Health Economics: Economic Evaluation Analysis Report - May 2018

This report presents a comprehensive overview of economic evaluation in healthcare, emphasizing its significance in resource allocation and policy formulation, particularly within the UK's NHS framework. It highlights the systematic identification and analysis of various healthcare interventions to determine their comparative effectiveness. The report applies NHS EED guidelines to a published economic evaluation of a population-based lifestyle intervention for cardiac rehabilitation non-attenders. The study, published in Heart, Lung and Circulation in 2016, investigates the cost-effectiveness of interventions using pedometer-based telephone coaching and physical activity programs compared to usual care, employing a Markov model to simulate cardiovascular disease progression and assess long-term outcomes, QALYs, and related costs. The report details the study design, population, data collection methods, and the application of economic analysis to assess the benefits and limitations of the interventions. The report also includes a detailed analysis of the study's findings regarding the cost-effectiveness of these interventions, which provides crucial information for managing cardiovascular mortality and associated healthcare costs. Furthermore, the report explains the use of the PANACHE trial and data collection from patients and the control group to conduct the analysis.

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Health Economics
Economic Evaluation
5TH May, 2018.

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1. Present a summary of why the economic evaluation is needed
Economic evaluation is the systematic identification, quantitative and qualitative analysis
of consumption and production of two or more substitute activities to yield a comparative
approach of the activities towards decision making on the viable and applicable techniques
mainly in health economics and technology [1]. Resultant analysis is useful in making decision
when allocating resources to the health sector. In the UK, economic evaluation is used to give a
guideline on national policy formulation as included in the technology appraisals [2].
Economic evaluation in health care is not just about analysis and for decision making, it
has now been an integral part in the medical facilities and is widely used in medical fields to
allow for better resource allocation and to ensure the maximum and great and effective benefit of
the process [3]. It is argued that Economists, as well as medical researchers, are at the moment
implementing and will in the future continue to do economics evaluation in the health sector. It is
a comparative measure to check as economics is not only about the theoretical approaches but
also focuses on the quantitative analysis that is there to facilitate the smooth running of the
medical fields [15].
Economic evaluation isn’t just a one-time process. It is rigorous because of the analytical
evaluation involved. The process alone is composed of many stakeholders involved. They can
include; government clinical practitioners, researchers, market surveyors, financers, economists’
research firms and the list goes on [6]. This means the data and information received and
gathered are verified and have guaranteed evidence in case modification is needed. Economic
evaluation has embraced the use of modern technology in a wide view. The incorporation of
technology has not only made work easier that has facilitated the speed to which data is gotten in
quite a reliable and efficient way minimizing the errors and possible mistakes that human can
make [7]. Technology appraisal has used various approach for assessments and other countries

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like Australia have identified many success stories of health economic evaluation focusing on the
best standards and best practices in the medical fields [19]. Economic may be viewed as just in
terms of costs and benefits but that alone is not enough. There have to be various merits on
which to base such important decisions to make proper judgment and also the decision makings
that surround the facility [22]. The different decision can be based upon.
2. Apply the NHS EED guidelines to the published economic evaluation
NHS ECONOMIC EVALUATION DATABASE
Cost-effectiveness of a population-based lifestyle intervention to promote healthy weight and
physical activity in non-attenders of cardiac rehabilitation. Heart, Lung and Circulation. 2016
Mar 1; 25(3):265-74.
Cheng Q, Church J, Haas M, Goodall S, Sangster J, Furber S.
Source Heart Lung and Circulation: heartlungcirc.org
Year of Publication 2015
Volume 25
Record status The content of this report was collected and compiled by CEA
health reviewers who sought to evaluate the extended cost-effectiveness
of two cardiac rehabilitation approaches and physical activity of patients
who had attended cardiac rehabilitation centers.
Study Question and
Perspective
The evaluation of long term cost-effectiveness based on two
approaches: one on home rehabilitation of patients and the other on
therapy through physical activity. A cost-effectiveness analysis will be
conducted through the two Randomised evaluation techniques where
one trial compares HW to PANACHE while the other one PANACHE

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study to the common care.
The perspective herein entailed partial societal economic
evaluation considering the cost of approach and expenses incurred by
the patients
Health Technology The approach included the use of pedometer telephone contact
and coaching, time sets concerning various parameters such as weight
variations over some time, feeding routines and nutritional intakes and
both personal and communal physical activities [12]. Theses parameters
were compared and contrasted to a previously undertaken exercise on a
group of patients who had prior information concerning brochures and
physical activity.
Intervention
Technique
Cardiac Rehabilitation
Disease Study Case Cardiovascular diseases in Australia is considered one of the
leading causes of death with over 3 million people having been
diagnosed with either long term or short term effects. Its burden is not
only evident in premature loss of lives but also in incapacitation and life
term disabilities.
Hypothesis The cost-effectiveness analysis was undertaken using data
obtained from the random analysis of two techniques. The hypothesis
for the two interventions were:

