Recognizing the determinants of catastrophic costs could provide an insight into approaches for mitigating catastrophic costs among the vulnerable TB patients and their households. This study confirms that a significant proportion of patients with DSTB (27%) incur catastrophic costs, despite free TB diagnosis and treatment. Further, it demonstrates the association between incurring catastrophic costs and poverty, disease severity and delayed treatment initiation. Low economic status is the most significant factor associated with incurring catastrophic costs. Patients who experience catastrophic costs have a lower economic status (pre-TB) and incur higher costs and productivity losses in relation to economic capacity. Patients with severe disease requiring inpatient care, and those who experience delay before treatment are also at a higher risk of incurring catastrophic costs. On the other hand, seeking care at a public health facility and a better nutritional status are protective factors.
Catastrophic Costs and Poverty
Being poor prior to TB illness is associated with the highest incidence of catastrophic costs, resulting in the medical poverty trap. Using household expenditure quintiles in this study demonstrates the higher risk associated with the decreasing economic status. This finding is similar to previous studies in other low- and middle-income settings like Uganda (16), Benin (34) Malawi (42) and China (33). These findings are also in line with Barasa et al. when considering OOP expenditure for general illness in Kenya (43). The median age of this study is 31 years representing a young productive age-group. Hence catastrophic costs among the poor can be explained by the loss of earnings during illness and absenteeism, coupled with increased spending on transportation and food as part of the care seeking and treatment process. There is low coverage of social protection measures such as health insurance and insurance against income loss when sick in Kenya (44, 45). The informal sector, which employed 80% of Kenyans in 2016 (46), is associated with low and irregular pay. The low pay poses a challenge for contributory health insurance schemes (47). Additionally, paid sick leave is uncommon in the informal sector (48). The findings of this study indicate that targeting the lower income households for social protection interventions may protect them from catastrophic costs.
Catastrophic costs and Disease Severity
Although a small number of participants in this study reported having been hospitalized (n = 6), five (83%) of them incurred catastrophic costs. These finding are similar to other studies in Uganda (16), and India (49). This may be attributed to costs like the bed fee and additional treatment which are not covered by the TB programme. Additionally, family members or treatment supporters may incur OOP costs for transportation, accommodation, in addition to missing out on their income earning activities. That only 0.6% of patients were hospitalized may indicate inaccessibility of services for poor patients. The TB care model in Kenya is predominantly community-based DOTS (50), with hospitalization for those with life-threatening symptoms requiring care such as oxygen therapy or intravenous fluid support. Since there is no literature available on the expected hospitalization rates for TB patients, it is difficult to compare with other settings. Nevertheless, these findings could imply that wealthier patient populations are able to afford inpatient care, compared to the poorer patients. In this study, hospitalization and household expenditure have no significant association. However, there is a significant association between hospitalization and seeking care at a private facility. Previous studies in Kenya also demonstrated pro-rich inequality in access to inpatient care and private facilities utilization for generalized illness (51, 52).
Low BMI is associated with a higher occurrence of catastrophic costs. Similar findings were reported in Ghana (53) and may be explained by the need to spend more on nutritious food and specialized diets (13). Malnutrition among TB patients is also associated with more severe TB disease (54, 55) and may affect treatment outcomes (56, 57) or even predispose to adverse effects (58), all factors that may increase costs of care. A study in Kenya showed that TB patients who received nutritional support had higher chance of completing their treatment (59).
Catastrophic costs and Health-seeking characteristics
Despite free TB diagnosis and medicines even in private facilities, receiving care in these facilities was associated with a higher incidence of catastrophic costs. Higher costs in private facilities is consistent with findings in Nigeria (60). This may be explained by extra medical costs at the private facilities which are not included in the NTP package made available to private providers. Continued support for subsidized care at private hospital is important to increase patient access to TB care. However, there is need to explore the extra costs in private facilities and how they hinder access to care.
