Burn Care Funding in the Era of Price Transparency-Does Verification Signal Bargaining Power?

The Price Transparency Rule of 2021 forced payors and hospitals to publicly disclose negotiated prices to foster competition and reduce cost. Burn care is costly and concentrated at less than 130 centers in the US. We aimed to analyze geographic price variations for inpatient burn care and measure the effects of American Burn Association (ABA) verification status and market concentration on prices. All available commercial rates for 2021-2022 for burn-related Diagnosis Related Groups (DRG) 927, 928, 929, 933, 934, and 935 were merged with hospital-level variables, ABA verification status, and Herfindahl-Hirschman Index (HHI) data. For the DRG 927 (most intensive burn admission) a linear mixed effects model was fit with cost as the outcome and the following variables as covariates: HHI, plan type, safety net status, profit status, verification status, rural status, teaching hospital status. Random intercepts allowed for individual burn centers. There were 170,738 rates published from 1541 unique hospitals. Commercial reimbursement rates for the same DRG varied by a factor of approximately three within hospitals for all DRGs. Similarly, rates across different hospitals varied by a factor of three for all DRGs, with DRG 927 having the most variation. Burn center status was independently associated with higher reimbursement rates adjusting for facility-level factors for all DRGs except for 935. Notably, HHI was the largest predictor of commercial rates (p<0.001). Negotiated prices for inpatient burn care vary widely. ABA-verified centers garner higher rates along with burn centers in more concentrated/monopolistic markets.

Highly sensitive and wide-range iontronic pressure sensors with a wheat awn-like hierarchical structure.

Flexible pressure sensors with high sensitivity and wide sensing range are highly desired in e-skins and wearable electronics. However, there is always a trade-off between high sensitivity and broad sensing range for most flexible pressure sensors. Herein, an artificial wheat awn-like hierarchical structure is designed onto the dielectric layer of the iontronic pressure sensor, realizing both high sensitivity and broad working range. The sensor is constructed by sandwiching a wheat awn-like polyvinyl alcohol/H3PO4 dielectric layer between two transparent electrodes of silver nanowires/thermoplastic polyurethane/ionic liquid. The obtained sensor exhibits a high precision of 1 Pa, a high sensitivity of 47.65 kPa-1 (1-200 Pa), a wide measurement range from 1 Pa to 238 kPa, short response/recovery time of 13 ms/12 ms, outstanding stability over 6000 cycles, as well as good transparency. Considering these excellent properties, the sensor shows promising potential in health monitoring, human-computer interaction, wearable electronics, etc.

Tennessee hospital noncompliance with price transparency legislation for 8 common laboratory tests.

OBJECTIVES: The goal of this study was to assess hospital compliance with federal price transparency mandates and barriers to pricing information in Tennessee. METHODS: All hospitals websites were queried for gross, cash, and BlueCross BlueShield of Tennessee prices for 8 high-frequency laboratory tests in 2 Centers for Medicare & Medicaid Services-mandated pricing sources: (1) a machine-readable file of all available services and (2) a consumer-friendly display of 300 shoppable services. Barriers, including click counts, data availability, and intrahospital price discrepancies, were noted. RESULTS: Of the 145 Tennessee hospitals assessed, 97.2% were noncompliant with the Centers for Medicare & Medicaid Services final rule. Subanalysis of available machine-readable files, price estimators, and shoppable services files demonstrated 49.6%, 95.1%, and 78.6% noncompliance, respectively. Barriers to pricing information included requiring protected health information (55.9%), missing at least 1 pricing source (7.6%), having no pricing sources available (6.2%), and involving more than 3 clicks to access the cash price in machine-readable files (54.1%) and price estimators (68.6%.) Average intrahospital discrepancy for basic metabolic panel cash prices across pricing sources was $101.30 (range, $0-1012.40). CONCLUSIONS: Our study showed high levels of noncompliance with price transparency laws, inconsistent and inaccessible pricing, and continued challenges facing patients in Tennessee.

