Queuing Model2 In any organization maximization of operational capacity and efficacy is the priority of any management system. More so in a busy emergency environment like a referral Hospital. The M/M/s parameters are applicable in this case for decision making on how to increase efficacy. Basing on discrete event simulation, steps that can be taken include, management of admission ofpatientsandprocedurescheduling,thepatientflowcouldalsobeincreasedthrough reconstruction of entry and exit models. Poisson’s queuing model is thus a very important tool in increasing efficacy in emergency departments (Sharif, Stanford, Taylor and Ziedins, 2014, p. 76) Different health care institutions may not necessarily use the same queuing principles in their operations, however, if so, there is a sense in comparing the effectiveness of queuing models in different healthcare institutions in spite of their implications (Lin, Patrick and Labeau, 2014, p. 95 ).This is because it can help in development of more concrete universally applicable policies and decisions of how best and when the models can be utilized to enhance effectiveness. The intern in PATA would have suggested more regular assessment of all service providers in the facility and provision of an always available platform where workers can air their concerns and suggestions as far as timely service provision is concerned (Sharif, Stanford, Taylor and Ziedins, 2014, p. 74). Furthermore, hiring of more personal so as to enable relieving of shifts on time should be another priority. All these coupled with other existing ethical virtues imparted and undertaken by the able and hardworking teams in PATA would render the institution the center of quality Health care in spite of the challenges behind them. In conclusion, Poisson distribution models are key tools that ought to be incorporated in any efficiency-oriented institution especially those with the desire to provide quality services for the good of subjects or service seekers.
Queuing Model3 References Lin, D., Patrick, J. and Labeau, F., 2014. Estimating the waiting time of multi-priority emergency patients with downstream blocking.Health care management science,17(1), pp.88-99. Sharif, A.B., Stanford, D.A., Taylor, P. and Ziedins, I., 2014. A multi-class multi-server accumulating priority queue with application to health care.Operations Research for Health Care,3(2), pp.73-79.