Rescheduling nursing shifts: scoping the challenge and examining the potential of mathematical model based tools

Comparing the Two Techniques for Nursing Staff Rescheduling to Streamline Nurse Managers' Daily Work in Finland

The aim of this study was to identify nurse managers' daily tasks during the rescheduling of sudden nursing staff absences by comparing two techniques: a paper-based system as phone calls and emails or information technology-based staffing systems. In addition, it is intended to evaluate the usability of information technology-based staffing solutions and evaluate estimated cost savings by using hospital permanent staff to cover sudden absences. A quasi-experimental pretest and posttest one-group study design was used to evaluate nurse managers' (n = 61) daily tasks (n = 5800) during rescheduling nursing staff sudden absences (n = 2628); furthermore, we engaged in observations and provided estimates of cost savings generated by our proposed intervention. The number of nurse manager tasks during rescheduling decreased significantly (P < .001) as well as unstaffed shifts (P < .001) and unplanned shift changes (P < .001) after the information technology-based scheduling system was implemented. The usability score ranged from 76 to 100, showing that the information technology-based scheduling solution has good usability. The use of information technology-based staffing solution can streamline the rescheduling process, save nurse managers time for other activities, and offer organizations opportunities for cost savings.

NHS managers’ use of nursing workforce planning and deployment technologies: a realist synthesis

Background

Policy and reviews of health-care safety and quality emphasise the role of NHS managers in ensuring safe, good-quality patient care through effective staffing. Guidance requires that NHS managers combine professional judgement with evidence-based workforce planning and deployment tools and technologies (WPTs). Evidence has focused on the effectiveness of WPTs, but little is known about supporting their implementation, or the impact of using WPTs across settings.

Objectives

The review answered the following question: ‘NHS managers’ use of workforce planning and deployment technologies and their impacts on nursing staffing and patient care: what works, for whom, how and in what circumstances?’.

Design

A realist synthesis was conducted. A programme theory was formulated and expressed as hypotheses in the form of context, mechanisms and outcomes; this considered how, through using WPTs, particular conditions produced responses to generate outcomes. There were four phases: (1) development of a theoretical territory to understand nurse workforce planning and deployment complexity, resulting in an initial programme theory; (2) retrieval, review and synthesis of evidence, guided by the programme theory; (3) testing and refinement of the programme theory for practical application; and (4) actionable recommendations to support NHS managers in the implementation of WPTs for safe staffing.

Participants

NHS managers, patient and public representatives and policy experts informed the programme theory in phase 1, which was validated in interviews with 10 NHS managers. In phase 3, 11 NHS managers were interviewed to refine the programme theory.

Results

Workforce planning and deployment tools and technologies can be characterised functionally by their ability to summarise and aggregate staffing information, communicate about staffing, allocate staff and facilitate compliance with standards and quality assurance. NHS managers need to combine local knowledge and professional judgement with data from WPTs for effective staffing decisions. WPTs are used in a complex workforce system in which proximal factors (e.g. the workforce satisfaction with staffing) can influence distal factors (e.g. organisational reputation and potential staff recruitment). The system comprises multiple organisational strategies (e.g. professional and financial), which may (or may not) align around effective staffing. The positive impact of WPTs can include ensuring that staff are allocated effectively, promoting the patient safety agenda within an organisation, learning through comparison about ‘what works’ in effective staffing and having greater influence in staffing work. WPTs appear to have a positive impact when they visibly integrate data on needs and resources and when there is technical and leadership support. A collaborative process appears to be best for developing and implementing WPTs, so that they are fit for purpose.

Limitations

The evidence, predominantly from acute care, often lacked detail on how managers applied professional judgement to WPTs for staffing decisions. The evidence lacked specificity about how managers develop skills on communicating staffing decisions to patients and the public.

Conclusions and recommendations

The synthesis produced initial explanations of the use and impact of WPTs for decision-making and what works to support NHS managers to use these effectively. It is suggested that future research should further evaluate the programme theory.

Study registration

This study is registered as PROSPERO CRD42016038132.

Funding

The National Institute for Health Research Health Services and Delivery Research programme.

A computational application for multi-skill nurse staffing in hospital units

Background

Approaches to nurse staffing are commonly concerned with determining the minimum number of care hours according to the illness severity of patients. However, there is a gap in the literature considering multi-skill and multi-shift nurse staffing. This study addresses nurse staffing per skill category, at a strategical decision level, by considering the organization of work in shifts and coping with variability in demand.

Methods

We developed a method to determine the nursing staff levels in a hospital, given the required patient assistance. This method relies on a new mathematical model for complying with the legislation and guidelines while minimizing salary costs. A spreadsheet-based tool was developed to embed the model and to allow simulating different scenarios and evaluating the impact of demand fluctuations, thus supporting decision-making on staff dimensioning.

Results

Experiments were carried out considering real data from a Brazilian hospital unit. The results obtained by the model support the current total staff level in the unit under study. However, the distribution of staff among different skill categories revealed that the current real situation can be improved.

Conclusions

The method allows the determining of staff level per shift and skill depending on the mix of patients’ illness severity. Hospital management is offered the possibility of optimizing the staff level using a spreadsheet, a tool most managers are familiar with. In addition, it is possible to evaluate the implications of decisions on workforce dimensioning by simulating different demand scenarios. This tool can be easily adapted to other hospitals, using local rules and legislation.

Electronic supplementary material

The online version of this article (10.1186/s12911-018-0638-2) contains supplementary material, which is available to authorized users.

Nurse workforce scheduling in the emergency department: A sequential decision support system considering multiple objectives

AIM

We propose a nurse scheduling framework based on a set of performance measures that are aligned with multiple outcome measures. A case study for the emergency department is presented.

METHODS

A total of 142,564 emergency department attendances over 1 year were included in this study. Operational requirements, constraints and historical workload data were translated into a mixed-integer sequential goal programming model, which considers the following outcome measures: (1) nurse-patient ratios; (2) number of favourable/unfavourable shifts; and (3) dispersion of rest days. Computational studies compared the performance of the mixed-integer sequential goal programming results with manually generated historical nurse schedules.

RESULTS

The maximum nurse-patient ratio deviation against the target was approximately 10% compared to 47% generated by the historical rosters (a 10% deviation translates to approximately two nurses). An on-line decision support system, which integrates shift preferences, staff databases and a workload forecasting module, was also developed.

CONCLUSION

A decision support system based on the mixed-integer sequential goal programming modelling framework was proposed. The application of the model in a case study for an emergency department demonstrated improvements over existing manual scheduling methods.

IMPLICATIONS FOR NURSING MANAGEMENT

This study demonstrates a mathematical, programming-based decision support system, which allows for managerial priorities and nurse preferences to be jointly considered in the automatic generation of nurse rosters.