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. 2021 Jan 27;16(1):e0245839. doi: 10.1371/journal.pone.0245839

Are Ethiopian diabetic patients protected from financial hardship?

Gebeyehu Tsega 1,*, Gebremariam Getaneh 1, Getasew Taddesse 1
Editor: Khurshid Alam2
PMCID: PMC7840028  PMID: 33503048

Abstract

Background

Globally, diabetes mellitus exerts an economic burden on patients and their families. However, the economic burden of diabetes mellitus and its associated factors were not well studied in Ethiopia. Therefore, the aim of this study is to assess the economic burden of diabetes mellitus and its associated factors among diabetic patients in public hospitals of Bahir Dar city administration, Ethiopia.

Methods

Across sectional study was conducted on 422 diabetic patients. The patients were selected by simple random sampling method. The prevalence-based model was used to estimate the costs on patients’ perspective. Bottom up and human capital approaches were used to estimate the direct and indirect costs of the patients respectively. Wealth index was constructed using principal component analysis by SPSS. Forty percent of nonfood threshold level was used to measure catastrophic diabetic care expenditure of diabetic patients. Whereas, the World Bank poverty line (the $1.90-a-day poverty line) was used to measure impoverishment of patients due to expenses of diabetes mellitus care. Data were entered by Epi data version 3.1and exported to SPSS version 23 for analysis. Simple and multiple logistic regressions were used.

Results

Four hundred one respondents were interviewed with response rate of 95%. We found that 239 (59.6%) diabetic patients incurred catastrophic diabetic care expenditure at 40% nonfood threshold level. Whereas, 20 (5%) diabetic patients were impoverished by diabetic care spending at the $1.90-a-day poverty line. Educational status of respondent, educational status of the head of household, occupation and wealth status were statistically associated with the catastrophic diabetic care expenditure.

Conclusions

The study revealed that the economic burden of diabetic care is very disastrous among the less privileged populations: the less educated, the poorest and unemployed. Therefore, all concerned stakeholders should design ways that can reduce the financial hardship of diabetic care among diabetic patients.

Introduction

Diabetes Mellitus (DM) is a chronic disease that occurs when there is a raised level of glucose in the blood [1–3]. DM is a major global health threat [4–6]. It exerts a heavy economic burden on society. The burden is related to direct costs, indirect costs, and intangible costs of diabetes mellitus that incurred by patients [7,8].

Nowadays, high attention is given for protecting people from financial hardship to access health care in the international and national strategic plans. Financial risk protection means that everyone can obtain the health care services they need without experiencing financial hardship. It is a key health system objective and one of the targets in the Sustainable Development Goals (SDGs), specifically SDG3. Financial risk protection is also the target of Health Sector Transformational Plan (HSTP) of Ethiopia [9]. However, literature stated that150 million people faced catastrophic health expenditure (at 40% threshold level) and one hundred million people are pushed in to poverty annually due to their out-of-pocket payments (OOPs) for health care at the $1.90-a-day poverty line threshold. Ninety seven percent (97%) of the impoverished population are found in Asia and Africa. Only in Africa region, 11 million people per year become impoverished as result of high out-of-pocket payments. According to the latest global monitoring report, catastrophic health spending as measured by SDG indicator 3.8.2 will continue to increase until 2030 [10–12].

In Ethiopia, out of pocket health spending amounted to 31% of the total health expenditure, which is higher than that of the global recommended target, 20%, [13]. People with chronic diseases like diabetes disproportionally suffered from financial hardship, catastrophic healthcare expenditure and impoverishment, especially in the low-income countries. For diabetic patients in low-income countries like Ethiopia, financial hardship is very disastrous as the poor or low socioeconomic groups may be forced to forego other vital needs such as dietary diversity in order to attain health services. Besides socioeconomic status, sex, educational status, household size, gender of household size, place of residence and the presence of vulnerable groups were determinant factors of catastrophic health expenditure (CHE) and impoverishment as the result of health care spending [14–16].

Evidence on financial hardship of diabetic care is essential to improve equity of diabetic health care among diabetic patients. It is also essential to remove financial barriers that are slowing down access to diabetic health care among diabetic patients in Ethiopia [17]. However, the economic burden and its associated factors of diabetes mellitus on diabetic patients were not well studied in Ethiopia. Therefore, the aim of this study is to assess the economic burden and its associated factors of diabetes mellitus on patients in public hospitals found in Bahir Dar city administration, Ethiopia.

Methods and materials

Study design, setting and participants

Across sectional study was conducted from September 15/2019 to December 30/2019 in public hospitals found in Bahir Dar city administration, Ethiopia. Bahir Dar city has three public hospitals (FelgeHiwot comprehensive specialized hospital, AdisAlem primary hospital and Tibebe Gihon hospital). These three hospitals are serving about 5.5 million people. Since Tibebe Gihon hospital has given services less than one year at the time of data collection, it was excluded from the study. About 1300 diabetic patients have follow up in FelgeHiwot comprehensive specialized hospital and AdisAlem primary hospital.

Diabetic patients with 14 or more years old, who are receiving services in the selected hospitals, were candidates for the study. However, community based health insurance enrolled diabetic patients were excluded from the study.

Sample size and sampling method

The number of study participants included in this study was determined by using the single population proportion formula. We used expected proportion (p) of the study participants who have catastrophic diabetic care expenditure of 50%, marginal error (d) 5% and confidence interval of 95%. Therefore, by considering 10% non-response rate, the final sample size was 422. Moreover, the 422study participants were randomly and proportionally recruited from the two public hospitals. Hence, we recruited 325 diabetic patients from FelegeHiwot comprehensive specialized hospital and97 diabetic patients from AddisAlem primary hospital by using simple random sampling method with computer generated random number.

