Balancing nurses' workload in hospital wards: Study protocol of developing a method to manage workload

Abstract

Introduction: Hospitals pursue different goals at the same time: excellent service to their patients, good quality care, operational excellence, retaining employees. This requires a good balance between patient needs and nursing staff. One way to ensure a proper fit between patient needs and nursing staff is to work with a workload management method. In our view, a nursing workload management method needs to have the following characteristics: easy to interpret; limited additional registration; applicable to different types of hospital wards; supported by nurses; covers all activities of nurses and suitable for prospective planning of nursing staff. At present, no such method is available. Methods/analysis: The research follows several steps to come to a workload management method for staff nurses. First, a list of patient characteristics relevant to care time will be composed by performing a Delphi study among staff nurses. Next, a time study of nurses' activities will be carried out. The 2 can be combined to estimate care time per patient group and estimate the time nurses spend on non-patient-related activities. These 2 estimates can be combined and compared with available nursing resources: this gives an estimate of nurses' workload. The research will take place in an academic hospital in the Netherlands. 6 surgical wards will be included, capacity 15-30 beds. Ethical considerations: The study protocol was submitted to the Medical Ethical Review Board of the University Medical Center (UMC) Utrecht and received a positive advice, protocol number 14-165/C. Discussion: This method will be developed in close cooperation with staff nurses and ward management. The strong involvement of the end users will contribute to a broader support of the results. The method we will develop may also be useful for planning purposes; this is a strong advantage compared with existing methods, which tend to focus on retrospective analysis.