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Evaluation of safety and care outcomes after the introduction of a virtual registered nurse model.
Savitz, Samuel T; Frederick, Ryannon K; Sangaralingham, Lindsey R; Lampman, Michelle A; Anderson, Stephanie S; Habermann, Elizabeth B; Bell, Sarah J.
Afiliación
  • Savitz ST; Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA.
  • Frederick RK; Division of Health Care Delivery Research, Mayo Clinic, Rochester, Minnesota, USA.
  • Sangaralingham LR; Department of Nursing, Mayo Clinic, Rochester, Minnesota, USA.
  • Lampman MA; Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA.
  • Anderson SS; Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA.
  • Habermann EB; Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA.
  • Bell SJ; Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA.
Health Serv Res ; 58(5): 999-1013, 2023 10.
Article en En | MEDLINE | ID: mdl-37525521
ABSTRACT

OBJECTIVE:

To evaluate the impact of a virtual registered nurse (ViRN) model on safety and care outcomes. ViRN is a telemedicine intervention that enables an experienced virtual nurse to assist the in-person care team in providing care to patients. DATA SOURCES AND STUDY

SETTING:

Electronic health records data were utilized from the Mayo Clinic during the intervention (December 2020-November 2021) and historical periods (December 2018-November 2019). ViRN was implemented on general medical units at the Mayo Clinic Rochester. We used general medical units at the Mayo Clinic Arizona as the comparison group. STUDY

DESIGN:

This study used a difference-in-differences design to evaluate the impact of ViRN compared to usual care on transfer to the intensive care unit (ICU), inpatient mortality, and length of stay (LOS). We used logistic regression for transfer to the ICU and inpatient mortality and negative binomial regression for LOS. We controlled for demographics, patient interaction with the health system, clinical characteristics, and admission characteristics. We clustered standard errors to account for patients who have multiple admissions during the study period. PRINCIPAL

FINDINGS:

There were no significant differences for transfer to the ICU (average marginal effect (AME) -0.08 percentage point [95% confidence interval (CI) -1.34, 1.18]), inpatient mortality (AME 0.43 percentage point [95% CI -0.33, 1.18]), or LOS (AME -0.20 days [95% CI -0.57, 0.17]). The findings were mostly consistent across the sensitivity analyses.

CONCLUSIONS:

Our results suggest that ViRN led to similar outcomes as usual care in general medical units. These findings support the potential to develop more advanced models of ViRN at the Mayo Clinic and the dissemination of the ViRN model to other systems. In the context of staffing shortages and other disruptions to the delivery of nursing care, it is critical to understand whether new models like ViRN provide nurse staffing alternatives without negatively affecting outcomes.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Contexto en salud: 1_ASSA2030 Problema de salud: 1_sistemas_informacao_saude Asunto principal: Telemedicina / Enfermeras y Enfermeros Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Health Serv Res Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Contexto en salud: 1_ASSA2030 Problema de salud: 1_sistemas_informacao_saude Asunto principal: Telemedicina / Enfermeras y Enfermeros Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Health Serv Res Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos
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