Abstract

BackgroundThis article investigates the extent and sources of late diagnosis of cancer in Tanzania, demonstrating how delayed diagnosis was patterned by inequities rooted in patients’ socio-economic background and by health system responses. It provides evidence to guide equity-focused policies to accelerate cancer diagnosis.MethodsTanzanian cancer patients (62) were interviewed in 2019. Using a structured questionnaire, respondents were encouraged to recount their pathways from first symptoms to diagnosis, treatment, and in some cases check-ups as survivors. Patients described their recalled sequence of events and actions, including dates, experiences and expenditures at each event. Socio-demographic data were also collected, alongside patients’ perspectives on their experience. Analysis employed descriptive statistics and qualitative thematic analysis.ResultsMedian delay, between first symptoms that were later identified as indicating cancer and a cancer diagnosis, was almost 1 year (358 days). Delays were strongly patterned by socio-economic disadvantage: those with low education, low income and non-professional occupations experienced longer delays before diagnosis. Health system experiences contributed to these socially inequitable delays. Many patients had moved around the health system extensively, mainly through self-referral as symptoms worsened. This “churning” required out-of-pocket payments that imposed a severely regressive burden on these largely low-income patients. Causes of delay identified in patients’ narratives included slow recognition of symptoms by facilities, delays in diagnostic testing, delays while raising funds, and recourse to traditional healing often in response to health system barriers. Patients with higher incomes and holding health insurance that facilitated access to the private sector had moved more rapidly to diagnosis at lower out-of-pocket cost.ConclusionsLate diagnosis is a root cause, in Tanzania as in many low- and middle-income countries, of cancer treatment starting at advanced stages, undermining treatment efficacy and survival rates. While Tanzania’s policy of free public sector cancer treatment has made it accessible to patients on low incomes and without insurance, reaching a diagnosis is shown to have been for these respondents slower and more expensive the greater their socio-economic disadvantage. Policy implications are drawn for moving towards greater social justice in access to cancer care.

Highlights

  • This article investigates the extent and sources of late diagnosis of cancer in Tanzania, demonstrating how delayed diagnosis was patterned by inequities rooted in patients’ socio-economic background and by health system responses

  • The analysis focuses on the patterning by socio-economic inequality

  • Descriptive statistical analysis demonstrates that the most disadvantaged patients in our data set generally faced the longest delays before diagnosis

Read more

Summary

Introduction

This article investigates the extent and sources of late diagnosis of cancer in Tanzania, demonstrating how delayed diagnosis was patterned by inequities rooted in patients’ socio-economic background and by health system responses. The analysis focuses on the patterning by socio-economic inequality. Makene et al BMC Health Services Research (2022) 22:189 of the time elapsed, pathway patterns and costs of reaching a cancer diagnosis for these respondents. The article documents the socially unjust, regressive impact of delay on the costs experienced by these respondents in their search for diagnosis. It identifies implications for interventions that could make cancer diagnosis more rapid and accessible, and less socially inequitable, contributing towards more equitable Universal Health Coverage (UHC). Access to cancer care in low-resource settings poses a major challenge for UHC. Current health expenditure per head was just USD 37 in 20181; of that, 24% was funded out-of-pocket, 1% from private insurance, 8% from social insurance (National Health Insurance Fund (NHIF)), 32% external funding, and 35% from domestic government expenditure [2]

Methods
Results
Discussion
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.