The objective of this study was to estimate patient’s total cost (direct and indirect) of treatment and compare individual cost components between private and public hospitals in Bangladesh. This section outlines the cost burden of disease by gender, age group, income quintile, disease type, and treatment modality in both public and private hospital.

Descriptive statistics

A total of 252 respondents participated in this study with 139 attending the public hospital and 113 attending the two private hospitals. The results in Table 1 present descriptive statistics on respondent’s characteristics: the mean age of respondents both in public and private hospital were almost similar. The average monthly income of public hospital respondents was half that of private hospital respondents. This indicates a common bias of higher income people obtaining health care from private hospitals in preference to public hospitals. Villagers from rural areas, who tend to be poorer than city dwellers go to public hospitals more than the city dwellers and overall 72 % of public hospital respondents came from villages.

Table 1 Respondents Characteristics Full size table

Table 2 demonstrates that the average direct cost of treatment for illness was marginally more for public than for private hospital patients. Direct costs in both were less than 4 % of overall total costs. The most significant direct cost issue for public patients were average transport costs and average informal payments which were much higher than for private patients. Average indirect cost or patient’s income loss were the most significant costs which in public hospital was 97 % of total costs and 95 % in private hospital patients. Results from Table 2 indicate that public hospital patients on average paid more for their health care compared to private hospital patients despite being poorer.

Table 2 Average cost of treatment by hospital type and treatment modality, BDT (US$) Full size table

The analysis in Table 3 shows that the average total costs for public hospital patients were higher than private patients across all income quintiles. Costs for the lowest income public patients were the second highest of any income quintile, either public or private. That is, those with the least capacity to pay are paying the highest costs of illness and treatment. Average indirect cost analysis in Table 3 shows that patients treated in public hospital paid more for their health care across all income quintiles.

Table 3 Average cost of treatment by income quintile, BDT (US$) Full size table

The total costs of treatment by age quintiles (Table 4) show a similar pattern with public patients at all age levels paying more than private hospital patients. Costs rise in line with age in both cohorts. Average direct cost was low compared to the average indirect cost for each age quintile in both public and private hospitals. The average direct cost analysis in Table 4 shows that patients treated in public hospital spend more money in each age quintile except 60 plus age. The average indirect cost analysis suggests that patients treated in public hospital faced more income or productivity loss in each age quintile than that of private hospital patients. From the above discussion the total costs of illness were much higher up to the third age quintile (36 to 60) for public hospital’s patients but were higher for the last age quintile (60 plus) for private hospital’s patients.

Table 4 Average cost of treatment by age group, BDT (US$) Full size table

The losses associated with children illness and adult care of them were significant as shown elsewhere [20].

In the public hospital the average total costs for males and females were higher than for public hospital patients. The analysis in Table 5 shows that average total costs of treatment for illness was higher in public hospital (BDT 9923 or $132.31) than that of private hospital (BDT 5607 or $74.77), regardless of patient’s gender but average direct cost was higher for females in both public and private hospitals. In addition, average indirect cost was higher for both males and females patients in public hospital.

Table 5 Cost of treatment by gender, BDT (US$) Full size table

Amongst children (under 14 years of age), analysis of total cost of treatment for illness is presented in Table 6. In public hospital the average total costs for male children were higher than in private hospital. However, this pattern was reversed for girl children treatment. However, for female children, total costs of illness in private hospital were higher than public hospital. These differentials may reflect the alternative attitudes towards girls in poorer compared to richer households and their potential future role as care givers to their parents.

Table 6 Gender differential in cost of treatment among children Full size table

Table 7 summarizes the total costs of illness by different disease types and specialized hospital departments. The average total costs do not have a consistent pattern across public and private hospitals. In fact much heterogeneity is evidenced especially direct costs. As such the results should be accepted but with caution. The analysis in Table 7 indicates that the total costs of treatment by illness varied across all hospital departments both in public and private hospitals. The direct costs of treatment for illness were higher in all hospital departments in public hospital than private hospital except surgery, gynecology, and orthopedics. Indirect costs of treatment for illness was also higher for public hospital patients except medicine, chest medicine, orthopedics, and rheumatology departments compared to private hospital patients.

