Evaluation of Cost of Illness and Quality of Life in Acute Myocardial lnfarction*

Evaluation of Cost of Illness and Quality of Life in Acute Myocardial lnfarction* | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 9 January 2025 V1 Latest version Share on Evaluation of Cost of Illness and Quality of Life in Acute Myocardial lnfarction* Authors : Ferda Işıkçelik 0000-0002-7975-4141 [email protected] , Ismail Agirbas , and Cansın Tulunay Kaya Authors Info & Affiliations https://doi.org/10.22541/au.173641414.45451746/v1 Published Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi Version of record Peer review timeline 187 views 121 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Background It is important to examine the effects of quality of life and determine the cost of illness of Acute Myocardial Infarction, one of the leading causes of death worldwide. factors, and comorbidities by this prospective study. Methods We calculated the cost of illness according to the bottom-up costing approach from the perspectives of patient and relatives, payer, and societal, and evaluated the disease-specific quality of life with HeartQoL and the general quality of life with EQ-5D-5L. Results The mean HeartQoL global score is 2.13±0.73. The mean EuroQol index score of the patients is 0.84±0.24, and the mean EuroQol VAS score is 70.74±22.94. The cost of illness per patient is $489.34 from the patient and relatives perspective, $641.98 from the payer perspective, and $1,131.32 from the societal perspective. The general quality of life scores of those without comorbidities are higher than those with comorbidities. Conclusion We concluded that the quality of life of patients with a family history of hypertension, diabetes, cholesterol, and obesity is lower than patients without any. It has been determined that the cost of illness is higher in patients with risk factors, and loss of income, medical supplies, and direct medical care costs have an important place in the cost of Acute Myocardial Infarction. We concluded that the quality of life of patients with low cost of illness compared better to patients with high cost of illness. Evaluation of Cost of Illness and Quality of Life in Acute Myocardial lnfarction* Cost of Illness and Quality of Life in Acute Myocardial lnfarction Ferda Işıkçelik a , İsmail Ağırbaş b , Cansın Tulunay Kaya c a Burdur Mehmet Akif Ersoy University, Faculty of Economics and Administrative Sciences, Department of Healthcare Management, Burdur, Türkiye, ORCID: 0000-0002-7975-4141 b Ankara University, Faculty of Health Sciences, Department of Healthcare Management, Ankara, Türkiye, ORCID: 0000-0002-1664-5159 c Ankara University, Faculty of Medicine, Department of Cardiology, Ankara, Türkiye, ORCID: 0000-0002-1168-9005 Correspending Author: Ferda Işıkçelik, [email protected] , Department of Healthcare Management, Burdur Mehmet Akif Ersoy University, 15200 Burdur, Türkiye *We produced our research from the doctoral dissertation titled ”Evaluation of Cost of Illness and Quality of Life in Acute Myocardial lnfarction”. Funding: It was supported by the Scientific and Technological Research Council of Türkiye (project number:123K003). Competing interests: The authors have no affiliations with or involvement in any organization or entity with any financial or non-financial interest in the subject matter or materials discussed in this manuscript Acknowledgements: We are grateful for the support from the Scientific and Technological Research Council of Türkiye. Abstract Background It is important to examine the effects of quality of life and determine the cost of illness of Acute Myocardial Infarction, one of the leading causes of death worldwide. factors, and comorbidities by this prospective study. Methods We calculated the cost of illness according to the bottom-up costing approach from the perspectives of patient and relatives, payer, and societal, and evaluated the disease-specific quality of life with HeartQoL and the general