In my essay practise revision notes, I took all of the past paper questions from previous years and split them up into sub-questions to help me to formulate paragraphs based on different concepts and arguments that I could memorise for the exam. The document will include my own style of writing and...
ESSAY PRACTISE - Waiting Times
Health Economics
1) Define the concept of waiting times for elective
treatments.
Waiting times for elective treatments, treatments that are not urgent and
can be scheduled, refers to the duration of time between the referral for
treatment and the elective treatment. People are put on waiting lists for
treatment when there is excess demand and limited capacity.
2) Describe how waiting times can be measured.
Common measures of waiting times include mean and median waiting
times where the distribution of waiting times is positively skewed. It is
reported that researchers observe waiting time at different percentiles of
the distribution and they measure the number of patients waiting more
than a threshold, for example, waiting more than six months.
3) Is there a relationship between waiting times and
demand for public elective treatments? If there is, is it
positive or negative? Explain why.
I would expect that there is a relationship between waiting times and
demand for public elective treatments and that it would be negative. This
means that an increase in waiting times will reduce demand for public
treatment. From my own perspective, if waiting times were excessive
and I could cope without treatment, I would not ask to be referred for
treatment. Not everyone is willing to wait very long for treatment that is
not urgent, even if they had the possibility of being better off after
treatment. Individuals who have the means to could also choose to go
private if they are not willing to wait too long for free treatment, but this is
not an option for everyone, thereby we still have some demand for
treatment, especially for those who really need it and cannot afford
private healthcare. As a result of an increase in waiting times, patients
with a low income and low benefit from treatment will forgo treatment,
and patients with high income and high benefit from treatment will go
, private. This is how waiting times can act as a rationing device at times,
which I will explain further later.
4) Explain the impact of an increase in waiting times on
the supply of public elective treatments.
An increase in waiting times essentially means that either demand has
increased without any change in supply so that there is little capacity to
treat everyone demanding treatment or that there has been a fall in
supply or capacity. For instance, the total budget for the hospital has
been reduced or has been shifted due to hospital management. Supply
will not initially change but the increase in waiting times could lead to
policy makers finding ways to increase supply to meet demand by
increasing the budget or hospitals can reallocate resources to meet their
demands. Waiting times experienced a positive demand shock when
COVID-19 hit the UK in 2020 and increased dramatically because
hospitals were forced to allocate their resources mostly for COVID
patients causing them to prioritise the pandemic over all other
treatments.
5) What would be the likely impact of an increase in
hospital capacity on waiting times?
An increase in hospital capacity will likely reduce waiting times, but the
significance of this reduction depends on how inelastic or elastic the
demand for elective treatments is.
If demand is inelastic then a change in waiting times will have little
impact on demand for elective treatments. Whereas, if demand is elastic
then a small change in waiting times will have a large impact on demand
for elective treatments. Martin and Smith (2003) investigated further in
their recent paper whether the demand and supply for elective
treatments are elastic or not. Their original paper was published in 1999
which showed a simpler empirical estimation of demand and supply
functions to see how inelastic or elastic demand and supply is. They
used a panel of annual data for 5499 small areas in England from 1992
to 1998. They used available data on waiting times for all specialties
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