Transparent layer constancy improves with increased naturalness of the scene.

The extent to which hue, saturation, and transmittance of thin light-transmitting layers are perceived as constant when the illumination changes (transparent layer constancy, TLC) has previously been investigated with simple stimuli in asymmetric matching tasks. In this task, a target filter is presented under one illumination and a second filter is matched under a second illumination. Although two different illuminations are applied in the stimulus generation, there is no guarantee that the stimulus will be interpreted appropriately by the visual system. In previous work, we found a higher degree of TLC when both illuminations were presented alternately than when they were presented simultaneously, which could be explained, for example, by an increased plausibility of an illumination change. In this work, we test whether TLC can also be increased in simultaneous presentation when the filter's belonging to a particular illumination context is made more likely by additional cues. To this end, we presented filters in differently lit areas of complex, naturalistically rendered 3D scenes containing different types of cues to the prevailing illumination, such as scene geometry, object shading, and cast shadows. We found higher degrees of TLC in such complex scenes than in colorimetrically similar simple 2D color mosaics, which is consistent with the results of similar studies in the area of color constancy. To test which of the illumination cues available in the scenes are actually used, the different types of cues were successively removed from the naturalistically rendered complex scene. A total of eight levels of scene complexity were examined. As expected, TLC decreased the more cues were removed. Object shading and illumination gradients due to shadow cast were both found to have a positive effect on TLC. A second filter had a small positive effect on TLC when added in strongly reduced scenes, but not in the complex scenes that already provide many cues about the illumination context of the filter.

Price transparency in Iranian healthcare market.

Insufficient price transparency has emerged as a pivotal contributor to patient dissatisfaction, escalating costs, and diminished productivity within Iran's health system. This study aims to delineate and elucidate a definition of price transparency, identify suitable strategies, and present the outcomes associated with establishing a health system that embraces transparent pricing while also addressing the challenges ahead. Employing a quantitative-qualitative research design, data were extracted from a semi-structured interviews with stakeholders. A purposive sampling method, encompassing sequential and snowball techniques, was employed to capture the perspectives of all stakeholders involved in the issue of price transparency in Iran. The interview data were analyzed using the grounded theory approach was classified into three categories: price transparency before, during, and after the receipt of healthcare services. Our findings reveal the causes of low price transparency, strategies to address the issue, and the consequences associated with increased levels of transparency. Ultimately, we contend that health systems can significantly enhance efficiency, patient satisfaction, and the performance of health insurance by adopting transparent pricing for health services, thus obviating the need for resource-intensive restructuring efforts.

Transparent Cellulose/Multi-Walled Carbon Nanotube Hybrids with Improved Ultraviolet-Shielding Properties Prepared from Cotton Textile Waste.

Plastics offer many advantages and are widely used in various fields. Nevertheless, most plastics derived from petroleum are slow to degrade due to their stable polymer structure, posing serious threats to organisms and ecosystems. Thus, developing environmentally friendly and biodegradable plastics is imperative. In this study, biodegradable cellulose/multi-walled carbon nanotube (MCNT) hybrid gels and films with improved ultraviolet-shielding properties were successfully prepared using cotton textile waste as a resource. It was proven that MCNTs can be dispersed evenly in cellulose without any chemical or physical pretreatment. It was found that the contents of MCNTs had obvious effects on the structures and properties of hybrid films. Particularly, the averaged transmittance of cellulose/MCNT composite films in the range of 320-400 nm (T320-400) and 290-320 nm (T290-320) can be as low as 19.91% and 16.09%, when the content of MCNTs was 4.0%, much lower than those of pure cellulose films (T320-400: 84.12% and T290-320: 80.03%). Meanwhile, the water contact angles of the cellulose/MCNT films were increased by increasing the content of MCNTs. Most importantly, the mechanical performance of cellulose/MCNT films could be controlled by the additives of glycerol and MCNTs. The tensile strength of the cellulose/MCNT films was able to reach as high as 20.58 MPa, while the elongation at break was about 31.35%. To summarize, transparent cellulose/MCNT composites with enhanced ultraviolet-shielding properties can be manufactured successfully from low-cost cotton textile waste, which is beneficial not only in terms of environmental protection, but also the utilization of natural resources.