quality of life with EQ-5D-5L. Results The mean HeartQoL global score is 2.13±0.73. The mean EuroQol index score of the patients is 0.84±0.24, and the mean EuroQol VAS score is 70.74±22.94. The cost of illness per patient is $489.34 from the patient and relatives perspective, $641.98 from the payer perspective, and $1,131.32 from the societal perspective. The general quality of life scores of those without comorbidities are higher than those with comorbidities. Conclusion We concluded that the quality of life of patients with a family history of hypertension, diabetes, cholesterol, and obesity is lower than patients without any. It has been determined that the cost of illness is higher in patients with risk factors, and loss of income, medical supplies, and direct medical care costs have an important place in the cost of Acute Myocardial Infarction. We concluded that the quality of life of patients with low cost of illness compared better to patients with high cost of illness. Keywords: Acute Myocardial lnfarction, Cost of illness, Health economic, Health, Quality of life Highlights The general quality of life scores of those without comorbidities are higher than those with comorbidities. The quality of life of patients with a family history of hypertension, diabetes, cholesterol, and obesity is lower than patients without any. the cost of illness is higher in patients with risk factors (family history of hypertension, cholesterol, smoking, obesity, diabetes, and age), and loss of income, medical supplies, and direct medical care costs have an important place in the cost of AMI. The quality of life of patients with low cost of illness compared better to patients with high cost of illness. Background Acute Myocardial Infarction (AMI) is one of the leading causes of death worldwide. 1 The incidence of AMI in the United States is over 780,000. 2 Approximately one million AMI occurs annually in the United States, resulting in the deaths of 300,000 to 400,000 people. 3 Approximately 80,000 people experience AMI annually in Turkey, and 2% of men and 1.9% of women in Turkey have AMI. 4 AMI imposes a heavy economic burden on patients, patient relatives, healthcare systems, and society. 5 After AMI, patients may encounter serious complications, have difficulty starting and maintaining lifestyle changes, and their quality of life is negatively affected. 6,7 In this context, it is important to examine the effects of the illness on people’s quality of life and determine the economic burden it creates on society by calculating its cost. In this study, we calculated the cost of illness of AMI from three different perspectives, evaluated the general and disease-specific quality of life of individuals with AMI, and determined the presence of risk factors and comorbidities in patients. We analyzed the cost of illness and quality of life according to risk factors and comorbidities. We evaluated the statistical difference between the cost of illness and quality of life. We did not find a study conducted in this context in the literature. In particular, our study, in which the cost of illness and quality of life were analyzed together, is original. With this study, we calculated the cost of AMI for the patient and relatives, the payer, and the society and determined the economic burden it brings to the country. By determining how much is spent on which cost item for this illness, we provided evidence-based information to control the cost of illness. Our study will contribute to the literature, especially by considering the cost of illness and quality of life together. Method We aimed to calculate the cost of illness of AMI according to quality of life, risk factors, and comorbidities in this prospective study. Study Population The study population consists of patients treated for AMI between January 2022 and December 2022 at a university hospital in Turkey (n=422). We excluded patients who were not alive (n=30) and for whom no contact information was available (n=79). 