Is distance associated with tuberculosis treatment outcomes? A retrospective cohort study in Kampala, Uganda

Although tuberculosis (TB) is both preventable and treatable, it is the leading cause of death due to a single pathogen worldwide [1]. One challenge in TB control is maintaining adherence to a minimum of six months of treatment. The World Health Organization estimates that 82% of patients worldwide who start treatment for TB experience treatment success (defined as treatment completion or cure); this percentage has not improved substantively in the past decade [1]. People with restricted access to health care may not be able to initiate and complete TB treatment as recommended. Risk factors for unfavorable treatment outcomes include demographic, clinical, and health systems characteristics [2‐4].

Geographic barriers to care, including physical distance to a health facility, may contribute to poor treatment outcomes. Distance from home to health facility has been associated with decreased access to a wide range of health services and outcomes, including poor HIV treatment clinic attendance [5] and antiretroviral adherence [6], lower likelihood of facility-based childbirth [7], and maternal [8] and child mortality [9]. Geographic barriers to care have been linked to delays [6, 10], loss-to follow up [11], and lack of adherence during the TB diagnostic evaluation and treatment processes [10]. Whether these associations translate into worse treatment outcomes remains uncertain. As the effect of geographic barriers has primarily been noted in rural areas where patients likely have limited options as to where they seek care and even the closest health care facilities may require more than an hour of travel, we aimed to understand the effect of these barriers on TB treatment outcomes in the context of a densely populated, urban setting where there are many TB treatment facilities available and patients may choose to seek care at facilities other than the ones closest to them.

Understanding links between geographic barriers to care and TB treatment outcomes may help identify a population at risk for unfavorable treatment outcomes that could be targeted with interventions to reduce barriers to care and improve outcomes. We therefore sought to characterize the association of distance from home to health facility and TB treatment outcomes in six public and private health facilities in Makindye division, Kampala district, Uganda.

This analysis of 1774 patients treated for TB across six urban clinics in the Makindye division of Kampala, Uganda, was suggestive of a protective association between longer distance from home to chosen treatment facility and composite unfavorable treatment outcomes. Facility notification rates for the included treatment facilities were high in parishes nearest to the facilities but were also high for some parishes far from the facilities. Nevertheless, despite the high density of TB treatment facilities in Kampala, 66% of patients starting TB treatment in these six facilities lived more than ≥2 km from the treating facilities (Table 1); compared to those who lived within 2 km of the facility, those living more remotely were 42% more likely to die but 43% less likely to be lost to follow-up.

Most patients in our study setting live within 2 km of multiple facilities and therefore can choose where they want to receive TB care. Patients may choose to seek care at a facility further away due to stigma against TB and a desire to hide their TB status [15‐17], convenience due to work or other travel [18], or perception of better care, particularly at private facilities [18]. This dynamic may explain the differences seen when considering death versus loss to follow up as an outcome. Death during TB treatment in this setting (where multidrug resistance is uncommon) likely reflects a patient’s severity of illness when diagnosed, whereas loss to follow-up may more closely reflect patient motivation and health system investment. Thus, patients who choose to travel more than 2 km to be treated may be those who experience other barriers to seeking care (e.g., stigma, job-related time limitations, unease with the healthcare system) which can cause delays in diagnosis and treatment. Such delays are associated with increased disease severity [19] and higher corresponding mortality rates [20‐22]. However, once treatment is initiated, these patients who are sicker and willing to travel longer distances may be more motivated to adhere to treatment, thereby reducing losses to follow-up. These findings illustrate how important distinctions between these two outcomes may be obscured when considering unfavorable treatment outcome as a composite measure.

Our study fills an important gap in knowledge regarding barriers to care and TB treatment outcomes. Prior studies have had mixed results regarding the effect of distance on delays in TB diagnosis and initiation of TB treatment [2‐4]. Our study suggests that, once treatment is initiated, distance is not associated with overall unfavorable treatment outcomes. Other studies have highlighted economic, socio-cultural, and health system barriers to care in high-burden settings as access-related risk factors for poor treatment outcomes [23]; the current research suggests that geographic distance to treatment facility may not be a strong measure of access to care, particularly in the urban sub-Saharan African setting. Additionally, our finding that travel distance using the shortest available route does not change our results compared to using Euclidean distance is in contrast with other research [24]. This may reflect the high population density and informal road network in our setting, such that travel paths are generally direct and the differences between Euclidean and travel distances are small, particularly if walking or using boda bodas (motorbike taxis) for transport.

This analysis does have some key limitations, largely due to the limited data available in facility TB registers. For example, these registers do not contain data on precise address of residence, thus limiting our measurement of distance to that of the parish centroid. Nevertheless, on average, participants will live within 500 m of the parish centroid, making major bias at the scale of our distance categories less likely. Additionally, while Euclidean distance does not directly capture the distance traveled to seek care, our assessment of travel distance yielded comparable results. Due to the limited data available in the TB registers, we are unable to assess the contribution of broader barriers to health care access, including economic, socio-cultural, and health system barriers. These factors may overlap or interact with geographic barriers. Additionally, we could not assess patients’ reasons for choosing particular facilities; further qualitative research could help to elucidate these motivations. Our study includes patients attending facilities in a densely crowded urban area, and our findings may not generalize to other settings (e.g., rural areas) where facilities are further apart and patients have fewer treatment options. While we do not have complete capture of any geographic region (e.g., people living in Kisugu and Wabigalo parishes) due to our sampling frame based on health facilities, we do have full capture of every patient seeking care at these facilities. Our final models excluded more than 20% of TB cases seen at these facilities due to missing data on either residence or treatment outcome; while our sensitivity analysis showed no major effect of excluding those missing treatment outcomes, we may have selection bias if those included in our analysis are not representative of those missing residential information in regards to the association of distance on treatment outcomes. Finally, since we only considered patients enrolled in care, we could not assess the role of geographic barriers in limiting initial access to care.

Distance from home residence to TB treatment facility was not associated with overall unfavorable treatment outcomes in this urban Ugandan population, but was associated with increased risk of death and decreased risk of loss to follow up. These findings suggest that those who seek care further from home may do so at a more advanced disease state, but once enrolled they may be more likely to remain in treatment. This is important for TB control programs to consider, as they may need to invest in programs that decrease delays in diagnosis among those living further away and improving treatment adherence among those who live closer to facilities. A detailed understanding of the patient population and the varying experiences of that population is key to appropriately focusing resources to improve TB treatment outcomes.