Harnessing ward‐level administrative data and expert knowledge to improve staffing decisions: A multi‐method case study

Nurse/midwife-to-patient ratios: A scoping review

BACKGROUND

A significant body of work has linked high nurse or midwife workload to negative patient outcomes. Anecdotal reports suggest that mandated ratio models enhance patient care and improve nurse job satisfaction. However, there is limited focused research.

OBJECTIVE

To identify key outcomes, implementation processes, and research needs regarding nurse/midwife-to-patient ratios in the Australian healthcare context.

DESIGN

Scoping review.

METHODS

Data sources were CINAHL, Open Dissertations, Medline, and Scopus. 289 articles screened, and 53 full text documents independently assessed against criteria by two reviewers and conflicts resolved by a third reviewer, using Covidence™. Three studies were included in this review.

RESULTS

Studies focused on nurse (job satisfaction, burnout), patient (mortality, readmission, length of stay) and system (costs) outcomes with limited information on implementation processes and no midwifery research.

CONCLUSIONS

Ratios provide benefits for patients, nurses, and hospitals although there is limited research in Australia. Implementation was poorly reported..

Extending the role of nursing assistants in mental health inpatient settings: A multi-method study

With continued growth in the demand for nursing care, many organizations have incorporated nursing assistants into the acute care workforce. However, role descriptions are often generic and do not provide clarity in specialist areas such as mental health inpatient settings. Issues have been noted regarding the role of assistants, delegation, and their integration with the nursing team. This study extended an existing set of care activities and explored the perceptions of nursing assistants and registered nurses regarding these activities. A modified Delphi approach added 14 new care activities for nursing assistants. A follow-up survey found significant differences between nursing assistants and registered nurses regarding utilization of the activities, delegation, teamwork, and role clarity. Future research must incorporate the perspectives of those with lived experience of mental health issues, and develop an understanding of the interactions between nursing assistant care activities and other factors such as local supports, skillmix, and the practice environment, as these may impact how an organization can introduce nursing assistants to specialty areas while maintaining consumer and staff safety.

Workforce management and patient outcomes in the intensive care unit during the COVID-19 pandemic and beyond: a discursive paper

AIMS

To highlight the need for the development of effective and realistic workforce strategies for critical care nurses, in both a steady state and pandemic.

BACKGROUND

In acute care settings, there is an inverse relationship between nurse staffing and iatrogenesis, including mortality. Despite this, there remains a lack of consensus on how to determine safe staffing levels. Intensive care units (ICU) provide highly specialised complex healthcare treatments. In developed countries, mortality rates in the ICU setting are high and significantly varied after adjustment for diagnosis. The variability has been attributed to systems, patient and provider issues including the workload of critical care nurses.

DESIGN

Discursive paper.

FINDINGS

Nursing workforce is the single most influential mediating variable on ICU patient outcomes. Numerous systematic reviews have been undertaken in an effort to quantify the effect of critical care nurses on mortality and morbidity, invariably leading to the conclusion that the association is similar to that reported in acute care studies. This is a consequence of methodological limitations, inconsistent operational definitions and variability in endpoint measures. We evaluated the impact inadequate measurement has had on capturing relevant critical care data, and we argue for the need to develop effective and realistic ICU workforce measures.

CONCLUSION

COVID-19 has placed an unprecedented demand on providing health care in the ICU. Mortality associated with ICU admission has been startling during the pandemic. While ICU systems have largely remained static, the context in which care is provided is profoundly dynamic and the role and impact of the critical care nurse needs to be measured accordingly. Often, nurses are passive recipients of unplanned and under-resourced changes to workload, and this has been brought into stark visibility with the current COVID-19 situation. Unless critical care nurses are engaged in systems management, achieving consistently optimal ICU patient outcomes will remain elusive.

RELEVANCE TO CLINICAL PRACTICE

Objective measures commonly fail to capture the complexity of the critical care nurses' role despite evidence to indicate that as workload increases so does risk of patient mortality, job stress and attrition. Critical care nurses must lead system change to develop and evaluate valid and reliable workforce measures.

Beyond ratios - flexible and resilient nurse staffing options to deliver cost-effective hospital care and address staff shortages: A simulation and economic modelling study

BACKGROUND

In the face of pressure to contain costs and make best use of scarce nurses, flexible staff deployment (floating staff between units and temporary hires) guided by a patient classification system may appear an efficient approach to meeting variable demand for care in hospitals.

