A community-based cross-sectional study on out-of-pocket expenditure for coronavirus disease patients in urban slums, Bengaluru Rural

DR Sunil Kumar; Lakshmi Hulugappa; R Vidya; S Manjula

doi:10.4103/JME.JME_128_22

ORIGINAL ARTICLE

Year : 2023 | Volume : 4 | Issue : 1 | Page : 23-28

A community-based cross-sectional study on out-of-pocket expenditure for coronavirus disease patients in urban slums, Bengaluru Rural

DR Sunil Kumar, Lakshmi Hulugappa, R Vidya, S Manjula
Department of Community Medicine, Akash Institute of Medical Sciences and Research Centre, Bengaluru, Karnataka, India

Date of Submission	12-Oct-2022
Date of Decision	29-Oct-2022
Date of Acceptance	17-Nov-2022
Date of Web Publication	26-Apr-2023

Correspondence Address:
Dr. Lakshmi Hulugappa
Department of Community Medicine, Akash Institute of Medical Sciences and Research Centre, Bengaluru - 562 110, Karnataka
India

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/JME.JME_128_22

Abstract

Background: Coronavirus disease 2019 (COVID-19) has caused unprecedented harm to humanity and economies worldwide. A study of economic impact of COVID-19 patients in urban slums is limited. Aims: Hence, this study was undertaken to estimate the out-of-pocket expenditure (OOPE), and compare amongst admissions in public and private hospitals and home isolation of COVID-19 patients. Patients and Methods: A community-based cross-sectional study was conducted in urban slums under the urban field practice area of a medical college between September 2021 and November 2021. Data from 108 COVID-19 patients were collected by a pre-tested semi-structured questionnaire by interview method. Results: The mean age of respondents was 41.99 ± 10.49. The most common symptom was fever 91.6%, followed by cough 69.4%. History of travel was present in 64% and contact with family member was 69%. The mean OOPE for COVID-19 disease was 36756 INR per patient. Overall, the mean direct cost for COVID-19 admission was 29143 INR and mean indirect cost was 7529.62 INR. On applying Krushkal Wallis test, OOPE for direct cost on COVID-19 patient hospital admission, lab investigations, medications was H=65.85, 53.52, 28.98 with P value< 0.05 respectively and was found statististically significant. Similarly for Indirect cost , Loss of wages, travel expenses of the patient and attenders was H=10.45, 31.23 respectively and was found to be statistically significant at P <0.05. Overall the mean direct cost with government, private, home isolation COVID-19 patients was highly significant χ² = 33.92, P = 0.000, and mean indirect cost χ² = 9.48, P = 0.002. Conclusions: The OOPE for COVID-19 disease was high. The direct and indirect cost in government facility was minimal. The government's timely response to the pandemic was able to reduce the costs to the patients or else the economic burden would be higher.

Keywords: Coronavirus disease 2019, health expenditure, out-of-pocket expenditure

How to cite this article:
Sunil Kumar D R, Hulugappa L, Vidya R, Manjula S. A community-based cross-sectional study on out-of-pocket expenditure for coronavirus disease patients in urban slums, Bengaluru Rural. J Med Evid 2023;4:23-8

How to cite this URL:
Sunil Kumar D R, Hulugappa L, Vidya R, Manjula S. A community-based cross-sectional study on out-of-pocket expenditure for coronavirus disease patients in urban slums, Bengaluru Rural. J Med Evid [serial online] 2023 [cited 2023 Jun 7];4:23-8. Available from: http://www.journaljme.org/text.asp?2023/4/1/23/374711

Introduction

Novel coronavirus disease (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. An outbreak of COVID-19 was first noticed in a seafood market in Wuhan city in Hubei Province of China in mid-December, 2019, and has now spread to 215 countries/territories/areas worldwide.^[1],[2] It was declared as 'Public Health Emergency of International Concern' by the WHO (under the International Health Regulations) on 30 January 2020. The WHO subsequently declared COVID-19 a pandemic on 11 March 2020. Majority of people infected with the virus will experience mild-to-moderate respiratory illness and recover without requiring special treatment; in some cases, they become seriously ill and require medical attention.^[2],[3]

It presents with the most common symptoms as fever, dry cough and difficulty in breathing. Few patients have also experienced aches and pains, nasal congestion, runny nose, sore throat or diarrhoea. Around 80% of confirmed COVID-19 cases recover without any serious complications. Around one out of every six people who get COVID-19 can become seriously ill and develop difficulty in breathing. In very severe cases, it has resulted in severe pneumonia and other complications which are treated only at district hospitals and tertiary hospitals. In a few cases, morbidity has occurred.^[1],[2],[4]

As of 25 April 2022 in Karnataka, total COVID-19 cases were 39,46,934, deaths were around 40,057 and total recovered cases was 39,05,159.^[5] According to the National Health Accounts 2017–18, a household's out-of-pocket expenditure (OOPE) on health is 48.8% of total health expenditure.^[6]