313 patients were included in the study; 6 patients refused to participate, 20 patients could not be reached, and 3 questionnaires were excluded. The final study population consists of 284 patients. Data Collection We obtained descriptive data about the patients from the hospital information management system. Risk factors, quality of life, and out-of-pocket payments were obtained from patients using a questionnaire comprising four parts. In the first part, there are two questions about cardiological risk factors (age, gender, family history of hypertension, diabetes, cholesterol, smoking, and obesity) and comorbidity. The second part includes HeartQoL to measure disease-specific quality of life, and the third part includes the EuroQol 5D-5L (EQ-5D-5L) Health Survey to determine the general quality of life. The fourth part contains the Patient and Relatives Cost Questionnaire, which we developed to identify out-of-pocket payments. In the questionnaire, we asked about expenses such as medical examination, drug, transport, nutrition, clothing, accommodation, medical equipment and devices, expenses incurred because of the inability to provide care for dependents, income losses, financial aid amounts received because of illness, and other expenses. The questionnaire form was applied as a data collection tool to the patients three months after the AMI. We calculated the cost of illness according to the bottom-up costing approach from the patient and relatives, payer, and societal perspectives. The cost of illness from the perspective of patients and relatives includes out-of-pocket payments, income losses, and transfer payments for direct medical and non-medical costs. The cost of illness from the payer perspective includes medical care costs covered by the Social Security Institution, and the cost of illness from the social perspective includes direct costs and indirect costs (income losses). Statistical Analysis Descriptive statistics were used to analyze the characteristics of the research group. To examine the univariate normality, the mean, mode, median, and skewness kurtosis coefficients of the variables were calculated, and histograms were drawn for the distribution of the scores. The Student’s t-test for normally distributed continuous variables and the Mann-Whitney U test for nonparametric continuous variables were used. For the t-test, we interpreted the partial square coefficient to evaluate the effect size. We calculated the mean to determine the threshold values that make up the cut-off points of continuous variables for the cost of illness. P<0.05 was considered as the statistical significance level. Sensitivity Analysis We analyzed the effect of possible uncertainties in the parameters that constitute the cost of illness on the cost by one-way and probabilistic sensitivity analysis. Sensitivity analyses were performed for the mean cost of illness from all perspectives by taking a time horizon of 1 year. In the one-way sensitivity analysis, the effect of a change in a single parameter (±5%) on the cost of illness was examined by keeping the value of all parameters constant in the model. In the probabilistic sensitivity analysis, 1,000 simulations were produced with Monte Carlo Simulation, and the distribution values of the analysis were evaluated with the result. Budget Effect Analysis We calculated the budget effect analysis for the cost of illness from all perspectives. According to the perspectives, we used the mean cost per patient and number of patients. The share of AMI in total health expenditures was calculated as the ratio of the total cost of illness calculated by budget effect analysis to total health expenditures. Ethical Approval Ethics committee approval was obtained from the Ankara University Institutional Committee for Science and Research Ethics (dated:03.08.2022, approval number 050.04.04/111903). Results The study population consisted of 284 patients. The mean age of females (16.5%) was 64.57±10.28, and that of males (83.5%) was 58.81±10.44. 