Reducing Disparities in No Show Rates Using Predictive Model-Driven Live Appointment Reminders for At-Risk Patients: a Randomized Controlled Quality Improvement Initiative

BACKGROUND: Appointment no shows are prevalent in safety-net healthcare systems. The efficacy and equitability of using predictive algorithms to selectively add resource-intensive live telephone outreach to standard automated reminders in such a setting is not known. OBJECTIVE: To determine if addin...

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Detalles Bibliográficos
Autores principales: Tarabichi, Yasir, Higginbotham, Jessica, Riley, Nicholas, Kaelber, David C., Watts, Brook
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10150669/
https://www.ncbi.nlm.nih.gov/pubmed/37126125
http://dx.doi.org/10.1007/s11606-023-08209-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10150669/
https://www.ncbi.nlm.nih.gov/pubmed/37126125
http://dx.doi.org/10.1007/s11606-023-08209-0

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