Automating the self-scheduling process of nurses in Swedish healthcare: a pilot study

The impact of electronic and self-rostering systems on healthcare organisations and healthcare workers: A mixed-method systematic review

AIM

To synthesise evidence from studies that explored the impact of electronic and self-rostering systems to schedule staff on healthcare organisations and healthcare workers.

DESIGN

Mixed-method systematic review.

METHODS

Studies were screened by two independent reviewers and data were extracted using standardised data extraction tables. The quality of studies was assessed, and parallel-results convergent synthesis was conducted.

DATA SOURCES

Academic Search Complete, CINAHL, ERIC, MEDLINE, PsycINFO and PsycARTICLES were searched on January 3, 2023.

RESULTS

Eighteen studies were included (10 quantitative descriptive studies, seven non-randomised studies and one qualitative study). Studies examined two rostering interventions including self-rostering (n = 12) and electronic rostering (n = 6). It was found that the implementation of electronic and self-rostering systems for staff scheduling impacted positively on both, healthcare workers and healthcare organisations. Benefits included enhanced roster efficiency, staff satisfaction, greater control and empowerment, improved work-life balance, higher staff retention and reduced turnover, decreased absence rates and enhanced healthcare efficiency. However, self-rostering was found to be less equitable than fixed rostering, was associated with increased overtime, and correlated with a higher frequency of staff requests for shift changes.

CONCLUSION

The impact of electronic and self-rostering systems to schedule staff on healthcare organisations and healthcare workers' outcomes was predominantly positive. Further randomised controlled trials and longitudinal studies are warranted to evaluate the long-term impact of various rostering systems, including electronic and self-rostering systems.

IMPLICATIONS FOR HEALTHCARE

Rostering is a multifaceted responsibility for healthcare administrators, impacting patient care quality, workforce planning and healthcare expenditure.

IMPACT

Given that healthcare staffing costs constitute a substantial portion of global healthcare expenditure, efficient and strategic resource management, inclusive of healthcare staff rostering, is imperative.

REPORTING METHOD

The 27-item Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) checklist.

PATIENT OR PUBLIC CONTRIBUTION

No Patient or Public Contribution.

Nurse rostering with fatigue modelling : Incorporating a validated sleep model with biological variations in nurse rostering

We use a real Nurse Rostering Problem and a validated model of human sleep to formulate the Nurse Rostering Problem with Fatigue. The fatigue modelling includes individual biologies, thus enabling personalised schedules for every nurse. We create an approximation of the sleep model in the form of a look-up table, enabling its incorporation into nurse rostering. The problem is solved using an algorithm that combines Mixed-Integer Programming and Constraint Programming with a Large Neighbourhood Search. A post-processing algorithm deals with errors, to produce feasible rosters minimising global fatigue. The results demonstrate the realism of protecting nurses from highly fatiguing schedules and ensuring the alertness of staff. We further demonstrate how minimally increased staffing levels enable lower fatigue, and find evidence to suggest biological complementarity among staff can be used to reduce fatigue. We also demonstrate how tailoring shifts to nurses' biology reduces the overall fatigue of the team, which means managers must grapple with the issue of fairness in rostering.

Giving nurses a voice through 'listening to staff' conversations to inform nurse retention and reduce turnover

Health and social care employers in the UK cannot afford to lose nurses given the current nursing workforce crisis. A variety of staff engagement initiatives aim to improve employee retention. This article describes how Listening to Staff (L2S) events were used as part of a service review to inform nurse retention strategies in one acute hospital trust. Over a 3-year period, 576 nurses took part in L2S events that examined nurses' perspectives of teamworking and support as well as career plans in areas with high nurse turnover rates. Comparative content analysis was used to analyse narrative data, which informed managers' retention plans. Examination of retention data before and after L2S events showed nursing turnover decreased, suggesting a variety of strategies to retain staff may have improved nurse retention. Findings imply capturing nurses' perceptions through staff engagement events may offer solutions for nurse retention.

The effect of self-scheduling on organizational justice and work attitudes through leader-member exchange: A cross-sectional study using propensity scores

BACKGROUND

Nurses have a very stressful and demanding job, which probably affects their health and well-being. This has resulted in a search for an optimal nurse schedule. Self-scheduling is one method to enhance flexibility and give more control to the employee. Literature on self-scheduling is scarce and mainly focused on the implementation process. So far, little is known about the long-term effects of self-scheduling.