Measurement and data collection

The study used a structured questionnaire, which consisted of questions on sociodemographic and socioeconomic characteristics, household expenditure as well as health care payments of DM (Additional file 1). The questionnaire was translated to local, Amharic, language (Additional file 2). Pretest was conducted and modifications were made accordingly. Trained data collectors, three BSC Nurses, have collected the data from study participants through face-to-face exit interview. The supervisor and principal investigator closely monitored the data collection process on daily base.

Participants were asked about their direct medical costs (medical card, laboratory test, insulin syringe and medications), direct non-medical costs (transportation, cafeteria, lodging) and indirect costs (patients and caregivers’ time loss) during exit interview.

Household consumption expenditure related data were collected by asking respondents/care givers for monthly estimates of amounts spent on food, housing, electricity, water, diabetic healthcare and others for the 12 months preceding the survey. Respondents were also asked about the availability of durable consumer goods such as radio, television, mobile phone, bicycle, farm equipment and agricultural land, livestock and also the amount of cereals and grains they collected over the preceding year.

Method of cost estimation

The costing method of the study was based on the patients’ perspective. Micro-costing(bottom-up) approach was used to estimate the direct costs of diabetes mellitus. Whereas, human capital approaches, in terms of productivity time losses, was employed to estimate the indirect costs of DM. Regarding to the time frame, prevalence based model was used. Costs were estimated for each patient for the 12 months preceding the survey [18,19].

We included costs for outpatient visits, drugs and laboratory tests to estimate the direct health costs of DM. Whereas, costs for transportation, meals and accommodation/lodging during outpatient visits, for both the patient and the accompanied person, were included to estimate the direct none medical costs of DM.

We calculated the indirect cost in terms of lost days of productivity for the patients and/or caregivers. In this category of cost, we included earnings lost because of travel to outpatient visits and those due to absences from work because of illness related to DM [20–22].

For formal employed workers (payroll paid) monetary value of lost days has been calculated by multiplying number of lost days with reported personal daily income (monthly income divided by 30). For farmers their reported annual income was determined by converting the cereals and grains they owned per year into monetary value using approximate market value of the year and then divided by 12 to get monthly income. Then, the monthly income of the farmer was divided by 30 days to get individual daily income and this was multiplied by lost days.

Measuring catastrophic health expenditure of diabetic care

The Wag staff and van Doorslaer method was used to measure the CHE and impoverishment. To calculate the catastrophic head count of diabetic care which is the percentage of patients/clients incurring catastrophic expenditures, we defined DMxi to be expenditure of the i th patient to receive care for DM for patient i, xi total expenditure for patient i, and f(x) food expenditures. The diabetic patient is said to have incurred catastrophic diabetic care payments, if [DMxi/(xi-f(x))] *100 exceeds a specified threshold, z (in our case 40% of nonfood threshold level was used for analytical statistics). But the choice regarding the threshold to use in determining catastrophic health expenditure is arbitrary and has typically varied between 10 and 40% of threshold level [23].

Measuring incidence and intensity of catastrophic diabetic care payments

The headcount (H) is the given by:-

H=1N∑i=1NEi (1)

Where N is the sample size and Ei equals 1 if DMxi/[xi-f(x)] > z and zero otherwise.

The headcount does not reflect the amount by which households exceed the threshold. We therefore used the catastrophic expenditure overshoot, which captures the average degree by which health expenditures (as a proportion of total expenditure or non-food expenditure) exceed the threshold z. The overall overshoot (O) is given by:-

O=1N∑i=1NOi (2)

Where Oi = Ei ((DMxi/xi-f(x)) − z).

The incidence (headcount) and the intensity (overshoot) of catastrophic expenditures are related through the mean positive overshoot (MPO) which captures the intensity of occurrence of catastrophic expenditures defined as overshoot divided by headcount:

MPO=OH;O=H*MPO (3)

Measuring impoverishment

Wag staff and van Doorslaer also describe methods to adjust poverty measures on the basis of household expenditure net of OOP spending on health care [23]. The three measures of poverty include;

  1. Poverty head count, which is the proportion of households living below the poverty line (PL);
    Hpovpre=1N∑i=1NPipre=μPpre (4)
    Where Hpovpre is poverty headcount before health payment and Pipre = 1 if Xi> PL and zero otherwise.
  2. Poverty gap, referring to the aggregate of all short falls from the poverty line;
    Gpovpre=1N∑i=1Ngipre=gμpre (5)
    Where Gpovpre is prepayment poverty gap, gipre = PL-Xi if PL>Xi and zero otherwise.

  3. Normalized poverty gap (NGpovpre) or poverty gap index is obtained by dividing the poverty gap by the poverty line.

NGpovpre=GpovprePL (6)

Calculating the three poverty measures requires setting a poverty line and assessing the extent to which health care payments push households below the poverty line. The World Bank poverty line1.9 USD dollar per person per day converted to Ethiopian birr based on average exchange rate (1USDdollar = 28.18 ETB) of September 2018-August 2019 was used to estimate poverty levels before and after healthcare payments. Replacing all the pre-payment superscripts, ‘pre’ by the superscript ‘post’ gives the analogous post-payment measurement.

The measures of poverty impact (PIH) of health payments are then simply defined as the difference between the pre-payment and post-payment measures, i.e.

PIH=Hpovpost−Hpovpre (7)

Where Hpovpost and Hpovpre are post and pre health payments poverty incidence respectively.

Data processing and analysis

The data were checked for completeness. Then, data were coded, organized and entered into Epi-data Version 3.1 and exported to SPSS version 23 software for cleaning and analysis. Descriptive statistical analysis, simple and multiple logistic regressions were conducted. All variables with p-value less than 0.25 in bi-variable analysis were considered as candidates for multivariable logistic regressions analysis. Adjusted odds ratio (AOR) with 95% CI was used to identify significantly associated variables. Wealth index was constructed using principal component analysis based on housing condition, water source and household durable assets.

