NURS 6231 Week 5 Care Delivery Model Review Example

What Virtual Nursing Changes and What It Leaves Alone: A Step-by-Step Review of a Remote Nurse Model

Student Name

College of Nursing, Walden University

NURS 6231: Healthcare Systems and Quality Outcomes

Instructor Name

Month Day, Year

What Virtual Nursing Changes and What It Leaves Alone: A Step-by-Step Review of a Remote Nurse Model

Virtual nursing places an experienced registered nurse on camera, working from a hub, to take on part of the work that bedside nurses usually carry. It is usually proposed with a list of outcomes it will improve: satisfaction, safety, throughput and retention. This review evaluates the model as a stand-in health system plans to run it on three medical units. It starts from what the remote nurse will actually do on a shift, maps each step of the admission and discharge pathways as changed, partly changed or unchanged, and derives from that map the outcomes that could move. The review concludes that the model should be expected to improve discharge timing, discharge information and medication reconciliation, and should not be credited with changes in falls or pressure injuries, which depend on bedside work the model does not alter. Published evaluations are then used to test those predictions.

The Model in Operational Terms

In the planned design, two virtual nurses per day shift and one at night cover three 30-bed medical units from a room on the fourth floor. Each patient room has a ceiling camera, a speaker and a screen, activated only when the virtual nurse calls in and the patient accepts. The virtual nurse has full access to the electronic record. The work assigned to the role is specific: the admission history and risk screens, medication reconciliation with the patient and family, discharge teaching with teach-back, and a review of each discharge packet before the patient leaves. The virtual nurse also answers questions from newer bedside nurses. Bedside staffing does not change. Each bedside nurse keeps the same number of patients and remains responsible for assessment, medication administration, mobility, turning and toileting.

This matches the model described by Schuelke et al. (2019), in which an expert nurse joins the room by video and works through six roles: patient education, staff mentoring, real-time quality and safety surveillance, physician rounding, admission activities and discharge activities. The planned design adopts four of those six. It leaves out physician rounding and continuous surveillance, which matters for the outcomes below.

Process Map

Table 1 marks each step of the admission and discharge pathways according to how the model touches it.

Table 1

Admission and Discharge Steps Marked by Degree of Change

The partly changed rows carry the most uncertainty. Removing admissions and discharge teaching from the bedside nurse should free some of that nurse's time. Whether the time goes to direct care, documentation or covering a colleague is not determined by the model. Any outcome that depends on freed bedside time is therefore a possibility, not a prediction.

Outcomes Derived From the Map

Three measures follow directly from changed steps. The first is the interval between the written discharge order and the moment the patient departs. On most medical units, discharge teaching waits until the bedside nurse is free, and a virtual nurse who begins teaching as soon as the order is written should shorten that interval. The second is the survey measure of discharge information from the national HCAHPS patient experience survey, along with its care coordination items, since both ask the patient about what they were told before leaving. The third is medication reconciliation completeness, measured by a pharmacist's audit of a monthly sample of admissions for unresolved discrepancies. Each of these has a clear step behind it.

Two measures do not follow from the map. Falls depend on how often patients are seen, how quickly call lights are answered and whether toileting is scheduled, and none of that work moves to the virtual nurse. Pressure injuries depend on turning and skin care, which also stay at the bedside. The design includes no continuous video surveillance, so the model does not watch patients at risk of falling. If fall or pressure injury rates improve after rollout, the review would look first for another cause, such as a concurrent fall bundle, before crediting virtual nursing. A model credited with an outcome it never touched teaches the organization the wrong lesson, and the error becomes costly when the next budget cycle cuts the step that really produced the result.

Staff turnover and bedside nurse satisfaction sit between the two groups. The mentoring role is a changed step, and a new nurse with an expert available by video may feel better supported. But turnover has many causes, and a single year of data on three units will be too noisy to attribute.

What Published Evaluations Show

The evidence tests these predictions only weakly. The pilot reported by Schuelke et al. (2019) described improvements in patient and staff satisfaction and in quality and financial measures after the virtual team was introduced, but it was a single-system pilot without a concurrent comparison group. A later multisite report by the same group examined missed nursing care using the MISSCARE survey and found that missed care linked to the virtual nurses' duties fell at one of two sites but not at the other (Schuelke et al., 2020). That split result is consistent with the partly changed rows in Table 1: freed time does not reliably turn into completed care.

The larger problem is measurement. A 2026 scoping review of virtual nursing studies found 78 different metrics across 36 sources, and fewer than half were clearly defined or operationalized (Cox et al., 2026). Studies emphasized staff processes and patient outcomes and rarely reported organizational or structural indicators. This means that published claims about virtual nursing are hard to compare, and a health system adopting the model should not expect the literature to predict its results. The review's own predictions, built from the process map, are a firmer guide than the published outcome lists.

Evaluation Plan

The system should evaluate the model on the three measures tied to changed steps, with baselines from the six months before rollout and a comparison with two medical units that do not adopt the model. Discharge order to departure is taken from time stamps in the record, the median reported monthly. Discharge information scores are taken from HCAHPS results for the three units by quarter. Reconciliation completeness comes from a pharmacist's audit of 30 admissions per unit each month, counting unresolved discrepancies. Falls and pressure injuries will continue to be reported, as balancing measures, to confirm that they do not worsen while bedside nurses adjust. Every measure has a defined numerator, denominator and period, answering the concern Cox et al. (2026) raised about undefined metrics. After 12 months, the system will judge the model on whether the changed steps produced the predicted results.

Conclusion

Reviewed step by step, virtual nursing is a change to specific parts of admission and discharge, not to bedside care as a whole. It can reasonably be expected to move the measures that sit downstream of those parts and should not be credited with measures that do not. Published evaluations are small, early and inconsistently measured, so the stand-in system's own evaluation, tied to mechanism, is the evidence that will count.

References

Cox, K., Watson, H., & Whalen, M. (2026). Measuring the impact of virtual nursing in inpatient care: A scoping review. Nursing Outlook, 74(3), Article 102751. https://doi.org/10.1016/j.outlook.2026.102751

Schuelke, S., Aurit, S., Connot, N., & Denney, S. (2019). Virtual nursing: The new reality in quality care. Nursing Administration Quarterly, 43(4), 322-328. https://doi.org/10.1097/NAQ.0000000000000376

Schuelke, S., Aurit, S., Connot, N., & Denney, S. (2020). The effect of virtual nursing and missed nursing care. Nursing Administration Quarterly, 44(3), 280-287. https://doi.org/10.1097/NAQ.0000000000000419