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Enregistrement W1212734513

Reinsuring Health: Why More Middle Class People Are Uninsured and What the Government Can Do

2010· article· en· W1212734513 sur OpenAlexaboutno aff
David A. Cather

Notice bibliographique

RevueJournal of Risk & Insurance · 2010
Typearticle
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueHealthcare Policy and Management
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésGovernment (linguistics)Health carePublic healthQuarter (Canadian coin)Face (sociological concept)Middle classPolitical scienceBusinessPublic administrationSociologyMedicineLawHistoryNursingSocial science
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Reinsuring Health: Why More Middle Class People Are Uninsured and What the Government Can Do, by Katherine Swartz, 2006, Russell Sage Foundation, New York, pp. 203. ISBN: 0-87154-787-2 In 2008, the number of nonelderly Americans without health insurance approached 47 million people, with millions of others concerned that a faltering economy may increase their chances of losing their own health care coverage. As the United States considers a variety of alternatives to decrease the ranks of the uninsured, Katherine Swartz offers a timely book on how the face of the uninsured has dramatically changed over the past quarter century and provides a thoughtful proposal for improving how health insurers can better address this crisis in coverage. In Reinsuring Health, Swartz examines whether a public-private health care reinsurance model can be implemented on a national level, designed as a program in which the federal government assumes the role of the reinsurer of catastrophically high health care risks. Reinsuring Health is divided into three broad sections: a comparison of how the face of the uninsured have changed from 1979 to 2004, a description of how the individual and small-group health insurance markets currently operate, and final proposal for a new public-private structure that may make private health insurance more affordable. Swartz, a professor of health policy and management at Harvard's School of Public Health, has thus written a scholarly book that covers a lot of ground, but in an accessible style that a nonacademic authence can fully appreciate. One of the clear strengths of Reinsuring Health is its description of how the population of Americans without health care in 1979 is radically different from the uninsured population today. In 1979, nearly 40 percent of the uninsured in the United States were children living in low-income families, a statistic that prompted the creation of a variety of public programs (e.g., the State Children's Health Insurance Programs, changes in Medicaid) that were designed to reduce this percentage. By 2004, these programs, combined with shifts in demographics and birthrates, had reduced the percentage of the iininsured population consisting of children by half. In their place, the profile of Americans without health insurance today is much more diverse, and often from families earning middle-class incomes. To explain how these differences occurred, Swartz provides a thorough summary of an extensive literature that documents how a variety of recent employment trends - e.g., outsourcing, the declining influence of labor unions, the growing ranks of the self-employed, replacing employees with independent contractors and contract employees, and an evolving job market that consists of fewer employees from large manufacturers and more employees from smaller service firms - have resulted in a larger fraction of the workforce holding jobs without employer-sponsored health care. As a result of these changes in the workforce, 40 percent of the uninsured today are between the ages of 25 and 44, and 30 percent come from a family with income above the national median. Thus, unlike 1979, the factors that have resulted in a significant number of uninsured people today are not tied as closely to unemployment and poverty but are increasingly attributable to conscious decisions by employers to pare down the portion of their workforce that is eligible for expensive benefits like group health insurance. In the second section of Reinsuring Health, Swartz describes how the individual and small-group health insurance markets operate. Chapter 3 explains why health insurance provided through an employer group generally costs less per person than health insurance through individual policies. Next, drawing heavily from the work of Klein (2003), the chapter chronicles the events that have led to U.S. employers becoming the first-line providers and financiers of health insurance. The remainder of the chapter explains why large employers are able to offer health insurance to their workers at a lower cost than small employers, focusing on large-firm economies of scale and their ability to spread the costs of adverse selection across a large group of employees. …

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,263
Score d'incertitude au seuil0,522

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,029
Tête enseignante GPT0,241
Écart entre enseignants0,212 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2010
Routes d'admission1
Résumé présentoui

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