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Record W4389487955 · doi:10.1186/s12962-023-00502-3

Cost analysis of the management of end-stage renal disease patients in Abuja, Nigeria

2023· article· en· W4389487955 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCost Effectiveness and Resource Allocation · 2023
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineEnd stage renal diseasePublic healthHealth administrationEmergency medicineHealth careHealth services researchCross-sectional studyDescriptive statisticsHealth economicsHemodialysisIndirect costsEnvironmental healthInternal medicineNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Although the treatment for end-stage renal disease (ESRD) under Nigeria's National Health Insurance Authority is haemodialysis (HD), the cost of managing ESRD is understudied in Nigeria. Therefore, this study estimated the provider and patient direct costs of haemodialysis and managing ESRD in Abuja, Nigeria. METHOD: The study was a cross-sectional survey from both healthcare provider and consumer perspectives. We collected data from public and private tertiary hospitals (n = 6) and ESRD patients (n = 230) receiving haemodialysis in the selected hospitals. We estimated the direct providers' costs using fixed and variable costs. Patients' direct costs included drugs, laboratory services, transportation, feeding, and comorbidities. Additionally, data on the sociodemographic and clinical characteristics of patients were collected. The costs were summarized in descriptive statistics using means and percentages. A generalized linear model (gamma with log link) was used to predict the patient characteristics associated with patients' cost of haemodialysis. RESULTS: The mean direct cost of haemodialysis was $152.20 per session (providers: $123.69; and patients: $28.51) and $23,742.96 annually (providers: $19,295.64; and patients: $4,447.32). Additionally, patients spent an average of $2,968.23 managing comorbidities. The drivers of providers' haemodialysis costs were personnel and supplies. Residing in other towns (HD:β = 0.55, ρ = 0.001; ESRD:β = 0.59, ρ = 0.004), lacking health insurance (HD:β = 0.24, ρ = 0.038), attending private health facility (HD:β = 0.46, ρ < 0.001; ESRD: β = 0.75, ρ < 0.001), and greater than six haemodialysis sessions per month (HD:β = 0.79, ρ < 0.001; ESRD: β = 0.99, ρ < 0.001) significantly increased the patient's out-of-pocket spending on haemodialysis and ESRD. CONCLUSION: The costs of haemodialysis and managing ESRD patients are high. Providing public subsidies for dialysis and expanding social health insurance coverage for ESRD patients might reduce the costs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.072
Threshold uncertainty score0.275

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.283
Teacher spread0.267 · 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