Logo-hpp
2023: Two-year Impact Factor: 2.4
Scopus Journal Metrics
CiteScore (2023):7.1
 
Platinum
Open Access

Health Promotion Perspectives. 13(1):68-76. doi: 10.34172/hpp.2023.09

Original Article

Catastrophic health expenditures in hospitalized patients with delta variant of COVID-19: A cross-sectional study

Zahra Gheinali 1ORCID logo, Esmaeil Moshiri 1, Masoumeh Ebrahimi Tavani 2, Mehdi Haghi 3, Farid Gharibi 1, *ORCID logo
1Social Determinants of Health Research Center, Semnan University of Medical Sciences, Semnan, Iran
2Quality Improvement, Monitoring and Evaluation Department, Center of Health Network Management, Deputy of Public Health, Ministry of Health & Medical Education, Tehran, Iran
3Social Determinants of Health Research Center, School of Health and Nutrition, Lorestan University of Medical Sciences, Khorramabad, Iran
*Corresponding Author: Farid Gharibi, Email: gharibihsa@gmail.com

Abstract

Background: Financial protection of populations against healthcare costs is one of the fundamental responsibilities of governments. This study aimed to investigate the incidence of catastrophic health expenditures (CHE) and it’s affecting factors in hospitalized patients with delta variant of COVID-19.

Methods: In this cross-sectional study, we included 400 hospitalized COVID-19 patients at Kosar Hospital of Semnan in 2022, using a researcher-made checklist. Based on qualitative nature of the variables, chi-square test was used to investigate the statistical associations between the demographic/background characteristics and the incidence of CHE.

Results: On average, COVID-19 imposed 1833.43 USD direct medical costs per one hospitalized patient. The ratio of direct-medical costs to household’s non-food expenses was 2.35, and 61% (CI:±4.78%) of the patients were subject to CHE. Besides, residence place, basic insurance type, benefitting from supplementary insurance, suffering from underlying diseases, hospitalization in ICU, falling into a coma, facing pulmonary failure, and performing hemoperfusion had significant associations with CHE (P<0.05).

Conclusion: The incidence of CHE in hospitalized COVID-19 patients was undesirable, which may be due to geographical, economical, and occupational inequalities apart from the factors related to the severity of the disease. So, health policymakers should pay attention to the provision of proper financial risk protection policies to make the health insurance system more efficient and appropriate.

Keywords: Catastrophic, Health expenditures, COVID-19

Copyright

© 2023 The Author(s).
This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Introduction

Recently, all world countries experienced the most fatal epidemic in the past century, known as coronavirus disease 2019 (COVID-19). The disease spread in such a quick manner that within four months it resulted in three million confirmed infections, and two hundred thousand deaths in more than 209 countries.1,2 The incidence speed and scope of the destructive consequences of this disease was such that the World Health Organization (WHO) announced it as a full-blown pandemic in March 2020 and called the countries to fight against it all-out.3

The most common symptoms of the disease include cough, fever, and shortness of breath, accompanied by general weakness, fatigue, dyspnea, muscle pain, sore throat, and loss of smell and taste.4 The patients with more severe conditions of the disease, such as breathing disorders, feeling pressure and pain in the chest, and loss of ability to speak and move require hospitalization and immediate clinical care. In addition to causing severe pulmonary problems, the disease can lead to serious cardiac complications, renal failure, acute hepatitis, hemoptysis, dyspnea, and leukopenia.4,5

The high prevalence of COVID-19, the remarkable rate of patients with severe conditions requiring hospitalization, and the need for various costly diagnostic and treatment care, especially in the intensive care unit (ICU) and cardiac care unit (CCU), caused COVID-19 to be known as a costly disease for communities, especially in developing countries.5-7 Hence, it is crucial to study the imposed costs on patients, insurance companies, and the health system. In a previous study, the annual imposed costs of COVID-19 on Medicare insurance was estimated to be more than 6.3 billion dollars, 92.6% of which were allocated to the hospitalized patients.8 The cost of hospitalization per patient was also estimated at 21 752 dollars.8 In Turkey, the annual imposed cost on the health system due to the outbreak of COVID-19 was more than 1.2 billion dollars, which was equal to 2% of the total annual budget of the health system and 0.8 thousandth of the country’s gross domestic product (GDP).9

Previous studies have only considered the costs on health insurance (as a third payer), health system, and society, and no study has yet assessed the imposed costs on patients with COVID-19, worldwide. Estimating the catastrophic health expenditures (CHE) indicator is one of the most critical actions to assess the imposed costs from the perspective of patients and their households, which can be helpful in indicating the financial supports provided to patients in different societies against health costs, and implementing promotional interventions, particularly in developing countries.10 CHE is calculated based on the amounts paid to the health care provider(s) by patients and their families, which is also referred to as the out-of-pocket payment and direct medical costs.11 In this study, we aimed to investigate the incidence of CHE in hospitalized patients suffering from COVID-19.


