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Building a Markov model for economic evaluation of a community-based CVDs prevention program – case North Karelia Project in Finland


Academic year: 2022

Jaa "Building a Markov model for economic evaluation of a community-based CVDs prevention program – case North Karelia Project in Finland"






Sara Alimam Master's thesis Public Health University of Eastern Finland Faculty of Health Sciences School of Medicine June 2020


Public health

ALIMAM, SARA: Building a Markov model for economic evaluation of a community-based CVDs prevention program – case North Karelia Project in Finland, 88 pages, 2 attachments (2 pages)

Supervisors: Dr. Eila Kankaanpää, senior lecturer (Health Economics), Dr. Javkhlanbayar Dorjdagva, senior lecturer (Public Health Policy and Economics), and Dr. Sohaib Khan, university lecturer (Public Health)

June 2020

Keywords: North Karelia Project, economic evaluation, Markov model, community-based CVDs prevention

Background and purpose. North Karelia Project was among the pioneers in dedicating efforts to prevent Cardiovascular Diseases (CVDs) on a community level. Yet, no full description of its economic evaluation has been found. Due to the importance of utilizing limited resources, economic evaluations are vital in assessing prevention interventions in countering increased burdens such as those in CVDs. Although measuring the cost-effectiveness of North Karelia Project contributes to the general understanding of community-based CVDs prevention; due to its evident health-wise success, its historical timeline and large scale work impose certain difficulties for its full evaluation needs. Thus, the aim of this study is not to run an economic evaluation but rather to define what it would mean for the North Karelia Project by building a Markov model, as a structure for economic evaluation. Public health community-based interventions to limit CVDs burden will be presented by North Karelia Project to frame the search for information needs and missing parts of the evaluation, and how decisions can be made accordingly.

Materials and methods relied on secondary data derived from the extensive literature around North Karelia Project. Markov model framework and economic evaluation in healthcare guidelines were used to steer this process.

Results and conclusion. This paper showed that despite the difficulties in assessing the project costs for economic evaluation, the most relevant needs gap relies on the proper health indicators of measuring the development of CVDs in North Karelia across its publications. Prevention projects focus efforts on initial stages before disease development like primary prevention, and they work on different risk groups in these stages which remain the core component of North Karelia Project objectives. Thus, they should have a substantial representation in the model.

Incidence rate was suggested as a suitable representative of intermediate health outcome through the paper due to its ability to illustrate significantly the costs and morbidity of CVDs. However, the information available from literature concerning CVDs incidence in North Karelia doesn’t cover the whole project period, and modifications of the model will be needed to cover this gap.

Adding a high-risk state to the model was discussed but further research is recommended to determine and acquire data to accommodate the focus on different risk groups before developing first CVDs event. So that, important health outcomes of North Karelia Project would fit the model requirements for its economic evaluation.


of patience and persistence a humble paper can hold between its words. At times it was surely difficult, but looking back at the efforts that were put into it, I can only sense how rewarding this experience is. This research wouldn't have been completed without the generous support from the caring hearts that joined me along this journey. I thank almighty Allah above all for having this opportunity in the first place.

I’m very grateful for Dr. Eila Kankaanpää who showed me how respect, appreciation, care, and academic professionalism can all exist in one person. Without her, this work would have never seen the light, and only through her continues advice and guidance I was able to write what was locked in my mind before. Also, the assistance provided by Dr. Sohaib Khan, Dr. Javkhlanbayar Dorjdagva, and Ms. Annika Männikkö till the very last days of my program in the department of public health in the UEF was greatly appreciated.

I’m eternally thankful for my family who gave me the trust and taught me the strength I needed in this life to travel and seek better chances for my future. My mother whom without her prayers and endless love, I’m nothing. And my father who believed in me. To my little sister Sana, who tolerated with me the distresses and offered with her emotional support more than I can ever give back. And my brother that motivated me before I knew how to hold a pen. Thank you.

I can’t help but express my deep gratitude to Eman, who took my hand in the darkest times, and helped me become who I am today, and still do! To all my friends in the UAE that triggered my longing to their days with their kindness and noble acts, Sara Qarouni, Muna, Mariam, Sara Hassan, Minna, and Rasha. And all the friends in Finland who joined my journey, supported me, and helped smooth my homesickness, and share great moments, to Sara Eltabgi and Samah, Nallely and Carlos, Eeva, Gazi, Mounir, Joona, Sara Eltayeb, and Kieu, I thank you all.

Finally, to all those who have been part of the 2 years journey, writing the thesis, getting my public health degree and reaching this point, I’m very thankful. It has been a very priceless experience, and I enjoyed all the unforgettable times.

Kuopio, Finland June, Sara Alimam







2.1 CVDs ... 9

2.1.1 Pathology ... 9

2.1.2 CVDs globally ... 10

2.1.3 CVDs in Finland ... 13

2.1.4 Economic burden of CVDs... 15

2.2 Prevention ... 17

2.2.1 Definition and classifications ... 17

2.2.2 CVDs recognition and prevention efforts ... 18

2.2.3 Evaluation of prevention programs ... 20

2.3 Economic evaluation ... 23

2.3.1 Definition ... 23

2.3.2 Concepts and use in healthcare ... 24

2.3.3 Decision-analytic modelling and Markov models ... 32

2.3.4 Validity and limitations ... 34

2.4 North Karelia Project ... 36

2.4.1 Health outcome ... 38

2.4.2 Evaluation of the project ... 40

2.4.3 Cost studies ... 42

3 AIMS ... 45


5 RESULTS ... 48


5.3 Markov model structure ... 53

5.4 Information needs for the model ... 61

5.5 Good modelling practice ... 65

5.6 Assessing information needs ... 66






CBA Cost-benefit Analysis CEA Cost-effectiveness Analysis CHD Coronary Heart Disease CHF Congestive Heart Failure CMA Cost-minimization Analysis CUA Cost-utility Analysis

CVDs Cardiovascular Diseases DALYs Disability-Adjusted Life Years HRQoL Health-Related Quality of Life

ICD International classification of diseases ICER Incremental Cost-effectiveness Ratio

LYs Life Years

MI Myocardial Infarction

NCDs Non-communicable Diseases QALYs Quality-Adjusted Life years RCTs Randomized-controlled trials SCD Sudden cardiac death

SDGs Sustainable development goals

UK United Kingdom

UN United Nations

USA United States of America WHO World Health Organization YLD Years lost due to Disability YLL Years of Life Lost



The concern of cardiovascular diseases (CVDs) has outspread in recent years globally. They are responsible for one-third of all deaths worldwide, making them the first threat for human lives in health terms (World Health Organization 2017). CVDs burden is distributed differently between developing and developed countries, but both are unignorably growing concerns.