Phosphorus and nitrogen supramolecule for fabricating flame-retardant, transparent and robust polyvinyl alcohol film.

Supramolecular flame retardants have attracted increasing attention recently due to their simple and eco-friendly preparation process. In this study, a novel flame retardant HEPFR was prepared using supramolecular self-assembly technology between piperazine and 1-hydroxy ethylidene-1,1-diphosphonic acid (HEDP). It was introduced into polyvinyl alcohol (PVA) matrix to form PVA/HEPFR composite film. Subsequently, the transparency, mechanical properties, thermal stability, and flame retardancy of PVA/HEPFR films were studied. Due to the hydrogen bonded cross-linked network structure between PVA and HEPFR, the mechanical properties of PVA/HEPFR films have been improved, while maintaining good transparency. With 10 wt% addition of HEPFR, PVA films can reach the VTM-0 level in UL-94 testing. And the limiting oxygen index can be increased from 18.5% of pure PVA to 26.5%. The peak heat release rate was reduced by 61.5%. The flame retardancy and thermal stability of PVA/HEPFR films have been greatly improved. This study provides a "one stone, three birds" strategy for preparing flame-retardant, transparent, and robust PVA film.

Money matters: a critique of 'informed financial consent'.

In recent years, concerns about the financial burdens of health care and growing recognition of the relevance of cost to decision making and patient experience have increasingly focused attention on financial 'transparency' and disclosure of costs to patients. In some jurisdictions, there have been calls not only for timely disclosure of costs information, but also for 'informed financial consent'. However, simply putting the 'financial' into 'informed consent' and invoking an informed consent standard for cost information encounters several ethical, legal, and practical difficulties. This article will examine the viability and desirability of 'informed financial consent', and whether it is possible to derive ideas from traditional informed consent that may improve decision making and the patient experience. We argue that, while there are important legal, ethical, and practical challenges to consider, some of the principles of informed consent to treatment can usefully guide financial communication. We also argue that, while medical practitioners (and their delegates) have an important role to play in bridging the gap between disclosure and enabling informed (financial) decision making, this must be part of a multi-faceted approach to financial communication that acknowledges the influence of non-clinical providers and other structural forces on discharging such obligations.

Preparation and characterization of water vapor-responsive methylcellulose-polyethylene glycol-400 composite membranes and an indication of freshness of shiitake mushrooms.

Intelligent packaging with freshness indication capability can help consumers purchase fresh food. However, current research primarily focuses on carbon dioxide-sensitive intelligent packaging, with limited research on water vapor-sensitive indication packaging. In this study, the water vapor-sensitive indicator membrane was prepared and used to determine the freshness of mushrooms. The results of this study showed that the water permeability of the indicator membrane decreased from 33.17 % to 21.59 % with the increase of Polyethylene glycol-400(PEG-400) content in methylcellulose(MC) membrane, and the contact angle of the indicator membrane increased from 87 % to 98 % with the addition of PEG-400. The addition of plasticizer PEG-400 increased the hydrophobicity of the indicator film, which could be attributed to the improvement of the molecular arrangement and crystallinity of the indicator film by the addition of PEG-400. After encountering water, the transparency of the indicator membrane changes from completely opaque (white) to transparent. Addition of PEG-400 reduces the rate of change in the transparency of the indicator membrane. The indicator membrane was successfully used to indicate the freshness of mushrooms and effectively reflected the freshness of mushrooms during storage. This technology could be applied to measure the freshness of other foods.