60.2% of patients were diagnosed with STEMI and 39.8% with NSTEMI. The average length of stay is 4.21 (min:0-max:38). 88.0% of the patients had at least one comorbidity, and all had at least one risk factor. 64.1% of patients had a family history, 83.0% were male gender, 90.49% were aged, 57% had hypertension, 41.5% had diabetes, 68.3% had cholesterol, 55.6% had smoking, and 13.7% had obesity risk factors. Quality of Life Outcomes Quality of life scores of the study population are given in Table 1. The mean HeartQoL physical score of the study group is 2.22±0.90, the mean HeartQoL emotional score is 1.88±0.54, and the mean HeartQoL global score is 2.13±0.73. The mean EuroQol index score of the patients is 0.84±0.24, and the mean EuroQol VAS score is 70.74±22.94. No significant difference exists between comorbidity, family history of cholesterol, obesity, and HeartQoL. However, there is a significant difference between gender, age, hypertension, diabetes, smoking, and HeartQoL (Table 2). No significant difference exists between a family history of cholesterol and EuroQol Index and EuroQol VAS. However, there is a significant difference between comorbidity, gender, age, and diabetes. According to the effect sizes calculated, the EuroQol index and VAS scores of patients with and without diabetes differed at a low level. No significant difference exists between hypertension, smoking, obesity, and EuroQol VAS and EuroQol Index. As a result of the effect sizes calculated, the EuroQol index scores of patients with and without hypertension differed at a low level. The EuroQol index scores of smoking and non-smoking patients differed at a low level. Cost Outcomes From the patient and relatives’ perspective, the total cost is $138,973.73, and the average cost is $489.34. From the payer’s perspective, the total cost of illness is $182,323.04, and the average cost is $641.98. From the societal perspective, the total cost of illness is $321,296.03, and the average cost is $1,131.32. (Table 4). There is a significant difference between diabetes and the cost of illness from a payer and societal perspective. According to the effect sizes, the mean cost of illness of people with and without diabetes differs significantly. There is a significant difference between obesity and the cost of illness from patients, relatives, and societal perspectives (Table 5). There is a significant difference between HeartQoL-physically, HeartQoL global, and the cost of illness from the perspective of patients and relatives. According to effect sizes, HeartQoL-physical scores of low and high-cost groups differ at a low level. Also, HeartQoL global of low and high-cost groups differ moderately (Table 6). Sensitivity Analysis Outcomes As a result of the one-way sensitivity analysis, the average cost of illness is between $479.85-$498.84 from the patient and relatives perspective, $623.92-$660.04 from the payer perspective, and $1,093.55-$1,169.10 from societal perspective. The cost item with the most significant impact on the total cost of illness has not changed in all perspectives (Figure 1). According to the results of probabilistic sensitivity analysis with Monte Carlo Simulation, the cost of illness in the 95% confidence interval is $476.17-$490.99 (mean=$483.58) for patient and relatives perspective; $628.44-$657.83 (mean=$643.14) for payer perspective, and $1,129.67-$1,131.93 (mean=$1,130.80) for societal perspective. Budget Effect Analysis Outcomes The number of applicants diagnosed with AMI in Turkey was 577,379 in 2022. The total health expenditure in Turkey was 36,515,643,900.10 $ in 2022. 