Ethical clearance

Ethical clearance was obtained from Institutional Review Board (IRB) of Bihar Dar University, School of Public Health on January 24/2019. The ethics approval reference number is RCS/010/2019. A formal letter, from the school was submitted to each concerned bodies to obtain their co-operation. Explanatory letter was added to each questionnaire to maintain participants rights, also, all patients asked to participate in the study and received full explanations about the research purposes. Respect, anonymity and confidentiality were given and maintained by consent form for each participants and the liberty to withdraw at any stage of the interview and their participation was undergo to any pressure. Then, written informed consent was obtained from the participant as per the Institutional review board (IRB) approval.

Results

Sociodemographic and socio economic characteristics of respondents

Four hundred one respondents were interviewed with response rate of 95%. The age of respondents ranges from 15–80 years with mean of 43.27 (SD ±14.5). Out of the total 401 respondents, 235(58.6%) were males whereas most of the respondents (74.6%) were orthodox Christians. The majority of the respondents were ethnically Amhara (83.8%). More than half of the respondents were married-244(60.9%). Nearly half of the respondents-183(45.6%) had no formal education. One hundred and eleven (27.7%) of the respondents were payroll paid and 84(21%) were farmers. Household’s family size ranges from one up to ten with the mean size of 4.24 (SD±1.82). The percentages of economically dependent members accounted for 11.81% of total households’ size. Majority of the respondents 289(72.1%) were urban dweller. The wealth status of the households was classified in to five categories from first quintile to fifth quintile, and 22.2% of households were on fifth quintile. The mean monthly income of the respondents was 4710 (Table 1).

Table 1. Socio-demographic and socio-economic characteristics of diabetic patients in Bahir Dar city administration public hospitals, Ethiopia, 2019.

Variables Frequency %
Sex Male 235 58.6
Female 166 41.4
Age in years 15–30 99 24.7
31–45 113 28.2
46–60 115 38.7
>60 34 8.5
Ethnicity Amhara 336 83.8
Others1 65 16.2
Religion Orthodox 299 74.6
Others2 102 25.4
Marital status Single 90 22.4
Married 244 60.9
Widowed/divorced 67 16.7
Educational status No formal education 183 45.6
Primary education 51 12.7
Above primary 167 41.7
Occupational status Unemployed 125 31.1
Employed (Payroll paid) 111 27.7
Farmer 84 21
Merchant 81 20.2
Place of residence Urban 289 72.1
Rural 112 27.9
Households monthly income < = 2,500 ETB 98 24.4
2,501–5,000 196 49.0
5,001–1,000 84 20.9
>10,000 23 5.7
Households socioeconomic status 1st quintile 81 20.2
2nd quintile 84 20.9
3rd quintile 79 19.7
4th quintile 68 17
5th quintile 89 22.2
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1 Oromo, Tigray, Gumuz;

2Muslim, Protestant, Catholic.

Clinical characteristics of diabetic mellitus and related issues

About 243(60.6%) respondents were type II Diabetic patients. The mean duration of illness of respondents living with diabetes mellitus was 7.72(SD±5.43) years. One hundred fifty eight (39.4%) of respondents had monthly follow upwhereas112 (27.9%) had follow up every three months. Majority of respondents,287(71.6%) were stressed because of being diabetic patient. Among the respondents, 170(42.4%) were doing preventive measures to control blood sugar level.

Cost of diabetes mellitus treatment, household expenditure

The mean total monthly household expenditure was 3568.40ETB with (SD ±2077.4). The average monthly household’s food, nonfood and health expenditures were 2285.49ETB with (SD ±1446.82), 1282.92ETB (SD ±1173.27) and 505 ETB (SD± 400.94), respectively.

The mean monthly direct medical cost was 382.48 ETB (SD± 324.46). As reported by 193(48.13%) respondents, the mean direct cost of insulin and insulin syringes were 190.98ETB (SD± 110.64) and 48.4ETB (SD ±51.63) respectively. The mean monthly direct medical cost for oral anti diabetic medication users, 223(55.61%) was 327.94ETB (SD ±124.01); and for laboratory service the average cost was16.56ETB (SD ±24.97) as reported by all respondents (Table 2).

Table 2. Expenditures of diabetic patients in Bahir Dar city administration public hospitals, Ethiopia, 2019.

Variable N Mean(ETB) Std. Dev. median
Household costs per month
 Total household expenditure 401 3568.4 2077.4 3095.5
 Household food expenditure 401 2285.49 1446.822 2000
Nonfood household expenditure 401 1282.92 1173.27 925
Direct medical cost per patient per month 401 382.48 324.46 346.66
 Insulin 193 190.98 110.64 166.67
 Insulin syringe 193 48.4 51.63 40
 Laboratory test 401 16.56 24.97 10
 Oral anti diabetics 223 327.94 124.01 400
 Medical card 401 6.2 4.05 5
Direct non-medical cost (monthly) 401 48.75 91.19 22.5
 Transport cost 354 28.16 51.94 13.33
 Food cost during hospital visit 193 38.17 49.36 25
 Lodging cost during hospital visit 32 69.66 76.45 50
Indirect monthly cost(due to lost days) 401 73.77 112.57 44.44
Total monthly health payment of DM 401 505 400.94 444.44
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Note: All monetary values are presented in Ethiopian birr, N—number of observations. Std. Dev.–Standard deviation.

Direct medical cost and direct non-medical costs accounted 75.74% and 9.65% of health expenditures, respectively. The mean monthly indirect cost calculated by taking lost days for both the patient and care givers and their estimated daily income into consideration was 73.77ETB(SD ±112.57); which accounts 14.61% of monthly health expenditure (Table 2).