A Novel Approach of Brain-Computer Interfacing (BCI) and Grad-CAM Based Explainable Artificial Intelligence: Use Case Scenario for Smart Healthcare.

BACKGROUND: In order to push the frontiers of brain-computer interface (BCI) and neuron-electronics, this research presents a novel framework that combines cutting-edge technologies for improved brain-related diagnostics in smart healthcare. This research offers a ground-breaking application of transparent strategies to BCI, promoting openness and confidence in brain-computer interactions and taking inspiration from Grad-CAM (Gradient-weighted Class Activation Mapping) based Explainable Artificial Intelligence (XAI) methodology. The landscape of healthcare diagnostics is about to be redefined by the integration of various technologies, especially when it comes to illnesses related to the brain. NEW METHOD: A novel approach has been proposed in this study comprising of Xception architecture which is trained on imagenet database following transfer learning process for extraction of significant features from magnetic resonance imaging dataset acquired from publicly available distinct sources as an input and linear support vector machine has been used for distinguishing distinct classes.Afterwards, gradient-weighted class activation mapping has been deployed as the foundation for explainable artificial intelligence (XAI) for generating informative heatmaps, representing spatial localization of features which were focused to achieve model's predictions. RESULTS: Thus, the proposed model not only provides accurate outcomes but also provides transparency for the predictions generated by the Xception network to diagnose presence of abnormal tissues and avoids overfitting issues. Hyperparameters along with performance-metrics are also obtained while validating the proposed network on unseen brain MRI scans to ensure effectiveness of the proposed network. COMPARISON WITH EXISTING METHODS AND CONCLUSIONS: The integration of Grad-CAM based explainable artificial intelligence with deep neural network namely Xception offers a significant impact in diagnosing brain tumor disease while highlighting the specific regions of input brain MRI images responsible for making predictions. In this study, the proposed network results in 98.92% accuracy, 98.15% precision, 99.09% sensitivity, 98.18% specificity and 98.91% dice-coefficient while identifying presence of abnormal tissues in the brain. Thus, Xception model trained on distinct dataset following transfer learning process offers remarkable diagnostic accuracy and linear support vector act as a classifier to provide efficient classification among distinct classes. In addition, the deployed explainable artificial intelligence approach helps in revealing the reasoning behind predictions made by deep neural network having black-box nature and provides a clear perspective to assist medical experts in achieving trustworthiness and transparency while diagnosing brain tumor disease in the smart healthcare.

Critical Gaps in Medical Research Reporting by Online News Media.

BACKGROUND: The integrity of medical research reporting in online news publications is crucial for informed healthcare decisions and public health discourse. However, omissions, lack of transparency, and the rapid spread of misinformation on digital and social media platforms can lead to an incomplete or inaccurate understanding of research findings. This study aims to analyze the fidelity of online news in reporting medical research findings, focusing on conflicts of interest, study limitations, statistical data, and research conclusions. METHODS: Fifty randomized controlled trials published in major medical journals and their corresponding news reports were evaluated for the inclusion of conflicts of interest, study limitations, and inferential statistics in the news reports. The alignment of conclusions was evaluated. A binomial test with a Bonferroni correction was used to assess the inclusion rate of these variables against a 90% threshold. RESULTS: Conflicts of interest were reported in 10 (20%) of news reports, study limitations in 14 (28%), and inferential statistics in 19 (38%). These rates were significantly lower than the 90% threshold (p<0.001). Research conclusions aligned in 43 (86%) cases, which was not significantly different from 90% (p=0.230). Misaligned conclusions resulted from overstating claims. CONCLUSION: Significant gaps exist in the reporting of critical contextual information in medical news articles. Adopting a structured reporting format could enhance the quality and transparency of medical research communication. Collaboration among journalists, news organizations, and medical researchers is crucial for establishing and promoting best practices, fostering informed public discourse, and better health outcomes.

ChatGPT as an "author": Bibliometric analysis to assess the validity of authorship.