While CVDs mortality rates have fallen significantly since the 1970s in the developed world, followed by plateau phases in later years, recent studies indicate local rises of CVDs mortality rate since decades, where the increase of diabetes and obesity played a role in altering these changes (Sanchis-Gomar et al. 2016). In the developing countries, morbidity and mortality from CVDs didn’t have trends of decline in a similar timeline, rather than more delayed improvements of health. CVDs rates are also expected to increase in the future resulting from complex factors of social and economic changes, westernized diets, physical inactivity, and an increase in smoking rates in those countries (Sanchis-Gomar et al. 2016). Regardless of the regional differences, it is absolutely crucial to take a deep look into the past trends and build mechanisms to make CVDs less of a burden on a global scale in the coming years.

Working from the Public Health perspective, CVDs have been frequently targeted by interventions and treatments in modern sciences, especially considering their modifiable risk factors. At the same time, advancement in technologies in healthcare has taken a crucial role in the human tackle against CVDs (WHO 2007). However, the problem of scarce resources has always been against the noble aims of doing the best in saving lives. Which means that sacrifices and difficult decisions continue to face healthcare professionals and policymakers.

What they choose to invest in, lead to the lack of some resources in other domains since they are limited to some extent. These matters would highlight the importance of predicting and estimating the consequences on people, health providers, and all stakeholders of any decision in healthcare, thus creating the need for economic evaluations, where all the aspects of alternatives are analysed along with their costs from the desired perspective; to inform decision making (WHO 2009, Drummond et al. 2015).

Finland has given a great example and a guiding model of public health work against CVDs since the 1970s with its national project of North Karelia that started then. Initially, it was a local public health initiative to stop the severe rise of CVDs deaths in one Finnish county:

North Karelia, through targeting its risk factors. Soon after, it has developed on a broad scale


across the country, and continued for 25 years, involving preventive health services, media campaigns, coordination with food manufacturers and local municipalities for following health measures, health education, seminars in nursing schools, meetings with different societal associations, and other modifications on social and environmental determinants of health. Their work wasn’t limited to CVDs later and had other focuses on risk factors of chronic illnesses, different age groups, and various interventions (Puska et al. 2009).

North Karelia Project has received huge attention globally due to its evident success in lowering the burden of CVDs in Finland. One of the main outcomes stated for the project is the decline of coronary heart disease (CHD) deaths by 82% for men, and 84% for women aged 35-64 years between 1969-1972 and 2012 in Eastern Finland (Jousilahti et al. 2016). In addition, the associated mean reduction of its main risk factors: blood pressure, cholesterol level, and smoking in North Karelia and whole Finland populations by different scales was reported along the project years (Borodulin et al. 2015, Vartiainen et al. 2000). During the same period, a lot has changed in CVDs primary and secondary prevention, treatments, and technologies which all contributed to this success. The achievements of North Karelia Project have been well-documented in literature in terms of health outcomes improvement.

Nevertheless, so far and according to the knowledge based on literature review in preparation of this paper, no proper economic evaluation of the North Karelia Project was conducted.

An economic evaluation of prevention programs, like the North Karelia Project, can help to explore the in-depth knowledge of certain processes associated with costs and consequences, especially with its health-wise cited success. This will contribute to the general understanding of community-based CVDs prevention by measuring its cost-effectiveness. However, due to the vast scale and long duration of the project, many challenges arise when conducting a full economic evaluation in terms of measuring health outcomes and accessing costs information.

Thus, the aim of this study is not to run an economic evaluation but rather to define what it would mean for the North Karelia Project. Accomplishing that would hopefully put cornerstone for evaluating its long term economic consequences in later research. The paper will explain building a Markov model, an economic evaluation method, in the frame of North Karelia Project as a public health community-based intervention to limit CVDs burden. In this process, information needs and missing parts of the evaluation will be illustrated, and how decisions can be made accordingly.



Due to the drastic shift in the burden of illness from infectious diseases to non-communicable diseases (NCDs) in the last century for many regions of the world; studies have taken place to understand the various aspects of the latter type. The shift varies between countries and is highly affected by development and income level. Generally, Among the NCDs, CVDs and cancer represent the leading causes of death worldwide. CVDs take more than 17 million lives every year, which is considered to be the biggest portion of chronic diseases burden overall (Ritchie & Roser 2018).

Even though research highlights in the developed world reflect the huge burden of CVDs in these aging populations for governments and societies, over three-quarters of CVDs deaths take place in low- and middle-income countries (World Health Organization 2017). Indicating that it is a truly global issue with various views on whether it is the most targeted health problem or not. And that the CVDs suffering for the elderly populations, their caregivers, and the health systems present huge concern worldwide regardless of the level of development, and countries’

differences (Global Health and Aging. 2011).

2.1 CVDs 2.1.1 Pathology

CVDs are a group of disorders of the heart and blood vessels. CHD and stroke contribute to around three-quarters of all CVDs deaths (Mackay et al. 2004), making them the most fatal diseases among other CVDs types. CHD is a disease of the blood vessels supplying the heart muscle, while stroke is part of cerebrovascular disease that is related to blood vessels supplying the brain. Both disorders are developed due to the underlying cause of atherosclerosis that disrupts blood supply. In atherosclerosis fatty material and cholesterol are deposited inside the lumen of medium and large-sized blood vessels (arteries), deposits (or plaques) cause inner surface of blood vessels to become irregular and lumen to be narrow, affecting normal blood flow. Eventually, the plaque can rupture, triggering the formation of a blood clot. The place where a blood clot is located will decide whether the person will suffer from CHD (in the heart) or stroke (in the brain) (Mendis et al. 2011). In this paper, much focus was given to CHD, while stroke has mentioned severally in the global and Finnish burden sections but due to simplicity reason and time constraints, it won’t be discussed thoroughly in further sections.


Factors that are known to promote the incidence of atherosclerosis or risk factors include behavioural risk factors like tobacco smoking, unhealthy diet (rich in salt, fat, and calories), harmful use of alcohol, and physical inactivity. They contribute to intermediate risk factors that directly increase the risk of CVDs like raised blood pressure, raised blood sugar, raised blood lipids (ex. Cholesterol), and obesity. Socioeconomic level, psychosocial factors, age, and other determinants also describe the risk of CVDs (Mendis et al. 2011).