Coping strategies

Nearly two-thirds (60.6%) of respondents used their own money (savings and salary), while 21.2% from family/relative support, 13.5% by selling assets and 3% by borrowing from someone to cope the diabetes care payment. About 50.63% and 24.67% households faced CHE cope cost of treatment for DM by drawing savings and relative/family support respectively. Moreover, 85% and 15% of impoverished households were tried to cope diabetes treatment care by drawing saving and by selling household assets, respectively.

Catastrophic health expenditure and impoverishment

The proportion of catastrophic health expenditure among diabetic patients using 40% (non-food) threshold was 59.6%. Among respondents who faced catastrophic health expenditure, 145 (60.67%) were urban dwellers, 139(58.16%) were married, 94(39.33%) were in the age range of 46–60 years, 136 (57%) had no formal education, 63(26.36%) were in the third quintile wealth status and 30(12.55%) were in fifth quintile wealth status (Table 3).

Table 3. Catastrophic health expenditure and impoverishment among diabetic patients in public hospitals of Bahir Dar city administration, Ethiopia, 2019.

Variables Categories Catastrophic health care expenditure of DM Impoverishment
No Yes No Yes
sex Male 108 127 221 14
Female 54 112 160 6
age 15–30 37 62 91 8
31–45 53 60 108 5
46–60 61 94 148 7
>60 11 23 34 0
Marital status Single 37 53 82 8
Married 105 139 235 9
widowed/Divorced 20 47 64 3
Religion Orthodox 113 186 287 12
1Others 49 53 94 8
Ethnicity Amhara 132 204 320 16
2Others 30 35 61 4
Educational status No formal education 34 136 166 4
Primary 19 33 51 1
Above primary 109 70 164 15
Occupational status Unemployed 38 87 123 2
Payroll paid 70 41 99 12
Farmer 42 39 78 3
Merchant 12 72 81 3
Place of residence Urban 144 145 275 14
Rural 18 94 106 6
Sex of household head Male 143 189 317 15
Female 19 50 64 5
Educational status of household head No formal education 39 144 178 5
Primary 23 28 50 1
Above primary 100 67 153 14
Frequency of follow up Monthly 56 102 150 8
Every two months 34 35 64 5
Every three months 43 69 106 6
Every four months 29 33 61 1
Socioeconomic status based on wealth index 1st quintile 34 47 78 3
2nd quintile 24 60 77 7
3rd quintile 16 63 75 4
4th quintile 29 39 66 2
5th quintile 59 30 85 4
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1Muslim, Catholic and Protestant;

2 Tigray, Gumuz, and Oromo.

Three hundred and four (75.8%) of the respondents were poor before paying for diabetes care whereas 20(5%) of them were impoverished after paying for diabetes care. Among impoverished respondents, 14(70%) were male participants, 15(75%) were educated above primary level. Regarding to wealth status, 9.1%, 5.3%, 4.3%, 3.8% and 3% of impoverished respondents were in the 2nd, 3rd, 5th, 1st and 4th quintiles respectively (Table 3).

The incidence (headcount) and intensity (overshoot) of catastrophic diabetic expenditures were59.6 and 23.46% respectively. On the other hand, the proportion of mean positive over shoot (MPO) was39.36% (Table 4).

Table 4. Extent and intensity of catastrophic health expenditure at variable threshold levels of diabetic patients in public hospitals of Bahir Dar city administration, Ethiopia, 2019.

Catastrophic health expenditure
As a share of total monthly expenditure As a share nonfood monthly expenditure
10(%) 20(%) 30(%) 40(%) 10(%) 20(%) 30(%) 40(%)
Catastrophic headcount (%) 74.3 28.7 9.7 4.2 98 85.8 74.8 59.6
Catastrophic overshoot (%) 8.05 3.16 1.4 1.19 47.37 38.19 30.16 23.46
Mean positive gap (%) 10.83 11.01 14.43 28.33 48.33 44.51 40.32 39.36
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Impoverishment was estimated by calculating poverty levels using consumption expenditures before and after paying for diabetic care. Both the headcount and the poverty gap were calculated based on the World Bank poverty line1.9 USD which is equivalent to ETB 1606.26 per person per month. About 75.8% of respondents were living below poverty line before paying for diabetic care. After paying for diabetic care, the headcount increased by 5%. The average shortfall from the poverty line (the poverty gap) were ETB 1960.8(69.58 USD) and ETB 2336.44(82.91USD) before and after accounting for diabetic care payments respectively. There was an increase in poverty gap of ETB 375.64(13.33 USD) after diabetic care payment. Whereas, the mean positive poverty gap before and after diabetic care payments were 45.66% and 52.5% respectively (Table 5).

Table 5. Average monthly poverty headcount and gap before and after paying for diabetic among diabetic patients in public hospitals of Bahir Dar City administration, Ethiopia, 2019.

Impoverishment status(monthly)
Poverty headcount Poverty gap (ETB (%))
Prepayment headcount 75.8% Prepayment poverty gap 1960.8(45.66%)
Post payment headcount 80.8% Post payment poverty gap 2336.44(52.5%
Percentage change 5% Point change 375.64 (19.16%)
Prepayment poverty gap index 34.61%
Post payment poverty gap index 42.42%
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Factors associated with catastrophic health expenditure

Occupation, educational status of respondents, educational status of household head and wealth status were independent predictors of catastrophic expenditure for diabetic care. However, sex of the respondents, religion of respondents, place of residence, marital status, sex of household head, presence of under five children, frequency of follow up and source of medication were not independent predictors of catastrophic expenditure for diabetic care (Table 6).

Table 6. Logistic regression results on predictors of catastrophic expenditure of diabetic care among diabetes mellitus patients in public hospitals of Bahir Dar city administration, Ethiopia, 2019.