Martials and Methods

Type of study and participants

This cross-sectional study was carried out on 400 patients with delta variant of COVID-19 hospitalized in Kosar Hospital of Semnan, Iran from September to December 2022. The inclusion criteria were being admitted to the hospital, and passing at least one month from the time of discharge. We considered ‘hospitalization’ as an inclusion criterion, because many patients have either no symptom or mild symptoms with no need to receive care. Also, the most of patients with symptoms receive cheap outpatient care and do not require hospitalization. Nevertheless, the hospitalized patients are hospitalized for more than two weeks on average and have a longer recuperation period and costs. “Passing at least one month from discharge” was another inclusion criterion, because the disease has a long recuperation period with especially respiratory complications and excessive fatigue, which may result in low levels of patients’ participation in the study. Also, “passing at least one month from discharge” minimizes the possibility of recall bias and the risk of transmission of disease to the interviewers. We excluded all patients who died, because the probability of participation by the family members was very low. Also, many of them might be unaware of the demographic and background characteristics of the deceased patients.

Semnan is a province in central Iran with a population of more than 700 000 people and an area of 96 816 square kilometers. Semnan is an industrial province due to its short distance from Tehran (the capital city), Karaj (a megapolitan city), and Northern provinces (as touristic area of Iran). Because of low population and appropriate job opportunities, Semnan is one of the best Iranian provinces in terms of economic status, especially in misery index (an economic indicator calculated by adding the seasonal adjusted unemployment rate to the annual inflation rate).

Sample size and sampling method

Sample size was calculated to be 384 (attrition rate of 5% = 400), based on the following formula. Due to the lack of similar studies, the standard deviation was estimated from a pilot study on patients.

n=zsd2=1.96*20000000200000002=384.16

The sampling method was simple random sampling from the list of patients. We collected the data related to direct medical costs imposed on COVID-19 patients by examining the medical records of the patients and patients’ interview. We also conducted interviews to collect other data related to demographic and background characteristics, direct non-medical costs, indirect costs, as well as the patients’ views on the imposed costs.

Study tools

We developed a checklist to obtain the required data. All components related to the imposed health costs and demographic/background characteristics were initially identified after a literature review, and interviewing the specialists and the patients. Then, the extracted components were considered as the items for the development of the initial checklist. Subsequently, the checklist was evaluated and confirmed by ten experts. To assess content validity, all the items of the checklist were examined from the perspective of experts based on the four indicators of necessity, relevance, transparency, and simplicity; content validity ratio (CVR) and content validity index (CVI) was calculated based on below formula12:

CVR/CVI=nEN2N2

Where nE was the number of experts choosing two positive spectrum choices and N indicated the total number of experts. Due to the participation of ten experts in this stage, the acceptance score of 0.62 was the basis for approving/disapproving the items to be included in the checklist.12 The final tool was a 75-item checklist, including 23 items related to demographic and background characteristics, 42 items related to the cost information of the disease, four items related to the income status of the patients and their family, and six items related to the patients’ views on the negative consequences of the disease costs. The validity of the checklist was confirmed by the experts. The final scores for CVR and CVI indicators were 0.88 and 0.92, respectively.

Main variable definition

The concept of CHE implies that the cost of health care is higher than the capacity to pay (CTP) of patients and their families. Also, if the direct health costs paid by patients and their families exceed 40% of the non-food expenses of the household, there would be a CHE occurrence.The main data examined in the study included the types of direct medical costs imposed on patients and their families in the form of out-of-pocket payments and at the time of receiving COVID-19-related health care (diagnosis, treatment, and rehabilitation). Therefore, the following formula was used to calculate the CHE13:

CHE=HealthE>CTP

HealthE: Direct medical costs based on out-of pocket payments

CTP: Expenses of equal and more than 40% of non-food costs of households for healthcare

Subsequently:

CHE=Direct Medical costs≥40% household non-food costs

To calculate CHE, the information related to the imposed health costs on the patients and their households during a defined period was calculated. Then, to determine the level of CHE occurrence, this amount was compared to the household income during the considered period. Due to the lack of comprehensive health records for the patients, the amount and type of mentioned expenses were collected from the patients through self-report, and the accuracy of the provided information was compared with their hospital records. As mentioned above, the main criterion for the incidence of CHE in a patient and his/her family was the amount of out-of-pocket payments reaching a certain threshold level of his/her income (capacity to pay). Based on the recommendations of the WHO and the most of similar studies, this threshold was considered as 40% of non-food expenses of a family.11 Since the amount of out-of-pocket payment was calculated solely based on the direct medical costs (diagnosis, treatment, and rehabilitation) and the direct non-medical costs (such as the cost of adapting [immunizing] the home and commuting to care centers), the indirect costs (such as absence in the workplace, and intangible costs such as the imposed pain on the patient and his/her family) were not considered in the study.

