Objetive: The Health Situation Analysis (ASIS in Spanish) is a methodology that has been implemented recently in Colombia. This study aims at understanding the experience of building, disseminating and using ASIS for decision-making in some territorial entities.
Methods: Semistructured interviews were applied to officials of the departmental health entities. The information was analyzed according to a set of categories previously established.
Results: The territorial entities implement ASIS by incorporating the Social Determinants of Health approach; however, the technical, economic and human capacities for the elaboration of this type of analysis are not equitable. Intersectoral and social participation is still weak and the results do not guide the decision making at territorial level yet.
Conclusions: The ASIS methodology seeks to position itself as one of the official mechanisms to generate evidence that guides health policy and decision making at national, regional and local levels. There are economic, institutional and political challenges for its consolidation as a useful strategy in health planning. ASIS is a methodology of great relevance for the territorial entities and its implementation should be further strengthened.
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http://dx.doi.org/10.15446/rsap.v19n3.62576 | DOI Listing |
JBJS Essent Surg Tech
May 2024
Radboud University Medical Center, Nijmegen, The Netherlands.
Background: This video article describes the use of bone-anchored prostheses for patients with transtibial amputations, most often resulting from trauma, infection, or dysvascular disease. Large studies have shown that about half of all patients with a socket-suspended artificial limb experience limited mobility and limited prosthesis use because of socket-related problems. These problems occur at the socket-residual limb interface as a result of a painful and unstable connection, leading to an asymmetrical gait and subsequent pelvic and back pain.
View Article and Find Full Text PDFBMJ Oncol
February 2024
Translational Radiobiology, Department of Radiation Oncology, Universitätsklinikum Erlangen & Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
Objective: Fast progression (FP) represents a desperate situation for advanced non-small cell lung cancer (NSCLC) patients undergoing immune checkpoint inhibitor therapy. We aimed to develop a predictive framework based on machine learning (ML) methods to identify FP in advanced NSCLC patients using blood test biomarkers.
Methods And Analysis: We extracted data of 1546 atezolizumab-treated patients from four multicentre clinical trials.
Toxicol Rep
June 2025
Department of Environmental Engineering, Graduate School of Engineering, Kyoto University, Kyoto 606-8501, Japan.
The Ijen crater volcano (ICV) is one of the active volcanoes with unique environmental conditions; it is the largest lake in the world with the most extreme acidity and a blue fire phenomenon and releases toxic volcanic gases, including dangerous sulfur dioxide (SO₂). It has an impact on the environment and ecosystem. This research aimed to investigate the blue fire phenomena and toxic gas SO and characterize the environmental conditions and health effects of the ICV.
View Article and Find Full Text PDFSex Offending
February 2024
The Lucy Faithfull Foundation, Epsom, United Kingdom.
The prevalence of online child sexual grooming offenses has been on the rise, posing significant risks to children. Child sexual grooming involves sexual communication with minors. This study aims to understand motivations and pathways of individuals who have engaged in online grooming behaviour, as well as propose effective prevention and intervention strategies.
View Article and Find Full Text PDFStat Methods Med Res
January 2025
Department of Statistics and Institute of Data Science, National Cheng Kung University, Tainan, Taiwan.
The article proposes a robust approach to jointly modeling multiple repeated clinical measures with intricate features. More specifically, we aim to expand the scope of the multivariate linear mixed model by using the multivariate contaminated normal distribution. The proposed model, called the multivariate contaminated normal linear mixed model with censored and missing responses (MCNLMM-CM), is designed to handle minor outliers effectively, while simultaneously accommodating censored measurements and intermittent missing responses.
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