CHE
variables No Yes COR(95% CI) AOR(95% CI)
Sex Male 108 127 1 1
female 54 112 1.764(1.166, 2.668) 0.902(0.510,1.596)
Religion Orthodox 113 186 1 1
1Others 49 53 0.657(0.418, 1.034) 0.912(0.519,1.603)
occupation Unemployed 38 87 1 1
Payroll paid 70 41 0.256(0.149, 0.440) 0.453(0.226,0.907)*
Merchant 42 39 0.406(0.227, 0.724 0.416(0.208,0.833)*
Farmer 12 72 2.621(1.275, 5.385) 0.651(0.206,2.064)
Educational status No formal education 34 136 1 1
Primary education 19 33 0.434(0.220, 0.855) 1.104(0.411,2.966)
Above primary education 109 70 0.161(0.099, 0.260 0.310(0.125,0.771)*
Place of residence Urban 144 145 1 1
Rural 18 94 5.186(2.979, 9.029) 2.138(0.875,5.224)
Marital status Single 37 53 1 1
Married 105 139 0.924(0.566, 1.509) 1.003(0.522,1.926)
Divorced/widowed 20 47 1.641(0.839, 3.209) 0.754(0.303,1.877)
Sex of household head Male 143 189 1 1
female 19 50 1.991(1.125, 3.525) 1.879(0.788,4.481)
Education of household head No formal education 39 144 1 1
Primary education 23 28 0.330(0.171, 0.635) 0.347(0.136,0.884)*
Above primary education 100 67 0.181(0.113, 0.290) 0.959(0.402,2.286)
U-5 children No 92 157 1 1
Yes 70 82 0.686(0.456, 1.034) 0.641(0.385,1.078)
Monthly 56 102 1 1
Frequency of follow up visit Two monthly 34 35 0.565(0.318, 1.003) 0.604(0.299,1.220)
Three monthly 43 69 0.881(0.534,1.454) 0.773(0.419,1.425)
Four monthly 29 33 0.625(0.344, 1.134) 0.672(0.325,1.388)
Source of medication Government 83 173 1 1
Non-government 79 66 0.401(0.264, 0.609) 0.664(0.393,1.123)
Socioeconomic status 1st quintile 34 47 2.719(1.458, 5.068) 1.482(0.683,3.217)
2nd quintile 24 60 4.917(2.577, 9.380) 2.448(1.094,5.475)*
3rd quintile 16 63 7.744(3.834, 15.641) 2.715(1.151,6.409)*
4th quintile 29 39 2.645(1.379, 5.073) 1.868(0.903,3.863)
5th quintile 59 30 1 1
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* = Significant at p<0.05.

Diabetic patients who attended above primary school were 68.8% (AOR = 0.312; 95%CI: 0.125, 0.776) less likely to have catastrophic expenditure for diabetic care as compared to those with no formal education. Diabetic patients whose households led by heads with primary education were 65.7% (AOR = 0.343; 95%CI: 0.134, 0.875) less likely to have catastrophic expenditure for diabetic care as compared to those with households led by a head with no formal education (Table 6).

Diabetic patients who were in 2nd and 3rd wealth quintiles were 2.4 times (AOR = 2.417; CI: 1.079, 5.413) and 2.7 times (AOR = 2.744; CI: 1.161, 6.187) more likely to encounter catastrophic expenditure for diabetic care respectively as compared with that of diabetic patients in the 5th wealth quintile (Table 6).

Diabetic patients who were formal employees and merchants were 54.8% (AOR = 0.452; CI: 0.225, 0.906) and 58.4% (AOR = 0.416; CI: 0.206, 0.827) less likely to catastrophic expenditure for diabetic care respectively as compared to those with unemployed diabetic patients (Table 6).

Discussion

This study aimed to assess the economic burden of health expenditure in diabetic patients in public hospitals of Bahir Dar city, North West Ethiopia. The study showed that the average monthly diabetic care expenditure is 505 ETB (17.92 USD). It is lower than that of a study done on catastrophic health care expenditure in Ethiopia (610ETB) [24]. The possible explanation for this difference might be due to the fact that the previous study incorporated catastrophic health care expenditure as results of all diseases while the current study was conducted on catastrophic expenditure for diabetic care.

In the current study, the direct medical cost of diabetic care accounted 75.74% of the total cost of diabetic care. This finding is in line with that of studies done in Ghana (78%) and Nepal (75.8%) [25,26]. But it is lower than that of a study done in china (90.9%) [27]. This difference might be due to the fact that the contexts of the studies are different in terms of socio economic status.

In this study at 10% threshold of total household expenditure, the incidence (headcount) of catastrophic health expenditure was 74.3%. This result is higher than that of a previous study done in Ethiopia in which the incidence was 24% [28]. The difference might be due to the fact that in the current study the study participants were diabetic patients which are prone to catastrophic health expenditure.

In the present study, catastrophic expenditure of diabetic care at 40% threshold was 59.6%. This is higher than that of previous studies done in South Africa (6%) and China (13.8%) [15,29]. The difference might be due to the fact that all study participants of the previous studies were urban dwellers and insured participants were included in the studies. Moreover, South Africa and China have better socioeconomic status than that of Ethiopia. The other difference might be due to the fact that in current study, cafeteria costs and care givers costs were included as opposed to that of South Africa and China. The incidence of catastrophic expenditure of diabetic care is also higher than that of a previous study done in 35 developing countries (17.8%) [30]. The difference might be due to different study contexts.

The catastrophic overshoot and MPO at 40% non-food threshold were 23.46% and 39.36%, respectively. The overshoot implied that on average all diabetic patients included in the study had invested 63.46% (23.46%+40%) of their monthly expenditure on diabetic care. Whereas, the MPO indicated that only those diabetic patients with catastrophic expenditure of diabetic care had invested 79.36% (39.36%+40%) of their monthly expenditure on diabetic care.

