Cost-Utility Analyses in Public Health: Measures and Differences in Disease Burden Assessments

This assignment discusses the measures used in cost-utility analyses (CUA) and the differences in disease burden assessments. It focuses on lung cancer, mental illness, and coronary heart disease as examples. The analysis explores the use of quality-adjusted life years (QALYs), disability-adjusted life years (DALYs), and years of potential life lost (YPLL) in determining the cost and utility of health outcomes.

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Cost-utility analyses refer to a technique used to govern the resource distribution
processes. This system of analysis comprises the cost of calculating the quality-adjusted life
years as well as the cost of disability-adjusted life years. Also considered in this assignment is
the measurement of Years of potential life lost or potential years of life lost, thus demonstrating a
measure of premature mortality figuratively. This can assist with public health forecasting,
through calculating the social and economic loss. The purpose of this assignment is to discuss the
varying measures used in CUA and to confer the differences in disease burden assessments
found by using the different measures. Lung cancer, mental illness, and coronary heart disease
are the disease burdens being presented. There are many mitigating factors when considering
disease burdens, and many studies of public health are becoming more defined as health
economists can utilize health indexes, which more accurately reflect current public health trends.
Cost-utility analyses (CUA) refers to economic analysis whereby the increasing program
costs from a certain point of view is assessed in comparison to the health improvement analyses
which is expressed using the QALYs units [1]. The cost-utility analysis helps in determining the
cost of utility terms that is in terms of the quantity and the quality. An example would be
comparing different groups of drugs or the procedures whose importance may be differing.
Therefore, the CUA is used in the expression of the money value in terms of health outcome
single type [1, 2].
Cost-utility analysis is the most complex type of pharmacy-economic analysis which
accounts for the quality improvement of life and the quantity of life that is granted by the
intervention of expended resources [3]. Benefits of CUA relate directly to ‘perceived values of
expected outcomes and allow measurement of outcome for ‘comparison of costs and outcomes in
different programs. Potentially, this allows for comparison models in health care assessing
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opportunity cost so that established models of care may be adopted in the budget, already proven
to be cost effective. Measurements of the outcome can be expressed as units of health portraying
quantity and life quality, with utility being the profits obtained from health and health care [3, 4].
These are used to provide information to health decision makers so they may be informed and
able to make decisions based on important economic evaluations (Lancsar et al., 2008).
Health consumers are not always able to know or understand expected health results, and
perception of life quality and preferences varies amongst individuals. Measurement techniques
like the EQ-5D (EuroQol) and Health Utilities Index aim to reduce the inconsistency in the way
health states are described and may reduce the disparity in the description of health states [5].
DALY is a summarized measure of the health of the population that is the reason for
mortality and nonfatal consequences of health. Disability-Adjusted Life Years (DALY) was
initially developed for the key purpose of quantification of the global burden of disease (GBD).
It was designed as an analysis unit tor relative magnitude measurement of the losses of the health
life affiliated to the different initiators of diseases and injuries [6]. Additionally, DALYs was
intended to become a health benefit metric in the cost-effectiveness of denominator ratios.
Worldwide, DALYs measure morbidity and the mortality. The DALY has been used to quantify
disease. It allows for a combination of the single indicator” years of life lived with disabilities”
and “the years of life from premature death (YLL)”[6, 7].
The QALY was invented back in the 1970s. It has now become recognized as a standard
tool internationally since the 1990s [8]. Quality-Adjusted Life Years (QALY) refers to a product
of arithmetic expectancy of life which is combined with the measurement of the life quality in
terms of the number of years remaining. The calculations that obtained are relatively
straightforward based on the time a person may likely stay in a specific health state which is
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weighted by a score of utility from the standard values that have been invented [9]. The values
equate that at ‘1', the health for someone is perfect, while at ‘0', the person's health is no more.
Due to the state of some health which is characterized by too much difficulty and pain which are
just regarded as equal to death, they are often given a value which is negative [8,9].
The QALY can combine the health effects of interventions on the morbidity and
mortality into a single index hence providing a common currency to help in comparing many
areas of diseases. With time, there have been varied individual experiences in different states of
health. At a point of weighing states of health based on the scores of utility affiliated with them
[10].
PYLL or YPLL refers to the estimate of the year's someone would have been able to live
if that person was had not died a premature death. Therefore, it is a premature mortality
measurement. YPLL or PYLL being a method and a different option to the mortality rates, it
offers more emphasis to deaths that happen to young people. It also considers the impact of both
inability and early death of persons with DALYs. YLL accounts for the age at which the deaths
happen through much consideration of the deaths of younger people and a small weight of the
death of persons who are old. The YLL indicates the measure that the YPLL because of the
proportion of the YPLL lost people is based on premature mortality. YPLL is obtained through
calculation of the number of the deaths then multiplied by the expected life standard at that age
the death of the young person happened [12]. The life expectancy standard that is used for the
Years of life lost at every age is similar for the deaths in every region of the world and similar to
the one used to calculate the DALYs. In addition, 3% discounting of time and age non-
uniformity weights, which one will give less weight to the year,’s that a person lives at a young
age or old age. Based on the non-uniformity age weights and the discounting of 3%, an infancy
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death in correspondence is at 33 YPLL and the deaths are at the ages of 5 to 20 or even to around
36 YPLL [11, 12].
The study of lung cancer needs consideration of many variables which include the type of
cancer, the treatment for each type of cancer and the success rates and the population of the
people affected. EQ-5D has become a well-recognized tool for measuring most cancers and
assisting of patients and healthcare persons with the preference-based measures of the health
gains. The European Organization Research on Treatment of Cancer (EORTC) has come up with
research tools like the QLQ-C30 questionnaire and the QLQ-LC13 module to help in performing
research. The HRQoL is dependent of QoL of a person and therefore needs to be included at a
functional capacity to help in ensuring the individual’s insight into their disease and the
symptoms for that disease [13].
