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Abstract P4-07-46: The Out-of-Pocket Cost of Breast Cancer Care in Nigeria: A Prospective Analysis

2023· article· en· W4322774790 on OpenAlexaff
Funmilola Wuraola, Chloe Blackman, Israel Adeyemi Owoade, Adeoluwa Oluwaseyi Adeleye, T. Peter Kingham, Olusegun Isaac Alatise, Gregory Knapp

Bibliographic record

VenueCancer Research · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Financial Impacts of Cancer
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineBreast cancerContext (archaeology)Health carePaymentCancerFamily medicineFinanceEconomic growthBusiness

Abstract

fetched live from OpenAlex

Abstract Introduction A major barrier to timely breast cancer diagnosis and care in Nigeria is attributable to the out-of-pocket cost of accessing healthcare services, despite the presence of a National Health Insurance Scheme (NHIS). Excessive out-of-pocket payments are often associated with a catastrophic health care expenditure (CHE). Despite the rising incidence of breast cancer in Nigeria, there is a paucity of economic data on the cost of care and the impact healthcare expenditure may have on a household. This study provides a comprehensive, prospective analysis of out-of-pocket spending for breast cancer care at a single tertiary care institution in South West Nigeria. Methods Consecutive patients undergoing curative intent surgery for a new diagnosis of breast cancer at Obafemi Awolowo University Teaching Hospital (OAUTH) between August 2019-April 2022 were approached for enrolment. A novel, context specific questionnaire was developed for this study and administered by trained personnel. The questionnaire was delivered to patients and caregivers during hospital admission and again during six-month follow-up. Participants were asked to estimate monthly household income and expenditures. Out-of-pocket direct and indirect expenses for breast cancer diagnosis and care were elicited. Where feasible, hospital accounting records and individual receipts were used to minimize recall bias. Sequelae of the out-of-pocket costs were also elicited, such as the use of debt financing and important forgone expenditures, such as childhood education. Capacity-to-pay was calculated for each household from the provided data as the sum of annual non-food expenditures. A CHE was defined as an aggregate healthcare expenditure that exceeded 40% of a household’s capacity-to-pay. All monetary figures were collected in the local currency (Naira) and converted to USD using the Nigerian Central Bank conversion rate of 415.83N to 1USD. Research ethics board approval was obtained for this study from OAUTH. Results Data were collected from 57 eligible patients with a mean age of 49.8 years (SD 12). The median household size was five (range 1-10) and the majority (75.4%) had completed at least secondary education. Seventy four percent (73.6%) of patients had ≥ Stage III disease at presentation and 89.5% received systemic chemotherapy. Only seven percent (4/received adjuvant radiotherapy. The mean annual capacity-to-pay for the cohort was $2,840.8 ($2,913.6). The mean cost of care, including direct and indirect expenditure was $3,379.7 (SD $3032.2). Excluding indirect costs, such as the cost of travel and self-reported lost income, the mean cost of direct expenditures associated with diagnosis and treatment was $1,705.3 (SD $1,236.6). Out of the 57 patients enrolled in the study 52 (91.2%) experienced a CHE as a result of their breast cancer treatment. As a result, 56% of households had to borrow money and seven percent withdrew children from school. Sixty-three percent of patients had no form of health insurance. Conclusions Over 90% of breast cancer patients at a tertiary care facility in Nigeria experience a CHE as a result of out-of-pocket costs associated with accessing care. This limits access to costly evidence-based adjuncts (i.e. radiotherapy) and has a negative impact on the wellbeing of the broader household. There is a need for national and global initiatives to ensure financial protection from the cost of breast cancer care. Citation Format: Funmilola Wuraola, Chloe Blackman, Israel Adeyemi Owoade, Adeoluwa Oluwaseyi Adeleye, Peter Kingham, Olusegun Alatise, Gregory Knapp. The Out-of-Pocket Cost of Breast Cancer Care in Nigeria: A Prospective Analysis [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P4-07-46.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.085
GPT teacher head0.373
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2023
Admission routes1
Has abstractyes

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