Regarding to impoverishment, both poverty headcount and poverty gap became higher after payment for the diabetic care. In this study, we found that 5% of diabetic patients fell into poverty after the diabetic care payment. This finding is in line with that of previous studies done in South Africa (4%), Ethiopia (5.8%) and Kenya (4% and 5.4%) [15,28,31,32].

The average shortfall from poverty line, poverty gap, following diabetic care payment was substantial. On average, the diabetic care expenditure increased the poverty gap of diabetic patients by 19.16% as compared to before diabetic care payment. This finding highlights that the diabetic care expenditure severely affected the pre-payment poor diabetic patients. The proportion of prepayment poverty gap index and post payment poverty gap index were 34.61% and 42.42%, respectively. This means, on average the diabetic patients werefar below the poverty line by 34.61% and 42.42% before and after diabetic care payment, respectively.

Diabetic patients which are in 1st wealth quintile had lowest incidence of impoverishment (3.8%) and those in the 2nd and 3rd quintiles had 9.1% and 5.3%incidence respectively. This finding is in line with that of previous study done in Kenya [32]. The reason for the lowest incidence for the 1st quintile can be explained by the fact that households in this quintile are already poor i.e. 90.1% of households are below the poverty line, even before diabetic care payment.

The current study revealed that catastrophic diabetic care expenditure, which was measured at 40% threshold (nonfood share), was affected by occupation, educational status of respondents, educational status of household heads and wealth status.

The result of this study revealed that diabetic patients which were in the higher wealth quintile have low probability of incurring catastrophic diabetic care expenditure or vice versa. This finding is consistent with that of previous studies done in South Africa [15,33]. Diabetic patients whose household headed by a person with a lower level of education were far more likely to encounter catastrophic diabetic care expenditure. This finding is consistent with that of a study done in Latvia [34].

The current study has its own limitation. The finding of the study may be affected by recall bias due to the fact that the respondents may not remember the information related to their past diabetic care payment during interviewing through retrospective questions.

Conclusions

The study showed that diabetes mellitus is imposing a significant economic burden to the patients. The current study also revealed that catastrophic diabetic care expenditure was affected by occupation, educational status of respondents, educational status of household heads and wealth status. Therefore, all responsible stakeholders should design ways that can reduce the financial hardship of diabetic care among diabetic patients, specifically the poor, unemployed and uneducated diabetic patients.

Supporting information

S1 Table. Clinical characteristics of diabetes mellitus and related issues among diabetic patients having regular follow up at public hospitals of Bahir Dar city administration, North West Ethiopia, 2019.

(DOCX)

Click here for additional data file. (14.7KB, docx)
S2 Table. Coping strategies for diabetes mellitus health care costs among diabetic patients having regular follow up at public hospitals of Bahir Dar city administration, North West Ethiopia, 2019.

(DOC)

Click here for additional data file. (51.4KB, doc)
S1 Text. Survey questionnaire in English.

(DOCX)

Click here for additional data file. (64.2KB, docx)
S2 Text. Local language version questionnaire (Amharic language).

(DOCX)

Click here for additional data file. (97.3KB, docx)

Acknowledgments

We would like to thank Bahir Dar University, study participants, data collectors and supervisors for their contributions for the study. We also thank Felegehiwot and AdisAlem Hospitals for their support during the process of the study.

Data Availability

All relevant data are within the paper and its Supporting information files.

Funding Statement

The author(s) received no specific funding for this work.

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Decision Letter 0

Khurshid Alam

12 Oct 2020

PONE-D-20-25611

Are Ethiopian diabetic patients protected from financial hardship?

PLOS ONE

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Comments to the Author

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Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

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**********

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**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The paper is about “financial hardship of diabetic care” which is an important topic as it is known and shown in the literature that financial hardship(risk) protection is the international and national agendas, such as SDG 3.8.2 and the Ethiopia’s health sector’s fifteen years strategic plan (2015-2035). One of the barrier to achieve universal health coverage by 2030 is financial barrier to get quality of health care, mainly in low income countries like Ethiopia. So it is important to know about the Ethiopian diabetic patients’ financial hardship protection status and its associated factors in Ethiopia to inform policy options in the country in order to attain the universal health coverage without financial hard.

Despite about it, there are some comments that need to be addressed before this paper could be published.

Comments:

1. Add the response rate in the abstract section of manuscript in the result part

2. In the introduction section of the manuscript, there are long sentences that can be broken down to simple, short and concise sentences as per the plos one journal recommendation. For instance, “It is a key health system objective and one of the target in the Sustainable Development Goals (SDGs), specifically SDG3, and Health Sector Transformational Plan (HSTP) of Ethiopia” can be broken down to two short and concise sentences.

3. On page 19, there is empty page, it should be omitted

4. The title of table 6 should be edited and why the authors make the footnote of table 6 bold?

5. The authors should add the questionnaire as supporting information for the manuscript

Reviewer #2: General comment

• The manuscript has presented an original work and has applied the techniques and requirements of a scientific study with strong conceptual and statistical analysis. It is publishable with some finer correctable suggestions forwarded here under step by step.

Simple Notice

• Please try to cancel the repeatedly used pronoun ‘we’ as a doer. The interest should be expressing on what has been done.

• In the conclusion part it is good if you state in such a way that Economic burden of DM care is stronger among the less privileged populations: the less educated, the poorest and unemployed. Because your regression result shows that.

Introduction:

• Reconstruct some lengthy sentences to make it simple and clear. Eg. In the second paragraph the last sentence and the second sentence in the last paragraph

Methods and Materials

Study Design and participants

• Cancel the phrase ‘Institutional based” because later on you mentioned that the study is conducted on hospitals. By implication the readers can understand that the study was institutional based. Don’t write the knowns.

• Mention whether you included both outpatients and inpatients or either of the two. Since DM care is part of CBHI benefit package, please declare that whether you included CBHI enrolled patients or not? If you included them, in the cost calculation you need to specify if you calculate the cost regardless of who pays or if you included only the OOP? You can use it as eligibility criteria.