Table 7 Cost of treatment by department Full size table

The higher indirect costs in public hospital patients is primarily explained by high travel and long waiting times, especially compared to private hospital patients. Public hospital patients spend on average almost double the time accessing treatment which includes travel time and waiting time at the hospital to see a doctor. Table 8 indicates that public hospital patients spend approximately double the time compared to private hospital patients. Most public hospital patients (71 %) were coming from rural areas and their travel time and cost is higher than that of patients who visited private hospitals who mainly resided in the city. In public hospital the numbers of doctors were insufficient and there were always long queues for treatment observed. Some of the public hospital patients tried to jump the queue by offering bribes to staff in an attempt to get to see the doctor more quickly. In public hospital, 114 out of 139 patients (82 %) paid money as informal payments to see the doctor earlier. On the contrary, only 44 out of 113 patients (38 %) paid money as informal payments to private hospitals.

Table 8 Travel and waiting time for treatment Full size table

Some patients in both the public and private hospital also expressed dissatisfaction about treatment and wanted to change their current hospital to access better treatment. The prevalence of this dissatisfaction was higher in the public hospital. In the public hospital, 22 % of patients were interested to change, compared to 8 % among the private patients (Table 9).

Table 9 Dissatisfaction with treatment received Full size table

Statistical analysis

Independent-sample t tests and one-way ANOVA tests were used to analyze if the outlined differences in direct and indirect costs in public and private hospitals were statistically significant.

Table 10 shows the independent-samples t test results of the group summary statistics of the total direct costs and total indirect costs. For public hospital patients, total direct medical costs and total indirect costs were higher than for private hospital patients. This result is antithetical to an equitable outcome for health care given the income and wealth differentials.

Table 10 Independent-sample t test summary statistics Full size table

In Table 11 the Levene’s Test for Equality of Variances show that for total direct cost the outcomes are not statistically significant. Further it can be concluded that the means of total direct costs for public and private hospital patients were not significantly different. The mean difference was 0.129, and the p-value is 0.621 which indicates the absolute difference between the two means is about 62 %.

Table 11 Independent-sample t test analysis Full size table

The Levene’s Test for Equality of Variances for the total indirect costs indicate statistical significance. This result suggests that variances for the two groups, public and private, were different. The mean difference was 31.06 which suggests that the difference in means is statistically significantly different from zero.

Table 12 shows the results of the one way ANOVA to test the homogeneity of variances for the total direct and total indirect costs. The test assumes that the two variances are the same, that is, H 0 : σ2 public = σ2 private . For total direct cost it failed to reject H 0 implying that there was little evidence that the variances were not equal and the homogeneity of variance assumption may be reasonably satisfied. On the contrary, for total indirect cost H 0 is rejected implying that there was evidence that the variances were equal and the homogeneity of variance assumption may not be reasonably satisfied.

Table 12 One way ANOVA test - test of homogeneity of variances Full size table

Table 13 shows the output of the one way ANOVA analysis indicating whether there were significant differences between group means. The results on total direct medical cost shows that there was no statistically significant difference between public and private hospital patient groups. On the contrary, the one way ANOVA on total indirect medical cost shows there was a statistically significant difference between public and private hospital patient groups.

Table 13 One Way ANOVA Test Analysis Full size table

Table 14 shows the results of the Robust Test of Equality of Means, which has been conducted using the Welch and Brown-Forsythe method. The result of the total direct medical costs show that there was no statistically significant difference between public and private hospital patient groups. On the contrary, the Welch and Brown-Forsythe test on total indirect medical costs show that there was a statistically significant difference between public and private hospital patient groups.