OBJECTIVES

We modelled the cost-effectiveness of different approaches to planning baseline numbers of nurses to roster on general medical/surgical units while using flexible staff to respond to fluctuating demand.

DESIGN AND SETTING

We developed an agent-based simulation, where hospital inpatient units move between being understaffed, adequately staffed or overstaffed as staff supply and demand (as measured by the Safer Nursing Care Tool patient classification system) varies. Staffing shortfalls are addressed by floating staff from overstaffed units or hiring temporary staff. We compared a standard staffing plan (baseline rosters set to match average demand) with a higher baseline 'resilient' plan set to match higher than average demand, and a low baseline 'flexible' plan. We varied assumptions about temporary staff availability and estimated the effect of unresolved low staffing on length of stay and death, calculating cost per life saved.

RESULTS

Staffing plans with higher baseline rosters led to higher costs but improved outcomes. Cost savings from lower baseline staff mainly arose because shifts were left understaffed and much of the staff cost saving was offset by costs from longer patient stays. With limited temporary staff available, changing from low baseline flexible plan to the standard plan cost £13,117 per life saved and changing from the standard plan to the higher baseline 'resilient' plan cost £8,653 per life saved. Although adverse outcomes from low baseline staffing reduced when more temporary staff were available, higher baselines were even more cost-effective because the saving on staff costs also reduced. With unlimited temporary staff, changing from low baseline plan to the standard cost £4,520 per life saved and changing from the standard plan to the higher baseline cost £3,693 per life saved.

CONCLUSION

Shift-by-shift measurement of patient demand can guide flexible staff deployment, but the baseline number of staff rostered must be sufficient. Higher baseline rosters are more resilient in the face of variation and appear cost-effective. Staffing plans that minimise the number of nurses rostered in advance are likely to harm patients because temporary staff may not be available at short notice. Such plans, which rely heavily on flexible deployments, do not represent an efficient or effective use of nurses.

STUDY REGISTRATION

ISRCTN 12307968 Tweetable abstract: Economic simulation model of hospital units shows low baseline staff levels with high use of flexible staff are not cost-effective and don't solve nursing shortages.

Staffing policy in aged care must look beyond the numbers

The COVID-19 pandemic has highlighted an aged care system struggling to meet the needs of vulnerable Australians. Staffing levels and skill mix in aged care have declined, whereas the health and social needs of an older and more clinically complex population have risen. Increasing staff and improving personal care workers' skills and education are essential steps to quality aged care in Australia, but it will not be possible without funding models that foster secure employment, development opportunities and long-term career pathways.

Costs and consequences of using average demand to plan baseline nurse staffing levels: a computer simulation study

Background

Planning numbers of nursing staff allocated to each hospital ward (the ‘staffing establishment’) is challenging because both demand for and supply of staff vary. Having low numbers of registered nurses working on a shift is associated with worse quality of care and adverse patient outcomes, including higher risk of patient safety incidents. Most nurse staffing tools recommend setting staffing levels at the average needed but modelling studies suggest that this may not lead to optimal levels.

Objective

Using computer simulation to estimate the costs and understaffing/overstaffing rates delivered/caused by different approaches to setting staffing establishments.

Methods

We used patient and roster data from 81 inpatient wards in four English hospital Trusts to develop a simulation of nurse staffing. Outcome measures were understaffed/overstaffed patient shifts and the cost per patient-day. We compared staffing establishments based on average demand with higher and lower baseline levels, using an evidence-based tool to assess daily demand and to guide flexible staff redeployments and temporary staffing hires to make up any shortfalls.

Results

When baseline staffing was set to meet the average demand, 32% of patient shifts were understaffed by more than 15% after redeployment and hiring from a limited pool of temporary staff. Higher baseline staffing reduced understaffing rates to 21% of patient shifts. Flexible staffing reduced both overstaffing and understaffing but when used with low staffing establishments, the risk of critical understaffing was high, unless temporary staff were unlimited, which was associated with high costs.

Conclusion

While it is common practice to base staffing establishments on average demand, our results suggest that this may lead to more understaffing than setting establishments at higher levels. Flexible staffing, while an important adjunct to the baseline staffing, was most effective at avoiding understaffing when high numbers of permanent staff were employed. Low staffing establishments with flexible staffing saved money because shifts were unfilled rather than due to efficiencies. Thus, employing low numbers of permanent staff (and relying on temporary staff and redeployments) risks quality of care and patient safety.