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BMC Medicine Dec 2023Sample self-collection for reproductive tract infection diagnosis has been found to offer greater convenience, privacy, autonomy, and expanded access to testing in... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Sample self-collection for reproductive tract infection diagnosis has been found to offer greater convenience, privacy, autonomy, and expanded access to testing in non-pregnant adults. This review aimed to determine whether sample self-collection is as accurate as provider-collection for detection of group B streptococcus colonisation in pregnancy and whether a strategy of self-collection compared to provider-collection might improve maternal and neonatal health outcomes.
METHODS
We searched CINAHL Plus, Medline, EMBASE, Maternity and Infant Care Database, Cochrane Central Register of Controlled Trials, and Cochrane Database of Systematic Reviews in June 2022. Eligible studies compared self-collected and provider-collected samples taken from the same participants or participants randomised to either self-collection or provider-collection for reproductive tract infection testing using the same test and testing method in pregnant individuals. We included trials and observational studies. Reviewers assessed risk of bias using the QUADAS-2 checklist and independently extracted data. Sensitivity and specificity for group B streptococcus colonisation of self-collected compared to provider-collected samples were pooled using a bivariate, random-effects, meta-analytic model. This review was registered with PROSPERO (CRD42023396573).
RESULTS
The search identified 5909 references, of which eleven diagnostic accuracy group B streptococcus studies were included (n = 3269 participants). No studies assessed the effects of self-collection in pregnancy on health outcomes. All studies had high or unclear risk of bias. Pooled sensitivities of self-collected samples for group B streptococcus detection were 82% (95% CI: 66-91%; I = 68.85%) in four trials (n = 1226) and 91% (95% CI: 83-96%; I = 37.38%) in seven non-randomised studies (n = 2043). Pooled specificities were 99% (95% CI: 98-99%; I = 12.08%) and 97% (95% CI: 94-99%; I = 72.50%), respectively.
CONCLUSIONS
Self-collected samples for group B streptococcus detection in pregnancy had high specificity compared to provider-collection, but lower sensitivity, particularly for included trials. Studies investigating the effect of self-collection on health outcomes, and further higher quality trials comparing accuracy of self-collection to provider-collection, are required.
Topics: Infant, Newborn; Adult; Pregnancy; Female; Humans; Reproductive Tract Infections; Streptococcus
PubMed: 38110910
DOI: 10.1186/s12916-023-03186-x -
Frontiers in Public Health 2023Services to treat problematic alcohol use (PAU) should be highly accessible to optimize treatment engagement. We conducted a scoping review to map characteristics of...
INTRODUCTION
Services to treat problematic alcohol use (PAU) should be highly accessible to optimize treatment engagement. We conducted a scoping review to map characteristics of services for the treatment of PAU that have been reported in the literature to be barriers to or facilitators of access to treatment from the perspective of individuals with PAU.
METHODS
A protocol was developed , registered, and published. We searched MEDLINE, Embase, the Cochrane Library, and additional grey literature sources from 2010 to April 2022 to identify primary qualitative research and surveys of adults with current or past PAU requiring treatment that were designed to identify modifiable characteristics of PAU treatment services (including psychosocial and pharmacologic interventions) that were perceived to be barriers to or facilitators of access to treatment. Studies of concurrent PAU and other substance use disorders were excluded. Study selection was performed by multiple review team members. Emergent barriers were coded and mapped to the accessibility dimensions of the Levesque framework of healthcare access, then descriptively summarized.
RESULTS
One-hundred-and-nine included studies reported an extensive array of unique service-level barriers that could act alone or together to prevent treatment accessibility. These included but were not limited to lack of an obvious entry point, complexity of the care pathway, high financial cost, unacceptably long wait times, lack of geographically accessible treatment, inconvenient appointment hours, poor cultural/demographic sensitivity, lack of anonymity/privacy, lack of services to treat concurrent PAU and mental health problems.
DISCUSSION
Barriers generally aligned with recent reviews of the substance use disorder literature. Ranking of barriers may be explored in a future discrete choice experiment of PAU service users. The rich qualitative findings of this review may support the design of new or modification of existing services for people with PAU to improve accessibility.
SYSTEMATIC REVIEW REGISTRATION
Open Science Framework doi: 10.17605/OSF.IO/S849R.
Topics: Adult; Humans; Substance-Related Disorders; Alcoholism; Health Services Accessibility
PubMed: 38106884
DOI: 10.3389/fpubh.2023.1296239 -
Urologic Oncology Mar 2024Recent progress in the realm of artificial intelligence has shown effectiveness in various industries, particularly within the healthcare sector. However, there are...