Background: Following the 2023 surge in popularity of large language models like ChatGPT, significant ethical discussions emerged regarding their role in academic authorship. Notable ethics organizations, including the ICMJE and COPE, alongside leading publishers, have instituted ethics clauses explicitly stating that such models do not meet the criteria for authorship due to accountability issues.Objective: This study aims to assess the prevalence and ethical implications of listing ChatGPT as an author on academic papers, in violation of existing ethical guidelines set by the ICMJE and COPE.Methods: We conducted a comprehensive review using databases such as Web of Science and Scopus to identify instances where ChatGPT was credited as an author, co-author, or group author.Results: Our search identified 14 papers featuring ChatGPT in such roles. In four of those papers, ChatGPT was listed as an "author" alongside the journal's editor or editor-in-chief. Several of the ChatGPT-authored papers have accrued dozens, even hundreds of citations according to Scopus, Web of Science, and Google Scholar.Discussion: The inclusion of ChatGPT as an author on these papers raises critical questions about the definition of authorship and the accountability mechanisms in place for content produced by artificial intelligence. Despite the ethical guidelines, the widespread citation of these papers suggests a disconnect between ethical policy and academic practice.Conclusion: The findings suggest a need for corrective measures to address these discrepancies. Immediate review and amendment of the listed papers is advised, highlighting a significant oversight in the enforcement of ethical standards in academic publishing.

Human-in-the-loop error detection in an object organization task with a social robot.

In human-robot collaboration, failures are bound to occur. A thorough understanding of potential errors is necessary so that robotic system designers can develop systems that remedy failure cases. In this work, we study failures that occur when participants interact with a working system and focus especially on errors in a robotic system's knowledge base of which the system is not aware. A human interaction partner can be part of the error detection process if they are given insight into the robot's knowledge and decision-making process. We investigate different communication modalities and the design of shared task representations in a joint human-robot object organization task. We conducted a user study (N = 31) in which the participants showed a Pepper robot how to organize objects, and the robot communicated the learned object configuration to the participants by means of speech, visualization, or a combination of speech and visualization. The multimodal, combined condition was preferred by 23 participants, followed by seven participants preferring the visualization. Based on the interviews, the errors that occurred, and the object configurations generated by the participants, we conclude that participants tend to test the system's limitations by making the task more complex, which provokes errors. This trial-and-error behavior has a productive purpose and demonstrates that failures occur that arise from the combination of robot capabilities, the user's understanding and actions, and interaction in the environment. Moreover, it demonstrates that failure can have a productive purpose in establishing better user mental models of the technology.

Future proofing core facilities with a seven-pillar model.

Centralised core facilities have evolved into vital components of life science research, transitioning from a primary focus on centralising equipment to ensuring access to technology experts across all facets of an experimental workflow. Herein, we put forward a seven-pillar model to define what a core facility needs to meet its overarching goal of facilitating research. The seven equally weighted pillars are Technology, Core Facility Team, Training, Career Tracks, Technical Support, Community and Transparency. These seven pillars stand on a solid foundation of cultural, operational and framework policies including the elements of transparent and stable funding strategies, modern human resources support, progressive facility leadership and management as well as clear institute strategies and policies. This foundation, among other things, ensures a tight alignment of the core facilities to the vision and mission of the institute. To future-proof core facilities, it is crucial to foster all seven of these pillars, particularly focusing on newly identified pillars such as career tracks, thus enabling core facilities to continue supporting research and catalysing scientific advancement. Lay abstract: In research, there is a growing trend to bring advanced, high-performance equipment together into a centralised location. This is done to streamline how the equipment purchase is financed, how the equipment is maintained, and to enable an easier approach for research scientists to access these tools in a location that is supported by a team of technology experts who can help scientists use the equipment. These centralised equipment centres are called Core Facilities. The core facility model is relatively new in science and it requires an adapted approach to how core facilities are built and managed. In this paper, we put forward a seven-pillar model of the important supporting elements of core facilities. These supporting elements are: Technology (the instruments themselves), Core Facility Team (the technology experts who operate the instruments), Training (of the staff and research community), Career Tracks (for the core facility staff), Technical Support (the process of providing help to apply the technology to a scientific question), Community (of research scientist, technology experts and developers) and Transparency (of how the core facility works and the costs associated with using the service). These pillars stand on the bigger foundation of clear policies, guidelines, and leadership approaches at the institutional level. With a focus on these elements, the authors feel core facilities will be well positioned to support scientific discovery in the future.

