Operations Management at the service of health care management: Example of a proposal for action research to plan and schedule health resources in scenarios derived from the COVID-19 outbreak - Juan A. Marin-Garcia; Jose P. Garcia-Sabater; Angel Ruiz; Julien Maheut; Julio J. Garcia-Sabater (Journal of Industrial Engineering and Management (JIEM), 2020)
Purpose: With this work, we intend to promote research on the application of Operations Management tools in order to assist with decision-making in health crisis situations. During the first six weeks of the COVID-19 crisis in Spain, we have contacted a large number of hospital and health department managers in the Valencian Community and other regions of Spain. The result is that very few, at least when contact was made and at the time of writing this article, had consulted staff members in the Operations Management area for advice on this situation, and they are quite reluctant to do so. This is in spite of the fact that some medical sources also consider this crisis to be one of resources, not merely a medical crisis. Our opinion is that Operations Management can make a useful and valuable contribution to anticipate and improve the management of scarce resources, even in times of crisis. If those responsible for public health or heads of hospitals do not see this usefulness, then there is a huge gap between research and practice in Operations Management and what is transmitted to the healthcare sector. Our aim is to help reduce this gap. Design/methodology/approach: In the first part of the article, we will justify that this crisis, besides being a medical crisis, is also a crisis in terms of resources. We will briefly review some of the Operations Management tools that we believe are appropriate for managing this crisis. We will focus on those that we will illustrate in the second part of the article as a practical example of the action research protocol (only the action planning phase), in which we are currently involved. Findings: Due to the peculiarities of the COVID-19 epidemic, it is reasonable to think that the evolution and duration of each outbreak, and the way it is dealt with, will be different in each hospital and/or each health department. Anticipating the number of patients who will require care and forecasting the consumption of resources over time is complex, due to the long and variable incubation times and the uncontrolled evolution of the treatments needed by each patient. Furthermore, since the evolution of new patient admissions is not homogeneous, the forecasting of requirements is difficult. Providing real-time support and detecting with a certain degree of anticipation the potential levels of demand for health care will enable hospitals to define what stages of the contingency plan to apply and how to (re)assign the available resources in the most efficient way possible. Research limitations/implications: Hardly any current data are available, not only publicly, but also through public health ministries and managers; those that are available are not very reliable and come from studies with non-representative samples. For this reason, all forecasts must be taken with a note of caution, and in particular, designing review mechanisms every time a new set of updated reliable data becomes available (something that occurs on a weekly basis). Originality/value: In this work, we will show an example of a proposal for the practical application of Operations Management tools. Our proposal may be useful to hospital managers and public administrators in the healthcare sector (regional ministries or their equivalents). Each health department, hospital or hospital group will generate the aggregate data that facilitate the calculation of needs as input parameters for the model (available and occupied beds, daily admissions, mean lengths of stay in each healing phase and the percent of patients who evolve from one stage to another in the progression of the disease/healing process) and will be able to analyze how the system responds and evaluate different strategies or mitigating actions. These tools have been shown to be useful and reliable in manufacturing and service contexts that show a strong seasonal demand (both occasional and recurring) requiring a great deal of resources. We believe these situations are analogous to those faced by hospitals and the healthcare system in an epidemic like COVID-19. With them, we could facilitate the aggregate planning of resources for hospital administrators in order to provide them operational support during the COVID-19 contingency plan. However, the array of useful tools for this crisis is not limited to those that we will illustrate. Our intent is to encourage the Operations Management academic community to demonstrate how they contribute to the service of society in this COVID-19 epidemic, providing knowledge that can be extrapolated to other similar situations in the future that we may be unfortunate enough to experience.
Keywords: 650; Action research; COVID-19 outbreack; discrete event simulation; theory of constraints; operations management; healthcare