COVID-19 has caused harm to humanity and financial constraints all over the world. There were reports of private hospitals charging exorbitantly for treating COVID-19 patients. The Government of Karnataka intervened and regulations were imposed on the fees that private hospitals can charge for testing and treating patients for COVID-19. The Government of Karnataka entered a Memorandum of Understanding with private hospitals and designated them as Covid Care Centre( CCC), Dedicated Covid Health Centres (DCHC) and Dedicated Covid Hospital (DCH). Expenses incurred by these COVID-19 centres are borne by the Government of Karnataka.^[4],[7],[8] Research regarding the economic impact of COVID-19 patients in urban slums is limited, hence this study was taken up with the following objectives.

Objectives

To describe the epidemiological and clinical profile of COVID-19 patients in urban slums, Bengaluru Rural
To estimate the OOPE of COVID-19 disease in urban slums, Bengaluru Rural
To compare the OOPE amongst public and private hospital admissions and home isolation COVID-19 patients in urban slums, Bengaluru Rural.

Materials and Methods

This community-based cross-sectional study was conducted in the urban field practice area in a medical college from September 2021 to December 2021. The urban field practice area mainly catered to the slum population. The sample size was calculated through n = Z²_α/2pq/d², with a prevalence of 46.7% of COVID disease as of September 2021 report, relative precision 53.3%, allowable error of 10%, the sample size was 95.62 and with 10% additional sample size the total sample size for the study was 108. The study participants were recruited through convenience sampling method. The study participants included were those diagnosed with COVID-19 disease and willing to participate and give informed written consent. Those who were seriously ill were excluded from the study.

Institutional Ethical Committee clearance was obtained before conducting the study. A pilot study was conducted to validate the questionnaire before the actual data collection. The data were collected by interview method. A pre-designed semi-structured questionnaire consisted of open- and close-ended questions. It consists of sociodemographic information and household characteristics. The epidemiological history included symptoms of COVID-19 disease, history of travel, history of contact with a COVID-19-positive family member, COVID-19 diagnosis, type of centres admitted, duration of onset of symptoms and admission to hospital and duration between diagnosis and admission. OOPE expenditure for COVID-19 disease was captured under direct cost(hospital admission, medications, lab investigations and consultation) and indirect cost (loss of wages, travel expenses, food expenses for patient and attender).

The data were entered in MS Excel and computed using SPSS 25 (Statistical Package for Social Sciences (SPSS)-25, IBM Bengaluru, Karnataka India). Categorical variables such as demographic, epidemiology and expenditure incurred for direct and indirect cost were computed using descriptive statistics. Inferential statistics such as Kruskal–Wallis test and Chi-square test was applied to assess the OOPE according to the place of treatment. P ≤ 0.05 was considered statistically significant at 95% confidence interval.

Results

Majority of study participants were in the age group of to >39 years 84(77.8%), were male69(63.9%), Hindus 94(87%) by religion, married 91(84.3%) and educated up to high school 30(27.9%), around 40 (37%) unemployed and total income was ≥10,000-20,000 in 49(45.4%) [Table 1].

Table 1: Sociodemographic profile of study participants (n=108)

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COVID- 19 admissions were 12(11.1%), 20(18.5%) and 76(70.3%) in the governments, private and home isolation respectively. Around 89 (82.4%) had no comorbidity. Most common symptom was fever 99(91.7%) [Table 2]

Table 2: Epidemiological and clinical profile of coronavirus disease 2019 disease in study participants

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In the present study on applying a Kruskal Wallis test to out of pocket expenditure for COVID-19 disease was compared with different place of treatment. Comparison of different place of treatment with hospital admission direct cost of the mean value were more in private hospitals (43625 INR), in laboratory investigation direct cost of mean value were more in private hospitals (33791 INR) and medication direct cost of mean value were more in private hospitals (83875INR) were statistically highly significant at P<0.001.

Comparison of different place of treatment with loss of wages of patients and attender indirect cost of the mean value were more in private hospitals (9666.6 INR) and travel expenses of patient's attender indirect cost of mean value were more in private hospitals (2566.66 INR) and food of patients were statistically significant at P <0.05 [Table 3].

Table 3: Component-wise distribution of out-of-pocket expenditure for coronavirus disease 2019 disease according to place of treatment

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Among the 108 participants, OOPE of direct cost was 2512500 INR(79.82%) in private hospitals, 476000 INR (15.12%) in home isolation and 159000 INR (5.01%) in government hospital, the mean value of direct cost 29.14 , on applying chi-square with different place of treatment it was found to be statistically significant at P <0.001 Chi Square 33.92

OOPE of indirect cost was 481500 INR (58.56%) in home isolation, 286800 INR(34.88%) in private hospital and 53900 INR(6.55%) in government hospital, the mean value of indirect cost was 7612.9,on applying chi-square to indirect cost with different place of treatment it was found to be statistically significant at P <0.001Chi-square 9.48

The OOPE for direct cost on COVID-19 patient hospital admission, laboratory investigation and medication was found statistically significant at P ≤ 0.005 on government, private hospitals and home isolation on applying Kruskal–Wallis test.

