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Enregistrement W7047307046

GAO Report Finds Excess Spending in Medicare

2013· article· en· W7047307046 sur OpenAlexaboutno aff

Notice bibliographique

RevueeYLS (Yale Law School) · 2013
Typearticle
Langueen
DomainePhysics and Astronomy
ThématiqueSuperconducting and THz Device Technology
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBeneficiaryMedicaidMedicare AdvantageQuarter (Canadian coin)PaymentGovernment (linguistics)Health carePopulation
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Despite tightening budgets, the federal government is substantially overpaying private insurers for Medicare benefits, according to a report recently issued by a federal auditor. Under the Medicare Advantage program, which covered roughly one quarter of the Medicare population in 2012, Medicare beneficiaries may elect to have a private insurer administer their Medicare benefits. In exchange, the federal government pays private Medicare Advantage insurers a monthly amount per enrollee for providing coverage, as calculated by applying a formula that considers enrollees’ health care risks. According to a recent U.S. Government Accountability Office (GAO) report, private insurers offering Medicare Advantage plans receive inflated payments because insurers tend to use relatively high risk rates when calculating what Medicare should pay insurers per enrollee. The Centers for Medicare and Medicaid Services (CMS) offsets these higher rates by decreasing payments using a risk score adjustment, but the GAO reports that the CMS has not adequately adjusted these payments. The GAO estimates that this has resulted in “substantial excess payments” to Medicare Advantage plans—totaling in the range of $3.2 to $5.1 billion between 2010 and 2012. CMS determines the rate it pays private insurers under Medicare Advantage plans based in part on enrollees’ demographic characteristics and health risk profiles, a process known as risk adjustment. CMS assigns each beneficiary a risk score, a measure of anticipated health care expenditures, based on individual characteristics such as age and sex, as well as medical diagnosis codes that these insurers provide. In theory, two individuals with the same characteristics and health status should have the same risk score, regardless of whether they participate in traditional Medicare or Medicare Advantage. Yet in reality, the risk scores of Medicare Advantage plan participants are typically higher than those of traditional Medicare enrollees. The GAO attributes this risk score discrepancy to differences in payment methodology and coding practices used by Medicare Advantage and traditional Medicare. Private companies offering Medicare Advantage plans have a financial incentive to exaggerate enrollees’ medical diagnosis codes to give the impression that Medicare Advantage enrollees are less healthy than they truly are. If the diagnostic codes reflect more costly or severe conditions, enrollees are assigned a higher risk score and the company receives greater compensation from CMS. In contrast, CMS determines the risk scores of individuals enrolled in traditional Medicare based on the claims that providers of traditional Medicare submit to get reimbursed. CMS then translates these claims into medical diagnoses. Traditional Medicare providers receive payment according to the services they actually render—not based on the medical diagnoses of their patients. As a result, risk scores for individuals enrolled in Medicare Advantage plans typically exceed those of traditional Medicare enrollees. To avoid overpaying Medicare Advantage plan providers because of this discrepancy in coding practices, CMS adjusts Medicare Advantage risk scores, reducing them by the percentage of the risk score that CMS attributes to differences in diagnostic coding practices between Medicare Advantage and traditional Medicare. In 2010, 2011, and 2012, CMS reduced Medicare Advantage enrollees’ risk scores by 3.4% annually, avoiding $2.8 billion, $3.0 billion, and $3.2 billion in overpayments, respectively. According to the GAO, however, these risk score reductions have inadequately discounted payments to Medicare, resulting in billions of dollars in overpayments. As a result, the GAO encourages CMS to increase its Medicare Advantage risk score adjustment to better account for these overpayments. In an earlier report, the GAO found that on average, Medicare Advantage risk scores in 2010 were actually 4.8 to 7.1% higher than traditional Medicare risk scores—a far more substantial discrepancy than CMS’s risk adjustment of 3.4%. In that report, the GAO urged CMS to increase the accuracy of its Medicare Advantage risk score adjustments by, for example, taking account of additional beneficiary characteristics and using the most updated information available. In its 2013 report, the GAO notes that CMS used updated data and considered a limited number of additional factors about beneficiaries in calculating the 3.4% risk adjustment CMS applied in 2012. As this 3.4% figure failed to adequately account for the discrepancy in coding practices between the Medicare and Medicare Advantage programs, the GAO encourages CMS to continue revising the adjustment formula going forward. The GAO also notes that CMS officials seem open to further revisions.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,008
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,048
Score d'incertitude au seuil0,095

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,008
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0030,006
Études des sciences et des technologies0,0010,000
Communication savante0,0020,001
Science ouverte0,0000,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0210,006

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 Opus0,017
Tête enseignante GPT0,264
Écart entre enseignants0,248 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

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

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

En bref

Citations0
Publié2013
Routes d'admission1
Résumé présentoui

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