Wait Times
Research Paper
Prepared By:
Lauren Scott
Nova Scotia Association of Health Organizations
October 2005
Wait Times
Research Paper
Introduction
A recent Supreme Court decision ruled that Quebec’s ban on private health care
insurance for medically necessary services is illegal. This issue was not really
about private versus public health care. The real underlying issue was about
wait lists or more accurately wait times.
The Canadian health care system never seems to resolve the issue of public
versus private health care but when one looks at the issue at a deeper level, one
of the issues at the heart of the debate is wait times. The call for a larger role for
private health care is mostly about the “right” to access service more quickly if
you have the ability to pay. This research paper intends to consider the issue of
wait lists and wait times in more detail.
Definitions
The following are definitions used by the Nova Scotia Department of Health in
their launch of the Nova Scotia Wait Times Web Site (2005):
Wait List Î wait lists are maintained by facilities and/or individual doctors to keep
track of people waiting to be scheduled for consults, tests or procedures, or
treatments.
Wait Time Î wait time is the time between when a patient and the doctor/nurse
practitioner determine a service is needed and when the service is actually
carried out.
Interestingly, defining wait time is one of the issues. For example, one survey
found that 58 per cent of organizations felt that when an MRI was booked was
the starting point for determining wait time (Sanmartin et. al., 2000). This is not
in sync with the above definition. In fact, when Nova Scotia’s information is
examined more closely not all wait times are measured as they have defined.
In Nova Scotia, cardiovascular surgery wait time is measured by “the number of
calendar days from the day the decision is made that surgery is necessary to the
day they receive the service”. This measurement is consistent with the above
definition. Whereas, referrals to specialists is measured by “the number of
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calendar days from the day the referral arrives in the cancer centre to the day the
specialist appointment takes place.”
If there were standardized definitions it would make it easier to compare data
across jurisdictions. In addition, there are complications based on the fact that
there is more than one method to measure wait times (Sanmartin et. al., 2000).
Measurement Methods
Cross-sectional Î This method answers the question, “how long have patients
currently on the list been waiting”.
Retrospective Method Î This method would be used to determine how long
people who had already received service, during a selected time period, had
waited. For example, how long did people who received the service in January
of 2005 wait.
Prospective Method Î This method follows people from the time they are placed
on the list until they receive service. For example, all people put on the list in
November 2005 would be monitored until their receive service.
All three methods are useful depending on what information is being gathered
and in fact, all three methods might be used to gain a more complete picture.
However, comparability is compromised if different measurement methods are
being used (Sanmartin et. al, 2005).
It appears that Nova Scotia is mostly using the retrospective method to
determine the wait times being reported on the new web site (NS Web Site,
2005).
Statistics
Wait times can be reported statistically as mean, median or interval measures
(Sanmartin et. al., 2000). The mean being the average and the median meaning
that half of the people waited shorter than the median number and half of the
people waited longer (NS Web Site, 2005). Interval measures are also used; an
example would be the “proportion of patients who have waited for more than 60
days” (Sanmartin et. al., 2000). Using mean wait times as a reporting
mechanism can be misleading; it is strongly influenced by small numbers of large
waits (Sanmartin et. al., 2000). It is the mean or the average wait time that Nova
Scotia seems to be using most frequently (NS Web Site, 2005).
Why Wait List?
Wait lists are always portrayed as a negative thing. First and foremost, it is
important to remember that wait lists in and of themselves are not necessarily a
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problem. “There is a significant difference between being on a long list and being
on a list for a long time” (Lewis et. al., 2000).
The intent behind wait lists is to ensure that those with the greatest need for the
service receive it first (Lewis et. al., 2000). “In theory universal coverage on
equal terms and conditions also allows all patients to be assessed, with wait list
priorities assigned according to need. This approach of managed delay can be
contrasted with the potential for arbitrary delay, and denial, based on insurance
coverage and/or income….(Naylor et. al., 1995).
If everyone were to receive service immediately, excess capacity would need to
exist within the system. This is not an efficient use of resources (Naylor et. al.,
1995). Not to mention, if individuals were to receive service immediately there is
no time for “sober second thought.” Waiting can also provide benefits in that
many patients choose not to go through with the procedure, seek a second
opinion, adapt to the condition, or gain benefit from trial management (Lewis et.
al., 2000).