2.1.2 CVDs globally

Like other chronic diseases, CVDs do not have an impact on the patient suddenly, rather they develop by the time, and their complications also progress through time. The healthy years lost due to any disease are described as disability-adjusted life years (DALYs). They combine the years lost due to disability (YLD) and years of life lost due to premature mortality (YLL) (WHO 2020). It is important to understand the DALYs caused by CVDs when we consider the burden of disease because it measures the lower quality of life for patients of CVDs and its long-term consequences that accompany them in their life journey for many years.

A related term to CVDs and DALYs is the quality-adjusted life years (QALYs) which is what is aimed for in terms of providing better health for patients of CVDs or any other disease.

Usually, QALYs are used in health economic evaluations to indicate effects of health interventions and protective factors for patients’ health, where it combines in the calculation the quantity of years lived, and the quality of life from health aspects. Gaining 1 QALY as a result of intervention X and cost Y $ can be an example of a study result, described as cost per QALY for intervention X = Y $ (Annemans 2017).

Since CHD and stroke account for the second and third global leading causes of DALYs respectively after neonatal disorders, it’s no shock that when combined with other CVDs types they become the cause of 366 million DALYs in 2017 alone, which is the highest number among all other causes. There’s a total decrease in age-standardized DALYs rate of CVDs (per 100000) of 9.9% (-11.0 to -8.8%) globally between 2007 and 2017 (Kyu et al. 2018). While it is still positive to mention such decline recently, observing the variation of trends in the last few decades, and the difference between developed and developing countries draws more attention to the importance of keeping up with prevention efforts to control the undesirable


increase of burden that will be discussed in details furthermore.

The common changes in lifestyle activities, food manufacturing, eating habits, and smoking were all behind the increase that occurred to the prevalence of CVDs in the 20th century. Rapid changes in healthcare, technologies and epidemiological studies could make it easier to track this phenomenon as well. The rates of CVDs were insignificant in the late 19th century but the increase started from then, to reach the most devastating numbers around the 1960s, mostly in the developed world (Jones & Greene 2013). In the United States of America (USA), the death rate due to CHD alone exceeded 800 per 100000 people between 1960 and 1964 (CDCP ).

While CVDs were responsible for 55% of all deaths in Australia for the same period, and rates show similar trends in other developed countries including Finland (Australian Institute of Health and Welfare 2017).

After that peak, some signs of decline started to be observed in the late 60s and early 70s.

Explanation of the change is still under debate. But as discussed by cardiologist Jeremiah Stamler in 1978, having several socio-medical trends that alternated rapidly in this short period, would lead to an absolutely impossible conclusion on the role of each factor alone. While in fact, several factors worked together leading to the decline of CVDs mortality rates (Jones &

Greene 2013). The factors are usually summarized by extreme advancement in healthcare technologies and medication, along with growing public awareness of risk factors around physical activity and food intake. These factors were supported by many public approaches and interventions in the 70s to reduce the health burden of CVDs in many countries of the developed world (Puska et al. 2009, Sanchis-Gomar et al. 2016).

Moreover, advanced statistical technologies enabled researchers to analyse the decline trends in terms of its association with risk factors and treatment development; so that percentages of responsibility of the decline were studied (Jones & Greene 2013). In a model on Scottish data of similar changes between the 70s and 90s, the roles of risk factors reduction, and modern medication were almost equal. 40% of change attributed to treatment, and 51% due to prevention. (Jones & Greene 2013). As well as results in the same time in the USA that associated one-half of the decline in CHD mortality to improvements in therapy including secondary prevention, and the rest to changes in risk factors (Sanchis-Gomar et al. 2016).

Studies from east and west reached similar results of that time.


In the global view, different trends were observed. In Russia, an increase in CVDs burden continued till the 90s, where the economic situation and collapse of the Soviet Union had troubled the situation. While in China, CHD mortality for Chinese men increased by 50% from 1984 to 1999 (Jones & Greene 2013). And the prevalence of CHD in urban India has increased by a factor of six to eight, to about 10% among persons 35 to 64 years of age from 1970s till the beginning of the 21st century. More concern of the burden of CVDs in low-income and middle-income countries is taking place due to the rapid population growth, poverty, lack of health access or universal health insurance schemes in those countries that predicts to catastrophic health issues in the near future (Reddy 2004).

Back to the developed world, the trends of decline had a slower rate after the 70s. In the US, as an example, the rates of decline dropped from 4% to 3% in the 1980s, and to 2.7% in the 1990s (Jones and Greene 2013). Other observations show more of a plateau effect after that period, entering the 21st century. The rise of obesity prevalence has been said to explain some of these changes or no decline in CVDs death rates anymore in many countries like Australia, Austria, Brazil, Germany, Netherlands, the UK, and the USA (Roth et al. 2018).

Overall, the current global trend of CVDs prevalence is still on the decline. Between 2007 and 2017 the age-standardized death rate per 100000 people of CVDs decreased by 10.3% (-11.4 to -9.3, even if the total number of deaths due to CVDs had actually increased by 21.1% (95%

UI 19·7–22·6) for the same period. It is mainly driven by aging and population growth factors.

Most of the decline in CVDs mortality rates are from rheumatic heart disease, which involves damage to the heart muscle and heart valves from rheumatic fever, caused by streptococcal bacteria (Mackay et al. 2004) that was reduced for the same decade by 21·3% (17·8–25·2). On the contrary, both stroke and CHD that account for more than 80% of CVDs deaths had smaller changes: -9.7% (-11.0 to -8.7) for CHD, and -13.6% (-15.0 to -12.1) for stroke (Roth et al.


More recent observations emphasize the slowing rate of decline in high-income countries, especially of the subnational level. Some pessimistic views are concerned about the chance of the rise in CVDs global rates for the first time since the 70s. As mentioned, the role of obesity and causation of other chronic illnesses is discussed now more often. We will look deeper into


prevention methods, but it is rather indisputable that medications which control risk factors of CVDs like elevated blood pressure and blood cholesterol are cost-effective measures in the hands of health systems. Matters of effective delivery and implementation are the bigger concern now (Roth et al. 2018). Collaborative work on all risk factors that cause CVDs is essential to achieve the United Nations (UN) goal of 25% reduction of CVDs mortality by 2025. However, poorer countries might fail to reach this aim even when targeting the various risk factors, due to the issues related to population growth, poverty, and securing insurance as discussed earlier. But the evidence of a slower decline is a motive for all countries, in general, to focus more on investing in cost-effective approaches to deliver treatment and medications properly, and utilize public health measures in risk factors’ trends changing (Roth et al. 2015).