8 The budget effect is 282,534,639.86 $ from the patient and relatives’ perspective, 370,665,770.42 $ from the payer perspective, and 653,200,410.28 $ from the societal perspective. According to the budget effect analysis, the share of the total cost of AMI in total health expenditures is 0.77 from the perspective of patients and relatives, 1.02 from the payer perspective, and 1.79 from the societal perspective. Discussion In this study, a comprehensive evaluation of AMI was performed. We found that 88% of the patients had at least one comorbidity, and 98% of women and 87% of men had comorbidities. In the literature, it is reported that AMI patients have at least one comorbidity and risk factor, and women with AMI have more comorbidities than men 9-21 In addition, the presence of diseases such as diabetes, cholesterol, and hypertension as risk factors increases the risk of comorbidities. We found a significant difference between comorbidities and general quality of life. The general quality of life scores of those without comorbidities are higher than those with comorbidities. We found that the patients had at least one of these risk factors: gender, and family history of hypertension, diabetes, cholesterol, smoking, and obesity. We found a significant difference between risk factors and quality of life. We concluded that the quality of life of patients with a family history of hypertension, diabetes, cholesterol, and obesity is lower than patients without any. It has been determined that the quality of life of patients with risk factors of smoking and males is higher. The cost of illness is higher in patients with risk factors such as family history of hypertension, cholesterol, smoking, obesity, diabetes, and age. Many studies have proven that the incidence of AMI can be reduced, and its adverse effects can be eliminated by controlling modifiable risk factors. 21, 22-25 We also found that patients with some risk factors had higher cost of illness and lower quality of life. According to research findings that study the cost of AMI from the payer perspective, Öksüz et al. (2018) calculated the cost of AMI patients with type 2 Diabetes in Turkey in 2018 as 6,044.6 $-895.1 $. 26 The cost difference between the two studies is due to inflation, time, and type 2 diabetes in the patients. Sloss et al. (2003), with 1995-1998 data in the USA, estimated the direct medical costs attributable to secondary AMI from a payer perspective to be $19,056 for those with private insurance and $16,845 for those with Medicare. 27 Le May et al. (2003), with 1997-1999 data in Canada, calculated the cost of first hospitalization due to AMI from payer perspective as $6,354 and $7,893 depending on different treatment methods, while it was $7,100 and $9,559 in 6 months. 28 Reinhold et al. (2011) calculated the mean cost of AMI from payer perspective in Germany as approximately 13,061±1,162 Euros per patient in 2004. 29 Allen et al. (2022) calculated the cost of illness for 2015-2016 from payer perspective in three months after AMI as $22,034. 30 Baustein et al. (2015) calculated the cost of AMI as 84,617 Czech Krona from payer perspective in a university hospital in the Czech Republic in 2012. 31 From the social perspective, the total cost of illness is $321,296.03, and the average cost is $1,131.32. Seo et al. (2015) calculated the cost of AMI in Korea from societal perspective as $1,427,643,854 in 2007 and $1,177,649,323 in 2012. 32 Tran et al. (2018) calculated the cost of AMI from societal perspective in Alberta between 2004 and 2013 as CA$1.033 million (based on 2016). 33 Ioannides-Demos et al. (2010), in a multicenter study covering ten hospitals in Australia, calculated that the first hospitalization cost of AMI from the societal perspective is AU$10,934 and the 1-year cost is AU$20,502 (cost year: 2005). 34 There are cost of illness studies from other perspectives in the literature. Montagne et al. (2000) calculated AMI costs from a hospital perspective according to treatment types in a tertiary hospital in France with 1999 data, and the total cost was found to be 849 Euros for coronary angiography, 4,762 Euros for stented coronary PTCA, and 3,945 Euros for PTCA. 35 Kauf et al. (2006), with 1999-2001 data in nine countries (Argentina, Australia, Canada, Czech Republic, Germany, Italy, Netherlands, New Zealand, USA), calculated the average cost for a first AMI hospitalization from hospital perspective as $9,993 ($9,702-$10,228); the lowest mean cost was found to be in Argentina as $1,605 and the highest in the USA as $9,196. 