Medicaid Education and Eligibility Planning for Caregivers: Website Usability and Validation Study
Notice bibliographique
Résumé
Background: Most older Americans have not saved enough to cover long-term care costs. Medicaid-a public health care program for low-income individuals-can help Americans with qualifying care needs pay for assistance in a nursing home or for services in the home. Determining financial eligibility for Medicaid is complicated, and the application process is often managed by family caregivers with limited knowledge of Medicaid programs. Objective: A one-stop digital solution is needed to help family caregivers plan for the cost of long-term care services and learn about getting help paying for services through Medicaid. We aimed to develop a web application that (1) educates informal caregivers about Medicaid programs and eligibility criteria, (2) informs them about the cost of home and institutional care in their local area with and without Medicaid coverage, and (3) uses a custom algorithm to provide personalized financial eligibility information based on the care recipient's income, assets, and monthly spending. Methods: We first interviewed aging services providers and informal family caregivers, then developed a web application that was refined based on user experience interviews with English- and Spanish-speaking caregivers. In the final validation phase, asynchronous usability sessions were recorded with 109 informal caregivers who completed a series of tasks. Participants viewed and rated animated Medicaid "explainer" videos, input financial information to enable the custom algorithm to determine the care recipient's eligibility for Medicaid, adjusted settings on a care cost calculator to estimate the regional cost of home and institutional care services, and completed a Medicaid knowledge quiz before and after using the website. Results: After engaging with the website and watching the videos, scores on a Medicaid knowledge quiz increased by 61.2% (2-tailed t92=12.9, P<.001). Participants found it easy to enter the care recipient's financial information to determine Medicaid eligibility (out of 7; mean 5.9, SD 1.3) and perceived the care cost calculator as very helpful (out of 7; mean 6.3, SD 1.2). The website received a very high System Usability Scale rating of 88.3 out of 100 (SD 13.1). Caregivers verbalized wanting more education on complex financial concepts that impact Medicaid eligibility and asset preservation. Conclusions: A comprehensive Medicaid planning website can significantly improve caregivers' knowledge of Medicaid and provide them with a personalized roadmap for accessing care services. The custom algorithm powering the Medicaid eligibility determination could be further refined to account for state-based exceptions. This application may reduce caregiver burden and help support the long-term care planning process.
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) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».