Perfil de Estudos da Rede Brasileira de Avaliação de  Tecnologia em Saúde (Rebrats) de 2004 a 2015

Elias, Flávia Tavares Silva; Morais, Rafael Dias Gomes de; Silva, Erica Tatiane da; Pereira, Daniella Cristina Rodrigues

doi:10.51723/ccs.v27i01.88

Cited by 2 publications

(3 citation statements)

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“…The result of this study showed that some characteristics of the reports (type of technology and the requester’s profile) predict the incorporation, and are not directly related to the criteria settled down. Previous studies that characterized the CONITEC by other methods, in particular descriptive analysis, showed a similar profile, with the drug technology being the most evaluated and approved, and the “government” claimant having the highest number of approved technologies (4;9;39).…”

Section: Discussion and Implementation Considerationmentioning

confidence: 63%

“…Over the years, several HTA agencies have been created in different countries with the purpose of improving decision-making regarding investments and disinvestments in health. These HTA processes have been the object of several studies to compare differences and similarities between them (e.g., criteria, health priorities, challenges or limitations, among other aspects) (2)(3)(4). Heupink et al (5) highlight that the HTA process requires time and resources.…”

Section: Introductionmentioning

confidence: 99%

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Application of natural language processing to predict final recommendation of Brazilian health technology assessment reports

Cardoso,

Machado-Rugolo,

Thabane

et al. 2024

Int J Technol Assess Health Care

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Introduction Health technology assessment (HTA) plays a vital role in healthcare decision-making globally, necessitating the identification of key factors impacting evaluation outcomes due to the significant workload faced by HTA agencies. Objectives The aim of this study was to predict the approval status of evaluations conducted by the Brazilian Committee for Health Technology Incorporation (CONITEC) using natural language processing (NLP). Methods Data encompassing CONITEC’s official report summaries from 2012 to 2022. Textual data was tokenized for NLP analysis. Least Absolute Shrinkage and Selection Operator, logistic regression, support vector machine, random forest, neural network, and extreme gradient boosting (XGBoost), were evaluated for accuracy, area under the receiver operating characteristic curve (ROC AUC) score, precision, and recall. Cluster analysis using the k-modes algorithm categorized entries into two clusters (approved, rejected). Results The neural network model exhibited the highest accuracy metrics (precision at 0.815, accuracy at 0.769, ROC AUC at 0.871, and recall at 0.746), followed by XGBoost model. The lexical analysis uncovered linguistic markers, like references to international HTA agencies’ experiences and government as demandant, potentially influencing CONITEC’s decisions. Cluster and XGBoost analyses emphasized that approved evaluations mainly concerned drug assessments, often government-initiated, while non-approved ones frequently evaluated drugs, with the industry as the requester. Conclusions NLP model can predict health technology incorporation outcomes, opening avenues for future research using HTA reports from other agencies. This model has the potential to enhance HTA system efficiency by offering initial insights and decision-making criteria, thereby benefiting healthcare experts.

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Section: Discussion and Implementation Considerationmentioning

confidence: 63%

Section: Introductionmentioning

confidence: 99%

Application of natural language processing to predict final recommendation of Brazilian health technology assessment reports

Cardoso,

Machado-Rugolo,

Thabane

et al. 2024

Int J Technol Assess Health Care

View full text Add to dashboard Cite

show abstract

“…In addition, 15 studies offered a comprehensive assessment of HTA in Brazil. Specifically, two studies were based on surveys with Brazilian experts about the HTA implementation in Brazil [19,31], five studies were opinion pieces presenting a critical appraisal on the current HTA institutions in Brazil [8,10,24,25,36], seven were reviews of the Brazilian HTA reports [15,16,18,20,26,27,38], and one study was a literature review addressing the use of real-world data on Latin America [22].…”

Section: Development Of the Questionnairementioning

confidence: 99%

Expectations for the Development of Health Technology Assessment in Brazil

Galendi

Caramori

Lemmen

et al. 2021

IJERPH

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The implementation of health technology assessment (HTA) in emerging countries depends on the characteristics of the health care system and the needs of public health care. The objective of this survey was to investigate experts’ expectations for the development of HTA in Brazil and to derive measures to strengthen the impact of HTA in Brazil on health care decisions. Based on a scoping literature review, a questionnaire was developed proposing eight theses for seven domains of HTA: (i) capacity building, (ii) public involvement, (iii) role of cost-effectiveness analysis (CEA), (iv) institutional framework, (v) scope of HTA studies, (vi) methodology of HTA, and (vii) HTA as the basis for jurisdiction. Thirty experts responded in full to the survey and agreed to five of the eight theses proposed. Experts suggested several measures to promote HTA within the scope of each domain, thus addressing capacity building related to HTA, availability, and reliability of population data, and legal endowment of the HTA system. Finally, HTA processes in Brazil should also address public health issues (e.g., appraisal of interventions directed at chronic diseases).

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Perfil de Estudos da Rede Brasileira de Avaliação de Tecnologia em Saúde (Rebrats) de 2004 a 2015

Cited by 2 publications

References 0 publications

Application of natural language processing to predict final recommendation of Brazilian health technology assessment reports

Application of natural language processing to predict final recommendation of Brazilian health technology assessment reports

Expectations for the Development of Health Technology Assessment in Brazil

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