We investigated different demographic and underlying variables such as age, gender, employment, and education status of the patient, having basic and supplementary health insurance, the pattern of receiving healthcare services (private and public centers), place of residence, suffering from a comorbidity, the type and severity of side effects, their association with the amount of imposed expenditure on patient and his/her family, and the catastrophic nature of these expenditures.

Data analysis

Missing data in the patients’ checklist were completed by contacting the respondents again. If a respondent was not available or did not answer the questions related to the missing data, his/her associated checklist was excluded from data analysis. In this case, the patient with the next assigned code was included in the study.

The data analysis was first descriptive and then analytical. The results of descriptive studies were considered and reported for qualitative variables as frequency (percentage) and for quantitative variables as mean (standard deviation). Primarily, the incurred direct medical costs were calculated in Iranian Rials (IRR) and then changed to US dollars (USD) using the exchange rate announced by the central bank of Iran (1 USD = 42 000 IRR).

Based on the qualitative nature of the variables, the chi-square test was used to investigate the statistical associations between demographic and background variables and the incidence of CHE. All analyses were performed using the SPSS v. 19, and P < 0.05 was considered as significant.


Results

Mean age of participants was 56.20 (± 59.77) years. The gender ratio of patients was almost equal and most of them were married. The most of patients were housekeepers and self-employed. A majority of the patients were urban dwellers and lived in the center of the province (Table 1).

Table 1. Demographic characteristics of the patients participated in the study (n = 384)
Demographic Variables Category Frequency Percent
Age1 to 20 years old61.50
21 to 40 years old10626.50
41 to 60 years old16140.25
61 years and older12731.75
GenderMale18847.00
Female21253.00
Marital statusSingle4511.25
Married34486.00
Divorced112.75
Educational statusIlliterate6215.50
Below high school diploma7117.75
High school diploma8621.50
Associate and bachelor degrees15939.75
Master degree225.50
Occupational statusOffice employee7819.50
Worker102.50
Self-employed8320.75
Housekeeper14235.50
Retired7318.25
Student123.00
Unemployed20.50
ResidencyCenter of province38395.75
Other places of province143.50
Outside of province30.75
Living placeUrban dwellers36490.50
Rural dwellers189.50

As there is shown in Table 2, almost all patients had basic health insurance, however, less than a third of patients had supplementary health insurance. A majority of patients received the needed care only from the governmental sector. Mostly, had a background disease, such as cardiac disease, hypertension, and diabetes. Most of the patients with a background disease reported that their condition was under control before contracting COVID-19. Although the majority of patients did not have continuous sports activity before the disease, almost half of them reported that they had enough physical activity due to the nature of their jobs. Less than a quarter of the patients needed hospitalization in the ICU. The mean hospitalization periods of the patients requiring hospitalization in the ward, ICU, and hospitalization in both the ward and ICU were 4.10, 1.62, and 5.69 days, respectively. Only 7% of the patients had experienced coma (0.28 days per patient), however, all had suffered serious side effects, especially respiratory failure and cardiac problems due to the COVID-19 infection (Table 2).

Table 2. Background characteristics of the participants (n = 384)
Background Variables Category Frequency %
Benefiting basic insurance 39097.50
Type of basic insuranceSocial security24963.80
Treatment services9223.50
Armed forced358.70
Other164.10
Benefiting supplementary insurance 11929.75
Place of careGovernmental center34085.00
Integration of private and public centers6015.00
Suffering from a background disease 34686.50
Type of background diseaseCardiac problems16240.50
Hypertension16541.25
Pulmonary diseases6817.00
Asthma307.50
Diabetes11829.50
Cancer41.00
Immune system defect297.25
Obesity246.00
Having background disease under controlYes33195.66
Somewhat154.34
Continuous exercise before the infectionYes4812.00
No25062.50
Somewhat10225.50
Having occupational physical activityYes4611.50
No16541.25
Somewhat18947.25
HospitalizationIn the ward36892.00
In the ICU9523.75
Both ICU and ward6215.50
Fall into a coma 287.00
Serious side effects39699.00
Type of side effectsCardiac problem27167.75
Pulmonary problem38496.00
Renal problem256.25
Need for hemoperfusion225.50

Examining the direct medical costs indicated that the largest part of the imposed diagnostic costs on the patients was the diagnostic costs associated to the side effects of the disease and laboratory services, respectively (Table 3). Also, the largest part of the medical services’ costs was allocated to hemoperfusion and medication preparation, respectively. Although hemoperfusion had only been performed for 5.5% of the patients, it imposed the highest treatment costs (Table 3). In total, 1833.43 USD (77 004 080 IRR) were allocated to direct medical costs imposed on each hospitalized COVID-19 patient.