Sample size and Sampling Method

• Make the sampling clear by mentioning how many samples you took from how many populations in both of the hospitals. It is good to specify sampling technique rather than broadly saying random technique: what specific random technique was used to recruit study participants. In fact, in your abstract you said it (simple random method), but still if possible, it is advisable to be very specific (What specific simple random method?).

Measuring catastrophic health expenditure

• Rather than saying health expenditure (which is more general), you need to say expenditure to diabetic care (your case). A curiosity question is that why did you represent expenditure to health care with Ti? What if you change it to Hi (H to mean health or DMxi- expenditure of the ith patient to receive care for DM) Then the formula would be

o [DMxi/(xi-Fxi)] *100 (look the formula again. It seems that 100 multiplies only the denominator).

• If you already used a threshold of 40%nonfood expenditure, what is the importance of the last sentence?

Measuring incidence and intensity of catastrophic payments

• Hopefully by saying ‘z’ you are referring to the threshold (40% of nonfood expenditure)!!! If that is the case say so. Otherwise mention what it is.

• Generally, the three formulas need to be more detail. Simply formula one is about the ratio of patients who experienced CHE? Is it that much important to sophisticate the formula?

• Is Ei in formula 2 similar with the one inf formula 1? – Don’t you think that this will positively inflate the overshoot? What about the negative overshoot?

Results

Socio-demographic and Socioeconomic……

• If you can it would be more informative to report mean income of patients. Because it would help the reader to compare it against the mean monthly total expenditure.

• In table 1- better to cancel the variable ’Sex’. Since the males are reported in the text the reader understands that the other share is for females. The same is true for Religion and Residence. Narrate the dichotomy variables in the text and avoid including it in the table. This helps the table to be smart.

Cost of diabetes mellitus treatment, household expenditure

• Better to mention how the mean monthly expenditures and costs were calculated. (You need to see the numerator and denominator).

Coping Strategies

• Correct the last two sentences. Grammatically they are not correct.

• Put it after the section next to it (Catastrophic health expenditure and impoverishment).

Catastrophic health expenditure and impoverishment

• Reporting these variables with its classification based on different variables do not add value. That means table 3 and majority of the preceding texts can be canceled. Because you are going to fit regression model for it, which can be more informative that this table.

Discussion

• In the 5th paragraph rather than using comma use brackets so separate the numbers you summed up. That is instead of putting as……. patients included in the study had invested 63.46%, 23.46%+40%, of the…….. write it as ……patients included in the study had invested 63.46% (23.46%+40%) of the…. . Moreover, you should see the interpretation of catastrophic overshoot and MPO again. The specified expenditures are for percentage of nonfood expenditure rather than percentage of total expenditure.

• Paragraph six- Is it fair to make that 5% impoverishment is similar with 24%, 19.1%, 29.9%? see it again.

• The four factors affecting CHE in your study indicated that ’those who were worse off socio economically are more prone to catastrophic expenditure than that of the counterparts.” This should be discussed very well.

Conclusion

• The last sentence should be specific. Specifically, the recommended protection mechanisms should target the have-nots like the poor, the unemployed and uneducated since the financial hardship is stronger for them than the other half.

Reference

• See some referencing styles. For example, reference number 27 can be rewritten in a better way using standard referencing style.

Reviewer #3: Financial hardship of diabetic careis the topic of this article which is a burning issue in both the global and in the Ethiopian contexts as the authors described in the introduction section of the manuscript.But as the best search of the reviewer, there is limited evidence about it in Ethiopia. The results of this study can be used as an evidence to design evidence based intervention in Ethiopia to protect diabetic patients from financial hardship, to ensure equity health care in the country. Therefore, this article is important and relevant to policy makers of Ethiopia’s health sector to accomplish Universal Health Coverage (UHC) by the year 2030.

However, the reviewer recommends the following minor revisions in the manuscript before publication.

In the introduction section: In the manuscript, some of the sentences are long which should be short as much as possible so that the potential readers will understand the paper easily.

o In the methods section of the manuscript, Describe your study area how many public hospitals found in Bahir Dar city administration?

o What is your sampling method? describe it clearly

Result section

o use appropriate punctuations in some of sentences and correct the editorials for language

o on table 1 'Amara' or 'Amhara'?

o make Table 5 clear in meaning and drawing as well

**********

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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Attachment

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PLoS One. 2021 Jan 27;16(1):e0245839. doi: 10.1371/journal.pone.0245839.r002

Author response to Decision Letter 0

11 Dec 2020

Dear reviewers and editor,

Thank you so much for your constructive comments to improve our manuscript.

Below are our point by point responses for the comments

Responses for the academic editor

1. We have adhered to the requirements of PLOS ONE's style as much as possible.

2. We, the authors, and our colleague (Dr.Walelign Kindie, Email: walelignkindie2@gmail.com, an academic staff of Bahir Dar University, Tel: +2519 38883386) thoroughly copyedited the manuscript for language usage, spelling, and grammar.

3. We, the authors, submitted the local language, Amharic, and English versions of questionnaire tools as additional files.

4. We have conducted pretest before survey as stated on page 6 line number 106 in the manuscript. The purpose of the pretest was to ensure that the understandability and clearness of the questionnaire for the respondents and it was modified accordingly. We modified the flow, order, skip patterns and the allocated time for interview in the questionnaire. The questionnaire was developed based on previous validated questionnaires (standard one) that is why validation is not done for our study.

Responses for the comments (reviewer 1)

1. We added the response rate in the abstract section of manuscript in the result part on page 2 line number 37.

2. In the introduction section of the manuscript, long sentences have been broken down to simple, short and concise sentences as per the comments. For instance the long sentence such as, “It is a key health system objective and one of the target in the Sustainable Development Goals (SDGs), specifically SDG3, and Health Sector Transformational Plan (HSTP) of Ethiopia” were broken down to two short and concise sentences: It is a key health system objective and one of the targets in the Sustainable Development Goals (SDGs), specifically SDG3. Financial risk protection is also the target of Health Sector Transformational Plan (HSTP) of Ethiopia (on page 4 line numbers 54-57).

