Community and health systems factors contributing to delayed tuberculosis detection in an urban setting: situating software and hardware bottlenecks in local health systems

Abstract

Background Despite several global interventions, tuberculosis (TB) remains a leading cause of death affecting millions of people globally. Many TB patients either have no access to quality care or go undetected by national health systems. Several multilevel factors account for under-detection of TB cases. This study sought to explore community and health systems software and hardware factors contributing to delayed TB detection in Lusaka District, Zambia. Methods This was an exploratory qualitative case study that adopted a software and hardware lens of conceptualizing health systems. Data were collected from across three sites – urban and peri-urban areas: Chongwe, Kafue, and Lusaka – within Lusaka Province, Zambia. Sixteen (n = 16) key informant interviews were conducted with the TB corner nurses, community TB treatment supporters and TB program managers in the sampled facilities. Six (n = 6) focus group discussions were conducted with the community members. Data were analyzed using thematic analysis approach. Results In terms of community health system software elements, the study identified inadequate TB knowledge and awareness, poor health-seeking behavior, and social stigma against TB patients in urban areas as factors contributing to delays. Meanwhile, hardware elements within the community health system, such as unbalanced schedules, and lack of training for TB treatment supporters, also play a role in prolonging TB detection. Within the formal health system, negative attitudes of health providers towards TB patients and demotivation of TB staff were identified as software elements contributing to delays in TB detection. Additionally, hardware elements leading to delays in the formal health system included high diagnostics and transportation costs, outdated diagnostics in primary care facilities, and slow referral mechanisms in urban settings. Conclusion This study moves beyond isolating individual factors contributing to delay in TB detection to appreciating the role of the complex interactions between community and health systems software and hardware. Our findings serve as a departure point for TB program managers to consider system strategies aimed at addressing the different pathways to TB care, thereby mitigating delays in early detection at both community and health systems levels.