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1. Healthy Weight pedometer-based telephone coaching CR program
for CVD patients that never attended CR is more cost-effective than
usual care.
2. Physical Activity pedometer-based telephone coaching CR program
for CVD patients that never attended CR is more cost-effective than
usual care.
In testing the second hypothesis, a randomized trial was used
with the Physical Activity (PA) being the intervention group and where
subjects were given instructions as well as support relating to physical
activity using telephone calls whereas the control group was sent 2
physical activity information brochures via email and did not receive
reinforcement telephone calls.
Of the two trials, one seeks to compare HW to PANACHE study
while the other one a study by Furber et al [13] which compared
PANACHE study to the common care techniques. The researchers
developed a Markov model which was developed and was utilized to
analyze the risk factors, body mass index (BMI) to yield the CVD risk
probability and life expectancy. The patient-condition and population
findings developed from the analysis were to use to determine the
transitions to CVD states and costs accruing from the utilization of
healthcare facilities and resources. The research model was further
diversified into cohorts of male and female units run concurrently. The
analysis incorporated univariate and probabilistic sensitivity analysis in

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order to gauge and build a strong database.
Type of economic
study
Cost-Effective Analysis
Study population The study population comprised of males and females who had
cardio vascular disorders and had been booked in rehabilitation centers
and those who had not.
Presentation and
statistical
extrapolation
Methods of
Collecting the Data
From the interpreted data and analytical findings, the resultant
cost-effectiveness ratios are derived from calculation difference in the
cost of the two aspects which is then divided by the net Quality
Adjusted Life Years (QALYs)
The study period was only for one year. This, however, seems to
be a shorter duration to help verify the hypothesis. It would be more
desirable to extend the study period to two years to come up with a
more trusted picture of the effectiveness of these interventions.
A Markov model was then built for tracking of the prolonged
extrapolation of CVD. This would help simulate and determine how the
alternative home cardiovascular rehabilitation techniques would affect
the life expectancy and the health quality as compared to the costs
related to quality of life and related costs related to health centers
rehabilitation. The Markov model is established by the use of data from
conducting the research through the use of the two approaches. It
consists of a randomized approach, Furber et al [13] which technically
evaluates the efficiency and effectiveness pedometer-based telephone

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communication with patients who took up on home-based CR. This
entails the providence of instructions, recommendations and support
facilities by use of telephone calls and also by means of physical
communication where the patients were sent two PA processes with no
telephone calls or physical.
The above figure shows the Markov model developed in this
study to stimulate long-run progression of CVD. It enabled the
evaluation of how alternative home-based CR interventions would
affect future mortality outcomes, QoL, and associated cost linked to
conventional hospital-oriented CR. The data from two trials helped
populate the Model. These were from Furber et al. that evaluated the
pedometer-oriented telephone intervention effectiveness for patients
who never attended a CR program. The second data was drawn from
PANACHE trial which evaluated a pedometer-oriented telephone

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coaching program effectiveness on weight and physical activity.
Setting PANACHE (Physical Activity, Nutrition and Cardiac Health)
means of study seeks to evaluate the reliability of pedometer –based
telephone calls for the training on physical activity. In this trial, the
patients who were contacted were required to report into hospitals in
The New South Wales state
Dates to which data
relate
The resource data and effectiveness was conducted from 30th
may, 2015 to 18th July, 2015.
Clinical and
Epidemiological
data
The data applied was obtained from the PANACHE trial which
included body weight of patients, BMI, PA, nutrition, QALYs and costs
arising from medical attention. This data was only from those who were
referred to CVR but failed to attend (HW:n=75;PA:n=73). The control
was sourced from data as collected by Furber et al. [13]
CVD patients classified by Markov Model
1.BMI=18.5-24.99kg/m2
2.BMI=25-29.99kg/m2
3.BMI=30-34.99kg/m2
4.BMI≥35kg/m2
Link between
effectiveness and
cost data
The Markov model used a population to simulate changes in the
risk of cardiovascular disorders and demonstrated that both the
approaches, pedometer-telephone coaching and pedometer-based
physical activity intervention were quite effective as compared to the