36 Tiemann (2008) calculated hospitalization costs from 45 hospitals in nine different countries, including Denmark, England, France, Germany, Hungary, Italy, Netherlands, Poland, and Spain, from hospital perspective for 2005. The total cost per case is 3,766 Euros; the lowest cost is in Hungary is 396 Euros; the highest cost is in Italy is 7,450 Euros; at the hospital level, costs range from 309 Euros to 2,542 Euros. 37 Piscitelli et al. (2012) calculated the direct cost of AMI across Italy as 742 million Euros in 2001, 787 million Euros in 2002, 830 million Euros in 2003, 851 million Euros in 2004, and 894 million Euros in 2005, and determined that it was Euro. 38 Wieser et al. (2012) calculated the cost of AMI in Switzerland as 52,135 Swiss Francs for STEMI and 46,791 Swiss Francs for NSTEMI. 39 When the cost of illness is examined according to cost items, the highest share in the cost of illness is loss of income from the patient and relatives perspective, medical supplies from the payer perspective, and direct medical care from the societal perspective. Montagne et al. (2000) found that most AMI cost include medical supplies/drugs, general hospital expenses, personnel expenses, and test expense items. 35 Reinhold et al. (2011) determined that the biggest burden in the first year after AMI was the hospitalization cost. 29 Cohen et al. (2014) determined the highest cost item in the pre-and post-AMI period as drugs; hospital costs were high during hospitalization due to AMI. 40 In the literature, it has been determined that most of the cost of AMI from different perspectives consists of medical care and hospitalization costs. 26,30,32,33,34,41 AMI patients’ mean general quality of life score was 0.847±0.246 with EQ-5D-5L. The mean quality of life score of patients after AMI was 0.903±0.145 42 , 0.78±0.18 43 , 0.78±0.04 for patients aged 85 years 44 , 0.66±0.31 for women and 0.74±0.28 for men in England 45 , 0.73±0.34 in Portuguese 46 ,0.7±0.2 for men and 0.8±0.2 for women in US and Spain. 9 A lower mean quality of life score for women than men (0.722±0.249 vs. 0.872±0.246). The mean VAS score of AMI patients was 71±23, and 70.90±22.71 for women, 70.75±22.94 for men. In different studies, VAS scores were found as follows: 70.5±4.5 44 , 65.8±18.5 47 , 65.0±22 43 , 9.8±20.4 for women and 64.5±20.9 in men in England 45 , 63.0±22.0 for women, and 67.0±20.0 for men in hospitals in the USA and Spain 9 . Our study found the mean disease-specific score of patients with AMI as 2.13±0.73 for the HeartQoL. The mean HeartQoL score was 2.4±0.5 in the first HeartQoL project 48 and 2.4±0.6 in the second HeartQoL project. 49 Rasmussen et al. (2017) calculated the mean HeartQoL score as 1.94±0.74. 43 Pogosova et al. (2018) reported the mean HeartQoL scores in three different patient groups with abdominal obesity as 1.61±0.58, 1.97±0.47, 2.01±0.47 at their first hospitalization, 2.61±0.64, 2.46±0.65, 2.08±0.93 at the 12th month. 50 Limitations This study has some limitations. Direct non-medical costs and indirect costs (productivity losses of patients and their relatives) were limited to 3 months. As there were no specific scores for Türkiye in analyses related to EQ-5D-5L quality of life, scores for Germany were used. Conclusion This study determined that most patients had at least one comorbidity. The general quality of life scores of those without comorbidities are higher than those with comorbidities. We found that the patients had at least one of the risk factors. It is concluded that the quality of life of patients with a family history of hypertension, diabetes, cholesterol, and obesity is lower than patients without any. It has been determined that the cost of illness is higher in patients with risk factors such as family history, hypertension, cholesterol, smoking, obesity, diabetes, and age, and loss of income, medical supplies, and direct medical care costs have an important place in the cost of AMI. The quality of life of patients with low cost of illness is compared better to patients with high cost of illness. REFERENCES 1. 