Technical Inefficiency of District Hospitals in Côte d'Ivoire: Measurement, Causes and Consequences
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.
Bibliographic record
Abstract
The aim of this study is to estimate the level of inefficiency and to identify the causes and consequences of Cote d’Ivoire public hospitals inefficiency. To that effect, we are using the non-parametric Data Envelopment Analysis (DEA) and the double Bootstrap procedures to analyze the data. The analysis of data from the Ministry of Health in Cote d’Ivoire reveals that districts’ hospitals are not technically efficient. This situation has a negative impact on hospital output in the country. Thus, the health system is impacted by the inefficiency of districts’ hospitals in accommodating the demand of health care. That technical inefficiency remains dependent on environmental factors that constitute an impediment for some of the levers ((ratio of doctors per capita, malnutrition, average length of stay, geographical access, and correlation Tuberculosis / HIV) and others (number of doctors in medical staff) able to increase hospitals technical efficiency. The outcomes of this study reveal two main stakes: firstly, the need for improvement of hospitals productive efficiency and secondly, the need for a better planning and utilization of the resources allocated to the health sector. Providing adequate responses to these concerns is extremely important for the country’s ambition to establish a universal health insurance system and improve the quality of health care services.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it