Out of Pocket, Out of Sight? An Unmeasured Component of the Burden of Cancer
Notice bibliographique
Résumé
While tremendous strides in prevention and treatment of cancer have been made in recent years, accumulating evidence shows that the costs associated with these advances have led to an increasing financial burden on health-care systems, patients and their families, and society overall (1,2). Medical care costs can often be documented from existing administrative health-care data systems, although other aspects of the financial burden of cancer—particularly, those aspects related to patient costs—are not measured systematically and, as a result, are rarely reported. In this issue of the Journal, Lauzier et al. (3) add valuable information to our understanding of the financial impact of cancer, describing out-of-pocket expenditures in the first year after treatment initiation among a cohort of women diagnosed with early-stage breast cancer and their spouses from Quebec, Canada. Using multiple measurement time points, the authors detail out-of-pocket costs related to cancer treatment, including those associated with transportation, domestic help, and other accommodations. Lauzier et al. report median net out-of-pocket costs of $1,002 for patients, comprised predominately of costs related to travel, accommodations and management of side effects, and $111 for spouses (2003 Canadian dollars). Further, the authors underscore wage loss as the primary driver of patients’ perceived change for the worse in their family’s financial situation. Although the authors conclude that out-of-pocket costs for the first year after treatment initiation are probably not unmanageable for most women with early-stage breast cancer, the financial consequences reported likely understate those for breast cancer patients diagnosed with distant metastases and other patients with more treatment-intensive cancers. Additionally, estimates from Canada may not reflect the out-of-pocket costs experienced by cancer patients in the United States or other countries because of fundamental differences in the organization and financing of health care. The magnitude of financial burden on cancer patients can vary widely, especially in the complex US health-care system, which is comprised of multiple payers, coverage policies, annual/lifetime benefit limits and insurance caps, coinsurance, copayments, and deductibles (4). In addition to costs for transportation and endocrine therapy faced by patients in Quebec, expenses for insured cancer patients in the United States would include deductibles and copayments for hospitalizations, doctor visits, surgical visits, and adjuvant treatments. For cancer patients without health insurance or those who have already reached a lifetime benefit limit, all costs of care would be considered out-of-pocket costs. It is not surprising, then, that a large proportion of US cancer patients and their families report hardship paying their cancer bills (5), with many families using all or most of their savings (6). Moreover, because health insurance in the working-age population is predominantly employer-based in the United States, rather than coverage provided universally as in Canada, maintaining insurance coverage during treatment can be more challenging for patients and their families. Cancer treatment can lead to substantial work loss for both patients and their families, which is manifested as fewer hours worked, change in jobs, or job loss—all of which can lead to a change in or loss of health insurance (4,7,8). Time demands associated with cancer treatment may also lead to reduced work and wage loss for patients and caregivers, an indirect cost of cancer care that affects families’ outlook about their financial well-being, as indicated by Lauzier et al. (3). In the United States, cancer patients may choose to forgo and/or delay recommended medical care, even potentially life-saving cancer treatment, because of an inability to pay or in an attempt to avoid further debt (4,6,9–11). Additionally, the decision to forgo or delay care because of cost may be more likely among individuals who are uninsured, low-income, and/or racial/ethnic minorities (6,9), which further perpetuates disparities that lead to poor health outcomes among the most vulnerable populations. As such, understanding the potential financial consequences of cancer care is increasingly important. Cancer accounts for approximately 5% of total health-care spending in the United States (12) and 5% to 7% of the health-care budget in Canada (13). Furthermore, the costs of cancer care in most developed countries are expected to rise because of population growth and aging alone (1,2). Much attention has recently focused on the soaring price of cancer drugs (14), some with price tags of more than $125 000 per drug per year (15), often with modest clinical benefits. For US patients facing a coinsurance of 20% to 33% for “top-tier” drugs (16), this can translate to out-of-pocket costs of approximately $41 000 a year. This phenomenon of patients being exposed to higher costs for expensive cancer medications is becoming more common in Canada as well (17). Therefore, for both US and Canadian oncologists, consideration of the patient costs associated with cancer treatment will be central to comprehensive discussions with patients and treatment recommendations. Nevertheless, for providers to be able to have substantive conversations about the costs of cancer treatment with their patients, more studies like that from Lauzier et al. (3) are needed to provide detailed longitudinal data on patient out-of-pocket costs, including those associated with medical treatment and wage loss. National data, such as the Medical Expenditure Panel Survey Experiences with Cancer Supplement, will provide information about the impact of cancer and its treatment on financial burden, health-care use and expenditures, and the employment of cancer survivors as well as their caregivers (18). Overall, such evidence on the scope of financial consequences of cancer care for patients and their families, in addition to the clinical benefits and risks, will enhance discussions of the “value” of cancer treatment, which is something oncologists in both the United States and Canada acknowledge as a fundamental component of high-quality care (17,19).
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 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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,002 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».