Unveiling the shadows: Beyond the hype of AI in education.

Despite the wave of enthusiasm for the role of Artificial Intelligence (AI) in reshaping education, critical voices urge a more tempered approach. This study investigates the less-discussed 'shadows' of AI implementation in educational settings, focusing on potential negatives that may accompany its integration. Through a multi-phased exploration consisting of content analysis and survey research, the study develops and validates a theoretical model that pinpoints several areas of concern. The initial phase, a systematic literature review, yielded 56 relevant studies from which the model was crafted. The subsequent survey with 260 participants from a Saudi Arabian university aimed to validate the model. Findings confirm concerns about human connection, data privacy and security, algorithmic bias, transparency, critical thinking, access equity, ethical issues, teacher development, reliability, and the consequences of AI-generated content. They also highlight correlations between various AI-associated concerns, suggesting intertwined consequences rather than isolated issues. For instance, enhancements in AI transparency could simultaneously support teacher professional development and foster better student outcomes. Furthermore, the study acknowledges the transformative potential of AI but cautions against its unexamined adoption in education. It advocates for comprehensive strategies to maintain human connections, ensure data privacy and security, mitigate biases, enhance system transparency, foster creativity, reduce access disparities, emphasize ethics, prepare teachers, ensure system reliability, and regulate AI-generated content. Such strategies underscore the need for holistic policymaking to leverage AI's benefits while safeguarding against its disadvantages.

A transparent approach: Openness in forensic science reporting.

There have been numerous calls for increased transparency and disclosure in forensic science. However, there is a paucity of guidance on how to achieve this transparency in reports, and the impacts it may have on criminal justice proceedings. We describe one multi-disciplinary forensic laboratory's journey to fully transparent reporting, disclosing matters of scientific relevance and importance. All expert reports across 17 disciplines now contain information regarding the fundamental principles and methodology, validity and error, assumptions and limitations, competency testing and quality assurance, cognitive factors, and areas of scientific controversy. Staff support for transparent reporting increased following introduction, with most reporting largely positive impacts. A slight increase in questioning in court has been experienced, with increased legal attention paid to the indicia of scientific validity. Transparency in expert forensic science reports is possible, and can improve the use of scientific evidence in courts without compromising the timeliness of service.

Beyond disclaimers: the need for a curation-based model of PubMed.

According to its own description, the biomedical meta-database PubMed exists "with the aim of improving health-both globally and personally." Unfortunately, PubMed contains an increasing amount of low-quality research that may detract from this goal. Currently, PubMed warns its users and protects itself from such problems with a disclaimer stating that the presence of any article, book, or document in PubMed does not imply an endorsement of, or concurrence with, its contents by the NLM, the National Institutes of Health (NIH), or the U.S. Federal Government. However, we are critical of a "disclaimer-only" stance and encourage PubMed to take further action against low-quality research being found and indexed in its database, and thus available for use. To address this problem, we offer two lines of reasoning to argue that PubMed should not function merely as a passive index of health-related research. Instead, we first argue that only trustworthy published research is able to further PubMed's goal of health improvement. Secondly, on the basis of surveys, we argue that researchers place a high level of trust in articles that are referenced in this meta-database. We cannot expect any one set of actors to ensure trustworthy content on PubMed, which requires collective responsibility among authors, peer reviewers, editors, and indexers alike. Instead, we propose a curation-based model that incorporates three mechanisms of collaborative content curation: open expert feedback on indexed content, journal auditing, and constant transparent reassessment of indexed entities.

