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

This assignment discusses the varying measures used in cost-utility analyses (CUA) and the differences in disease burden assessments found by using different measures. It focuses on lung cancer, mental illness, and coronary heart disease as examples of disease burdens. The assignment also explores the benefits and applications of CUA in informing health practitioners and society for decision-making processes.

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Abstract
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.
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Introduction
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 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].
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Disability-Adjusted Life Years (DALY)
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].
Quality-Adjusted Life Years (QALY)
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
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].
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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].
Potential Years of Life Lost (PYLL) or Years of Potential Life Lost (YPLL)
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 through the use of 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. Also, 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 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].
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The burden of Lung Cancer Disease
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
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].
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The burden of Mental illness disease
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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The burden of Heart illness
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].
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Conclusion
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
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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References
1. Zarnke, K.B., Levine, M.A. and O'Brien, B.J., 1997. Cost-benefit analyses in the health-
care literature: don't judge a study by its label. Journal of clinical epidemiology, 50(7),
pp.813-822.
2. Weatherly, H., Drummond, M., Claxton, K., Cookson, R., Ferguson, B., Godfrey, C.,
Rice, N., Sculpher, M. and Sowden, A., 2009. Methods for assessing the cost-
effectiveness of public health interventions: key challenges and
recommendations. Health policy, 93(2-3), pp.85-92.
3. Sach, T.H., Desborough, J., Houghton, J., Holland, R. and CAREMED study team, 2015.
Applying micro‐costing methods to estimate the costs of pharmacy interventions: an
illustration using multi‐professional clinical medication reviews in care homes for older
people. International Journal of Pharmacy Practice, 23(4), pp.237-247.
4. Lancsar, E. and Louviere, J., 2008. Conducting discrete choice experiments to inform
healthcare decision making. Pharmacoeconomics, 26(8), pp.661-677.
5. Bowling, A., 2014. Research methods in health: investigating health and health services.
McGraw-hill education (UK).
6. Murray, C.J., Vos, T., Lozano, R., Naghavi, M., Flaxman, A.D., Michaud, C., Ezzati, M.,
Shibuya, K., Salomon, J.A., Abdalla, S. and Aboyans, V., 2012. Disability-adjusted life
years (DALYs) for 291 diseases and injuries in 21 regions, 1990–2010: a systematic
analysis for the Global Burden of Disease Study 2010. The Lancet, 380(9859), pp.2197-
2223.
7. Anand, S. and Hanson, K., 1997. Disability-adjusted life years: a critical review. Journal
of health economics, 16(6), pp.685-702.
Your Name Health Economics Research Assignment

10
8. Mehrez, A. and Gafni, A., 1989. Quality-adjusted life years, utility theory, and healthy-
years equivalents. Medical decision making, 9(2), pp.142-149.
9. Torrance, G.W. and Feeny, D., 1989. Utilities and quality-adjusted life
years. International journal of technology assessment in health care, 5(4), pp.559-575.
10. Räsänen, P., Paavolainen, P., Sintonen, H., Koivisto, A.M., Blom, M., Ryynänen, O.P.
and Roine, R.P., 2007. Effectiveness of hip or knee replacement surgery in terms of
quality-adjusted life years and costs. Acta orthopaedica, 78(1), pp.108-115.
11. Romeder, 1.J., and McWhinnie, J.R., 1977. Potential years of life lost between ages 1 and
70: an indicator of premature mortality for health planning — international journal of
epidemiology, 6(2), pp.143-151.
12. Tjepkema, M., Wilkins, R., Pennock, J., and Goedhuis, N., 2011. Potential years of life
lost at ages 25 to 74 among Status Indians, 1991 to 2001. Health reports, 22(1), p.25.
13. Murray, C.J. and Lopez, A.D., 1997. Global mortality, disability, and the contribution of
risk factors: Global Burden of Disease Study. The Lancet, 349(9063), pp.1436-1442.
14. Ferkol, T. and Schraufnagel, D., 2014. The global burden of respiratory disease. Annals
of the American Thoracic Society, 11(3), pp.404-406.
15. Vigo, D., Thornicroft, G., and Atun, R., 2016. Estimating the true global burden of
mental illness. The Lancet Psychiatry, 3(2), pp.171-178.
16. Rice, D.P., Kelman, S. and Miller, L.S., 1992. The economic burden of mental
illness. Psychiatric Services, 43(12), pp.1227-1232.
17. Ustün, T.B., 1999. The global burden of mental disorders. American journal of public
health, 89(9), pp.1315-1318.
Your Name Health Economics Research Assignment

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18. Tsuyuki, R.T., Shibata, M.C., Nilsson, C. and Hervas-Malo, M., 2003. The contemporary
burden of illness of congestive heart failure in Canada. The Canadian journal of
cardiology, 19(4), pp.436-438.
19. Australian Institute of Health and Welfare, 2016. National Bowel Cancer Screening
Program: Monitoring Report 2016. Cancer Series No.: 98.
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