes
that do (Watson, 1994).
Work processes are the sets of procedures or
activities, tasks, and steps where the real work of the
422
Damij N. and Damij T. (2010).
HEALTHCARE PROCESS IMPROVEMENT USING SIMULATION.
In Proceedings of the Third International Conference on Health Informatics, pages 422-427
DOI: 10.5220/0002717504220427
Copyright
c
 SciTePress

organization is accomplished to produce the
economic output that generates the profitable return
on the capital employed (Watson, 1994).
Business process modelling generates a model to
describe a certain business process in an enterprise
using different techniques. The model is a
representation of a business process and reflects its
reality by capturing all the necessary information on
process behaviour. The modelled process is then
analysed and improved instead of the real business
process. In this paper, we present process modelling
using a technique called the Activity Table.
The activity table is organized as follows: the
first column represents the business process and the
second column shows the work processes of the
business process discussed. The activities of the
listed work processes are shown in the rows of the
third column. The resources are introduced in the
remaining columns of the second row grouped by
the departments to which they belong.
To make the activity table reflect the real world,
we link the activities horizontally and vertically.
Horizontal linkage means that each activity must be
connected with those entities in the columns which
are involved in it. Vertical linkage is used to define
the order in which the activities are performed. Each
activity is connected with one or more predecessor
activities, except the first one, and is also linked to
one or more successor activities, except the last
activity.
To model a process, the activity table uses
symbols such as:
□, ◇, →, ↓, ○, and .
Symbol □ in square(i,j) means that resource(j)
performs activity(i), where j ranges from 1 to the
number of resources and i ranges from 1 to the
number of activities. Symbol ◇ in square(i,j) means
that activity(i) is a decision activity. Symbols → and
↓ are used to connect the activity horizontally and
vertically. An arrow → drawn from square(i,j) to
square(i,k) shows the horizontal linkage of
activity(i). An arrow ↓drawn from square(i,j) to
squre(k,j) indicates that activity(i) is linked
vertically to its successor activity(k). Symbol
○
indicates a start of the process and symbol
means
an end of the process.
Surgery: The business process “Surgery” was
modelled by developing Table 1, which represents
the activity table.
3 SIMULATION
A simulation is the imitation of the operation of a
real-world process or system over time. Simulation
involves the generation of an artificial history of a
system, and the observation of that artificial history
to draw inferences concerning the operating
characteristics of the real system (Banks et al.,
2001).
The functioning of the process discussed is
observed in order for it to be understood completely.
Understanding the behaviour of a process over time
enables as to model it and create a simulation
scenario based on a set of data and assumptions
about the operation of its activities.
When the process model is created, we have to
check and validate it to find out if it reflects the real
process. Then the model is analysed carefully using
different "what-if" questions to test several options
and possibilities concerning the functioning of the
process. Such versions of process behaviour are then
simulated to find out their impact on process
performance and to compare them in order to choose
the best solution.
Business processes are modelled with the aim of
analysing their current states within the organization,
as well as improving them through the execution of
potential ‘‘what-if” simulation scenarios (Aguilar-
Saven et al., 2002). The use of scenario-based what-
if analyses enables the design team to test various
alternatives and choose the best one (Laguna et al.,
2005).
Process modelling, creating scenarios of its
behaviour, and running its simulation enable the
analyst to obtain knowledge and new ideas that
could be very important in process improvement.
This is usually achieved by changing the simulation
input data and analysing the simulation outputs. This
technique leads us to find out which data or
parameters are essential for process improvement.
Discrete-event system simulation is the
modelling of systems in which the state variable
changes only at a discrete set of points in time.
Discrete-event models are appropriate for those
systems for which changes in system state occur
only at discrete points in time (Banks et al., 2001)
and business processes are such systems.
Below we list some of the major concepts of a
discrete-event model of a system, as they are defined
in "Discrete-Event System Simulation" by Banks,
Carson, Nelson and Nicol:
- System: A collection of entities (e.g., people and
machines) that interact together over time to
accomplish one or more goals;
- model: An abstract representation of a system
that describe a system, usually containing
structural, logical, or mathematical relationships
HEALTHCARE PROCESS IMPROVEMENT USING SIMULATION
423