The OOPE for indirect cost on COVID-19 patients for loss of wages, travel expenses and food of both the patient and attender was found statistically significant at P ≤ 0.005 on government, private hospitals and home isolation on applying Kruskal–Wallis test [Table 2].

There was an association for direct and indirect OOPE for COVID-19 disease between government, private and home isolation study participants with Chi-square 33.92, P = 0.000, and Chi-square 9.48, P = 0.002, and was significant [Table 4].

Table 4: Association between out-of-pocket expenditure with government, private hospitals and home isolation study participants

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Discussion

In the present study,study participants with fever was 91.7%, cough 69.4%, nausea 44.4%, rhinorrhoea 39.8%, fatigue 27.8%, diarrhoea 25%, difficulty in breathing 23.1% , anorexia in 13% and vomiting in 10.1% whereas in a study conducted by Bose et al9 fever was the most common clinical presenting symptom in 57.1%, followed by cough 23.8%, respiratory distress 23.8%, convulsion 20%, skin manifestation 10% and diarrhoea 8.6%.^[9] Fever was the most common clinical presenting symptom in 57.1%, followed by cough 23.8%, respiratory distress 23.8%, convulsion 20%, skin manifestation 10% and diarrhoea 8.6%. This difference can be attributed due to this study conducted in children. This observed difference could be due to the study population where the participants were only children.

Study conducted by Parmar et al.^[10] revealed generalised weakness in 59.6% and fever 53.4% as the most commonly reported symptoms. This difference may be due to the selection of different study population groups, i.e., the healthcare workers. This difference may be due to the selection of different study population groups, i.e., the healthcare workers.

The present study showed a history of comorbidity in 17.6% similar to the study conducted by Samant et al.^[11] The current study revealed hypertension in 12%. Similarly, the prevalence of hypertension was 9.5%, 12% and 15% in studies carried out by Liu et al.,^[12] Xiao-Wei et al.^[13] and Huang et al.^[14] It is higher, i.e., 31.2% and 30% in studies carried out by Wang et al.^[15] and Zhang et al.^[16] The difference may be due to different age groups of study population.

In the present study, 70.4% were home isolated. A study by Parmar et al.^[10] revealed that 52.8% needed home isolation. In our study, 29.6% needed hospital admission which was similar to Parmar et al.^[10] 21.1%. Studies conducted in Canada (2.5%) and Spain (5.2%) revealed lower hospital admission. This can be due to different study settings, study populations and different health policies of the governments.

Out-of-pocket expenditure is already a common concern in India, particularly for people without insurance, and those in worse health. According to Pandey et al.,^[17] out-of-pocket medical expenses make up about 62% of all healthcare costs in India. The National Health Policy 2017 estimated that 7% of the Indian population is pushed into poverty each year because they are not able to afford the out-of-pocket (OOP) costs. It is of even greater concern in the time of COVID-19 pandemic.^[18]

In the present study the highest contributor for total OOPE in direct cost was for medications 56.54% similar to the study by Swetha N B et al.^[19] The present study revealed in the indirect expenditure incurred loss of wages was highest with 79.8%, expenses for food contributed to 10.7% and travel expenses contributed to 9.35%. There are limited studies available in reference to COVID-19 disease and hence could not be compared.

In comparison with OOPE in government, private, home isolation participants, the highest expenditure in direct cost was for medication with 52.83%, 51.52% and 85.60%, respectively, which is higher. In the indirect expenditure incurred in government, private and home isolation participants, the expenditure incurred for loss of wages was highest with 59.92%, 78.88% and 82.76% respectively.

A study by Chua et al.,^[20] 4.6% of hospitalisations for privately insured patients and 1.3% of hospitalisations for Medicare Advantage patients had out-of-pocket spending for facility services. Amongst these hospitalisations, the mean total out-of-pocket spending was $3840 for privately insured patients and $1536 for Medicare Advantage patients. A study by Nandi et al.^[21] found that where OOP expenditure was incurred, amounts were eight times higher in private than in public facilities for people covered with insurance.

Conclusions and Recommendations

The OOPE for COVID-19 disease was high. The direct and indirect cost in the government facility was minimal. Our study concludes that OOPE due to COVID-19 puts a heavy financial burden on families.

This study provides the relevant information for the policymakers and programme managers to make the necessary interventions to ensure equality in health and universal health coverage. The government's timely response to the pandemic was able to reduce the costs to the patients or else the economic burden would be higher.

Limitations

There could be recall bias in participants because of retrospective assessment of expenditure. Verification of cost expenditure was not conducted by bills. The sample size was small.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

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