Telehealth Impact in Frontier Critical Access Hospitals: Mixed Methods Evaluation
Notice bibliographique
Résumé
BACKGROUND: Frontier areas are sparsely populated counties in states where 65% of the counties have 6 or fewer residents per square mile. Residents access primary care at critical access hospitals (CAHs) located in these rural communities but must travel great distances for specialty care. Telehealth could address access challenges; however, there are barriers to broader use, including reimbursement and the need for practical implementation support. The Centers for Medicare & Medicaid Services implemented the Frontier Community Health Integration Project (FCHIP) Demonstration to assess the impact of telehealth payment change and technical assistance to adopt and sustainably use telehealth for CAHs treating Medicare fee-for-service patients in frontier regions. OBJECTIVE: We evaluated the impact of the FCHIP Demonstration telehealth payment change and technical assistance on telehealth adoption and ongoing use using a mixed methods approach. METHODS: We conducted a mixed methods evaluation of the 8 CAHs in Montana, Nevada, and North Dakota that participated in the FCHIP program. Key informant interviews and FCHIP program document review were conducted and analyzed using thematic analysis to understand how CAHs implemented their telehealth programs and the facilitators of program adoption and maintenance. Medicare fee-for-service claims were analyzed from August 2013 to July 2019 relative to a group of CAHs that did not participate in the demonstration project to understand the frequency of telehealth use for Medicare fee-for-service beneficiaries receiving care at the participating CAHs before and during the Demonstration program. RESULTS: CAH staff noted several key factors for establishing and sustaining a telehealth program: clinical and administrative staff champions, infrastructure changes, training on telehealth processes, and establishing strong relationships with specialists at distant facilities to deliver telehealth services to patients of CAH. There was a modest increase in telehealth services billed to Medicare during the FCHIP Demonstration that were limited to a handful of CAHs. CONCLUSIONS: The frontier setting is characterized by a low population; and thus, the volumes of telehealth services provided in both the CAHs and comparison sites are low. Overall, CAHs reported that patient satisfaction was high and expressed the desire for more virtual services. Telehealth service selection was informed by perceived community needs and specialist availability. CAHs made infrastructure changes to support telehealth and expressed the desire for more virtual services. Implementation support services helped CAHs integrate telehealth into clinical and operational workflows. There was some increase in telehealth services billed to Medicare, but the volume billed was low and not enough to substantially improve hospital revenue. Future work to inform policy and practice could include standardized, formal community need assessments and assistance finding distant providers to meet those needs and further technical assistance around billing, service selection, and ongoing use to support sustainability.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,116 | 0,102 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,007 |
| Bibliométrie | 0,004 | 0,004 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,004 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».