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control analysis
Study sample The researchers found out that despite the effectiveness of the
trial to facilitate information on the reduction of CV mortalities it still
got some limitations.
Study design The approach was undertaken on a six-month duration with a
consistent collection of data from the patients and referral institutions
offering rehabilitation to patients. For the consistency of the data
collection, several assumptions had to be made and constrictions
overlooked. Specific assumptions over occurrence probabilities of
mortalities which are independent of age and other health factors apart
from CVD were made so as to facilitate continuous data collection.
Individuals who had not been enrolled into cardiovascular disorders
rehabilitation centers but already diagnosed were assumed to be in the
model at a starting age of 64 years. Based on gender discrepancies, male
and female analysis were carried out separately. The Markov model was
run using TreeAge Pro 2013.
Effectiveness
Analysis
The randomized data obtained from the study in the area of
interest groups obtained from PANACHE which includes PA, nutrition,
health attention costs and body weight were analyzed by the reported
questionnaires at baseline, six months.
Economic Benefits This approach provides vital information concerning the steps to
undertake so as to contain the overall mortality and costs arising from
handling of CRV patients. In the model, the anticipated costs were used

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to evaluate costs of health attention for each state.
Effectiveness of
results
In the male study, the thirty year records indicate that running
the control division incurred the least cost though it yielded lesser
QALYs as compared to the physical activity group. How much the
average patient was willing to pay helps set a threshold for an additional
QALY? It is evident that in Australia, there exist no such ceiling on
willingness to pay. Under this study, $50,000 per QALY was specified
to be the ceiling on the ability and willingness to pay for an extra.
Comparators Although the analysis showed varying values in BMI for CVD,
these different ratios does not affect the ICERs. The Canadian data
record is stipulated to either overestimate or underestimate Australia’s
mortality risk.
conclusions Being the first Australian study aimed at evaluating the
prolonged cost-effectiveness of CVD patients undergoing coaching and
rehabilitation and those that do not, it does not lay a foundation for
comparison with earlier economic evaluations. The analysis show that
the control group are less cost effective in comparison with physical
activity representing usual care. These results obtained give a guideline
to economic policy makers on assurance that conventional hospital
based CR poses a cost effectiveness approach for cardiovascular
disorder patients as compared to hospital based rehabilitation. The costs
incurred in intervention were found to surpass those in effectiveness
cycles as both HW and PA portrayed cost-effectiveness only at the

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$50,000 per QUALY ceiling
The interventions costs stayed beyond cycles as opposed to
effectiveness. The PA and HW interventions
remained cost-effective at the threshold of $50,000/QALY. This depicts
cost-effectiveness even with shorter cycles and time of effectiveness. A
recommendation is made that internet-based techniques should be
utilized as an intervention for the patients Southard et al. [23]
Study Implications The Markov results demonstrated that the willingness to pay the
set threshold for both the approaches are long term cost effective as
compared to the control group containing the common care.
Country code Australia
Analysis The use of decision analysis techniques bring about a buildup of
uncertainty, this can be counteracted and redistributed by the
researchers by sensitivity analysis approach so as to test the strength of
results
Scenarios Analysis This is a type of a kind of sensitivity analysis and they have been
used in this study to test robustness of the results and made changes to
small variables. In other word, both scenario analysis and sensitivity can
are used together to test the results of the model. The four scenarios
analysis used in this study focused on testing the impact of frequency at
which interventions were delivered and how long the intervention
effects lasted. For example base case (scenario 1) had the model run for
sixty cycles and interventions delivered per cycle.

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They assumed effectiveness to last till the end of stimulation. In
the second scenario, the authors delivered the intervention only one and
they assumed effectiveness to last for sixty cycles. The scenario 3 had
the stimulation ending after sixty cycles, however, both the
interventions and effectiveness remain applied solely in the first cycle.
The scenario 4 had sixty cycle of stimulation and the intervention was
given in the initial ten cycles whereas the effectiveness lasted for 4
cycles and it assumed a warning adherence to intervention.
In the 2nd and 3rd scenarios with intervention solely given in 1st
year, the HW interventions show dominance over the remaining two
arms because it was the least costly as well as most effective
intervention. As opposed to base-case scenario analysis, the outcome
from 3rd and 4th scenarios favored HW intervention because its cost was
decreased to a large degree whereas effectiveness of intervention
endured in the entire stimulation. Both HW and PA were effective at a
threshold of $50,000/QALY in the 4th scenario with costs of
interventions lasting for more cycles as opposed to effectiveness. Thus,
the scenario analysis shows the cost-effectiveness results robustness
even with shorter cycles and durations of effectiveness tested in this
model.
The four approaches used to regulate the ways in which the
interventions impacted on the strength of the interventions were
delivered in each cycle. After running the Markov model for 60 cycles,