When the lung cancer is detected early, they can easily be destroyed through the new
advancement of technology that enables chemotherapic treatment through the cost of treatment is
high. Yang in his study identified QALY as a unit of measure of QoL to help in estimating the
adjusted life expectancy and the loss of Quality-adjusted life expectancy when compared to the
QALY for instances of operable and the inoperable non-small lung cancer. It concurred that
DALY, while able to allow possible international contrasts, the loss-of-QALE allowed for ‘direct
comparisons of different diagnosis and treatments strategies' and it would follow that this would
produce a more useful method to be applied to decision making within national health policy
cost-effectiveness identification [15]. Hence, how a study is performed can affect the results of
QALY and DALY, with the disease burden that is at the stage of disease’s treatment that is being
provided adjusting the results for everyone. Depending upon the sample group, size, and severity
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of the disease, the PYLL may not be a true correlation of all lung cancers, however, may identify
trends for increasing QoL through early detection and prevention [14].
Types of costs associated with mental health care are inclusive of direct costs, indirect
costs, patient costs, future costs, and intangible costs. Outside of the healthcare system, costs
associated with imprisonment, special housing provision, and special education provided also
impact society through cost burden. Measurement of QALY is affected by the alternative
therapies which quantify the cost, and this is adversely affected by methodological uncertainty,
structural uncertainty and parameter uncertainty [15]. These points demonstrate how the studies
themselves may affect the outcome measures through study bias, however as mental illness is
‘the largest single cause of disability in Australia’ there are many aspects of the burden of this
disease which may affect the HRQoL (Atun et al., 2016).
PYLL is affected by the duration of the illness, as evidenced by Vos, with various states
of mental illness having periods of remission. It is also dependent upon comorbidities, whereby
if there are two or more diagnosed mental disorders there is the possibility of overestimating
DALY (attributing a score over 1, the equivalent of deceased) [16]. Age-related weights also
affected DALYs and indicate that PYLL values are regulated ‘by the product of incidence and
duration. [16] Shows how the burden of mental illness affects those aged between 16-54 years of
age, the prime working years which would indicate the burden of the disease on the Government,
and on society. [17] Describes how QALYs are used as a generic measure in mental health
outcomes, linking them to ‘subjective appraisals of how bad it is to experience these outcomes.
The estimated incremental cost per QALY can be affected by the comparison of one intervention
against another and is affected by uncertainty, making it difficult to estimate accurate cost
assessments [15, 16, 17].
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CHD is reported as the second highest burden of disease in 2011 (15%) after cancer
(19%), with mental and substance use disorders coming in 3rd with 12% (AIHW 2016). Using
DALY, the effect on cardiovascular disease could be explained utilizing the disability weight
(health loss) of a specific disease type within the classification under several specific diseases
under heart disease in the ICD-11 (Australian Institute of Health and Welfare, 2016). Health loss
relating to angina has a disability weight of 0.167 according to the Global Burden of Disease
(GBD) 2010 [18]. Multiply this figure with 1 (year), (0.167 x 1=0.167 years of living with a
disability, YLD). If an individual was to have a heart attack during this year, his short-term
health loss of about two months with a disability rate of 0.48 (0.48x 2/12=0.08) This would equal
a total of 0.25 YLD for health loss due to CHD. In this instance, if the individual would perish at
the end of that year, several years are lost due to premature death. Theoretically, a female may
live to the age of 84 in Australia, so if a woman were to pass at the age of 54, then she would
lose 30 years of life due to dying prematurely (PYLL), or fatal burden plus the non-fatal burden
of disease. To calculate the total DALY relating to this example, we would add 0.25 plus 30
PYLL, providing 30.25 DALY. It appears that the effects on DALY and PYLL are obvious, in
that if years are lost due to a change in the condition with the disability weight, that is an episode
of care causing an increase in illness or time lost due to a temporary change in health, this can
significantly alter the incidence of lost years of life [19].
The analysis of utility cost is a clear way which helps in evaluating the degree of cost-
effectiveness of health practices in the public health. It allows for the practitioners of health to
determine the variety of diseases in terms of their burden states and help in considering the
establishment of the right methodology which has the better economic effectiveness. The use of
QALYs, PYLLS, and the DALYs assist in the provision of health economist information to help
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in informing the health practitioners and the society for informed decision-making processes.
Benefits gained from this type of analysis also includes the ability to guide health economists to
measure emotional, social and physical well-being, implementing tools designed for this. It is
possible that health-related benefits correlate with budgetary constraints while using CUA, and
this method can be applied to all disease states, including more complex cases.
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