Evidence map›Paper›PMID 37525521›Full record

ArticleHealth services research2023

Evaluation of safety and care outcomes after the introduction of a virtual registered nurse model.

Samuel T Savitz, Ryannon K Frederick, Lindsey R Sangaralingham, Michelle A Lampman, Stephanie S Anderson, Elizabeth B Habermann, Sarah J Bell

Open access · bronzeAbstract read
In one paragraph

Article in Health services research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
3.8field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 13 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Samuel T SavitzRobert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA.ORCID 0000-0003-3190-7740
Ryannon K FrederickDepartment of Nursing, Mayo Clinic, Rochester, Minnesota, USA.
Lindsey R SangaralinghamRobert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA.
Michelle A LampmanRobert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA.
Stephanie S AndersonRobert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA.
Elizabeth B HabermannRobert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA.
Sarah J BellDepartment of Nursing, Mayo Clinic, Rochester, Minnesota, USA.
Mayo Clinic in Arizona · USMayo Clinic · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo 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

settingElectronic 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

designThis 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

findingsThere 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.

conclusionsOur 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.

Indexed as

NursesTelemedicineHospital MortalityHumansIntensive Care UnitsLength of Stayhospitalizationnursingquality improvementquality of caretelemedicine

Identifiers

PMID37525521
PMCPMC10480082
OpenAlexW4385441877

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.