Economic Burden of Diabetic Mellitus and its Associated Factors among Patients Attending Public Regional Hospitals in Addis Ababa, Ethiopia, 2018

Solomon Assefa Huluka^* and Melkamu Tiruneh
^*Correspondence: Solomon Assefa Huluka, Department of Pharmacology and Clinical Pharmacy, University of Addis Ababa, Addis Ababa, Ethiopia, Tel: 251 912482293, Email:

Keywords

Diabetes mellitus • Leptospirosis • Insulin • Oral hypoglycemic agents • Direct cost • Indirect cost

INTRODUCTION

Diabetes Mellitus (DM) is a chronic disease that occurs when the body cannot produce sufficient insulin, cannot use insulin effectively, or both [1]. It is one of the most common and costly chronic disease, the burden of which has become an important public health issue all over the world [2]. Nearly 425 million people are affected by DM in 2017 [3]. About 80% of them live in Low-and Middle-Income Countries (LMIC). If these trends continue, by 2035, close to 592 million people will have diabetes [4]. As one of the LMIC, Ethiopia is highly affected by DM. According to the 2017 estimate by IDF, Ethiopia has 2.57 million (5.2%) adult people aged 20-79 years with diabetes, making it the largest diabetes population in sub-Saharan Africa [5].

DM can impose havoc when health care systems are not aligned and consistently functioning against DM [6]. Moreover, the economic burden (direct and indirect cost) on patients and society is enormous [7]. The global economic burden of Non-Communicable Diseases (NCDs) such as DM is large, estimated at US $6·3 trillion in 2010, rising to $13 trillion in 2030 [8]. The economic burdens of diabetes comprises of direct costs, indirect costs and intangible costs patient/caregivers pay [9]. Studies showed that the relative cost for DM to be between 2% and 3% of every country’s healthcare expenditure [10]. This in turn made global economic development to be hindered due to DM burden to appreciable extent [11].

In sub Saharan African countries the problem of DM was once considered a rare condition [12]. But, because of rapid urbanization, the aging population and other factors, its prevalence is raising rapidly [13]. Recent reports indicated that prevalence-estimates of DM in these countries range between 2.1 and 6.0%, and the number of people suffering from the disease is likely to double within 25 years [14]. Generally, the 7.02 million cases of diabetes recorded by African countries in 2000 resulted in a total economic loss of $25.51 billion [15]. In developing countries like Ethiopia, most health-care costs must be paid by patients out-of-pocket [16].

The cost of health care for DMs creates a significant strain/load on household budgets, particularly for lower-income families [17].

Although there is a well-established health infrastructure for diabetics care in Addis Ababa, the diabetic care is below the acceptable standard [18]. Moreover, adequate studies on costs (medical and non-medical costs) of DM are not available for most of the developing countries, including Ethiopia [19]. In spite of data limitations, DM keeps on inflicting a substantial economic burden on developing countries of the African region [20]. Thus, this study aimed to estimate the economic burden of DM and its associated factor among patients attending public regional hospitals in Addis Ababa [21].

Materials and Methods

Study setting and period

In this study, institutional based cross sectional study was employed from May 1 to June 20, 2018 in four public regional hospitals (Menelik II referral hospital, zewuditu memorial hospital, yekatit 12 memorial hospital, and ras desta memorial hospital) of addis ababa, Ethiopia. These hospitals provide a diabetic care service [22].

Sample size and sampling technique

DM patients, who were attending in public regional hospitals of Addis Ababa during the study period, were employed as a study population [23]. Diabetic patients (385), who attended in these hospitals and had a follow up, at least for the last 1 year, were included in the present study. The respective study participants were selected through a systematic random sampling technique using the assumption of equal and proportional allocation. The sample size of participants to be included in this study was determined using a single mean formula considering the d2=Range/4 and Range=Maximum cost-minimum cost. The margin of error was set to be 0.05 with 95% Confidence Interval (CI). With an added contingency of 10% for non-response, the final sample was calculated to be 408 participants. But, only 385 participants have completed the interview [24].

Data collection

Data were collected by interviewing patients using a structured questionnaire. The questionnaire was checked for internal consistency and completeness. The data were collected by well-trained nurses, who were trained on the objective of the study. Pretest was done on 20 interview encounters to check its suitability and validity prior to the main data collection. Data quality was further assured by checking data completeness after each data collection. The data management and its quality were considered throughout the design, data collection and analysis.

From the collected data, direct and indirect cost was determined. An out-of-pocket expense (in Birr: The unit of currency in Ethiopia) paid by patients and their families, for medical and non-medical purposes were considered as a direct cost. Indirect costs, on the other hand, consist of opportunity cost of time lost due to losses of time invested by patients/family. Total tangible cost of diabetes comprises both direct costs as well as indirect costs. The 2018 exchange rate of Birr was $1=27.68.

Data analysis

The collected data were cleaned and organized using EPI-INFO and then exported and analyzed using SPSS version 22. The analyzed data were described in frequency counts and percentages. Mean, median, standard deviations and inter quartile range was calculated for continuous variables. Linear regression was done for associated factors related with cost of DM and p-value<0.05 was considered to be statistically significant.