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Effects of two different preventive counselling programs on selected psychosocial risk factors and quality of life in coronary patients with abdominal obesity. Eur Heart J. 2018;39(suppl_1):15. Table 1. Quality of Life Outcomes Untitled Document Generated on Tue Jan 7 14:20:01 2025 by LaTeXML & 0.01 EuroQol VAS 284 0 100 70.74 75 22.94 1.36 Table 2. Disease Spesific Quality of Life (Heartqol) According to Comorbidity and Risk Factors Median (Min-Max) Comorbidity No 34 2.64 (0.43-2.79) 0.07 Yes 250 2.36 (0.21-2.79) Gender Male 237 2.50 (0.21-2.79) 0.00* Female 47 1.93 (0.21-2.79) Age <50 54 2.67 (0.79-2.79) 0.01* ≥50 230 2.36 (0.21-2.79) Family History No 102 2.22±0.65 0.09 Yes 182 2.07±0.76 Hypertension No 122 2.27±0.64 0.00* Yes 162 2.03±0.77 Diabetes No 166 2.21±0.71 0.02* Yes 118 2.10±0.74 Cholesterol No 90 2.19±0.72 0.31 Yes 194 2.10±0.73 Smoking No 126 2.10±0.75 0.01* Yes 158 2.22±0.69 Obesity No 245 2.43 (0.21-2.79) 0.18 Yes 39 2.14 (0.21-2.79) Table 3. General Quality of Life (EuroQol) According to Comorbidity and Risk Factors EuroQol Index Comorbidity No 34 1.00 (0.25-1.00) 0.00* Yes 250 0.99 (-0.21-1.00) EuroQol VAS No 34 80 (2-100) 0.00* Yes 250 70 (0-100) EuroQol Index Gender Male 237 1.00 (-0.04-1.00) 0.00* Female 47 0.90 (-0.21-1.00) EuroQol VAS Male 237 75 (0-100) 0.04* Female 47 70 (0-70) EuroQol Index Age <50 54 1.00 (0.55-1) 0.01* ≥50 230 0.99 (-0.21-1.00) EuroQol VAS <50 54 80 (10-100) 0.03* ≥50 230 70 (0-100) EuroQol Index Family History No 102 0.85±0.26 0.70 Yes 182 0.84±0.23 EuroQol VAS No 102 72.50±23.83 0.33 Yes 182 69.76±22.43 EuroQol Index Hypertension No 122 0.88±0.23 0.01* 0.02 Yes 162 0.81±0.25 EuroQol VAS No 122 73.54±21.68 0.07 Yes 162 68.64±23.68 EuroQol Index Diabetes No 166 0.88±0.22 0.01* 0.02 Yes 118 0.81±0.28 EuroQol VAS No 166 73.56±21.78 0.01* 0.02 Yes 118 66.79±24.02 EuroQol Index Cholesterol No 90 0.86±0.27 0.43 Yes 194 0.84±0.23 EuroQol VAS No 90 73.10±22.35 0.24 Yes 194 69.65±23.19 EuroQol Index Smoking No 126 0.80±0.28 0.00* 0.03 Yes 158 0.89±0.21 EuroQol VAS No 126 68.87±24.84 0.21 Yes 158 72.25±21.27 EuroQol Index Obesity No 245 1.00 (-0.21-1.00) 0.00* Yes 39 0.91 (-0.12-1.00) EuroQol VAS No 245 75 (0-100) 0.50 Yes 39 70 (0-100) Table 4. Cost of Illness Outcomes Patient and Relatives Perspective Co-payment 284 12,747.97 44.89 9.17 Transportation 284 25,426.32 89.53 18.3 Nutrition 284 21,229.65 74.75 15.28 Clothing 284 4,335.23 15.26 3.12 Loss of Income 284 53,931.83 189.9 38.81 Private Hospital 284 15,564.58 54.8 11.2 Medical Supplies and Devices 284 3,923.94 13.82 2.82 Other * 284 1.813,46 6.39 1.3 Total 284 138.973,00 489.34 100 Payer Perspective Surgery 284 8,511.17 29.97 4.67 Pharmacy 284 24,851.29 87.5 13.63 Laboratory 284 7,654.70 26.95 4.2 Radiology 284 13,458.33 47.39 7.38 Medical Supplies 284 102,571.64 361.17 56.26 Hospitalization 284 9,098.97 32.04 4.99 Other medical services 284 14,728.58 51.86 8.08 Other** 284 1.448.36 5.1 0.79 Total 284 182.323.04 641.98 100 Societal Perspective Direct Medical Care Costs 284 214,559.53 755.49 66.78 Indirect Medical Care Costs 284 52,804.67 185.93 16.43 Indirect Cost (Income Loss) 284 53,931.83 189.9 16.79 Total 284 321,296.03 1,131.32 100 *Other includes supply, accommodation, care expenses and financial aid. ** Other consists of anesthesia, genetics, blood center, nuclear medicine, package expenses. Table 5. Cost of Illness According to Comorbidity and Risk Factors Patient and relatives perspective comorbidity No 34 138.70 (0-4,152) 0,85 Yes 250 160.8 (10.74-3,790.96) Payer perspective No 34 471.01 (216.79-2,429.37) 0,99 Yes 250 499.17 (64.96-3,470.78) Societal