Entity 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.
Activ ity
Reception Office Clinic X-Ray Surgery Block
Surgery
Registration
1. Register
patien t
2. Forward
patien t
HospitalizationCarrying out Surgery
Business Process
Work Process
Lab Anaesthesia
Nurse Doctor Nurse-In Doctor Doctor
Department
Anaesth etist Su rgeon Patien t
4. Send
blood
3. Examine
patien t
Nurse-Cl Surgeon Technician
5. Test
blood
6. Forward
blood
findings
7. Decide
type of
treatment
8. Issue a
release
report
9. Order
hospitali-
zation
10.Accept
hospitali-
zation order
11. Prepare
exam ination
order
12.Make x-
ray
exam ination
13. Create
anaesthetic
report
14. Forward
medical
findings
15. Analyze
findings
16. Decide
on surgery
17. Explain
surg ery
18.
Schedule
surg ery
19. Get
inform ation
for
anaesthesia
20. Sign
documents
25. Wake
up patient
26. Post-
surg ery
recovery
21. Wait for
surg ery
22. Prepare
patien t
23. Carry
out
anaesthesia
24. Carry
out surgery
YES
NO
YES
NO
Figure 1: The Activity table.
HEALTHINF 2010 - International Conference on Health Informatics
424

Figure 1: The Activity table (cont.).
which describe
- the system in terms of state, entities and their
attributes, sets, processes, events, activities, and
delays;
- State: A collection of variables that contain all
the information necessary to describe the system
at any time;
- Entity: Any object or component of the system
which requires explicit representation in the
model (e.g., a server, a customer, a machine);
- Attribute: The properties of a given entity (e.g.,
the priority of a waiting customer, the routing of
a job through a job shop);
- Activity: A duration of time of specified length
(e.g., a service time or arrival time), which is
known when it begins (through it may be defined
in terms of a statistical distribution);
- Delay: A duration of time of unspecified
indefinite length, which is not known until it
ends (e.g., a customer’s delay in a last-in, first-
out waiting line which, when it begins, depends
on future arrivals);
- Clock: A variable representing simulated time.
4 PROCESS IMPROVEMENT
The relationship between the essence of business
process modelling and overall business effectiveness
and the efficiency of the organization depends on the
consumer’s satisfaction with the desired output. If
the latter is everything the consumer required and
aimed for, business processes are well-designed,
efficient, as well as effective and will in time result
in successful organizations (Al-Mashari et al., 2000).
On the other hand, if the consumer lacks appropriate
satisfaction or the organization’s growth and profit
are decreasing, it is crucial to understand that
improvement of business processes has to be
planned and carefully carried out.
The purpose of business process improvement is
to improve the way an organization functions by
carrying out the necessary changes in their processes
to give them more value, increase effectiveness,
without duplication of procedures and activities, and
to make them less costly, in order to achieve greater
customer satisfaction.
A great deal of effort has been focused on
continuous improvement of subprocesses, activities,
and tasks (Harrington et al., 1997). If the
management of the organization stops the evolution
of the process once business process improvement
Entity 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.
Activity
36. Issue a
release form
35. Check
recovery
34. Resting
33. Treat
patient
32. Place in
Clinic
31. Check
recovery_IN
30.
Resting_ IN
29. Observe
patient
Recovery
27. Place in
intensive
28. Treat
patient_IN
Anaesthetist Surgeon PatientDoctor
Surgery
Surgery Block
Nurse Doctor Nurse-In Nurse-Cl Surgeon Technician Doctor
Clinic Lab X-Ray Anaesthesia
Business Process
Work Process
Department Reception Office
HEALTHCARE PROCESS IMPROVEMENT USING SIMULATION
425