Table 3. Direct medical costs imposed on the patients participated in the study (n = 384)
Domain Type of costs Minimum Maximum Mean (standard deviation)
IRR USD IRR USD IRR USD
Diagnosing servicesLaboratory services0030000000714.281858300 (± 21222310)44.24 (± 505.29)
Radiology0014700003510050 (± 107920)0.24 (± 2.57)
CT scan00138000032.85107250 (± 199890)2.55 (± 4.76)
Other diagnosing costs0098000000023333.336857150 (± 74381400)163.26 (± 1770.98)
Sum of diagnosing expenditures0098126000023363.338798470 (± 77084110)209.48 (± 1835.33)
Treatment servicesVisiting general physician00100000023.80114200 (± 1067900)2.71 (± 25.42)
Visiting specialist physician 009900000235.71452170 (± 1067900)10.76 (± 25.42)
Sum of visiting expenditures0010400000247.61566370 (± 1205220)13.48 (± 28.69)
Hospitalization services002500000005952.384520730 (± 19353590)107.63 (± 460.79)
Medication003800000009047.6127585000 (± 41162380)656.78 (± 980.05)
Traditional treatments005000000119.04119090 (± 547110)2.83 (± 13.02)
Treatment cares at home 0023000000547.61565000 (± 2500910)13.45 (± 59.54)
Hemoperfusion00130000000030952.3835025120 (± 170903340)83393 (± 4069.12)
Unofficial payments000000
Sum of treatment services (apart from visits)00168009000040002.1467639230 (± 200349660)1610.45 (± 4770.23)
Sum of expenditures0 19800900004714577004080 (± 22819737)1833.43 (± 543.32)

The mean monthly income of the patients’ families was about 1651.07 USD (69 345 000 IRR), within which 779.52 USD (32 740 000 IRR) was spent on non-food expenses. Calculating the incidence of CHE in the examined patients showed that the mean ratio of direct medical costs to non-food expenses of the families was 2.35, which was six times greater than its normal amount (less than 0.4 or 40%). Accordingly, 61% (CI: ± 4.78%) of the examined patients were subject to CHE.

As the patients reported, 39% had given up and 34.5% had delay in receiving the necessary services recommended by the doctors, due to their high costs. Also, 38.5% attempted to receive cheaper and/or lower quality health care. Meanwhile, 26.5% received financial assistance from their friends and charitable institutions to cover their treatment costs, and 48.5% obtained loans or borrowed money from banks and friends. Generally, 60.5% reported that they faced serious problems to meet their medical expenses.

As reported in Table 4, among demographic and background characteristics, the place of residency, type of basic insurance, benefitting supplementary insurance, suffering from an background disease, hospitalization in ICU, combined hospitalization in both the ward and ICU, falling into coma, respiratory failure, and hemoperfusion had a statistically significant association with CHE (P < 0.05). According to the results, the incidence of CHE in the patients living in urban areas was 37% higher than those living in rural areas. CHE in the patients with supplementary insurance was 73% lower than those without the insurance. Furthermore, in patients hospitalized in ICU, the CHE was 20% higher than ICU non-hospitalized patients. Also, in patients with a history of coma, the CHE was 34% higher than those without such history. In individuals with a history of hemoperfusion, CHE was 42% higher compared to those without hemoperfusion experience (Table 4).

Table 4. Statistical association between demographic/background characteristics and CHE incidence
Variable Category Incidence (CI) as % P value*
ResidencyUrban58 (± 4.83)0.002
Rural95 (± 2.13)
Type of insuranceSocial security65 (± 4.67) < 0.001
Treatment services72 (± 4.40)
Army forces23 (± 4.12)
Others (banks, petroleum company, etc)0 (0)
Benefiting supplementary insuranceYes10 (± 2.94) < 0.001
No83 (± 3.68)
Suffering from a background diseaseYes58 (± 4.83)0.020
No72 (± 4.40)
Hospitalization in an ICUYes65 (± 4.67)0.224
No45 (± 4.87)
Hospitalization in both the ward and ICUYes84 (± 3.59)0.003
No57 (± 4.85)
Falling into a comaYes93 (± 2.50)0.010
No59 (± 4.82)
Respiratory failureYes59 (± 4.82)0.024
No0 (0)
HemoperfusionYes100 (0)0.008
No58 (± 4.83)

* Chi-square test.