2.1.3 CVDs in Finland

Finland is one of the Nordic countries in Europe that went through rapid development after World War II. And similar to other countries in the developed world, in Finland, CVDs mortality was of remarkable increase after the 40s (Salomaa et al. 2016), commonly explained by the change of lifestyle factors, diet, and physical activity as discussed earlier. Mortality rates reached their peak by the 70s, not only compared to recent history, but Eastern Finland region had, in fact, the highest deaths rates due to heart disease in comparison to the world (Puska 2010).

Many projects in Finland specifically, generally in Europe and globally have taken place to target the rapid increase of CVDs burden back then. We will go through the processes that led to the decline in Finland’s rates in details throughout this paper. Nowadays, as provided by Official Statistics of Finland (2017), the importance of CVDs as a cause of death for the Finnish population has decreased from 44% to 36% over the last 20 years. The observed decline is presented as age-standardized mortality rates from CHD from an earlier time, between 1971, and 2017 in Figure 1. Both males and females had a drastic change in their mortality rates due to heart disease in the last 50 years, with males’ rates starting and ending almost double the rates for females despite the similar decreasing trend. Elderly population shared part of the change too. While all socioeconomic groups have benefited from the efforts spent to enhance their health, some disparities between groups still exist (Jakovljević et al. 2001). Most importantly, studies have summarized the change due to the decline in the first incidence of CHD, combined with case fatality reduction. The first type indicates the plausible results of


primary prevention and community-based efforts. While the decline in case fatality shows the significant effect of advanced treatment and less severity overtime. (Salomaa et al. 2016).

In other references, trends of risk factors decline that backed up the CHD mortality seen in the figure above were stated to level off during the 1980s. Some Finnish officials discussed this

“relapse” as a form of losing interest from the public after the intensive prevention period in the 70s. Also, the tobacco and food industries may have acted to their favor after this lack of interest. Prevention of mass disease was realized later by health professionals and laypeople that it is an extremely long process that requires their dedication. Counter messages and creative ideas raised to implement the positive changes deeper in the society. And two main concerns were discussed to strengthen these acts: the continuation of political will for improving CVDs situation in Finland, and to avoid repeated messages that would cause community boredom and loss of aim novelty (Jones and Greene 2013).

Nowadays, Finland shares similar CVDs mortality profile with neighboring countries in Northern Europe (OECD 2018). Despite the remarkable decline in death rates, CHD mortality is still considered high in Finland compared to other developed countries, like France, Spain, or Italy. It is partially explained by the historic higher rates initially in this area (Salomaa et al.

2016). In 2017, one in five deaths, and one in six deaths were due to CHD for men and women respectively in Finland. However, a notable change in the CVDs death rates in Finland is concerning the age group of survivors. In 2017, less than 10% of deaths due to CHD were in working age groups, while it was around 40% in 1971 (Official Statistics of Finland 2017).

Figure 1. Age-standardised mortality from ischaemic heart disease in 1971 to 2017 provided by (Official Statistics of Finland 2017).


This information particularly relates to the effect of disease on society from economic burden perspective that will be discussed later.

2.1.4 Economic burden of CVDs

As discussed earlier, we summarized the global health burden of CVDs, and what happened in Finland in tackling this disease. CVDs still take lives every day more than any other disease does worldwide. Needless to say, how much the loss of these lives mean to the human being, the society, and nations. In this part, we will go through the economic meanings of this loss.

Defining the impact of illness from an economic point of view is stated to be distinct from clinical and epidemiological approaches of understanding, but acts as a complementary function, not an alternative one to inform about the consequences of disease. The economic burden view addresses 2 levels of costs' weights. The first level is concerned about the cost to households, firms, or governments while the other one studies the impact of disease on the national gross domestic product or future growth aspects. These two levels follow microeconomic and macroeconomic schemes respectively. Economic losses identification helps decision-makers recognize its magnitude, distribution across many factors, and guides policies towards the reduction of costs and burden using evidence-based medical or preventive approaches. The regularly used methodologies of assessing economic burden usually combine direct costs of medical care with indirect costs of productivity loss due to morbidity and mortality (WHO 2009).

Responsible for around one-third of global deaths every year, CVDs economic burden has been frequently investigated and illustrated in forms of comparison between countries, and predictions of how CVDs might threat the economies of the future. Also, many studies are interested in evaluating the costs of CVDs due to its highly modifiable nature, where preventive individual and public approaches had proven clinical improvements and effectiveness. This fits with the noble aim of economic burden studies to guide policymaking towards strategies that favour health and proper resources allocation.

A recent report from the American Heart Association has estimated the total annual costs of CVDs in the USA between 2014 and 2015 to be $351.2 billion. It includes $213.8 billion in expenditures (direct costs), and $137.4 billion in lost future productivity attributed to premature


CVDs mortality (Benjamin et al. 2019). While prediction for the situation in 2030 showed annual productivity loss in the USA to reach $275 billion, and total costs to be $818 billion (Giedrimiene & King 2017)

In comparison, a report from European Heart Network in 2017 presented the overall cost of CVD to the EU economy to be €210 billion a year. Of which, around 53% (€111 billion) is due to health care costs, 26% (€54 billion) to productivity losses and 21% (€45 billion) to the informal care of people with CVD (Wilkins et al. 2017). One particular issue that was discussed in these reports is aging populations in the developed world. Thus, even if decline has been prevalent in age-standardized CVDs mortality rates, but the number of deaths has increased as mentioned earlier. And the projected increase in its economic burden will have significant trends.

Shares of burden present huge concern in low- and middle-income countries as well due to the drastic consequences it will impose on economic systems that are already tired, and societies who will be pushed more into poverty and catastrophic health expenditure due to CVDs burden.

The cumulative economic lost output due to CVDs in low- and middle-income countries was estimated to amount to $3.7 trillion between 2011 and 2025, representing approximately half the NCDs economic burden as per WHO projection report (Bloom et al. 2011). Due to the competing health priorities in these countries, the resources targeted for preventive approaches to manage the burden of CVDs are limited. However, the process of moving towards NCDs globally, including these countries indicates that failure to act now will result in large increases in avoidable CVDs, placing serious pressures on the national economies (WHO 2007).

In Finland, cost of CVDs was estimated in relation to the consequences of North Karelia Project that aimed for its prevention. The most updated version was in 2009 publication of the project estimating that total social costs of CVDs in the year 1992 accounted for 2.6 USD billion, having almost 1 USD billion as direct costs, and 1.6 USD billion as indirect costs. Also, a significant difference is seen between men and women in those shares. Men have indirect costs as 76.3% of total costs, while it is only 34.1% for women (Puska et al. 2009). These results were based on an earlier study investigating the CVDs costs in Finland (Kiiskinen et al. 1997).


