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

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.

Exploring the COVID-19 Pandemic's Impact on the Health Technology Assessment Process of the National Commission for the Incorporation of Technologies Into the Brazilian Health System.

OBJECTIVES: This study aimed to evaluate the impact of the COVID-19 pandemic on Brazilian health technology assessment processes based on public reports from the National Committee for Health Technology Incorporation (CONITEC). METHODS: This descriptive study analyzed CONITEC's official reports on Brazil available on its website between 2018 and 2021 that aimed to propose recommendations for technologies to be incorporated into its public healthcare system. We used descriptive statistics covering the number of technologies and number of reports about drugs per year, objective, type of technology, demanding sector, and outcome before 2018 to 2019 and during the COVID-19 pandemic (2020-2021). Furthermore, we used logistic regression to explore any association between the final decision labeled as "incorporated" and the emergence of the COVID-19 pandemic. RESULTS: A total of 278 reports were analyzed. Approximately 85% (136 of 278), 79% (220 of 278), and 45% of the reports (125 of 278) were about drugs, for incorporation, and requested by the government, respectively. Moreover, 74 of 130 (57%) and 56 of 148 decisions (38%) were "incorporated" before and during the pandemic, respectively. No significant association was noted between incorporated decisions and the arrival of the COVID-19 pandemic for all technologies (odds ratio 1.43; 95% CI 0.84-2.46; P = .192) and for drugs (odds ratio 1.43; 95% confidence interval 0.81-2.53; P = .223) while adjusting for the type of technology and demandant. CONCLUSIONS: The COVID-19 pandemic has brought many challenges, but it does not seem to have had a significant impact on the health technology assessment approval decisions of CONITEC in Brazil.

Risk and protective factors for suicide: a populational case-control study, Brazil, 2019.

OBJETIVE: To estimate risk and protection factors associated with suicide in Campinas, Brazil, in 2019. METHODS: This is a populational case-control study analyzing 83 cases of suicide that occurred in 2019 in Campinas, a Brazilian city with about 1.2 million inhabitants. Controls were composed of 716 inhabitants. An adjusted multiple logistic regression was used. Cases and controls were the dichotomous response variables. Sociodemographic and behavioral variables were the predictor variables. RESULTS: The categories which presented higher risk of suicide were: males [OR = 5.26 (p < 0.001)]; people aged 10-29 years [OR = 5.88 (p = 0.002)]; individuals without paid work [OR = 3.06 (p = 0.013)]; individuals presenting problematic use of alcohol [OR = 33.12 (p < 0.001)] and cocaine [14.59 (p < 0.007)]; and people with disabilities [OR = 3.72 (p < 0.001)]. Moreover, the perception of fear was associated with reduced suicide risk [OR = 0.19 (p = 0.015)]. Higher district HDI levels also showed a 4% decrease in risk for each 0.01 increase in district HDI levels [OR = 0.02 (p = 0.008)]. CONCLUSIONS: This study evidenced the association between sociodemographic and behavioral variables and suicide. It also emphasized the complexity in the dynamics between personal, social, and economic factors to this external cause of death.

Risk and protective factors for suicide: a populational case-control study, Brazil, 2019

ABSTRACT OBJETIVE To estimate risk and protection factors associated with suicide in Campinas, Brazil, in 2019. METHODS This is a populational case-control study analyzing 83 cases of suicide that occurred in 2019 in Campinas, a Brazilian city with about 1.2 million inhabitants. Controls were composed of 716 inhabitants. An adjusted multiple logistic regression was used. Cases and controls were the dichotomous response variables. Sociodemographic and behavioral variables were the predictor variables. RESULTS The categories which presented higher risk of suicide were: males [OR = 5.26 (p < 0.001)]; people aged 10-29 years [OR = 5.88 (p = 0.002)]; individuals without paid work [OR = 3.06 (p = 0.013)]; individuals presenting problematic use of alcohol [OR = 33.12 (p < 0.001)] and cocaine [14.59 (p < 0.007)]; and people with disabilities [OR = 3.72 (p < 0.001)]. Moreover, the perception of fear was associated with reduced suicide risk [OR = 0.19 (p = 0.015)]. Higher district HDI levels also showed a 4% decrease in risk for each 0.01 increase in district HDI levels [OR = 0.02 (p = 0.008)]. CONCLUSIONS This study evidenced the association between sociodemographic and behavioral variables and suicide. It also emphasized the complexity in the dynamics between personal, social, and economic factors to this external cause of death.