Ethical consideration

Prior to the data collection, all of the study participants were provided with clear explanations about the purpose of the study and asked for their consent to participate in the study with a written informed consent. Participant’s information obtained from the questionnaire was kept confidential via data coding.

Results

Demographic and socio economic characteristics

As depicted, this study interviewed 385 respondents that made a response rate of 94.4%. More than half (51.12%) of the study participants were females and about a third (29.9%) of the DM patients were within the age group of 46 to 55. Among the respondents, participants with a secondary school (9-12) level of education constituted the highest proportion (26.2%; 101). As it is indicated in Table 1, more than three-quarter (77.1%) of the respondents were diagnosed with type 2 DM. Majority (75.6%) of the study participants cover their expenses for the management of DM out of their pocket (Table 1).

Economic burden of DM

Table 2 shows direct cost for the management of DM among the participants. The average total monthly cost of the participants was 1035.82 (± 998.87) Birr or 37.4 USD per patient per months with 95% CI (935.73, 1135.92). Of which, the highest (895.49) expense was paid for the management of patients’ admission due to DM. Cost of DM for a single purchasing of insulin and insulin syringe were 325.26 (± 229.06) and 86.90 (± 81.24), respectively (Table 2).

Logistic regression of independent variables with economic burden of diabetes mellitus

Simple linear regression analysis, in this study, showed that tangible cost had an association with educational status (p ≤ 0.05), income (p ≤ 0.001), distance for the facility (p-value ≤ 0.05), admission to inpatient (p ≤ 0.001), emergency visit (p ≤ 0.001), and number of drugs prescribed (p ≤ 0.005). In this study, the average value of tangible cost was increased by 0.16 Birr as a result of one unit change of income. Moreover, as number of prescription increased by one unit the average value of cost was increased by 84.22 Birr (Table 3).

Discussion

DM exerts a heavy economic burden on society and the nation. This burden is related to health system direct cost incurred by society in managing the disease and indirect costs resulting from productivity losses due to disability and premature mortality. Moreover, time spent by family members when patients seek care and other intangible costs, which include psychological pain to the family and beloved ones are among the burden of the disease. Diabetes and associated complications in Ethiopia are major causes of morbidity and mortality with consequential economic impact. The present study is aimed at assessing the direct and indirect cost of diabetes care on Ethiopian diabetic patients with or without complications.

In the current study, the overall monthly average total tangible cost of DM was 1035.82 Birr per patient per months. However, a previous study done in Addis Ababa, Ethiopia [17]. Reported a lower overall monthly direct cost of DM that was 630.33 Birr per patient per month. Regular median monthly medication cost in our study was 468.50 Birr. This is much more superior to a similar unpublished study done in Addis Ababa In considering the direct cost calculations, this cost differences may be due to the inflation occurred in pharmaceutical and other sectors in Ethiopia. Moreover, recall bias as a result of collecting information during a six month period.

In a study, the total cost of diabetes was estimated at 17 USD per person monthly. Accordingly, patients enrolled in our study expend more than North Indian patient per month. On contrary, the mean monthly average total cost of DM of a study done in China was superior to the current study. This could be due to health system difference between these countries. In China, direct medical and direct nonmedical costs per case averaged 1320.90 USD and 180.80 USD, respectively.

Financial sources for cost of DM in this study were from self (75.6%), family/relatives (51.7%) and insurance (6.2%). Study in Jimma identified that most (69.1%) of hospital diabetic patients’, source of costs for their treatment was for free payment. The report from Jimma was somewhat different from this; the possible reason might be this study excludes waiver privileged DM patients.

Education and income level found to have significant association with cost of DM, in the current study. This may be because of more awareness of disease with higher educational status and that more educated people earn more; hence can afford more for their health. People with a higher income may have better access to health services. Another hypothesis for this result is that people with a higher income could be more affected by the illness. In line with our results, income was a predictor of DM cost, in Mali. Another study done in Pakistan reported that income has significant association with cost of DM. However, opposite to our finding, a similar study in Mali reported that higher level of education was a predictor of low cost in DM.

The highest (895.49) expense in the current study was paid for the management of patients’ admission as a result of DM. In the US, the largest component of medical expenditure was hospital inpatient care, accounting for 43% of the total medical costs. Similarly, in Argentina, admission cost is the most important direct cost of DM. Both studies are in line with our study. In Brazil and Mali, nevertheless, the greatest portion of direct costs was attributed to medication (48.2%) and, laboratory tests, respectively.

Conclusion

This study showed that DM imposes a high economic burden on patients and their families. Medical costs, laboratory investigation, insulin, oral anti hyperglycemic agent and insulin syringe costs being a major contributor to the tangible cost of diabetes care. Moreover, costs economic burden of DM had an association with Educational status, income, Type of DM, admission to in patient, Emergency visit and number of drug prescription. It also makes clearly evident that the largest share of costs was being paid by patients and their families.

Limitations

As the respondents were interviewed in the compound of the hospital, study bias could have occurred. Moreover, the study was conducted in a governmental hospital that provides care to the certain group of the population in the city and the sample size used is not that large enough. As such, the result may not be a reflective of the situation in the general population. The finding of this study is interpreted in light of several limitations. The cross-sectional design gives only a snap shot of events.

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