Critical Review on Pros and Cons of Queueing as a mathematical tool
for problem solving in healthcare sector.
Queuing theory is one of the formal way of studying a concept of waiting
in line and related discipline in the department of operational
management.
Queuing theory can be used to assess things like customer waiting time,
staff schedules, customer waiting environment, staff productivity and
working environment.
The conventional queueing system like long queues can lead to unfair,
frustrating and unexplained waiting time which will affect the overall
satisfaction of the customers towards service.
Healthcare industry is also like a service oriented industries, functioning
in a increasing competitive industry.
Several literature studies have shown the dissatisfaction of the
customers due to long waiting time and also a common source of
conflicts and anxiety among customers and staff.
Healthcare sector is honeycombed with delays. Most of us would have
waited for days or a week to get an appointment with the doctor or to
schedule any procedures and also waiting for our turn in OPDs.
Most of patients have to wait for beds in hallways, and also experience
delays for diagnostic procedures or surgery.
Disparity between the capacity available to meet the demand and
demand for service has resulted in a long delays in healthcare sector.
Also resources, which are necessary, are unscheduled and random in
nature.
In healthcare facilities, decisions on number of beds, when and how to
allocate the staff, equipment’s and other resources is important to
minimize the waiting period of patients. And this is more difficult than
the service oriented industries, as it involves huge cost and adverse
consequences.
Queueing theory is one of the most practical and very powerful tool to
formally manage the delays also which requires relatedly little data and
sample to use.
This theory has been very successfully applied in other service oriented
industries.
Unfortunately, most of the hospitals distract the waiting period of
customer by providing comfortable conditions, entertainment (TV) and
refreshments (coffee).
In hospitals, queuing theory can be used to assess a different variables
such as consultation time, patient waiting time, patient counseling time,
time taken for outpatient procedures and technician staffing levels.
Other use of queuing analysis and simulation in healthcare includes
Infrastructure and resources planning for public health and management
of disasters.
Queuing models are very helpful in many are part of the hospital which
mainly deals with elective cases.
Her queueing is also helpful in identifying long term resource or capacity
needs in the hospitals which primary deal with non-elective admissions.
The simplicity and the speed of mathematical queueing help us to
quickly formulate and compare various options for service.
Healthcare service system is one of the complex system in which we can
expect predictable and unpredictable events or sources of variability.
In such conditions we can analyse the patient data and frequency of
admissions by using queueing methods which will help in determining
the arrival rates and length of the patient stay in hospital after
admission.
The time spent by a patient in hospital due to pre-op evaluation
admission surgical procedures post of evolution and recovery. Most of
the times patient will be referred to different specialties like cardiology,
oncology or neurology which will also determine the stay of the patient
in hospital.
Queueing theories could be used to analyze these types of
demographics and patient data to prepare the hospital with the required
amount of resources so that amount of time spend unnecessarily by the
patient will be reduced.
These theories can also be accurately used in services like home health
agency other than health care hospitals resources.
Queueing concept will help in discharging the patient quickly, preventing
congestion, reducing the waste of time, better care delivery, providing
resource planning saving money and also increase in profits.
Conditions under which Queueing does not work and suggested
alternatives
However hospitals are not simple service sector, it consists of complex
interdependent variables which vary significantly from one case to other
case.
For example in the clinic most of the patients comes with the
appointments but same time you can expect cases which are emergency
nature and need attention without appointments like cardiac cases or a
broken limb.
In these Conditions correctly triaging critical patient will help reducing
congestion and capacity problems more than mathematical queuing
methods
These types of variability and the time taken between the arrival and
service processes make the healthcare systems very complex.
The number of cases and types of cases are not always regular due to
seasonal variability in diseases.
The government regulations and the hospital regulations may delay the
procedures and prevent discharge of the patient early which are
unavoidable.
Also extensive paperwork in health care will delay healthcare delivery.
While using queueing models some important data like arrivals that are
turned away due to long waiting period or some other reason is not
routinely collected. Hence healthcare queueing models should collect
the acurate data and good sample size.
So a queueing analysis might require a data collection effort to estimate,
the time that a care provider spends with a patient.
For smaller nursing homes are clinics who don’t have large quantity of
data may lead to miss calculation of resource utilization or demand.
Data Sample Sizes although the algorithm is relatively simple, software
systems will still need significant enhancement in order to collect the
data needed.
The data like staffing, management of equipment, number of the
patients, time spent with doctors should be linked to the algorithm.
Stance taken and justification
Queuing concept is one of the powerful management tool which is often
overlooked in hospital management systems.
Proper usage of the queue in concept can yield a impressive result.
By using queuing models in hospitals we can help in discharging the
patient quickly, preventing congestion, reducing the waste of time,
better care delivery, providing resource planning saving money and also
increase in profits.
By good usage of queuing theory and taking proper measures associated
with waiting time of patients, administrators can make a good planning
of resources which will satisfy the, patients, employees and
management.
Hence service mangers must use tools like automatic queuing
technology and computer simulation which assist in maintaining
discipline in the department of operational management
