What do we know about the impact of hospital nurse staffing on patients, staff and the costs of care?

What is the aim of this review?

The aim of this Cochrane Review was to find out if changes made to nurse staffing in hospitals improve outcomes for patients or nurses, or have an impact on the cost of health care. Nurse staffing can refer to the number of nurses per patient, the mix of different types of nurses in a hospital unit, or models used to allocate nurses to patients in a hospital unit.

Key messages

The research relating to hospital nurse staffing is very limited and the findings should be treated with caution.

It is unlikely that adding nurses with advanced nursing skills (Nurse Practitioners (NPs)) or with expertise in a particular area of practice (Clinical Nurse Specialists (CNSs)) to hospital nurse staffing makes any difference to patient death rates. We cannot be sure what other effect it might have on patients, for example, if it reduces the time patients spend in hospital or the costs of patient care. We cannot be sure if changes to the way in which nurses are allocated to patient care reduces the numbers of nurses resigning, or if introducing unqualified nurses to the nursing workforce reduces costs, as the research here is very limited too.

What was studied in the review?

We found studies that looked at the effects of four main strategies or models of nurse staffing: adding advanced or specialist nurses to the nursing workforce, introducing less-qualified nursing personnel to the nursing workforce, changing the way in which nurses are allocated within a hospital unit to provide patient care, and changing the way hospital units schedule nursing shifts. We were most interested in the impact of these interventions on seven main outcomes: nursing-staff resignations (turnover), patient deaths, patients being readmitted following discharge from the hospital, patients attending the Emergency Department (ED) for care following discharge, the number of days patients stayed in the hospital, the number of patients with pressure sores, and the costs of care.

What are the main results of the review?

We found 11 studies where advanced or specialist nurses were added to the nursing workforce. None of the studies reported the impact of this intervention on nursing-staff resignations; three studies found that it may make little or no difference to patient deaths. We cannot be sure whether this intervention has an effect on reducing the number of patients being readmitted following discharge from hospital or attending an ED for care after discharge because the research is very limited. As well, we are uncertain about its effect on reducing the number of days patients stayed in the hospital, the number of patients with pressure sores, or healthcare costs, again because the research is very limited.

We found one relevant study that looked at adding nursing assistants to the nursing workforce, which was aimed at reducing costs. We cannot be sure about the effect on costs as the research is very limited.

We found five studies of primary nursing (where one nurse is responsible for the total care of a number of patients 24 hours a day, seven days a week) and two studies of nurse-staffing models. One nurse-staffing model study tested hospital units scheduling their own nursing shifts (self-staffing), and the other study compared different ways to schedule nursing shifts. We cannot be sure about the impact of primary nursing or nurse-staffing models on nurse resignations or costs because the research is very limited.

How up-to-date is this review?

The review authors searched for studies that had been published up to March 2018.

Authors' conclusions: 

The findings of this review should be treated with caution due to the limited amount and quality of the published research that was included. We have most confidence in our finding that the introduction of advanced or specialist nurses may lead to little or no difference in one patient outcome (i.e. mortality) with greater uncertainty about other patient outcomes (i.e. readmissions, ED attendance, length of stay and pressure ulcer rates). The evidence is of insufficient certainty to draw conclusions about the effectiveness of other types of interventions, including new nurse-staffing models and introduction of nursing assistive personnel, on patient, staff and cost outcomes. Although it has been seven years since the original review was published, the certainty of the evidence about hospital nurse staffing still remains very low.

Read the full abstract...
Background: 

Nurses comprise the largest component of the health workforce worldwide and numerous models of workforce allocation and profile have been implemented. These include changes in skill mix, grade mix or qualification mix, staff-allocation models, staffing levels, nursing shifts, or nurses’ work patterns. This is the first update of our review published in 2011.

Objectives: 

The purpose of this review was to explore the effect of hospital nurse-staffing models on patient and staff-related outcomes in the hospital setting, specifically to identify which staffing model(s) are associated with: 1) better outcomes for patients, 2) better staff-related outcomes, and, 3) the impact of staffing model(s) on cost outcomes.

Search strategy: 

CENTRAL, MEDLINE, Embase, two other databases and two trials registers were searched on 22 March 2018 together with reference checking, citation searching and contact with study authors to identify additional studies.

Selection criteria: 

We included randomised trials, non-randomised trials, controlled before-after studies and interrupted-time-series or repeated-measures studies of interventions relating to hospital nurse-staffing models. Participants were patients and nursing staff working in hospital settings. We included any objective reported measure of patient-, staff-related, or economic outcome. The most important outcomes included in this review were: nursing-staff turnover, patient mortality, patient readmissions, patient attendances at the emergency department (ED), length of stay, patients with pressure ulcers, and costs.

Data collection and analysis: 

We worked independently in pairs to extract data from each potentially relevant study and to assess risk of bias and the certainty of the evidence.

Main results: 

We included 19 studies, 17 of which were included in the analysis and eight of which we identified for this update. We identified four types of interventions relating to hospital nurse-staffing models:

- introduction of advanced or specialist nurses to the nursing workforce;

- introduction of nursing assistive personnel to the hospital workforce;

- primary nursing; and

- staffing models.

The studies were conducted in the USA, the Netherlands, UK, Australia, and Canada and included patients with cancer, asthma, diabetes and chronic illness, on medical, acute care, intensive care and long-stay psychiatric units. The risk of bias across studies was high, with limitations mainly related to blinding of patients and personnel, allocation concealment, sequence generation, and blinding of outcome assessment.

The addition of advanced or specialist nurses to hospital nurse staffing may lead to little or no difference in patient mortality (3 studies, 1358 participants). It is uncertain whether this intervention reduces patient readmissions (7 studies, 2995 participants), patient attendances at the ED (6 studies, 2274 participants), length of stay (3 studies, 907 participants), number of patients with pressure ulcers (1 study, 753 participants), or costs (3 studies, 617 participants), as we assessed the evidence for these outcomes as being of very low certainty. It is uncertain whether adding nursing assistive personnel to the hospital workforce reduces costs (1 study, 6769 participants), as we assessed the evidence for this outcome to be of very low certainty. It is uncertain whether primary nursing (3 studies, > 464 participants) or staffing models (1 study, 647 participants) reduces nursing-staff turnover, or if primary nursing (2 studies, > 138 participants) reduces costs, as we assessed the evidence for these outcomes to be of very low certainty.

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