Recent progress in the realm of artificial intelligence has shown effectiveness in various industries, particularly within the healthcare sector. However, there are limited insights on existing studies regarding ethical, social, privacy, and technological aspects of AI in the health sector, which is the gap our study aims to fill. This study aimed to synthesize empirical studies on the challenges and opportunities of using AI by conducting a systematic review. We reviewed 33 articles published between 2015 and 2022 in the PubMed, IEEE Xplore, and Science Direct databases. The results show that artificial intelligence has the promise of improving health care and faces obstacles when implemented. Most of the reviewed studies indicated that the use of AI provides several opportunities, including teamwork and decision-making, technological advancement, diagnosis and patient monitoring, drug development, and virtual health assistance. However, the findings show that the use of AI in the health sector hinders multifaceted challenges, including ethical and privacy-related issues, lack of awareness, unreliability of technology, and professional liability. The findings highlight that artificial intelligence has the potential to transform healthcare and that addressing these challenges is crucial to fully utilize its potential.
Topics: Artificial Intelligence; Databases, Factual; Delivery of Health Care
PubMed: 38101991
DOI: 10.1016/j.urolonc.2023.11.019 -
Journal of Medical Internet Research Dec 2023Electronic health care databases are increasingly used for informing clinical decision-making. In long-term care, linking and accessing information on health care... (Review)
Review
Toward an Interdisciplinary Approach to Constructing Care Delivery Pathways From Electronic Health Care Databases to Support Integrated Care in Chronic Conditions: Systematic Review of Quantification and Visualization Methods.
BACKGROUND
Electronic health care databases are increasingly used for informing clinical decision-making. In long-term care, linking and accessing information on health care delivered by different providers could improve coordination and health outcomes. Several methods for quantifying and visualizing this information into data-driven care delivery pathways (CDPs) have been proposed. To be integrated effectively and sustainably into routine care, these methods need to meet a range of prerequisites covering 3 broad domains: clinical, technological, and behavioral. Although advances have been made, development to date lacks a comprehensive interdisciplinary approach. As the field expands, it would benefit from developing common standards of development and reporting that integrate clinical, technological, and behavioral aspects.
OBJECTIVE
We aimed to describe the content and development of long-term CDP quantification and visualization methods and to propose recommendations for future work.
METHODS
We conducted a systematic review following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) recommendations. We searched peer-reviewed publications in English and reported the CDP methods by using the following data in the included studies: long-term care data and extracted data on clinical information and aims, technological development and characteristics, and user behaviors. The data are summarized in tables and presented narratively.
RESULTS
Of the 2921 records identified, 14 studies were included, of which 13 (93%) were descriptive reports and 1 (7%) was a validation study. Clinical aims focused primarily on treatment decision-making (n=6, 43%) and care coordination (n=7, 50%). Technological development followed a similar process from scope definition to tool validation, with various levels of detail in reporting. User behaviors (n=3, 21%) referred to accessing CDPs, planning care, adjusting treatment, or supporting adherence.
CONCLUSIONS
The use of electronic health care databases for quantifying and visualizing CDPs in long-term care is an emerging field. Detailed and standardized reporting of clinical and technological aspects is needed. Early consideration of how CDPs would be used, validated, and implemented in clinical practice would likely facilitate further development and adoption.
TRIAL REGISTRATION
PROSPERO CRD42019140494; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=140494.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)
RR2-10.1136/bmjopen-2019-033573.
Topics: Humans; Access to Information; Clinical Decision-Making; Databases, Factual; Delivery of Health Care, Integrated; Electronics
PubMed: 38096009
DOI: 10.2196/49996 -
Frontiers in Public Health 2023The Hyperledger Fabric (HF) framework is widely studied for securing electronic health records (EHRs) in the healthcare sector. Despite the various cross-domain... (Review)
Review
The Hyperledger Fabric (HF) framework is widely studied for securing electronic health records (EHRs) in the healthcare sector. Despite the various cross-domain blockchain technology (BCT) applications, little is known about the role of the HF framework in healthcare. The purpose of the systematic literature review (SLR) is to review the existing literature on the HF framework and its applications in healthcare. This SLR includes literature published between January 2015 and March 2023 in the ACM digital library, IEEE Xplore, SCOPUS, Springer, PubMed, and Google Scholar databases. Following the inclusion and exclusion criteria, a total of 57 articles emerged as eligible for this SLR. The HF framework was found to be useful in securing health records coming from the Internet of Medical Things (IoMT) and many other devices. The main causes behind using the HF framework were identified as privacy and security, integrity, traceability, and availability of health records. Additionally, storage issues with transactional data over the blockchain are reduced by the use of the HF framework. This SLR also highlights potential future research trends to ensure the high-level security of health records.