OBJECTIVE

The comparison of effects of self-scheduling versus fixed scheduling on three dimensions of organizational justice (distributive, procedural, interactional justice) and three work attitudes (job satisfaction, affective commitment, global empowerment). This total effect is decomposed into direct and indirect effects via hypothesised mediators (leader-member exchange and organizational justice).

DESIGN

A cross-sectional multisite-matched study.

SETTING

A questionnaire was distributed to nurses and nurse assistants of twelve nursing homes in Flanders (Belgium). Six matched pairs of nursing homes were formed, each containing a nursing home that uses self-scheduling (for at least one year) and one that uses fixed scheduling.

PARTICIPANTS

The study sample included 308 nurses and nurse assistants, of which 160 surveys were from nursing homes using fixed scheduling, versus 148 surveys from nursing homes using self-scheduling.

METHODS

Using a double robust fixed effects regression model adjusted for the propensity score, the total effect of self-scheduling compared to fixed scheduling was analysed on the proposed outcomes. Subsequently, a (multiple) mediation analysis was performed.

RESULTS

If all people would have used self-scheduling instead of fixed scheduling, on average a significant decrease in the mean procedural justice score (estimated mean difference = -0.20, 95% CI -0.36 to -0.05) would be found. There is a significant negative direct effect (estimated mean difference = -0.12, 95% CI -0.21 to -0.03) and indirect effect via the mediator leader-member-exchange (estimated mean difference = -0.08, 95% CI -0.15 to -0.01) on procedural justice. In addition, significant negative indirect effects of self-scheduling were found via the mediator leader-member exchange on all the investigated outcomes.

CONCLUSION

Drawing up the work schedule is perceived as less fair in the case of self-scheduling. Furthermore, self-scheduling has a negative indirect effect on several work attitudes as a result of the changed relationship between the head nurse and the employees. The increase in task variety and decision-making autonomy for the employees and the altered leadership role of the head nurse can have a major impact on the dynamics of the entire team.

Systematic review: What is the impact of self-scheduling on the patient, nurse and organization?

AIM

To systematically review and evaluate the literature on the impact of self-scheduling on patient, nurse and organization-related outcomes.

DESIGN

A systematic review.

DATA SOURCES

PubMed, Embase, Web of Science, Cinahl, Scopus, Google Scholar, ERIC and Cochrane Library were screened until October 2019 (week 40) for peer-reviewed, empirical articles, written in English, Dutch or French.

REVIEW METHODS

Two reviewers screened title and abstract using predetermined eligibility criteria and one reviewer screened the full texts of relevant hits. Quality was assessed with the Mixed Methods Appraisal Tool.

RESULTS

Studies (N = 23) were retained and classified into explanatory and descriptive studies. The articles reported on a range of outcomes: patient- and nurse-reported quality of care, job satisfaction, satisfaction with scheduling, work/life balance, planning involvement, interaction with colleagues, health and well-being, psychosocial factors, professional development, nurse manager's scheduling time, general working conditions, turnover, temporary employment agency use and absenteeism, recruitment and retention.

CONCLUSION

The evidence base is limited. Several studies confirmed the positive impact of self-scheduling on the nurse and the organization. However, other studies found negative outcomes or no change. These outcomes should be interpreted in the light of contextual factors and the implementation process, which was often not without difficulties. Future research should use a multimethod longitudinal design, bear in mind the possibilities of quantitative research (e.g. for studying psychosocial factors) and employ a theoretical framework.

IMPACT

This review informs about the inconsistent evidence on the association between self-scheduling and patient, nurse and organization-related outcomes and includes enablers and barriers to a successful implementation. These outcomes are influenced by the implementation process and the sustainability of the self-scheduling system, which are still major challenges for healthcare management. This demonstrates the urgent need for further research.

Sustainable Personnel Scheduling Problem Optimization in a Natural Gas Combined-Cycle Power Plant

This paper deals with a sustainable personnel scheduling problem of personnel working in a large-scale natural gas combined-cycle power plant in Turkey. The proposed model focuses on employee complaints due to unfair work schedules and the results of balanced assignments based on power plant interruptions. Eighty personnel work in three shifts at this natural gas combined-cycle power plant. The model is solved with respect to some of the workers’ skills, and there are 20 criteria regarding skills. The analytic network process method is used to get the weights of workers’ skills, which are calculated and included in the model. Goal programming is used in this paper. Our proposed model gives cost minimization and fair work schedules for the power plant. Compared with the literature, the number and set of criteria are unique in terms of personnel competency in the energy sector. Minimizing cost and imbalanced assignments was achieved by the proposed model for the first time without considering the sector.