has been completed, the organization will lose the
value gained. Consequently, continuous
improvement tasks need to be performed.
The purpose of this work was to carry out
process improvement using a simulation technique.
To do that, we simulate one or more alternative
versions of the business process discussed in order
to change its functioning and improve it by solving
real problems, removing obstacles and identifying
existing bottlenecks in the process.
To run the simulation, we used iGrafx software.
The steps of process simulation are summarized as
follows:
a) Create the process model from the
information stored in the activity table;
b) Define the properties of process activities;
c) Define process simulation parameters and run
the simulation;
d) Carefully analyse the simulation results;
e) Make changes to improve the process if
possible; and
f) Return to c if changes have been made.
Business process improvement is an iterative
process and therefore it should be repeated several
times in order to produce a better and more efficient
business process.
Surgery:
To carry out simulation of the process
‘‘Surgery”, a process model was built by using the
information stored in the property table (Table 1) to
define the model’s characteristics.
The simulation of the process ‘‘Surgery” was run
taking into consideration a Clinic for abdominal
surgery with a capacity of 30 beds; 20 patients were
already in the Clinic in different phases of the
process, and 30 patients were scheduled for different
forms surgery. In addition to this, we postulated that
3 patients of the planned 30 patients were
hospitalized every day.
To do that, a standard calendar was used, that is,
8 h/day, 5 days/week and 22 days/month. And the
following resources were defined: 1 Nurse and 1
Doctor in the Reception Office, 4 Nurses and 4
Surgeons in the Clinic, 1 Nurse in the Laboratory, 1
Nurse and 1 Doctor in the X-Ray unit, 1 Nurse and 1
Doctor in Anaesthesia, 2 Anaesthetists and 2 Nurses
for performing anaesthesia in the Surgery block, 2
Anaesthetists and 2 Nurses for waking up patients
and post-surgery recovery in the Surgery block, and
2 Nurses working with the Surgeons to carry out
operations in the Surgery Block.
Iteration 1: The results of running the simulation of
the business process ‘‘Surgery” are as follows:
- Average cycle time for one patient is 14.68 days;
- Elapsed time for carrying out surgery for 30
patients is 25.57 days. This is understandable
because the simulation software needed 10 days
to enter 30 patients into the Clinic (3 patients per
day);
- Average time for performing different activities
before surgery is 2.94 days. This is 1.43 days for
performing various medical examinations in the
Reception Office and Clinic, and 1.51 days
waiting for surgery;
- Average time for performing anaesthesia,
surgery and post-surgery recovery in the Surgery
block is 7.1h;
- Average time for recovery in Intensive care is
4.26 days;
- Average time for recovery in the Clinic is 6.39
days;
- Average time for creating a release form is
0.78h.
Iteration 2: These results show that the process
‘‘Surgery” could be improved by considering the
following suggestions:
1. The time for performing different activities
before surgery (average is 2.94 days) could
be shortened by carrying out most of these
activities before the patient’s hospitalization
or organizing them better;
2. The recovery time in Intensive Care (average
is 4.26 days) should be reduced when
possible; and
3. The recovery time in the Clinic (average 6.39
days) should be shortened when possible.
To implement the above suggestions, we changed
the process model and prepared a new simulation
scenario that takes into the account the following
changes:
- To implement the first suggestion, activities 11-
13, 16-18 and 21 are removed from the process
model because the patient obtains the necessary
medical findings before hospitalization;
- To implement the second suggestion, the
recovery time in the Intensive Care (activities
27-31) is reduced by 0-3 days;
- To implement the third suggestion, the recovery
time in the Clinic (activities 32-36) is reduced by
3-7 days.
After running the simulation using the new scenario,
we obtained the following results:
• Average cycle time for one patient is 9.14
days (instead of 14.68 days);
• Elapsed time for carrying out surgery for 30
patients is 19.20 days (instead of 25.57);
HEALTHINF 2010 - International Conference on Health Informatics
426

• Average time for performing different
activities before surgery is 5.6 hours
(instead of 2.94 days);
• Average time for performing anaesthesia,
surgery and post-surgery recovery in
Surgery block is 6.99 hours (instead of 7.1
hours);
• Average time for recovery in Intensive Care
is 0.72 days (instead of 4.26 days);
• Average time for recovery in the Clinic is
6.28 days (instead of 6.39 days);
• Average time for creating a release form is
0.59 hour (instead of 0.78 hours).
The simulation results obtained from iteration 2
represent a great improvement of the "Surgery"
process and should be implemented.
5 CONCLUSIONS
The aim of this paper was to introduce simulation as
an important and very helpful technique capable of
handling the difficult and complex problem of
business process improvement.
To demonstrate this, simulation of the business
process "Surgery" was carried out in two iterations.
In the first iteration, we ran the simulation of the as-
is model of the business process; that is, the model
of the process as it exists in reality. This iteration of
the process simulation helped us to imitate the
process and discover all its problems. In the second
iteration, we ran the simulation of the “to-be” model
of the process; that is, the model after making
changes necessary to improve it.
The results obtained from both models were very
encouraging, and a simple comparison between them
shows that a great improvement was made to
process performance by reducing the average cycle
time for one patient from 14.68 to 9.14 days. This
result may lead to an increase in the quality of the
process (e.g. by reducing waiting time).
Also, the time elapsed for carrying out surgery
for 30 patients was reduced from 25.57 to 19.20
days. This fact means reducing the cost of the
surgery carried out. Unfortunately, we cannot show
the value of cost minimization because the staff of
the Clinic refused to divulge any information
concerning the costs of their activities or medical
personnel.
In addition to this, we are certain that further
improvements are possible, particularly in the
framework of the work process Recovery.
Finally, we maintain that this simulation is a
very capable and useful technique, and could be
utilized successfully widely in the field of business
process improvement.
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