It is well-known that unpredictable variations in supply and demand of capacity in healthcare systems create the need for flexibility. The main tools used to create short-term volume flexibility in the healthcare system include overtime, temporary staff from internal calling lists, moving staff across units, internal staffing pools, external staffing agencies, queuing patients, and purchasing care from external providers. We study the creation of short-term volume flexibility in healthcare systems to manage short-term capacity losses and demand fluctuations. A questionnaire was developed and distributed among healthcare managers in the Region Västra Götaland healthcare system. Respondents were asked to what extent they used each tool to create short-term flexibility in capacity. Data were analyzed using multiple regression analysis. Several significant tendencies were found, including that acute units use overtime and internal staffing pools to a larger extent, and queuing patients and external providers to a lesser extent than planned units. The prerequisites and required managerial approaches used to efficiently manage aggregate capacity in the system differ substantially between different parts of the system. These differences must be addressed when, for example, capacity pools are considered. These results serve as a stepping stone towards a more thorough understanding of efficient capacity management in healthcare systems.

This study examines how staff pooling can be used to create a higher service level at a predetermined total capacity in the healthcare sector. We develop new empirical knowledge through a systematic empirical study, using a mixed-methods approach, with a preliminary interview study followed by a principal quantitative survey study, with data from a multihospital system. The purpose was to explore practical barriers for a staff pooling strategy in healthcare systems. Three barriers were identified:recruitment difficulties, community view, and specialisation. Significant differences in perceived height among these barriers were found. The results from this study have important managerial implications for healthcare systems when implementing a staff pooling approach. This study contributes to the existing literature since, to the best of our knowledge, no previous research has been done where barriers to staff pools are systematically identified using a holistic approach that includes all healthcare professions in a multihospital system.

Healthcare systems worldwide are faced with continuously increasing demand for care, while simultaneously experiencing insufficient capacity and unacceptably long patient waiting times. To improve healthcare access and availability, it is thus necessary to improve capacity utilization and increase the efficiency of existing resource usage. For this, variations in healthcare systems must be managed judiciously, and one solution is to apply a capacity pooling approach. A capacity pool is a general, collaborative capacity that can be allocated to parts of the system where the existing workload and demand for capacity are unusually high. In this study, we investigate how basic mean-variance methodology from portfolio theory can be applied as a capacity pooling approach to healthcare systems. A numerical example based on fictitious data is used to illustrate the theoretical value of using a portfolio approach in a capacity pooling context. The example shows that there are opportunities to use capacity more efficiently and increase service levels, given the same capacity, and that a mean-variance analysis could be performed to theoretically dimension the most efficient pooling organization. The study concludes with a discussion regarding the practical usefulness of this methodology in the healthcare context.