BackPage Online, August 2019
Notice bibliographique
Résumé
Is the WHO Choosing Profits For Big Pharma Over Human Lives? The World Health Organization (WHO) has the reputation of being a dependable proponent of good health and evidence-based medical care. However, the WHO fell down on the job when it came to the opioid overuse and addiction epidemic. According to a recent US Congressional investigation by representatives Katherine Clark (Democrat from Massachusetts) and Hal Rogers (Republican from Kentucky), the WHO allowed itself to become a conduit for inaccurate claims about opioid risks and benefits—and to become a marketing arm for Purdue Pharma and other opioid developers. And they suspect that these WHO's promotional efforts will lead to a replication of the deadly US opioid crisis in other parts of the world. “We hope the WHO will no longer allow the same companies and the same people who recklessly chose profits over human lives in the United States to inflict the opioid crisis on the rest of the world,” according to Clark and Rogers. In an article at BMJ, Purdue Pharma asserted that the Congressional report “seeks to vilify the company through baseless allegations.” A WHO spokesman said that the agency is reviewing the report point by point. Here is a link to the full Congressional report: https://katherineclark.house.gov/_cache/files/a/a/aaa7536a-6db3-4192-b943-364e7c599d10/818172D42793504DD9DFE64B77A77C0E.5.22.19-who-purdue-report-final.pdf Here is a link to the BMJ article on the report: www.bmj.com/content/365/bmj.l2343.full US Healthcare System Seeking Cost Savings by Exploiting a Key Group of Workers? Burnout has become a huge issue among healthcare providers in the United States and other affluent nations. It diminishes the futures of patients and providers alike—and is costing society a small fortune, as many healthcare providers are dropping out of the practice of medicine altogether. According to a recent article by internist Danielle Ofri, MD, of Bellevue Hospital in New York, the corporate healthcare system is attempting further cost savings by taking advantage of the professionalism and ethics of doctors and nurses—and manipulating them to work endlessly. “By now, corporate medicine has milked just about all the ‘efficiency’ it can out of the system. With mergers and streamlining, it has pushed the productivity numbers about as far as they can go. But one resource that seems endless—and free—is the professional ethic of medical staff members,” according to Ofri. This is bad business and bad medicine. Here is a link to the full article at the New York Times: www.nytimes.com/2019/06/08/opinion/sunday/hospitals-doctors-nurses-burnout.html?action=click&module=Opinion&pgtype=Homepage Has the Healthcare System Lost Sight of “Healing” as Its Main Priority? A recent article at the Harvard Business Review makes a compelling argument that the medical system has lost sight of a key priority: “healing.” “Health care plays a unique and sacred role in society—to provide healing—and it is up to its leaders to reclaim the primacy of this role before it is too late. Healing requires more than medication and technology directed toward physiological improvement. Emotional and spiritual rehabilitation matter, too,” according to critical care specialist Rana L. A. Awdish, MD, and health services researcher Leonard Berry. “Clinicians who work to understand the complex emotions that diagnosis and treatment evoke—and then show kindness to patients as they face those challenges—can mitigate some of the suffering that illness confers. Kindness helps to heal not just the recipient, but also the giver. Kindness can be learned, and that starts by embedding it in organizational culture, just as protocols for the safe administration of medications are embedded.” Here is a link to their powerful argument that medicine has gone astray and needs to keep its eyes on the most important priority: https://hbr.org/2019/05/putting-healing-back-at-the-center-of-health-care
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,007 | 0,003 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,934 | 0,919 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».