Delayed treatment initiation is a significant determinant for catastrophic costs in this study. About 24% of participants with catastrophic costs waited longer than four weeks after onset of symptoms to start treatment. Severe symptoms, increased need for hospitalization, more expensive non-TB treatment or even more frequent visits to the facilities may partially explain why delayed treatment initiation was associated (61–63). Similar findings have been reported in other studies, associated with multiple visits to inappropriate providers; including formal providers that do not have the capacity to screen for TB or are untrained to recognize TB symptoms or informal providers such as traditional healers (16, 34, 64). A patient pathway analysis conducted in Kenya, showed that although majority of patients (84%) seek care within a formal health facility, only 43% of the facilities had the capacity to diagnose TB and another 45% could support TB treatment (22). This leads to the health system delay in starting treatment. On the other hand, patient factors such as economic status, beliefs and stigma also contribute to a delay in seeking care (65). There is a need to further explore contextualized barriers to seeking and receiving care as a preventive measure for catastrophic costs.
This study differed from existing literature regarding the association of catastrophic costs with sex (16, 42), HIV co-infection (16, 49, 60) and household size (15). In this study, the patient’s sex was not a significant determinant of catastrophic costs. This may be due to the measurement process: Household expenditure and wages to quantify indirect costs were not sensitive to patient’s sex. This observation, may also be attributed to the empowerment of women in Kenya regarding family spending and decision-making (66). A comparison of gender indices shows significant differences in women decision-making over the household spending and their health (67).
Although HIV is associated with treatment delay and X-ray testing, it was not a significant predictor of catastrophic costs. This is contrary to similar studies conducted in Uganda, Nigeria and India (16, 49, 60). In Kenya additional social support from the HIV programme is provided (22). In this study, there is a strong association between HIV coinfection and receiving nutritional support which may have alleviated the food costs and therefore resulting in less costs. These findings may also indicate positive integration of TB/HIV collaborative health service delivery care in Kenya. Finally, household size was not a predictor of catastrophic costs in this study. When DRTB patients were included however, household size was associated with catastrophic costs (15). Other studies show an association between household size and catastrophic health expenditure for health in Kenya (43). This may suggest that larger households have a different way of coping with TB costs such as selling assets, borrowing or seeking extra income (52).
This study took into account both direct and indirect costs, recognizing that time spent seeking care contributes significantly to the burden of TB Costs (7). The indirect costs for this study were calculated using the Human Capital approach due to the low level of formal employment. Although this approach captures all time off work due to the illness and care seeking, it does not take into account household mitigation efforts to compensate for lost income. This may have caused an over-estimation of the productivity losses.
For the denominator, the study used the non-food consumption expenditure as a proxy for Household income. This approach provides a better estimate for permanent income in LMICs where the rate of formal employment is low (27, 28). Asset-based wealth was not used since there is a poor correlation with permanent income and tends to overestimates the wealth status of the poor (28, 68).
The 20% threshold defined by WHO was used to define catastrophic costs. This threshold may underestimate the burden of catastrophic costs in Kenya based on contextual factors such as the level of poverty and ongoing social protection interventions. However, using the 20% threshold ensured comparability with other countries. The study incorporated a sensitivity analysis at 10% and 40% thresholds to check compatibility and ensure reliability of the results.
The patient survey enrolment was facility-based, therefore excluding TB patients who did not seek care at facilities or who may have dropped out of the system prior to treatment. This may lead to late presentation and severe disease and at a higher risk of incurring catastrophic costs when they present for TB care. This study did not take these patients and their determinants into account. The Kenya national TB prevalence survey showed that male patients aged 25–34 and 65 years and above delayed seeking care even when symptomatic (21). Additionally, since costs are a barrier to seeking care, it could have excluded the very poor who do not make it to the health facilities.
The study findings can be generalized to DSTB patients in Kenya. Cluster sampling was used in the original survey, taking into account the regional distribution of patients in 2016 and to counter coverage bias. The participants demographic and socio- economic characteristics is representative of the various profiles of DSTB patients in Kenya.
This study looked at predictors of OOP costs borne by patients. However, it would be interesting to explore household coping mechanisms such as selling assets and how these affect the identified predictors of catastrophic costs. Documenting intangible costs such as social consequences, stigma and to value quality of life losses is another opportunity for research.