perspective No 34 716.83 (359.61-5,339.65) 0,82 Yes 250 767.85 (142.44-5,523.91) Patient and relatives perspective Gender Male 237 157.66 (0-4,152) 0,81 Female 47 165.48 (10.74-3,790.96) Payer perspective Male 237 492.55 (216.79-2,429.37) 0,69 Female 47 506.82 (64.96-3,470.78) Societal perspective Male 237 756.95 (359.61-5,339.65) 0,35 Female 47 768.34 (142.44-5,523.91) Patient and relatives perspective Age <50 54 190.15 (7.22-4,840.99) 0,19 ≥50 230 154.95 (0-4,152) Payer perspective <50 54 486.77 (109.42-1,620.94) 0,80 ≥50 230 499.81 (64.17-8,765.52) Societal perspective <50 54 762.96 (315.45-5,039.75) 0,60 ≥50 230 757.36 (95.01-8,913.78) Patient and relatives perspective Family History No 102 453.19±726.18 0,57 Yes 182 509.60±862.40 Payer perspective No 102 693.80±929.26 0,32 Yes 182 612.94±463.17 Societal perspective No 102 1,146.99±1,219.16 0,85 Yes 182 1,122.55±980.82 Patient and relatives perspective Hypertension No 122 410.46±615.79 0,15 Yes 162 548.75±835.40 Payer perspective No 122 661.04±563.17 0,67 Yes 162 627.63±739.39 Societal perspective No 122 1,071.50±937.07 0,41 Yes 162 1,176.38±1,161.68 Patient and relatives perspective Diabetes No 166 425.41±731.72 0,11 Yes 118 579.28±915.71 Payer perspective No 166 575.59±414.92 0,04* 0,01 Yes 118 735.38±907.26 Societal perspective No 166 1,001±889.21 0,01* 0,02 Yes 118 1,314.67±1,264.35 Patient and relatives perspective Cholesterol No 90 265.09±566.02 0,08 Yes 194 546.98±903.46 Payer perspective No 90 714.88±998.79 0,21 Yes 194 608.16±437.77 Societal perspective No 90 1,079.97±1,205.19 0,58 Yes 194 1,155.15±1,004.31 Patient and relatives perspective Smoking No 126 390.01±732.86 0,06 Yes 158 568.55±869.56 Payer perspective No 126 676.83±561.51 0,41 Yes 158 614.19±743.49 Societal perspective No 126 1,066.85±988.91 0,35 Yes 158 1,182.74±1,131.77 Patient and relatives perspective Obesity No 245 150.43 (0-4,840.99) 0,03* Yes 39 355.03 (19.47-4,152) Payer perspective No 249 485.59 (64.17-8,765.52) 0,15 Yes 39 536.59 (95.01-8,913.78) Societal perspective No 245 727.40 (128.11-4,149.51) 0,00* Yes 39 996.02 (147.57-5,148.83) Table 6. Quality of Life and Cost of Illness HeartQol-Physically Patient and relatives perspective low 218 2.17±0.7 0,04* 0,02 high 66 1.98±0.8 HeartQol-Emotional low 218 2.27±0.87 0,14 high 66 2.08±0.98 HeartQol Global low 218 1.92±0.5 0,01* 0,04 high 66 1.74±0.63 EuroQol Index low 218 0.86±0.23 0,08 high 66 0.8±0.28 EuroQol VAS low 218 71.63±23.25 0,23 high 66 67.8±21.78 HeartQol-Physically Payer perspective low 201 2.15±0.7 0,46 high 83 2.08±0.79 HeartQol-Emotional low 201 2.26±0.86 0,32 high 83 2.14±0.99 HeartQol Global low 201 1.87±0.54 0,54 high 83 1.91±0.56 EuroQol Index low 201 0.85±0.25 0,51 high 83 0.83±0.24 EuroQol VAS low 201 70.21±23.65 0,54 high 83 72.21.20 HeartQol-Physically Societal perspective low 199 2.16±0.70 0,24 high 85 2.05±0.78 HeartQol-Emotional low 199 2.26±0.87 0,25 high 85 2.13±0.96 HeartQol Global low 199 1.9±0.51 0,45 high 85 1.84±0.60 EuroQol Index low 199 0.85±0.23 0,21 high 85 0.81±0.27 EuroQol VAS low 199 71.72±22.87 0,27 high 85 68.44±23.06 Figure 1. Tornado Diagram Information & Authors Information Version history V1 Version 1 09 January 2025 Peer review timeline Published Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi Version of Record 30 Mar 2026 Published Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords acute myocardial lnfarction cost of illness health health economic quality of life Authors Affiliations Ferda Işıkçelik 0000-0002-7975-4141 [email protected] Burdur Mehmet Akif Ersoy Universitesi View all articles by this author Ismail Agirbas Ankara Universitesi Saglik Bilimleri Fakultesi View all articles by this author Cansın Tulunay Kaya Ankara Universitesi Tip Fakultesi View all articles by this author Metrics & Citations Metrics Article Usage 187 views 121 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Ferda Işıkçelik, Ismail Agirbas, Cansın Tulunay Kaya. 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