Competition among healthcare organizations has
become intense, especially for outpatient services
in Taiwan. Increasingly, traditional inpatient services
are provided on an outpatient basis because
of technology advancement as well as the demands
of national health insurance (NHI) [1]. As a result,
outpatient services play a major role in healthcare
delivery. Two-thirds of Taiwan’s total NHI expenditure
is currently spent on outpatient services.
Hence, managing outpatient services is of great
importance to healthcare organizations.
Since people are free to select their healthcare
providers under NHI, walk-in patients are common
in most outpatient clinics in Taiwan. Therefore,
managers of these outpatient clinics may face the
following problems: (1) they need to maintain high
levels of personnel and equipment to provide
services within a limited period of time; (2) they
must employ diverse professionals such as physicians,
nurses, social workers, administrators, etc.
(however, patients are prone to select other clinics
if, during visits, they encounter too lengthy waiting
or throughput times); and (3) managers must
predict exactly how many patients will come to
the outpatient clinics and at what time. It is nearly
impossible to predict these if outpatient clinics
lack an optimal scheduling system. Thus, it becomes
most important and quite complicated to
manage a scheduling system because most patients
prefer to walk-in directly instead of getting an
appointment. For example, the walk-in rate is 72%
compared with a 28% scheduled rate of subject
clinics in this research study.
Operations research and management techniques
have been applied to healthcare organizations
to gain insight into the results of restructuring or
reengineering operation systems. Previous studies
have used motion/time method (MTM) studies,
queuing models [2/6], and simulation models to
improve the healthcare delivery process. MTM
studies are usually applied to explore each specific
activity movement, while queuing studies are
aimed to target system’s waiting behavior or waiting
line, but is restricted by some theoretical
assumptions. However, both MTM and queuing
models ignore interactions among subsystems,
although they can clearly define the healthcare
delivery process. Computer simulation allows much
more accurate modeling of these systems, including
transient conditions based on random patient
arrival and service time with realistic statistical
distribution, and can more potentially reveal the
results of various alternatives, although it also
requires more theoretical and technical learning.
Some authors employ simulation methods to model
the complex and general systems successfully [7/
20]. They not only provide alternative solutions to
a particular problem in the systems, but also
evaluate human resources, equipment utilization,
process change, and benefits in the rapidly expanding
health delivery field. Thus, simulation is a
useful tool to analyze and exhibit the results of
system alternations, instead of utilizing trial and
error processes to reach optimal policy, saving both
administrator and patient exertion.
This study proposes a better scheduling philosophy
by showing how a simulation model can be
applied to outpatient clinics that provide registration
for both the scheduled and walk-in patients,
and recommends the best feasible solution to this
kind of system. Several simulated alternatives
demonstrate the impact on outcomes such as
patient waiting time and throughput time.