2.2 Prevention

2.2.1 Definition and classifications

The majority of CVDs risk factors are considered to be modifiable, i.e. direct efforts to control these risks are highly achievable, and possible to reduce their unpleasant consequences. World Health Organization (WHO) identifies feasible and cost-effective interventions that target the prevention and control of CVDs. They consist of population-wide and individual-level interventions that are better combined for better results of burden reduction (World Health Organization 2017).

The population-level approach is considered to be more cost-effective, and applicable in limited resources settings. Examples can be related to policies and regulations for tobacco and alcohol use, increased taxation that targets the reduction of fatty, sugary and salty food intake, building environments that encourage more physical activity, and implementation of health education in young age groups. While individual approach mainly works within the healthcare sector for primary and secondary prevention of CVDs for the high-risk groups. It targets patients with hypertension, hypercholesterolemia, or any other increased risk of developing cardiovascular disorder both medically and with lifestyle-related interventions (World Health Organization 2017).

These preventive approaches are classified in other definitions based on selection, where universal prevention, similar to the population approach, considers the whole population at risk, and all would benefit from such interventions. It minimizes labelling of groups and includes different classes, which may discourage policymakers to support this type (Offord 2000). One feature for the wider level is targeting social and environmental determinants of health (Puska 2010). Indicated prevention targets already diagnosed individuals, or those who develop early symptoms of the disease. While selective prevention works in the middle, for people who have a higher risk of developing diseases. Tailored interventions are designed to fit the needs of these groups through risk assessments (Sonderlund et al. 2014). Indicated and selective prevention match the individual approach identified by WHO earlier.

The recent decline in CVDs mortality in some parts of the world is highly connected to developments in treatments and technologies in healthcare, as well as the combination of


different approaches of prevention discussed. The moderate risk is usually highly spread among people, because it’s related to daily lifestyles, while high-risk groups represent a smaller portion in the population. Therefore, choosing to target the population with wider approaches or community-based interventions results in a major change in the risk factors profile for the whole population, hence less burden of CVDs. In other words, community-based interventions are able to shift the risk factor distribution curve to the left rather than target the high-risk end of the curve only (Puska et al. 2009).

On the other hand, neglecting high-risk groups’ need of additional efforts may result in keeping the CVDs burden on them and the whole society, since they would still cause skewness of profile to the increased risk direction. Therefore, the combination of all approaches, even if it requires more hard work to assess and design specified and general interventions together, but it presents highly cost-effective results on the long run for people and government that pays off. In the UK, CHD mortality had declined 62% in men and 45% in women between 1981 and 2000. The decline was explained by 58% reductions in population-wide risk factors, but these changes attributed more than 50% to high risk and pre-symptoms populations (Unal et al.


All in all, the majority of populations usually consist of people with low to moderate risk of developing CVDs. They will continue to suffer from its illnesses if no population-wide public health interventions targeted this issue. These strategies should encourage lifestyle behaviour change for people with high risk as well, and slow down the unpleasant scenarios. Additionally, they also help in reducing other NCDs burden through shared risk factors’ decline, like cancer, diabetes, and chronic respiratory disease (WHO 2007). “The advantage of community-based lifestyle prevention programs is that the health gains achieved through population-based approaches often exceed those achievable by targeting specific groups in clinical or subclinical settings” (Saha et al. 2010). Through-out this paper, we will continue to talk about universal (or population) level prevention since our targeted community-based project (of North Karelia) follows this approach.

2.2.2 CVDs recognition and prevention efforts

WHO and other global parties have set different goals and spent huge efforts in the prevention of CVDs in the last few decades. International projects were important collaborations that


saved millions of lives and created better lifestyle settings and helped in the effective prevention of CVDs in the recent era. Among these projects, there are few examples of pioneer efforts that need to be presented.

The Framingham Heart Study

Considered to be one of the best-known studies, focusing on CVDs, The Framingham Heart Study involved many thousands of men and women living in Framingham, Massachusetts, examined and followed up with them regarding certain personal factors that are suspected to be strong and consistent with increased risk of CHD. The study was launched in the early 1950s, and still ongoing till today. With continues efforts in the recognition of associations of disease, the concept “risk factors” was later identified, and the common cholesterol, smoking, blood pressure, and other risk factors were later highlighted. It represents a model for many other works in relation to CVDs follow up, and resulted in many prevention projects consequently (Mahmood et al. 2014).

The Seven Countries Study

In line with the initiation of Framingham study, the Seven Countries Study was established in the mid-20th century by bringing together researchers from all over the world. The aim was to explain the large variation in death rates from CHD in different countries. Finland was one of the seven countries chosen for its high-risk CHD prevalence. This study found the classic Framingham risk factors to differ in the importance of predicting variation in coronary risk between whole populations in different countries (Menotti et al. 1993).

WHO CVDs prevention

National and global level projects were initiated slightly after the results of those early efforts started to show some correlations of diseases. North Karelia Project was one of the first programs leading the prevention against CVDs, we will go into its details later. But, it is important to know that by the early 70s it influenced the establishment of many other national and international works. For example, it led to the demonstration of WHO-related programs:

- Comprehensive Cardiovascular Community Control Program (CCCCP) in Europe.

- Countrywide Integrated NCDs Intervention (CINDI) in Europe.

- CARMEN (Actions for the Multifactorial Reduction of NCDs) in the Americas.

- Interhealth (WHO headquarter, 12 countries from all regions)


As well as local projects such as the Stanford Three-Community Study, Stanford Five-City Project, Minnesota Heart Health Program, all in the US (Fu 2019).

In the present time, WHO sustainable development goals (SDGs) also identified the global objective that is designed for the reduction of CVDs burden. It is included in the 3rd goal of ensuring healthy lives and well-being by 2030, through reducing by one-third premature mortality from non-communicable diseases through prevention and treatment and promote mental health and well-being, including the morbidity and mortality from CVDs (WHO 2019).

2.2.3 Evaluation of prevention programs

CVDs prevention programs, as stated earlier comprise a combination of medical individual interventions and population-level public interventions. Variation in CVDs prevention projects is observed worldwide. It is part of the valuable meaning of research in medical studies and other sciences to compare these interventions; in order to reach the most effective, and most efficient desired objectives. In public health, different methodologies and implementations of prevention programs occur. They do have various results as well. Therefore, it is of high importance to study, evaluate, and compare those interventions; to summarize the best implementation methods, and its suitability based on context for the valuable aims of better practices in saving lives against CVDs. As the question in this battle isn’t anymore what should be done, rather how it should be done (Puska et al. 2009).