Topics: Blockchain; Electronic Health Records; Delivery of Health Care; Privacy; Technology
PubMed: 38089022
DOI: 10.3389/fpubh.2023.1272787 -
Computational Intelligence and... 2023[This retracts the article DOI: 10.1155/2022/8303504.].
[This retracts the article DOI: 10.1155/2022/8303504.].
PubMed: 38074363
DOI: 10.1155/2023/9838129 -
Journal of Medical Internet Research Dec 2023Persons diagnosed with serious chronic illnesses and their caretakers experience multiple types of financial costs that strain their income and generate financial... (Review)
Review
BACKGROUND
Persons diagnosed with serious chronic illnesses and their caretakers experience multiple types of financial costs that strain their income and generate financial distress. Many turn to medical crowdfunding (MCF) to mitigate the harms of these costs on their health and quality of life.
OBJECTIVE
This scoping review aims to summarize the research on MCF for persons diagnosed with serious chronic illness regarding study designs and methods; the responsible conduct of research practices; and study foci as they relate to stress, stress appraisals, and the coping processes.
METHODS
This review was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. Eligible studies were conducted in countries designated as high income by the World Bank and focused on beneficiaries diagnosed with serious chronic illness. The findings of the included studies were summarized as they related to the key concepts in a conceptual framework derived from an established stress, appraisal, and coping framework and a conceptual model of financial toxicity in pediatric oncology.
RESULTS
Overall, 26 studies were eligible for inclusion in the review. The main findings included a lack of integration of qualitative and quantitative approaches and the inconsistent reporting of the responsible conduct of research practices. The included studies focused on financial stressors that contributed to financial burden, such as out-of-pocket payments of medical bills, basic living expenses, medical travel expenses, and lost income owing to illness-related work disruptions. Few studies addressed stress appraisals as threatening or the adequacy of available financial resources. When mentioned, appraisals related to the global financial struggle during the COVID-19 pandemic or the capacity of social network members to donate funds. The consequences of MCF included the receipt of 3 forms of social support (tangible, informational, and emotional), privacy loss, embarrassment, and the propagation of scientifically unsupported information. Studies found that friends and family tended to manage MCF campaigns. Although most of the studies (21/26, 81%) focused on monetary outcomes, a few (5/26, 19%) concentrated on peoples' experiences with MCF.
CONCLUSIONS
The identified methodological gaps highlight the need for more robust and reproducible approaches to using the copious data available on public MCF platforms. The integration of quantitative and qualitative methods will allow for nuanced explorations of the MCF experience. A more consistent elaboration of strategies to promote the responsible conduct of research is warranted to minimize risk to populations that are vulnerable and express concerns regarding the loss of privacy. Finally, an examination of the unanticipated consequences of MCF is critical for the development of future interventions to optimize existing supports while providing needed supports, financial and nonfinancial, that are lacking.
Topics: Child; Humans; Medical Tourism; Pandemics; Quality of Life; Health Expenditures; Chronic Disease
PubMed: 38048149
DOI: 10.2196/44530 -
BMC Medical Ethics Dec 2023Conventional consent practices face ethical challenges in continuously evolving digital health environments due to their static, one-time nature. Dynamic consent offers... (Review)
Review
BACKGROUND
Conventional consent practices face ethical challenges in continuously evolving digital health environments due to their static, one-time nature. Dynamic consent offers a promising solution, providing adaptability and flexibility to address these ethical concerns. However, due to the immaturity of the concept and accompanying technology, dynamic consent has not yet been widely used in practice. This study aims to identify the facilitators of and barriers to adopting dynamic consent in real-world scenarios.
METHODS
This scoping review, conducted in December 2022, adhered to the PRISMA Extension for Scoping Reviews guidelines, focusing on dynamic consent within the health domain. A comprehensive search across Web of Science, PubMed, and Scopus yielded 22 selected articles based on predefined inclusion and exclusion criteria.
RESULTS
The facilitators for the adoption of dynamic consent in digital health ecosystems were the provision of multiple consent modalities, personalized alternatives, continuous communication, and the dissemination of up-to-date information. Nevertheless, several barriers, such as consent fatigue, the digital divide, complexities in system implementation, and privacy and security concerns, needed to be addressed. This study also investigated current technological advancements and suggested considerations for further research aimed at resolving the remaining challenges surrounding dynamic consent.