Discussion

In this study, we investigated the incidence of CHE in hospitalized patients suffering from COVID-19. According to the results, contracting COVID-19 imposed a mean of 1833.43 USD (77 004 080 IRR) direct medical costs on each Iranian hospitalized patient. Li et al., reported the total (direct and indirect) incurred costs on patients with COVID-19 in china to be 6827 USD.14 Bartsch et al in the United States also estimated the direct medical costs of the disease as 3045 USD.15 In Iran, Ghaffari Darab et al reported the direct medical costs as 3755 USD, 16 and Nakhaei et al estimated the direct (medical and non-medical) costs as 3362 USD.17

In our study, the largest part of the imposed costs was due to hemoperfusion and medication preparation, respectively, in a way that these two components accounted for 81% of the direct medical costs (out-of-pocket payments). Since most of the used equipment and medicines in the treatment of Iranian COVID-19 patients are imported, they impose a high cost on the health system. If such equipment and medicines were produced inside the country, their cost would be greatly reduced for both the patients and the health system. Also, the possibility of lack of equipment and medicines during conditions like COVID-19 pandemic around the world is very high. Such shortages may be due to the governing principles of a competitive economy, which can lead to a sharp increase in market prices due to high demand and insufficient supply. However, we should not ignore the strong role of political, economic, and health sanctions that severely limit the access of some countries to necessary equipment and medicines and/or their production technology.18

Although hemoperfusion for the patients with severe blood oxygen depletion was performed only in 5.5% of the patients, it accounted for half of the total direct medical costs. Hemoperfusion is not recommended as an essential care in any of the clinical protocols and guidelines, and thus only a small number of specialists, based on their personal experience, perform and recommend it. Therefore, absolute adherence to reliable scientific evidence can have a significant role in reducing the imposed costs on the patients. In the study conducted by Nakhaei et al., age, having supplemental health insurance, hospitalization in ICU and death were the factors associated to the amount of incurred cost on the patients.17

In our study, although the mean monthly income of the patients’ families was 1651.07 USD (69 345 000 IRR), half of the amount was spent on non-food expenses, and an amount greater than the total income (1833.43 USD equal to 77 004 080 IRR) was spent on health care. We also found that the mean ratio of direct medical costs to non-food expenses of families was 2.35, which was six times greater than its normal amount (less than 0.4 or 40%). Accordingly, 61% of the examined patients were subject to CHE. It should be noted that this study was conducted in a public hospital affiliated to the Ministry of Health, which strictly adheres to governmental tariffs. Certainly, conducting a similar study in private hospitals might show a higher incidence of CHE.

As far as we know, no study has yet been published to evaluate the CHE in patients with COVID-19 infection. Few studies evaluated the COVID-19-related costs mostly based on the imposed costs on the health system and health insurance organizations (as third-party payers), and not from the perspective of the patients and their families. So, these studies cannot judge the social protection of citizens against the COVID-19 costs.

Studies on the incidence of CHE in other diseases showed that CHE in cancer patients was estimated as follows: 27%,19 43%,20 and 95%21 in China, 75% in Ethiopia,22 48% in Malaysia,23 50% in South Korea,24 and 79% in India.25 In addition, the incidence of CHE in patients with heart diseases was reported to be 54%26 and 84%27 in India, and 55% in Iran.28 Also, CHE in patients suffering from hypertension was calculated to be 24%29 and 14%30 in China. Likewise, in a study in Iran, the CHE imposed on multiple sclerosis patients was estimated to be 54%.10 The results of another study indicated that 6.2% of the families with a neoplasm patient, 12.9% of the families with a member suffering from brain diseases, 9.6% of the families with a diabetes patient, 7% of the families with a member suffering from arthritis, 23.6% of the patients with kidney disease, 7.3% of the patients with hypertension, and 11.7% of the families with a member suffering from ischemic heart diseases faced CHE.31

Although literature showed that CHE often occurs in chronic diseases, especially diseases that require surgery and complex and expensive treatments, infectious diseases have also the potential for the incidence of CHE. Accordingly, the incidence of CHE was estimated to be 52% in the patients with tuberculosis in China,32 and 33% in the hospitalized patients with gastroenteritis in Malaysia.33 Even mental-psychological disorders such as depression can make 24% of the patients and their family experience CHE.34

Our results showed that living in urban areas, having basic insurance of specific types (army forces, banks, petroleum company, etc), and having supplementary insurance strongly affected the incidence of CHE. These findings indicate the role of geographical, occupational, and financial inequalities in access to health care needed by COVID-19 patients. We also found that 60% of people with basic insurance experience CHE, which shows poor and ineffective coverage of this insurance even in the governmental centers. Another study on multiple sclerosis patients showed that the geographical, economical and job-related factors affected the occurrence of CHE, significantly.18