Complexity is one of the main features of current prevention programs. The trend throughout the decades shifted from smaller scale sanitation, hygiene or vaccine programs in public health, to inter-sector, interpersonal, and long-term scale. Prevention is determined more than ever by socioeconomic, demographics, and other available or limited settings. With the increase of complexity and resource consumption, the need for studying, investigating and accounting increases. Therefore, the role of documentation of programs processes, and implementation, is getting more attention. As well as the need for a description of outcome measures to define the accurate achievements and shortcomings. (CDCP 2011).

Assessing prevention effectiveness is defined to involve: “quantitatively analyzing the impact of prevention on health outcomes and examining the societal consequences of disease and injury-prevention activities, including any medical, legal, ethical, or economic factors”


(Thacker et al. 1994). It is important to recognize that even with consideration of these various factors in evaluations, the main aim stays towards better health, with limited resources, not to simply minimize the resources consumed in this process, or cut the costs.

In order to provide proper information in the evaluation of prevention programs, assessment and evaluation need to be an ongoing process. This acts as a better role to convince policymakers of funding health programs more than single evaluations does. (Thacker et al.

1994). In general, the evaluation process is carried along with the steps of the programs, from planning and implementation phases, until the evaluation of outcomes and impact (Rural Health Information Hub 2020). Within these types and stages of preventive program evaluations, there are several aspects to be studied and clarified, such as management of resources to be used for conducting the evaluation, stating its approaches, models, or theories, engagement of stakeholders, identifying the key characteristics of the program and its context of interest, and how the approach will fulfil its objectives. Also, the collection of data about evidence and findings should be agreed-upon to help to report and accept the results and quality of the evaluation (Western Michigan University 2020). These considerations help in building reliable evaluation structures.

Various reasons highlight the need for evaluation of public health programs along its stages and after completion. First, observing if the progress is contributing to the program objectives and if the processes are capable of handling the desired health outcomes. Second, it enables the in-depth investigation of population groups of interest, their variation, different risk factors, health distribution and inequalities. In this way, the evaluation would help in justifying the need for further research and action, and finding opportunities for improving the quality of work. Economic wise, it informs about the effective use of resources and decision of their allocation (CDCP 2011).

Because prevention usually aims at health improvements in the long run and the progress of diseases has different stages; economic evaluations involving Markov models, as one form of evaluation, has the features and functions that help cover these aims, and more will be discussed regarding these models in further sections. But it is rather pessimistic to consider the prevention project’s effectiveness is measured only during the intervention period, and very optimistic if it’s thought of continuing till population of interest death (Saha et al. 2010). Therefore, the


point of timeline in the evaluations of preventive programs do create a significant matter that affects how the results of the evaluation can be used and interpreted.

Borrowed from social sciences, the timeline perspective is frequently discussed in assessing health interventions; due to its consequences on objectives, inputs, prices, and results of effectiveness determined by the evaluation. Figure 2 below works well in representing the project phases, and the types of evaluation that follow on its timeline. Most frequently, interim and final evaluations are used in the implementation phase of the projects due to their importance in management and control information to avoid or correct mistakes. However, the use of ex-post and ex-ante evaluations is less prevalent, despite their huge importance (Samset

& Christensen 2017).

Figure 2. Evaluation during different project phases, adapted from (Samset & Christensen 2017)

The ex-ante evaluation provides strategic information about the main choices at an early stage when the possibility to influence the course of an undertaking is greatest. It enables the identification of which alternatives has the highest potential of benefits using the given investment. On the other hand, ex-post evaluation is capable of informing about design and decision improvement for future implications of similar projects. Its goal is to find the lessons learned and motivates the comparison of different project for the best practices (Samset &

Christensen 2017).

Idea and decision phase

Implementation phase

Operational phase

Ex-ante evaluation

Interim evaluation

Final evaluation

Ex-post evaluation


2.3 Economic evaluation 2.3.1 Definition

After stating the need and importance of continuously evaluating health intervention, we will elaborate on a major type of evaluations, the economic evaluation. Although it is introduced from the other sciences, economic evaluation represents a valid source of documentation and assessment for various decisions in healthcare. That is due to the whole picture, a full economic evaluation draws on all aspects of health interventions studied. It consists of a set of techniques aimed at examining alternative courses of action, in terms of their costs and benefits, with a purpose to help make a choice (Drummond et al. 2015).

In simple terms, the main requirements for economic evaluations would comprise of comparison of two alternatives, with associated costs and consequences of the two alternatives.

As discussed earlier, many reasons motivate the evaluation of health interventions in general.

However, for the prominence of economic evaluations in healthcare decision making, the main reasons are usually, the increased pressure on limited resources that pushes the move from finding clinical effectiveness only, to aim for clinical and cost-effectiveness combined. Also, jurisdiction and accounting for the use of resources derive the need for economic evaluations and justified funding mechanisms. These aims have led to the frequent utilization of these studies in pharmaceuticals, their market entry, regulation of prices, and reimbursement. As well as public health interventions, and public settings that have single-payer health systems where financing a decision directly affects other health interventions decisions (Drummond et al.


To elaborate, economic evaluation can’t guarantee the prediction of all possibilities in the future for specific compared alternatives in healthcare, rather, it helps in providing evidence to support the decision that needs to be taken anyway for what and how to choose, and the most desired feasible outcome (Drummond et al. 2015). The impact of decisions would fall on different groups depending on the nature of health systems, coordination within the health sector and between other public sectors. For health systems that tend to be more independent, where health expenditure is internally shared between services, interventions, and needs, funding decisions would influence mainly the other health domains and services, thus, priorities are set within healthcare only. While other health systems might have integration of


decision responsibility and share financing schemes with other public sectors like education, transportation, media, etc. Expenditure on health in these cases would have a broader impact on other domains. Decision of funding a health project is therefore dependent on the capability, resources, and consequences on multi-sectors. Whether decisions in health have limited effects within health sector or outside it, would lead to the importance of providing evidence base for estimating costs and consequences, and informing decision making, the role that economic evaluations in health care tries to fulfil (Drummond et al. 2015).

An economic evaluation of health project provides reasons and explanations why giving up certain costs is justified or at least backed up by evidence to promote health or save more lives.

However, as discussed earlier, the main aim of health studies and interventions is the health and quality of life. Economic evaluation does not indicate to contain costs of such aim, rather than minimizing the costs of promoting health by avoiding unnecessary spending on less effective work, while more achievements are possible with a similar cost (Briggs et al. 2006).