While it is possible to identify benefits to some period of waiting, excessive waits
clearly raise the possibility of suffering and irreparable damage to a person’s
health.
Root Causes of Excessive Waits
The most commonly sited reasons for long waits are (Sanmartin et. al., 2000):
•
•
Inadequate resources (funding, human resources, OR time etc.); and
Poor management of existing resources.
Most of the focus is on the first one, particularly funding.
Solutions
Additional Resources
Just as the focus of the problem is on inadequate resourcing, the solutions are
also most frequently targeted there. In fact, research has demonstrated that if
asked “what is the best solution to reduce wait times” most respondents believe
more funding (Sanmartin et. al., 2000).
There is evidence that these types of solutions can make positive change.
British Columbia’s cardiac wait lists were reduced by one-third in 10 months
through more funding and better recruitment of staff. More importantly, wait
times were reduced from 18 weeks to 14.9 weeks (Jones, 2004).
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However, there is strong evidence that this type of targeted increase in funding
does not have a lasting impact on wait times or can result in undesired
outcomes.
For example, in the UK funding was made available to provide service to those
who had waited beyond a predetermined threshold (all those who had waited 12
months or more for example). This reduced the wait list over all but had the
unintended result that wait times were increased for higher-priority patients. In
some cases, wait lists became even longer when funding was targeted for their
reduction. Sanmartin et. al. (2000) refer to this as a “feedback” phenomenon,
meaning that family physicians tend to refer patients for those services that have
a decreasing wait time.
It must also be recognized that when resources are put into the system to reduce
specific wait times, those resources have to come from elsewhere. This applies
to more than just funding. For example, if more operating room time is allocated
to reduce the wait time for a specific procedure this may mean that other
procedures are backing up (Lewis et. al., 2000).
Private Health Care
One of the most common solutions presented to reduce wait times is to allow for
an expanded role for private health care. The idea being that those who can
afford to pay for service in the private sector will do so, receive faster care and in
doing so decrease the number of people waiting in the public sector (Sanmartin
et. al., 2000).
There are problems with this theory, however. A shortage of health care
professionals already exists. With the expansion of the private sector it is difficult
to imagine how this would not drain the public sector of workers thereby
increasing wait times further. It is possible that more people could be trained but
this is a lengthy process that takes time before results are achieved. It is also
very expensive and is mostly done at public expense. It is unclear how the public
would feel about training health care professionals with public funds only to have
them go and work in the private sector (Flood and Sullivan, 2005; Sanmartin et.
al., 2000).
The more important response to this theory is that there is no clear evidence that
this is what actually occurs. In fact, the evidence appears to be the contrary in
many cases – wait times appear longer in countries with two-tier health care
(Flood and Sullivan, 2005). In the UK, private health care is focused on hips,
hernias, haemorrhoids, cataracts and gynaecological problems. Despite these
services being provided in the private sector these same services have some of
the longest wait times in the public sector. In addition, “regions with the longest
wait lists also have the highest rates of private surgery” (Sanmartin et. al., 2000).
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Health Care Guarantee
A health care guarantee is when there is a predetermined time for each
procedure that is deemed acceptable to wait. These predetermined thresholds
should be scientifically determined. When patients reach that predetermined
threshold of waiting “too long” then the government pays for them to receive the
procedure in another jurisdiction. The Standing Senate Committee on Social
Affairs, Science and Technology (2002) supports the implementation of a health
care guarantee in Canada.
One of the issues with a health care guarantee is that it is really a method of
targeted reduction discussed under the section additional resources and hence,
has the same difficulties. If the focus is on ensuring individuals do not have to
wait past a predetermined time rather than on priority it increases the wait for
individuals of high priority.
Better Management
Wait lists are generally managed by individual physicians and/or facilities
(Sanmartin et. al., 2000), which is also how Nova Scotia has chosen to define it.
It is this very fact that causes part of the problem. As Steven Lewis said (2000),
“the probability that tens of thousands of individual, uncoordinated decisions
taken in a large, complex and diverse system will combine to yield fairness for all
is vanishingly low.”
Nova Scotia is making progress with the establishment of a wait times’ web site
for some services. This does enable patients to see that waits may be shorter
elsewhere and discuss with their physician seeking the service there. However,
this not pooling lists together. Nova Scotia is the first Atlantic province to make
this information available to the public.
