BACKGROUND
The global COVID-19 pandemic has had profound effects on access to health care globally. Of
these effects, disruption to planned (elective) surgery has been particularly prominent. In highincome countries with universal health systems, such as the United Kingdom (UK) and
Australia, waiting lists for surgery act as a non-price rationing mechanism to manage health
system resources. As health systems recover from the pandemic shock it is appropriate to
evaluate the lessons inherent in the response and understand how to manage the historically
large number of patients now awaiting planned surgery.
AIM
To understand some of the factors affecting access to and waiting times for planned surgery,
and to develop a clear picture of the effects of the pandemic on planned surgery in the Australian
health care system.
METHODS
A number of studies were conducted and are described in this thesis. The first examined the
effect of socioeconomic status (SES) on access to specialist surgeons. To do this, data were
obtained from Medicare Australia – the government body that finances medical consultations
in the Australian health care system – regarding the postcode of residence of patients who claim
for a surgical consultation along with age, gender, and the subspecialty of the surgeon. The
postcode of residence was used to estimate the patients’ SES and rurality (a major factor
affecting health care access in Australia) and correlate this with rates of first visit with a
surgeon. Data were stratified by age, gender, and surgical specialty and analysis performed in
Genstat.
The second study examined SES and rates of surgery for high- and low-value procedures using
data from the Australian Institute of Health and Welfare (AIHW). The data were analysed with
age stratification and gende,r and analysis performed to graph any potential SES gradient.
The third study used data from the Australian National Surgical Waiting List Dataset – which
contains data on every operation performed in Australian Public Hospitals – obtained from the
AIHW to quantify the effects of the pandemic on performance of planned surgery in Australian
public hospitals. Data were analysed and regressions performed in Excel and Genstat.
The fourth and final study examined the effects of gender on access to planned surgery during
the pandemic using the Australian National Inpatient Procedural Database curated by the
AIHW. Again, data were stratified by age and gender and regression models developed in
Excel and Genstat.
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RESULTS
Results from the first study showed that in young Australians aged less than 20 years, the rate
of surgical visits showed a gradient with reduced rates associated with decreasing SES. For
this group, rurality was influential but manifest an inverse-U curve. Most concerning was lack
of access by Indigenous children to ENT care with concomitant impacts on education and future
life opportunities. For adults there were age and gender gradients confirming an effect of SES,
but for several specialties the results were inverse compared to children and adolescents. These
findings confirm the correlation between SES, rurality, and access to care although the findings
were complex and would benefit from further study.
Results from the second study showed confirmed an inverse gradient – with higher SES
associated with lower rates of surgery – in both the high- and low-value procedures. Since lowvalue surgery is undesirable, identifying and reducing the use of low-value procedures has the
potential to improve surgical access in a time of crisis.
Modelling in the third study showed that waiting times for, and the proportion of patients who
waited longer than clinically recommended for, planned surgery increased across all key
procedures and have not returned to pre-pandemic levels. An estimate of the number of planned
procedures not performed during the pandemic yielded a range between 216,000 and 412,000
procedures. Australia also had state-based pandemic public health responses to the pandemic:
tight border controls in Western Australia; intermittent prolonged lockdowns in Victoria; and,
a laissez faire approach in New South Wales. The effects on waiting lists for surgery using
these three approaches revealed increases in waiting times for surgery and high levels of interhospital variation with no obviously superior approach.
Results from the final study revealed that for every procedure studied, females were less likely
to have undergone surgery than males, suggesting an inherent gender bias in access to, and
uptake of, planned surgery.
CONCLUSION
Taken together, these studies suggest that in the Australian health system there is considerable
inherent inequality of access and update across SES, rurality, and gender, affecting access to
planned surgery in public hospitals. Reducing these inequalities would be expected to improve
access to and outcomes from health care in future.