2.3.2 Concepts and use in healthcare Evidence in economic evaluations

Since economic evaluations are highly dependent on sources of information used, the validity of results varies accordingly. Stronger evaluations can’t be driven from one clinical study rather than its need for systematic approaches in data collection (Drummond et al. 2015). The evidence used in these studies follows the same hierarchy as other scientific researches, where Randomized Control Trials (RCTs), systematic reviews, and meta-analysis are found of top quality resources (Burns et al. 2011). However, it is good to mention that in the case of population approaches in prevention, RCTs, even if they’re good evidence for effectiveness, but they’re not applicable to be used. As usually, RCTs cannot last long enough for prevention studies. Therefore the use of modelling studies is needed. Modelling can combine information and data from different, multiple sources instead (Briggs et al. 2006).

In addition, an economic evaluation study describes a point in time, not a complete future scenario, therefore it is expected to have changes of results through time, based on input developments, and change of knowledge resources. There isn’t a perfect choice among all times, but the accumulation of information and continuous work is worthy for reaching better knowledge.



In conducting economic evaluation in healthcare, one of the main principles is based on the scope of the evaluation or its perspective. It is the point of view adopted when deciding which types of costs and health benefits are to be included in an economic evaluation (Perspective.

2016). The question evaluation tries to answer can be of governmental, health sector, or societal related. These perspectives don’t only direct the purpose and interpretation of evaluation, but also will result in different information included in the analysis. Deciding on which perspective to be directed is based on the interaction of stakeholders with the project itself, benefits of the result, parties responsible for decision making, and those who will be affected by the decisions, whether they are receivers of intervention, or lacking other consequences because of it. They are all in consideration when assessing information needs but mainly the economic evaluation should aim for leading informed decision making on a specified scope among the others, in order to extrapolate its results (Drummond et al. 2015).

Several arguments are described for the advantages and disadvantages of using different perspectives in economic evaluations. The interest in health sector (or health services) perspective is backed up by its deep involvement in the costs, capacities, and people’s utilization of health services. In systems where the health sector is highly universal, this reflect a societal view within the health sector view since the whole population is involved in health services. However, it may still fail to prioritize the maximization of the welfare gains to society as a whole, and the discussion of a completely equitable universal health for all is often under debate even in systems following the highest standards (Byford & Raftery 1998).

On the other hand, societal perspective is argued to have better potential in including the impact on whole societies, not merely those interacting with healthcare services. It involves the direct costs on health sector as well as the productivity losses due to time lost from work because of illness outside the limited health perspective. Besides, through weighting the cost shifts between sectors, the societal approach takes into account the alternative use of resources outside the health sector that may impose bigger benefits to the society (Byford & Raftery 1998).

Both approaches do not necessarily consider the value of losses and consequences to the non-


working groups whether due to retirement or any other reasons if not studied particularly, thus may bias the results against these groups (Perspective. 2016). For this reason, as an example, the National Institute for Health and Care Excellence in the UK recommends the combination of personal, social, and National Health Service in assigning perspectives for economic evaluations (Perspective. 2016). So that specific treatment, services, and adverse events costs are included within the personal view even if missed in the other views. In general, an important consideration in specifying perspectives in studies is to explicitly state and explain the justification of choice no matter what information and challenges attributed to the decision eventually, so it helps keep the usage of results in a valid representative manner (Byford &

Raftery 1998).

Economic evaluation aims to inform decision making but more necessarily is how decisions are made on behalf of others. In this way economic evaluation raises accountability and shared responsibility, especially when there is lack of complete information, yet decisions have to be made anyway. Budget constraints, preferences, habits, etc. have all an impact on decision making. The social value of deciding what to do that will benefit some groups but will take benefit or limit it from others. In which, an economic evaluation tries to state the criteria for that clearly. Also, if these studies do not pay much attention to who will gain the health benefits and who will face the costs, that should be done in addition to economic evaluation.

The importance of perspective in economic evaluations relates also to the decision making that occurs based on the threshold of payment of the questioned authority, or if not set explicitly, then it’s the decision maker’s willingness to pay extra for the better effectiveness. Without a comparable threshold, results of studies cannot be directly reflected in real-world decisions, unless the willingness to pay is implied within society. Payment thresholds are associated with health authorities and governments in many countries. For example, the UK specifies 20,000£

and 30,000£ as cost-effectiveness threshold, which provide guidance on how resources are intended to be used for health interventions; in order to guide studies, and work on health projects (McCabe et al. 2008).


In order to provide full economic evaluation that can compare the cost and consequences of certain projects in health care, a clear statement of alternatives is needed. Alternatives are the


main pathways of comparison that economic evaluations rely on, and they compose the rationale of the need for decision making, as they create options to choose from. The identification of alternatives for interventions in healthcare needs critical assessment on the feasible, effective, and realistic choices. The selection of the other alternative of interest would directly affect how results are observed. And it should be the responsibility of the decision- maker, which means, choosing unrealistic alternatives may bias the results and encourage the decision towards the desired outcome. That’s why assessing alternatives is highly critical and can be developed based on the perspective to be studies and systemic data collection on best alternatives, its effectiveness and costing information (Drummond et al. 2015). But to make things clear, even if different alternatives have effects on different subgroups (with various history or reflections) but in the economic evaluation, we study the different alternatives on a single group only to help direct the efforts and create the full picture for decision making.

Costs and opportunity costs

A brief explanation of costs types in healthcare have been mentioned earlier in section 2.1.4 Economic burden of CVDs. However, it is relevant to state the concepts behind costs understanding, and more of its methodologies in economic evaluations. Briggs et al. discuss that individuals decide the potential value of benefits offered to them through services or products, then decide whether or not to pay based on market prices, therefore, the decision of cost is dependent on improving their welfare. Prices do not simply indicate what things ‘cost’

but they also represent the social value of the inputs and outputs of an alternative (Briggs et al.


The earlier discussion on perspective is highly connected with choices of costs in the economic evaluation, as it creates the resources frame and boundaries of decision for cost information to be included in the study. This results in a large frame of costs for societal perspective for example and a reduced limited boundaries frame for specific organisation or health sector perspectives (Raftery 2000).

Other implication of perspectives is to the stages of costing that involve three different concepts for costs: Identification, measurement, and valuation. First, by identifying costs in economic evaluations, scholars list all possible costs before excluding some of them based on the set framework. Measurement is concerned about how the cost information will be assessed, like


prices of drugs, time, working hours, and their weights, people involved, bed prices, and all kinds of measures related to direct and indirect cost of diseases. Finally, valuation stage is more related to economic theories of cost and societal value, and how the meaning of price varies between economy and health domains (Raftery 2000).

The cost of illness approach that defines direct and indirect cost of disease was formalized since the 1960s by the efforts of different scholars and several discussions supporting or opposing to the valuation and methodologies of costs in health economic studies have followed since then.