The lower probability of CHE incidence in the urban population can be due to financial (economical) and geographical (physical) issues and even better cultural access to the needed care, which may lead to earlier and better follow-up of the disease, and receiving timely and complete appropriate treatments. Another reason might be the higher mean income of urban dwellers, as their jobs are more specialized, lucrative, and permanent compared to the seasonal jobs of rural participants. Obviously, the type of basic health insurance, which is an occupational advantage, can also be considered as a serious source for inequality. As previously noted, the factors like patients’ age, supplemental health insurance, hospitalization in ICU and death (as disease severity factors) were associated to the amount of incurred cost on patients.17 Similar studies have also shown that benefiting from basic health insurance,35-37 having supplementary health insurance,10,38 and having certain types of insurance with specific advantages27 can lead to a significant reduction in the probability of CHE incidence. Also, living conditions of the patients and their families, being close to the central parts of the province due to the possibility of benefiting from treatment facilities,10,38 and the area of residence (rural or urban)19,37,39 had significant effects on the incidence of CHE.

In terms of the severity of the disease and its negative consequences, we found that the hospitalized patients in the ICU, patients with a history of being hospitalized in both the ICU and ward, patients experiencing coma, those with respiratory failure (as one of the side effects of COVID-19), and patients with a history of hemoperfusion due to a severe deplete in blood oxygen faced significantly higher health costs than other patients. Accordingly, the patients with a more severe disease need more supportive health insurances. In terms of hemoperfusion, which significantly increases the probability of CHE, we found that 100% of the patients receiving this service experienced CHE, despite the fact that performing this procedure as a necessary action is not confirmed by treatment protocols. Some previous studies identified the severity of the disease and subsequently the need for the patient to benefit from more complex, specialized, and expensive facilities as the factors affecting CHE.10,39

One of the limitations of this study was the impossibility of data collection for deceased cases. If it was possible to benefit from the data of those who suffered a more severe disease and possibly experienced a higher cost, the CHE would be higher than the current amount. Another limitation was the impossibility of collecting data from private hospitals to compare with governmental centers, which could have produced more interesting results, because generally hospitalized patients in private hospitals have a much higher cost and are more likely to face CHE. The last limitation was the collection of data in the period from September to December 2021 while Iran was at the peak of the Delta strain. Therefore, the results of this study cannot be attributed to other strains and their peaks.

Based on the results of this study, it is recommended that the country officials attempt to increase the value of national currency, provide better access to equipment and medicines, and develop the production technology related to equipment and medicines. To do so, some strategies might be as follows: paying attention to the internal capacities to produce necessary equipment and medicines by strengthening the knowledge-based companies, developing treatment protocols and guidelines for COVID-19 and its various strains, monitoring the unconditional compliance of health centers with the developed treatment protocols, paying more attention to COVID-19 vaccination and encouraging citizens to inject the vaccine and its boosters on time, creating a more efficient screening mechanism and timely diagnosis of the disease, creating more efficient insurance mechanisms, especially with emphasis on rural patients who lack financial ability, and the expansion of insurance coverage for acute and serious cases of diseases to reduce exposure to CHE in COVID-19 patients. Further studies in private hospitals are required during different peaks and strains of the disease to assess the current situation and the impact of possible implemented interventions.


Conclusion

Our results showed that in contrast to the idea that the incidence of CHE is often attributed to chronic diseases or complex surgeries, infectious diseases such as COVID-19 can lead to CHE if the patient is hospitalized. Also, serious geographical, financial, and occupational inequalities might lead to the incidence of CHE. As the existing insurance systems fail to provide adequate support for the complex and severe cases of this disease, it seems to be essential to develop national-level interventions aiming at improving the social protection systems of the patients. The results of present study can help health policymakers and those in charge of state health insurance to understand the importance of the CHE issue and plan for the development of appropriate interventions.


Acknowledgments

We thank all the patients for their participation in this study. We also acknowledge the staff of Kosar Hospital of Semnan for providing the necessities for the research and the Vice-Chancellor for Research and Technology of Semnan University of Medical Sciences for financial support.


Competing Interests

The authors declare that they have no conflict of interest.


Ethical Approval

All patients were free to accept or refuse to participate in the study. An informed consent was obtained from all participants, and they were assured that the results would be published in an anonymous manner. The privacy of the study participants was respected, and the participants were assured that the obtained results would be used only for research aims. Also, the Ethics Committee of Semnan University of Medical Sciences approved the research protocol (code: IR.SEMUMS.REC.1400.204).


Funding

The study was founded by Semnan University of Medical Sciences, Iran.


