Capacity Analysis and Queuing Theory

Posted: August 26th, 2021

Capacity Analysis and Queuing Theory

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Capacity Analysis and Queuing Theory

Why Capacity Analysis is Important

The capacity analysis encompasses the primary core functions of a health system and the standards of practice for developing and utilizing driver-based future projections in demand for health services and related capacity requirements. Such forecasts form the basis for capital planning and implementation. As such, the health system is effectively driven through proper decision making to address issues around outpatient and inpatient facilities and employees, among other investments. For instance, if an organization identifies that its outpatient health system is becoming less competitive to support the health plan of an organization, capacity analysis is anessential tool to help upgrade its network. In this way, an integrated capacity analysis and planning tool come in handy to help meet the required standards of a health system. Some notable input examples are worker hours, equipment, supplies, and facilities, and output include ambulatory care visits, number of surgeries, patient days, and meals served.

Importance of Applications of Queuing Theory in a Health Services Environment

Queuing theory is critical in improving a health service environment to facilitate better satisfaction among patients. A health service environment requires effective management of patient queues. As such, without having proper queuing, health system productivity may likely be affected. In this case, good queuing systems help manage the queuing process through automation, besides improving service delivery in the health environment. For example, through queuing, it is possible to optimize physician practices. In this case, all the unique practices assigned both to inpatient and outpatients would be modelled and effectively optimized. Subsequently, there would be less crowding in rooms, thus an increased level of appointments. Hence, it is possible to use the queuing theory to help predict the operations of the hospital environment through the implementation of adequate physical and behavioral changes at workplaces.

References

Hall, R. (2006). Patient flow: reducing delay in healthcare delivery. New York: Springer.

Langabeer, J. & Helton, J. (2016). Health care operations management: a systems perspective. Burlington, MA: Jones & Bartlett Learning.

Story, P. (2011). Dynamic capacity management for healthcare: advanced methods and tools for optimization. Boca Raton: CRC Press.