Lessons from the Brazilian radiotherapy expansion plan: A project database study
Notice bibliographique
Résumé
Background: The Radiotherapy Expansion Plan for Brazil's Unified Health System (PER-SUS) was an innovative program designed by the Ministry of Health in 2012 to provide improvements to the challenging problem of access to radiotherapy in the country. This study sought to analyze the execution and implementation of installations proposed by PER-SUS, and their capacity to address the problems of radiotherapy access in Brazil. Methods: From the first release (February 2015) until October 2021, all PER-SUS monthly progress reports were retrospectively analyzed. The beneficiary institutions, project location, project status, project type, dates of the progress on the stages, and reasons for cancellations or possible justifications for changing the status were collected. Brazilian geographic data, health care demands, and cancer incidences were correlated. Finally, we performed an Ishikawa diagram and 5W3H methodology, aiming to better understand the findings and to yield possible ways to improve the access to radiotherapy. Findings: After ten years, the PER-SUS project delivered nearly 50% of the planned implementation of radiotherapy equipment. There was a 17% growth in the national number of linear accelerators (LINACS) with PER-SUS, against a 32% increase in cancer incidence in Brazil in the same period. The following points were identified: a high rate of beneficiary exclusions reflecting inappropriate selection or inadequate planning; delays in execution related to bureaucratic obstacles and underestimation of the requirements (logistics/people); early closing of the equipment factory as a result of lack of project prioritization by the Government. Interpretation: Only about 50% of PER-SUS are being carried out. However, delays and exclusions of beneficiaries were observed. The dimension of the need for radiotherapy care in Brazil is greater than considered, and might not be fully attended by PER-SUS. Geographic, epidemiological, logistical, and economic variables could be reevaluated to allow better strategic planning and improvement proposals. PER-SUS could be optimized for the next decade, by involving all stakeholders' participation, alignment, and engagement. In the future, the States and regions with a higher LINAC shortage should be prioritized to improve RT access across the country. Considering the data and the initial project deadline, PER-SUS did not achieve the pre-established goals specified by the Brazilian Government. Funding: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».