Auditing of wait lists is rarely done in Canada. However, it has the potential to
have a significant impact on wait times in this country. Research has
consistently shown that there are many patients on wait lists inappropriately.
Inappropriate placements range from 15 to 70 per cent, with research indicating
numbers most commonly between 20 to 40 per cent (Sanmartin et. al., 2000).
These inappropriate individuals include:
• Procedure has already been done;
• Procedure is no longer required;
• Patient is unaware that they are on the wait list and request to be removed
when notified;
• Patient has died;
• Procedure is not appropriate for the patient;
• Alternate procedure is preferable; and
• Change in patient’s clinical condition.
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There is also a significant issue of missed appointments that needs to be
addressed. A study done in the UK found that if people notified the care provider
of when they were going to miss an outpatient appointment wait times could have
been reduced from 6 months to one week (Rachlis, 2000).
In Nova Scotia, it was found that 113 people could have received service faster
as in July 2005 ten per cent of the 1, 136 patients scheduled for an ultrasound at
the QEII did not show up. Also in July, 2005 twenty per cent of people scheduled
to receive an upper GI and Barium Enema at a hospital in the province did not
show up (Nova Scotia Web Site, 2005).
Information and Information Systems
First, there needs to be tools in place that allow patients to be prioritized first
within individual lists and then again when placed on pooled lists (Lewis et. al.,
2000).
Then there needs to be reliable data on which to do analysis. Research has
shown that Canada focuses its spending on direct health care and has been
reluctant to invest in those supportive components of health care such as
information systems, although, arguably this is shifting. Lewis et. al. (2000)
states that Canada is held, “hostage to its own failure to invest in the
fundamental infrastructure for intelligence gathering.” In order for Canada to be
able to effectively reduce wait times and see results over the long term the
situation must first be understood.
Series of Solutions
Lewis et. al. (2000) identify a series of actions that they believe will result in an
increased understanding of wait times and the reduction of those wait times:
•
•
•
•
Standardized concepts and terms Î as previously discussed, it is
important that all jurisdictions are defining and measuring wait times in the
same way.
Audit, evaluation and quality control Î wait lists need to audited to ensure
that those who are on the list are appropriate.
Systematic, not isolated solutions Î as previously discussed, targeted
solutions can have the unintended effect of increasing the wait times of
those with higher priority who do not meet the threshold of having waited
too long.
Public ownership of lists Î Lewis et. al (2000) argue that the public needs
an opportunity to weigh in on this debate and declare their values and
preferences. For example, there are ongoing debates about whether
factors such as employment status and age should effect where you are
placed on a waiting list. Public ownership of lists is also about giving the
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public an opportunity to choose to seek services from physicians or
facilities with shorter wait times.
•
It is also important to understand patients’ acceptance of wait times. One
study found that the strongest predictor of patients’ response to wait times
was how long they perceived the wait was going to be. The same study
found that when asked how long was acceptable to wait, their general wait
time was shorter than they were willing to wait themselves (wait time for
an ultrasound should be no longer than three months but when asked how
long they are willing to wait might say four months) (Dunn et. al., 1997).
Fairness among providers Î when the public is given the opportunity to
redirect their service to the shortest wait lists then conflict between
providers may arise. If operating in a fee for service environment,
providers “losing” patients to another provider represents a loss of income;
thereby making providers less willing to allow patients to move around.
It need to be understood why some providers have shorter wait times than
others. It is not sufficient to shift patients between lists without
understanding the reasons for variability. There are any number of
reasons for variability that are acceptable but it must be understood –
does a provider have short wait times because they are efficient? does a
provider have long wait times because they are not following best practice
or do they have long wait times because they are perceived as “best in the
business” and everyone wants to see receive service from them (Lewis et.
al., 2000).
Conclusion
Clearly, reducing wait times is a far from straight forward issue. However, it is
reassuring to realize that there are a number of avenues to consider in
determining how to bring wait times under control. It is also important to realize
that not all solutions are extreme. It is not necessary to create a larger role for
the private sector immediately. The system has yet to consider the impact of
wait list auditing and controlling for missed appointments, for example.
This is an issue to which there are solutions. The action that needs to be taken
is to determine which solutions are likely to have the best chance for success
and which ones are most palatable to the Canadian public.
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