The most common approach includes in the direct costs all the medical and non-medical expenses that incurred because of illness. This involves medical care, travel costs, prevention, treatment, rehabilitation, and may add training, medical research, and other modifications due to illness. While the indirect cost of illness is mainly driven by the lost production because of reduced working time, it remained more complex in terms of measurement in economic evaluations and doesn’t have a unified understanding or guideline (WHO 2009). Average wages, unemployment rates, and the value of non-work-related productions are some of the matters discussed for this concept but this review limitations cannot take the terms’ discussion further.

The intangible costs of disease are a third type that usually isn’t utilized similarly in economic evaluation studies due to its difficulties of measurement and valuation as can be understood from its name. Intangible costs include the human suffering, pain, and grief of the patient and caregivers that usually fall out of the scheme of economic studies. Therefore, identification of evaluation scope, or perspective is rather important in all the previous costs understandings because it defines what matters in economic evaluation conclusions, and what crucial parts are identified outside of its boundaries but still take part in making decisions eventually (WHO 2009).

In a health perspective of cost understanding in economic evaluation, the same cost dedicated to a certain health intervention is usually withdrawn from other use. The missed use in other health project or different sectors describes what so-called “opportunity cost”. The opportunity cost of one alternative is defined as the benefit foregone from not being able to have the next best alternative (Kattan 2009). Opportunity cost depends on the nature of the health system. If health expenditure is restricted, it falls on the health sector, and if it’s not restricted, it will


affect public consumption. Generally, some opportunity cost would fall on both. Even when economic evaluations are not able to include these costs into account for direct calculation, at least identification of those groups who have the costs and consequences of alternatives relevant to them directly or indirectly in important (Drummond et al. 2015).

Health gain and types of economic evaluation

Measuring health gain in research and economic evaluations is rather argumentative. In general, any indicator should aim to describe health effects, whether they are improvements or side effects, and should depend on valid sources of knowledge. In comparison terms, QALYs have been frequently used due to its ability to describe a unified quantity for different health outcomes. Given than in QALY weighting: 1 value describes perfect health, and 0 value describes death or (no health), the variation of health outcomes in QALYs’ terms would include both morbidity and mortality. It aims to involve the value of “peace of mind” as well rather than other health indicators (Annemans 2017).

Others argue that as opposed to health effects, some studies are empathizing use of willingness- to-pay or monetary benefits due to the dissatisfaction of QALYs capability to reflect preferences and its poor reflection of all aspects of healthcare like compliance from increased convenience of screening and assurance. As well as the costs and effects that go beyond the health care budget (Drummond et al. 2015). However, even with the use of QALYs, when society’s perspective is chosen in publicly funded systems, all the relevant services and their costs should be included in economic evaluations, or at least considered as discussed earlier.

There are different types of economic evaluations in healthcare. They are classified based on consequences or health outcome measured. Each health outcome measure would influence how results can be compared to other studies and interventions. Also, the value put to health outcome is affected by the perspective in which an intervention is evaluated. While in all types, cost measure is always in monetary values, the main differences are seen in table 1 below between the consequences measurements.


Table 1. Types of economic evaluations, adapted from (Adhikari 2017).

Types of

analysis Costs Consequences Result

Cost- minimisation analysis (CMA)


value Identical in all respects Least cost alternative Cost-benefit

analysis (CBA)

Monetary value

As for CUA but valued in money. Eg. Willingness-


Net $ Cost: Benefit ratio Cost-

effectiveness analysis (CEA)

Monetary value

Different magnitude of a common measure. Eg.

LYs gained, BP reduction

Cost per unit of consequences.

Eg. Cost per LY gained

Cost-utility analysis (CUA)

Monetary value

Single or multiple necessarily common, valued as “utility” Eg.


Cost per unit of consequences.

Eg. Cost per QALY LYs, life years; QALYs, quality-adjusted life years; BP, blood pressure.

1- Cost-minimization analysis (CMA):

In this type of economic evaluations, two or more interventions are compared when they have identical outcomes, yet their costs varies. Investigation is applied through to identify the intervention with the lowest cost. It enables the assessment of technical efficiency of interventions and doesn’t require huge information needs in comparison to other types.

However, the assumption of identical health outcomes should be strong enough and do not impose differences attributable to disease studied (Klarenbach et al. 2014).

2- Cost-benefit analysis (CBA):

Both cost of the intervention and its benefit incurred are measured in monetary values in this method of economic evaluation, where the net benefit equals the subtraction of costs from direct intervention benefits. So that, when benefits exceed costs, it should be valid to continue with the intervention. The valuation of health outcomes in economic terms is the matter of discussion in this type (Adhikari 2017).

3- Cost-effectiveness analysis (CEA):

More commonly used in healthcare, the CEA uses natural units like life years gained, measured improvements in levels of risk factors like units of blood pressure or cholesterol to assess the


health outcomes, or effectiveness. Then, the cost is measured against the effectiveness of the intervention, and similar measures among interventions are compared where result is expressed as cost per unit of health. Although this type has often accessible data on health outcomes readily available from clinical trials, results may be difficult for interpretation. Comparison between populations and diseases is not possible due to the differences in health outcome measurements. For example, it is not logical to compare 1 life year gained with 30% reduction of smoking rate. Besides, effectiveness outcomes lack the ability to capture all relevant health outcomes around interventions, especially on the large scale like public health programs (Klarenbach et al. 2014).

4- Cost-utility analysis (CUA):

The utility term related to health measured as intervention consequence of this type refers to QALYs or DALYs that is more used when multiple objectives of programs are measured, and when both quality and quantity of life is important for the study. CUA is more common to make policy level decisions due to its capability of comparing outcomes between populations and different diseases, expressed as cost per QALYs for different interventions compared.

Also, the metric scale of QALY comprehensively measures health aiming to cover more dimensions than single health units. QALYs identification is usually based on population valuation of health outcomes from representative surveys, and do not involve personal view of health. With its components, this type of economic evaluation requires the most data among other types, and is highly demanding of resources (Klarenbach et al. 2014, Adhikari 2017).


In the matter of comparing results and interpreting economic evaluations, one important factor to be discussed is implementation. Different aspects are studied regarding implementation and economic evaluations of health interventions. There is the effect of different implementation strategies of health interventions on costs and effectiveness, thus, will change the information used for economic evaluations. And, the use of economic evaluation results in informing better practices of health interventions implementation, since cost-effectiveness is one of the factors needed for better implementation strategies. So, economic evaluations work interactively with implantations studies informing each other (Hoomans & Severens 2014).

There are more forms where both sciences interrelate, economic evaluations are basically



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