References

  1. Serological approaches for COVID-19: epidemiologic perspective on surveillance and control. Front Immunol 2020; 11:879. doi: 10.3389/fimmu.2020.00879 [Crossref]
  2. Counting the cost of COVID-19. Int J Inf Technol 2020; 12(2):311-7. doi: 10.1007/s41870-020-00466-0 [Crossref]
  3. A new coronavirus associated with human respiratory disease in China. Nature 2020; 579(7798):265-9. doi: 10.1038/s41586-020-2008-3 [Crossref]
  4. A comprehensive review of COVID-19 characteristics. Biol Proced Online 2020; 22:19. doi: 10.1186/s12575-020-00128-2 [Crossref]
  5. Clinicopathological characteristics of 8697 patients with COVID-19 in China: a meta-analysis. Fam Med Community Health 2020; 8(2):e000406. doi: 10.1136/fmch-2020-000406 [Crossref]
  6. The emergence of COVID-19 as a global pandemic: understanding the epidemiology, immune response and potential therapeutic targets of SARS-CoV-2. Biochimie 2020; 179:85-100. doi: 10.1016/j.biochi.2020.09.018 [Crossref]
  7. Characteristics of SARS-CoV-2 and COVID-19. Nat Rev Microbiol 2021; 19(3):141-54. doi: 10.1038/s41579-020-00459-7 [Crossref]
  8. Patient characteristics and costs associated with COVID-19-related medical care among Medicare fee-for-service beneficiaries. Ann Intern Med 2021; 174(8):1101-9. doi: 10.7326/m21-1102 [Crossref]
  9. COVID-19 healthcare cost and length of hospital stay in Turkey: retrospective analysis from the first peak of the pandemic. Health Econ Rev 2021; 11(1):39. doi: 10.1186/s13561-021-00338-8 [Crossref]
  10. The catastrophic out-of-pocket health expenditure of multiple sclerosis patients in Iran. BMC Health Serv Res 2021; 21(1):257. doi: 10.1186/s12913-021-06251-4 [Crossref]
  11. Limitations of methods for measuring out-of-pocket and catastrophic private health expenditures. Bull World Health Organ 2009; 87(3):238-44, 44a. doi: 10.2471/blt.08.054379 [Crossref]
  12. Incidence, socio-economic inequalities and determinants of catastrophic health expenditure and impoverishment for diabetes care in South Africa: a study at two public hospitals in Tshwane. Int J Equity Health 2019; 18(1):73. doi: 10.1186/s12939-019-0977-3 [Crossref]
  13. Economic costs incurred by the patients with multiple sclerosis at different levels of the disease: a cross-sectional study in Northwest Iran. BMC Neurol 2020; 20(1):205. doi: 10.1186/s12883-020-01790-5 [Crossref]
  14. Treatment of coronavirus disease 2019 in Shandong, China: a cost and affordability analysis. Infect Dis Poverty 2020; 9(1):78. doi: 10.1186/s40249-020-00689-0 [Crossref]
  15. The potential health care costs and resource use associated with COVID-19 in the United States. Health Aff (Millwood) 2020; 39(6):927-35. doi: 10.1377/hlthaff.2020.00426 [Crossref]
  16. The economic burden of coronavirus disease 2019 (COVID-19): evidence from Iran. BMC Health Serv Res 2021; 21(1):132. doi: 10.1186/s12913-021-06126-8 [Crossref]
  17. Direct and indirect cost of COVID-19 patients in Iran. Health Policy Technol 2021; 10(4):100572. doi: 10.1016/j.hlpt.2021.100572 [Crossref]
  18. Relationship between political-economic sanctions and catastrophic health costs in multiple sclerosis patients in Iran. Iran J War Public Health 2022; 14(4):455-64. doi: 10.58209/ijwph.14.4.455 [Crossref]
  19. Socioeconomic disparities in cancer treatment, service utilization and catastrophic health expenditure in China: a cross-sectional analysis. Int J Environ Res Public Health 2020; 17(4). doi: 10.3390/ijerph17041327 [Crossref]
  20. How great is current curative expenditure and catastrophic health expenditure among patients with cancer in China? A research based on “System of Health Account 2011”. Cancer Med 2018; 7(8):4036-43. doi: 10.1002/cam4.1590 [Crossref]
  21. Catastrophic health expenditure of cancer patients at the end-of-life: a retrospective observational study in China. BMC Palliat Care 2019; 18(1):43. doi: 10.1186/s12904-019-0426-5 [Crossref]
  22. Catastrophic healthcare expenditure and coping strategies among patients attending cancer treatment services in Addis Ababa, Ethiopia. BMC Public Health 2020; 20(1):984. doi: 10.1186/s12889-020-09137-y [Crossref]