Staff Task-Based Shift Scheduling Solution with an ANP and Goal Programming Method in a Natural Gas Combined Cycle Power Plant

Shift scheduling problems (SSPs) are advanced NP-hard problems which are generally evaluated with integer programming. This study presents an applicable shift schedule of workers in a large-scale natural gas combined cycle power plant (NGCCPP), which realize 35.17% of the total electricity generation in Turkey alone, as at of the end of 2018. This study included 80 workers who worked three shifts in the selected NGCCPP for 30 days. The proposed scheduling model was solved according to the skills of the workers, and there were nine criteria by which the workers were evaluated for their abilities. Analytic network process (ANP) is a method used for obtaining the weights of workers’ abilities in a particular skill. These weights are used in the proposed scheduling model as concepts in goal programming (GP). The SSP–ANP–GP model sees employees’ everyday preferences as their main feature, bringing high-performance to the highest level, and bringing an objective functionality, and lowering the lowest success of daily choice. At the same time, the model introduced large-scale and soft constraints that reflect the nature of the shift requirements of this program by specifying the most appropriate program. The required data were obtained from the selected NGCCPP and the model solutions were approved by the plant experts. The SSP–ANP–GP model was resolved at a reasonable time. Monthly acquisition time was significantly reduced, and the satisfaction of the employees was significantly increased by using the obtained program. When past studies were examined, it was determined that a shift scheduling problem of this size in the energy sector had not previously been studied.

Optimizing nurse capacity in a teaching hospital neonatal intensive care unit

Patients in intensive care units need special attention. Therefore, nurses are one of the most important resources in a neonatal intensive care unit. These nurses are required to have highly specialized training. The random number of patient arrivals, rejections, or transfers due to lack of capacity (such as nurse, equipment, bed etc.) and the random length of stays, make advanced knowledge of the optimal nurse a requirement, for levels of the unit behave as a stochastic process. This stochastic nature creates difficulties in finding optimal nurse staffing levels. In this paper, a stochastic approximation which is based on the required nurse: patient ratio and the number of patients in a neonatal intensive care unit of a teaching hospital, has been developed. First, a meta-model was built to generate simulation results under various numbers of nurses. Then, those experimented data were used to obtain the mathematical relationship between inputs (number of nurses at each level) and performance measures (admission number, occupation rate, and satisfaction rate) using statistical regression analysis. Finally, several integer nonlinear mathematical models were proposed to find optimal nurse capacity subject to the targeted levels on multiple performance measures. The proposed approximation was applied to a Neonatal Intensive Care Unit of a large hospital and the obtained results were investigated.

Insights into physician scheduling: a case study of public hospital departments in Sweden

PURPOSE

The purpose of this paper is to describe current physician scheduling and concomitant opportunities for improvement in public hospital departments in Sweden.

DESIGN/METHODOLOGY/APPROACH

A total of 13 departments spread geographically across Sweden covering seven different specialties participated in the study. Data were collected through interviews with individuals involved in creating physician schedules. All departments investigated provided copies of the documents necessary for physician scheduling.

FINDINGS

Physician scheduling required the temporal coordination of patients, physicians, non-physician staff, rooms and equipment. A six-step process for creating physician schedules could be distinguished: capacity and demand overview, demand goal and schedule setting, vacation and leave requests, schedule creation, schedule revision, and schedule execution. Several opportunities for improvement could be outlined; e.g. overreliance on memory, lacking coordination of resources, and redundant data entering.

RESEARCH LIMITATIONS/IMPLICATIONS

The paucity of previous studies on physician scheduling lends an exploratory character to this study and calls for a more thorough evaluation of the feasibility and effects of the approaches proposed. The study excluded the scheduling of non-physician staff.

PRACTICAL IMPLICATIONS

To improve physician scheduling and enable timeliness, three approaches are proposed: reinforcing centralisation, creating learning opportunities, and improving integration.

ORIGINALITY/VALUE

This paper is among the few to investigate physician scheduling, which is essential for delivering high quality care, particularly concerning timeliness. Several opportunities for improvement identified in this study are not exclusive to physician scheduling but are pervasive in healthcare processes in general.

Guidelines for successful self-scheduling on nursing units

Self-scheduling programs are an increasingly popular strategy utilized by employers to address the individual and organizational challenges resulting from employee work-life imbalance among the nursing workforce. Certain key components will ensure buy-in and support from staff when self-scheduling programs are developed.