3. In the previous manuscript ,there is empty page, it was omitted right now

4. The title of table 6 was edited and its footnote was unbold?

5. The authors added the questionnaire as supporting information in the current manuscript.

Responses for the comments (reviewer 2)

1. We used pronoun ‘we’ as a doer as the reviewer has commented on the manuscript. Even though, the interest is expressing on what has been done, to make it clear the doer is also important as per the norm of scientific writing.

2. In the conclusion part of the abstract we stated in such a way that economic burden of DM care is stronger among the less privileged populations: the less educated, the poorest and unemployed as per the recommendation of the reviewer on page 3 line numbers 43-44.

3. We edited lengthy sentences to make it simple and clear throughout the manuscript.

4. In the methods part the phrase “institutional based “was used to indicate the type of study design that we used to answer our research question. The readers (those who are not expertise in epidemiology) might not understand the type of study design by reading the setting of the study as reviewer stated.

5. We, the authors, included patients who are not CBHI enrolled as stated on page 6 line numbers 91-93 in the manuscript.

6. We, the authors, mentioned (on page 6 line numbers 100-102) how many samples we took from how many populations in both of the hospitals. We recruited 325 diabetic patients from Felege Hiwot comprehensive specialized hospital and 97 diabetic patients from Addis Alem primary hospital by using simple random sampling method with computer generated random number.

7. We, the authors, replaced health expenditure to expenditure of diabetic care in the measuring catastrophic health expenditure part of the manuscript. Moreover, we used DMxi instead of Ti. - Expenditure of the ith patient to receive care for DM. All formulas were edited as per the comments of reviewer.

8. We used a threshold of 40% nonfood expenditure for analytical analyze, however, we also reported the results at different recommended levels: varied between 10 and 40% of threshold level.

9. We elaborated more about the overshoot in the current version.

10. In the result part, we reported the monthly income in the table in the previous version. As per the comment of the reviewer, we have stated the mean monthly income in the current version of the manuscript on page 12 line numbers 207-208.

11. In table 1- the reviewer recommended that “better to cancel the variable ’Sex’. Since the males are reported in the text the reader understands that the other share is for females. The same is true for Religion and Residence. Narrate the dichotomy variables in the text and avoid including it in the table. This helps the table to be smart”. However, if we cancel these important variables, the table may not be self-explanatory or self-contained that leads to ambiguity due to the incomplete information in the table.

12. We have mentioned how the mean monthly expenditures and costs were calculated in the method of costing part starting from on page 7 line number 119.

13. Regarding to table 3 in the result part, the table informs the readers the proportion of catastrophic diabetic care expenditure and impoverishment due to diabetic care in each category, more specifically those variable not reported in the regression table. Hence, it adds value for the readers.

14. We have edited and corrected the discussion as per the recommendation of the reviewer’s comments on page 23 line numbers: 334,336 and 340.

15. In conclusion part, we have specified the last sentence as per the reviewer’s comment on page 25 line numbers 372 and 373.

16. We have edited the references list in the manuscript.

Responses for the comments (reviewer 3)

1. In the introduction section, we edited the long sentences in the current version of abstract.

2. In the method section, we described about the study area in which how many public hospitals found in Bahir Dar city administration on pages 5&6 line numbers 85-90.

3. Regarding to sampling method, we stated about it on page 6 line number 99-102.

4. In the result part, we and our colleague have copy edited the whole manuscript including result part.

Attachment

Submitted filename: Author-responses letter.docx

Click here for additional data file. (22KB, docx)

Decision Letter 1

Khurshid Alam

11 Jan 2021

Are Ethiopian diabetic patients protected from financial hardship?

PONE-D-20-25611R1

Dear Dr. Tsega,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Khurshid Alam, Ph. D.

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #3: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

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Reviewer #3: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

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Reviewer #3: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

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Reviewer #3: Yes

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Reviewer #3: The results of this study can be used as an evidence to design evidence based intervention in Ethiopia to protect diabetic patients from financial hardship, to ensure equity health care in the country. Therefore, this article is important and relevant to policy makers of Ethiopia’s health sector .

I found that all comments were provided are corrected.

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Reviewer #3: No

Acceptance letter

Khurshid Alam

13 Jan 2021

PONE-D-20-25611R1

Are Ethiopian diabetic patients protected from financial hardship?

Dear Dr. Tsega:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Khurshid Alam

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Table. Clinical characteristics of diabetes mellitus and related issues among diabetic patients having regular follow up at public hospitals of Bahir Dar city administration, North West Ethiopia, 2019.

    (DOCX)

    Click here for additional data file. (14.7KB, docx)
    S2 Table. Coping strategies for diabetes mellitus health care costs among diabetic patients having regular follow up at public hospitals of Bahir Dar city administration, North West Ethiopia, 2019.

    (DOC)

    Click here for additional data file. (51.4KB, doc)
    S1 Text. Survey questionnaire in English.

    (DOCX)

    Click here for additional data file. (64.2KB, docx)
    S2 Text. Local language version questionnaire (Amharic language).

    (DOCX)

    Click here for additional data file. (97.3KB, docx)
    Attachment

    Submitted filename: Recomandation.docx

    Click here for additional data file. (18.1KB, docx)
    Attachment

    Submitted filename: comments to the Author.docx

    Click here for additional data file. (13KB, docx)
    Attachment

    Submitted filename: Author-responses letter.docx

    Click here for additional data file. (22KB, docx)

    Data Availability Statement

    All relevant data are within the paper and its Supporting information files.

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