  23. Catastrophic health expenditure among colorectal cancer patients and families: a case of Malaysia. Asia Pac J Public Health 2017; 29(6):485-94. doi: 10.1177/1010539517732224 [Crossref]
  24. Changes in economic status of households associated with catastrophic health expenditures for cancer in South Korea. Asian Pac J Cancer Prev 2014; 15(6):2713-7. doi: 10.7314/apjcp.2014.15.6.2713 [Crossref]
  25. Disease-specific out-of-pocket and catastrophic health expenditure on hospitalization in India: do Indian households face distress health financing?. PLoS One 2018; 13(5):e0196106. doi: 10.1371/journal.pone.0196106 [Crossref]
  26. Microeconomic costs, insurance, and catastrophic health spending among patients with acute myocardial infarction in India: substudy of a randomized clinical trial. JAMA Netw Open 2019; 2(5):e193831. doi: 10.1001/jamanetworkopen.2019.3831 [Crossref]
  27. Catastrophic health expenditure & coping strategies associated with acute coronary syndrome in Kerala, India. Indian J Med Res 2012; 136(4):585-92.
  28. Emamgholipour S, Akbari Sari A, Geravandi S, Mazrae H. Estimation of out-of-pocket and catastrophic expenditures among patients with cardiovascular diseases in Khuzestan. Payavard Salamat 2017;11(3):297-307. [Persian].
  29. Catastrophic healthcare expenditure and its inequality for households with hypertension: evidence from the rural areas of Shaanxi Province in China. Int J Equity Health 2017; 16(1):27. doi: 10.1186/s12939-016-0506-6 [Crossref]
  30. Catastrophic health expenditure: a comparative study between hypertensive patients with and without complication in rural Shandong, China. BMC Public Health 2020; 20(1):545. doi: 10.1186/s12889-020-08662-0 [Crossref]
  31. Association between chronic disease and catastrophic health expenditure in Korea. BMC Health Serv Res 2015; 15:26. doi: 10.1186/s12913-014-0675-1 [Crossref]
  32. Extent and determinants of catastrophic health expenditure for tuberculosis care in Chongqing municipality, China: a cross-sectional study. BMJ Open 2019; 9(4):e026638. doi: 10.1136/bmjopen-2018-026638 [Crossref]
  33. Household catastrophic healthcare expenditure and impoverishment due to rotavirus gastroenteritis requiring hospitalization in Malaysia. PLoS One 2015; 10(5):e0125878. doi: 10.1371/journal.pone.0125878 [Crossref]
  34. Catastrophic health expenditure and impoverishment in households of persons with depression: a cross-sectional, comparative study in rural Ethiopia. BMC Public Health 2019; 19(1):930. doi: 10.1186/s12889-019-7239-6 [Crossref]
  35. Catastrophic health expenditure on acute coronary events in Asia: a prospective study. Bull World Health Organ 2016; 94(3):193-200. doi: 10.2471/blt.15.158303 [Crossref]
  36. Multiple sclerosis and catastrophic health expenditure in Iran. Glob J Health Sci 2016; 8(9):53778. doi: 10.5539/gjhs.v8n9p194 [Crossref]
  37. Severe injuries and household catastrophic health expenditure in Vietnam: findings from the Household Living Standard Survey 2014. Public Health 2019; 174:145-53. doi: 10.1016/j.puhe.2019.06.006 [Crossref]
  38. Catastrophic health expenditure and its determinants in older adults in Tehran, Iran. Caspian J Health Res 2018; 3(3):69-74. doi: 10.29252/cjhr.3.3.69 [Crossref]
  39. Impoverishing effects of catastrophic health expenditures in Malawi. Int J Equity Health 2017; 16(1):25. doi: 10.1186/s12939-017-0515-0 [Crossref]
Submitted: 21 Aug 2022
Revised: 08 Jan 2023
Accepted: 05 Feb 2023
First published online: 30 Apr 2023
EndNote EndNote

(Enw Format - Win & Mac)

BibTeX BibTeX

(Bib Format - Win & Mac)

Bookends Bookends

(Ris Format - Mac only)

EasyBib EasyBib

(Ris Format - Win & Mac)

Medlars Medlars

(Txt Format - Win & Mac)

Mendeley Web Mendeley Web
Mendeley Mendeley

(Ris Format - Win & Mac)

Papers Papers

(Ris Format - Win & Mac)

ProCite ProCite

(Ris Format - Win & Mac)

Reference Manager Reference Manager

(Ris Format - Win only)

Refworks Refworks

(Refworks Format - Win & Mac)

Zotero Zotero

(Ris Format - FireFox Plugin)

Abstract View: 424
PDF Download: 389
Full Text View: 159