Wetting Transparency of Single-Layer Graphene on Liquid Substrates.

Graphene's wetting transparency offers promising avenues for creating multifunctional devices by allowing real-time wettability control on liquid substrates via the flow of different liquids beneath graphene. Despite its potential, direct measurement of floating graphene's wettability remains a challenge, hindering the exploration of these applications. The current study develops an experimental methodology to assess the wetting transparency of single-layer graphene (SLG) on liquid substrates. By employing contact angle measurements and Neumann's Triangle model, the challenge of evaluating the wettability of floating free-suspended single-layer graphene is addressed. The research reveals that for successful contact angle measurements, the testing and substrate liquids must be immiscible. Using diiodomethane as the testing liquid and ammonium persulfate solution as liquid substrate, the study demonstrates the near-complete wetting transparency of graphene. Furthermore, it successfully showcases the feasibility of real-time wettability control using graphene on liquid substrates. This work not only advances the understanding of graphene's interaction with liquid interfaces but also suggests a new avenue for the development of multifunctional materials and devices by exploiting the unique wetting transparency of graphene.

From "exceptional ethics" to public health ethics. Patients and proxies facing COVID-19. Ethics and public health during COVID-19 / D'une « éthique d'exception ¼ à une éthique de la santé publique. Patients et proches face à la COVID-19. Éthique et santé publique en temps de COVID-19.

The study aimed to elicit the perception and ethical considerations of patients and proxies with respect both to the individual medical decisions and public health decisions made during the COVID-19 crisis. It used a qualitative, multi-center study based on semi-directive interviews, conducted by an interdisciplinary team. The analysis was conducted using a thematic analysis approach and an ethical framework. Three themes emerged from the analysis: 1) patients, unlike proxies, did not complain about their diminished role in the decision-making process. Both highlighted the importance of "basic care" as opposed to a technical approach to treatment; 2) despite the transparency of the information process, a deep "crisis of trust" has developed between citizens and public authorities; 3) although both patients and proxies accepted the limitations of personal liberties imposed in the name of public health, they argued that these limitations should respect certain boundaries, both temporal and spacial. Above all, they should not affect basic affective human relationships, even if such boundaries are a factor in an increased risk of infection. The study showed that there is a need to reconsider the definition and the main principles of public health ethics, namely transparency and proportionality.

L'étude vise à analyser la perception que les patients et les proches de patients pris en charge pendant la crise de la COVID-19, ont pu avoir de leur prise en charge, et leurs réflexions éthiques sur la place et la définition de la santé publique. L'étude a utilisé une méthode qualitative et multicentrique. Les entretiens semi-directifs ont été conduits par une équipe pluridisciplinaire et analysés avec une approche thématique et une grille de lecture éthique à partir des principes de l'éthique biomédicale. Trois thèmes ont émergé : 1) Les patients ont exprimé peu de revendications de participer aux décisions médicales les concernant, contrairement aux proches qui se sont sentis exclus de leur rôle. Tous ont mis l'accent sur l'importance des soins de base par rapport aux soins techniques ; 2) La gestion de la crise n'est pas jugée sévèrement, mais une crise de confiance importante a été mise en évidence, malgré la « transparence ¼ affichée de l'information ; 3) les contraintes collectives ont été largement acceptées au nom de la solidarité, mais on a jugé qu'elles doivent avoir des limites (temporelle et spatiales). Surtout, elles ne doivent pas empêcher des relations humaines simples et essentielles. L'étude met en évidence qu'il est nécessaire de développer une réflexion nouvelle autour de l'éthique de la santé publique : il convient de questionner les principes de « transparence ¼ et de « proportionnalité ¼ et d'adopter une définition de « santé publique ¼ plus large que la minimisation du risque infectieux.