Healthcare expenditure in the United States of America in the last year of life: where ethics, medicine and economics collide?
Notice bibliographique
Résumé
To the Editor: A just published article in the Lancet from the Harvard School of Public Health in the United States of America reported on a retrospective cohort study of elderly beneficiaries of fee-for-service Medicare in the USA, aged 65 years or older, who died in 2008 (1). Of 1,802,029 elderly beneficiaries of fee-for-service Medicare who died in 2008, 31.9% (95% CI 31.9–32.0; 575,596 of 1,802,029) underwent an inpatient surgical procedure during the year before death, 18.3% (95% CI 18.2–18.4; 329,771 of 1,802,029) underwent a procedure in their last month of life and 8.0% (95% CI 8.0–8.1; 144,162 of 1,802,029) underwent a procedure during their last week of life. The authors of this report concluded that many elderly people in the USA undergo surgery in the year before their death (1). Similarly, there has been established very clearly over the years, the fact that medical expenses in the last year of life in general compared with total lifetime healthcare expenses here in the United States of America is very much skewed in favour of the former (2-7). In 2006, treatment for patients in the United States of America in their last year of life accounted for more than one-quarter of Medicare spending (2). Moreover, marked geographical variation in Medicare end-of-life spending is well documented (3). Furthermore, this geographical variation in end-of-life healthcare related expenditures is believed to be driven by physician practice styles rather than by differences in patients’ preferences for aggressiveness of treatment at the end of life (4). There is increasing concern in certain quarters that this expensive care may have limited clinical effectiveness and may be contrary to what the receiving patients actually wanted (5). Surveys report that many patients do not wish to receive aggressive treatment at the end of their lives; however, these preferences are often undocumented (6, 7). This brings up the question of advanced directives which even when properly documented as patients’ wishes, can get turned around by family members ‘when the chips are down’. The ethical implications of such practices resonate around the intensive care units and other acute care settings around the country, every single day. From the foregoing, we submit that healthcare delivery is at the crossroads of ethics and marketing. We in the United States of America, and other similarly affected countries, must as a society have to confront these apparent inequities and inefficiencies and potentially unethical practices in our healthcare system regarding medical/surgical treatment of the elderly. This is one place where ethics, medicine and economics collide. We have dubbed this the syndrome of ‘Ethicomedicinomics’. None.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,025 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».