CONCLUSIONS
Dynamic consent emerges as an ethically advantageous method for digital health ecosystems, driven by its adaptability and support for continuous, two-way communication between data subjects and consumers. Ethical implementation in real-world settings requires the development of a robust technical framework capable of accommodating the diverse needs of stakeholders, thereby ensuring ethical integrity and data privacy in the evolving digital health landscape.
Topics: Humans; Ecosystem; Communication; Privacy; Technology; Informed Consent
PubMed: 38041034
DOI: 10.1186/s12910-023-00988-9 -
BMC Pregnancy and Childbirth Dec 2023The occurrence of orofacial Clefts (OFCs) is a congenital disease caused by many factors. According to recent studies, air pollution has a strong correlation with the... (Meta-Analysis)
Meta-Analysis
BACKGROUND
The occurrence of orofacial Clefts (OFCs) is a congenital disease caused by many factors. According to recent studies, air pollution has a strong correlation with the occurrence of OFCs. However, there are still some controversies about the current research results, and there is no relevant research to review the latest results in recent years.
OBJECTIVE
In this paper, the authors conducted a systematic review and meta-analysis to explore the correlation between ambient air pollution and the occurrence of neonatal OFCs deformity.
METHODS
We searched Pubmed, Web of science, and Embase databases from the establishment of the database to May 2023. We included observational studies on the relationship between prenatal exposure to fine particulate matter 2.5 (PM2.5), fine particulate matter 10 (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO) and the risk of cleft lip (CL), cleft palate (CP), cleft lip with or without palate (CL/P). the Newcastle-Ottawa quality assessment scale (NOS) was used to evaluate the quality of the literature. Funnel plot and Egger's regression were used to verify the publication bias. Random effect model or fixed effect model was used to estimate the combined relative risk (RR) and 95% confidence interval (95%CI).
RESULTS
A total of eleven studies were included in this study, including four cohort studies and seven case-control studies, including 22,453 cases of OFCs. Ten studies had low risk of bias and only one study had high risk of bias. Three studies reported that PM was positively correlated with CL and CP, with a combined RR and 95%CI of 1.287(1.174,1.411) and 1.267 (1.105,1.454). Two studies reported a positive correlation between O and CL, with a combined RR and 95%CI of 1.132(1.047,1.225). Two studies reported a positive correlation between PM and CL, with a combined RR and 95%CI of 1.108 (1.017,1.206). No association was found between SO, CO, NO exposure during pregnancy and the risk of OFCs.
CONCLUSION
The results of this study showed that there was a significant statistical correlation between exposure to PM, PM, O and the risk of OFCs in the second month of pregnancy. Exposure assessment, research methods and mechanisms need to be further explored.
Topics: Infant, Newborn; Female; Pregnancy; Humans; Air Pollutants; Cleft Lip; Cleft Palate; Air Pollution; Particulate Matter; Ozone; Sulfur Dioxide; Nitrogen Dioxide; Environmental Exposure
PubMed: 38041018
DOI: 10.1186/s12884-023-06104-4 -
Frontiers in Oncology 2023Europe works to improve cancer management through the use of artificialintelligence (AI), and there is a need to accelerate the development of AI applications for...
INTRODUCTION
Europe works to improve cancer management through the use of artificialintelligence (AI), and there is a need to accelerate the development of AI applications for childhood cancer. However, the current strategies used for algorithm development in childhood cancer may have bias and limited generalizability. This study reviewed existing publications on AI tools for pediatric brain tumors, Europe's most common type of childhood solid tumor, to examine the data sources for developing AI tools.
METHODS
We performed a bibliometric analysis of the publications on AI tools for pediatric brain tumors, and we examined the type of data used, data sources, and geographic location of cohorts to evaluate the generalizability of the algorithms.
RESULTS
We screened 10503 publications, and we selected 45. A total of 34/45 publications developing AI tools focused on glial tumors, while 35/45 used MRI as a source of information to predict the classification and prognosis. The median number of patients for algorithm development was 89 for single-center studies and 120 for multicenter studies. A total of 17/45 publications used pediatric datasets from the UK.
DISCUSSION
Since the development of AI tools for pediatric brain tumors is still in its infancy, there is a need to support data exchange and collaboration between centers to increase the number of patients used for algorithm training and improve their generalizability. To this end, there is a need for increased data exchange and collaboration between centers and to explore the applicability of decentralized privacy-preserving technologies consistent with the General Data Protection Regulation (GDPR). This is particularly important in light of using the European Health Data Space and international collaborations.
PubMed: 38016063
DOI: 10.3389/fonc.2023.1285775