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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
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Filename: controllers/Detail.php
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Filename: models/Detail_model.php
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Filename: controllers/Detail.php
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File: /var/www/html/index.php
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Filename: controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
Line: 260
Function: _error_handler
File: /var/www/html/index.php
Line: 316
Function: require_once
Severity: Warning
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Filename: controllers/Detail.php
Line Number: 260
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Objective: to evaluate the attribute longitudinality in different models of assistance in Primary Health Care and observe its association with demographic, socioeconomic and health care characteristics.
Method: a cross-sectional study, carried out in 2015 with 1076 adult users of primary care services in the 32 cities of the 4th Regional Health Care Core of Rio Grande do Sul State. The Primary Care Assessment Tool was used with definition of low (<6.6) or high (≥6.6) score for longitudinality. The association with independent variables was observed through the Poisson regression.
Results: the attribute was better assessed in the Family Health Strategy and associate with age, housing health region and care model.
Conclusion: the study points out the Family Health Strategy as a promoter of longitudinal care, and so, it suggests the expansion of this assistance model coverage for quality improvement in health care.
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http://dx.doi.org/10.1590/0034-7167-2017-0014 | DOI Listing |
J Med Internet Res
December 2024
Else Kröner Fresenius Center for Digital Health, Dresden University of Technology, Dresden, Germany.
Background: The integration of connected medical devices (MDs) into health care brings benefits but also introduces new, often challenging-to-assess risks related to cybersecurity, which have the potential to harm patients. Current regulations in the European Union and the United States mandate the consideration of these risks in the benefit-risk analysis (BRA) required for MD approval. This important step in the approval process weighs all the defined benefits of a device with its anticipated risks to ensure that the product provides a positive argument for use.
View Article and Find Full Text PDFJ Med Internet Res
December 2024
College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.
Background: Wearable technologies have become increasingly prominent in health care. However, intricate machine learning and deep learning algorithms often lead to the development of "black box" models, which lack transparency and comprehensibility for medical professionals and end users. In this context, the integration of explainable artificial intelligence (XAI) has emerged as a crucial solution.
View Article and Find Full Text PDFIntern Med J
December 2024
Royal Adelaide Hospital, Central Adelaide Local Health Network, Adelaide, South Australia, Australia.
This review of telehealth research describes the landscape of Australian digital health and telehealth research from 1999 to 2022, focusing on outlining past, present and future trends. A scoping review was conducted using the Joanna Briggs Institute methodology and PRISMA extension for scoping reviews framework, which identified 495 primary research studies of digital or telehealth interventions aimed at improving health outcomes. Data were charted according to technological modality, health focus, professional representation, participant location, year and size.
View Article and Find Full Text PDFInt J Clin Pharm
December 2024
Monash Addiction Research Centre, Eastern Health Clinical School, Monash University, Level 2 Building D, 47-49 Moorooduc Highway, Frankston, Melbourne, VIC, 3199, Australia.
Background: Opioid medications are widely prescribed for acute, chronic and cancer pain. In Australia, opioid prescribing rates remain high.
Aim: This study aimed to document patterns of primary care opioid prescribing from 2017 to 2022 by demographic characteristics in Victoria, Australia.
Sci Eng Ethics
December 2024
Institute of History and Ethics in Medicine, Department of Preclinical Medicine, TUM School of Medicine and Health, Technical University of Munich, Ismaninger Straße 22, 81675, Munich, Germany.
Integrating artificial intelligence (AI) into critical domains such as healthcare holds immense promise. Nevertheless, significant challenges must be addressed to avoid harm, promote the well-being of individuals and societies, and ensure ethically sound and socially just technology development. Innovative approaches like Embedded Ethics, which refers to integrating ethics and social science into technology development based on interdisciplinary collaboration, are emerging to address issues of bias, transparency, misrepresentation, and more.
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