During the current epidemic,it is necessary to ensure the rehabilitation treatment of children with serious illness.At the same time,however,it is essential to effectively prevent cross-infection and prevent infection...During the current epidemic,it is necessary to ensure the rehabilitation treatment of children with serious illness.At the same time,however,it is essential to effectively prevent cross-infection and prevent infections from occurring within the hospital setting.To resolve this contradiction,the rehabilitation department of Nanjing Children’s Hospital adjusted its bed allocation based on the queuing model,with reference to the regional source and classification of the children’s conditions in the rehabilitation department ward.The original triple rooms were transformed into a double room to enable the treatment of severely sick children coming from other places.A M/G/2 queuing model with priority was also applied to analyze the state of patient admissions.Moreover,patients in Nanjing were also classified into mild and severe cases.The M/M/1 queuing model with priority was used for analysis of this situation,so that severely ill children could be treated in time while patients with mild symptoms could be treated at home.This approach not only eases the bed tension in the ward,but also provides suitable conditions for controlling cross-infection.展开更多
This paper concerns the problem of inpatient bed allocation for two classes of patients(scheduled and non-scheduled)when there is uncertainty about daily available capacity.In the afternoon of each day,patients from t...This paper concerns the problem of inpatient bed allocation for two classes of patients(scheduled and non-scheduled)when there is uncertainty about daily available capacity.In the afternoon of each day,patients from the scheduled class,also called backlogged elective admissions,are selected from a waiting list,for the admission on the next day.The non-scheduled class,also called emergent admissions,are new requests that arise randomly each day with emergent needs.The capacity of available beds for a medical specialty to provide hospitalization services is uncertain when backlogged elective pa-tients are chosen.Admitting too many of elective patients may result in exceeding a day’s capacity,which can potentially necessitate"overflowing"or"postponing"some emergent requests that should be performed as soon as possible.Therefore,the problem faced by the medical specialty facility at the decision-making point of each day is how many of the backlogged elective patients can be admitted.We formulate this problem as a Markov decision process(MDP)and study the structural properties of the model to characterize the nature of the optimal policy.We propose easy-to-implement policies(the fixed quota policy and the best fixed quota policy),which perform well under fitted distributions.By reporting numerical analyses using real data from a Chinese public hospital,we finally compare the improvements that our proposed solutions could bring to the hospital with the existing practices under several different cost structures.展开更多
文摘During the current epidemic,it is necessary to ensure the rehabilitation treatment of children with serious illness.At the same time,however,it is essential to effectively prevent cross-infection and prevent infections from occurring within the hospital setting.To resolve this contradiction,the rehabilitation department of Nanjing Children’s Hospital adjusted its bed allocation based on the queuing model,with reference to the regional source and classification of the children’s conditions in the rehabilitation department ward.The original triple rooms were transformed into a double room to enable the treatment of severely sick children coming from other places.A M/G/2 queuing model with priority was also applied to analyze the state of patient admissions.Moreover,patients in Nanjing were also classified into mild and severe cases.The M/M/1 queuing model with priority was used for analysis of this situation,so that severely ill children could be treated in time while patients with mild symptoms could be treated at home.This approach not only eases the bed tension in the ward,but also provides suitable conditions for controlling cross-infection.
基金This research is supported by National Natural Science Foundation of China(No.71532007).
文摘This paper concerns the problem of inpatient bed allocation for two classes of patients(scheduled and non-scheduled)when there is uncertainty about daily available capacity.In the afternoon of each day,patients from the scheduled class,also called backlogged elective admissions,are selected from a waiting list,for the admission on the next day.The non-scheduled class,also called emergent admissions,are new requests that arise randomly each day with emergent needs.The capacity of available beds for a medical specialty to provide hospitalization services is uncertain when backlogged elective pa-tients are chosen.Admitting too many of elective patients may result in exceeding a day’s capacity,which can potentially necessitate"overflowing"or"postponing"some emergent requests that should be performed as soon as possible.Therefore,the problem faced by the medical specialty facility at the decision-making point of each day is how many of the backlogged elective patients can be admitted.We formulate this problem as a Markov decision process(MDP)and study the structural properties of the model to characterize the nature of the optimal policy.We propose easy-to-implement policies(the fixed quota policy and the best fixed quota policy),which perform well under fitted distributions.By reporting numerical analyses using real data from a Chinese public hospital,we finally compare the improvements that our proposed solutions could bring to the hospital with the existing practices under several different cost structures.
