2,201 research outputs found

    Managing daily surgery schedules in a teaching hospital: a mixed-integer optimization approach

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    Background: This study examined the daily surgical scheduling problem in a teaching hospital. This problem relates to the use of multiple operating rooms and different types of surgeons in a typical surgical day with deterministic operation durations (preincision, incision, and postincision times). Teaching hospitals play a key role in the health-care system; however, existing models assume that the duration of surgery is independent of the surgeon's skills. This problem has not been properly addressed in other studies. We analyze the case of a Spanish public hospital, in which continuous pressures and budgeting reductions entail the more efficient use of resources. Methods: To obtain an optimal solution for this problem, we developed a mixed-integer programming model and user-friendly interface that facilitate the scheduling of planned operations for the following surgical day. We also implemented a simulation model to assist the evaluation of different dispatching policies for surgeries and surgeons. The typical aspects we took into account were the type of surgeon, potential overtime, idling time of surgeons, and the use of operating rooms. Results: It is necessary to consider the expertise of a given surgeon when formulating a schedule: such skill can decrease the probability of delays that could affect subsequent surgeries or cause cancellation of the final surgery. We obtained optimal solutions for a set of given instances, which we obtained through surgical information related to acceptable times collected from a Spanish public hospital. Conclusions: We developed a computer-aided framework with a user-friendly interface for use by a surgical manager that presents a 3-D simulation of the problem. Additionally, we obtained an efficient formulation for this complex problem. However, the spread of this kind of operation research in Spanish public health hospitals will take a long time since there is a lack of knowledge of the beneficial techniques and possibilities that operational research can offer for the health-care system

    A Robust Site Selection Model under uncertainty for Special Hospital Wards in Hong Kong

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    This paper process two robust models for site selection problems for one of the major Hospitals in Hong Kong. Three parameters, namely, level of uncertainty, infeasibility tolerance as well as the level of reliability, are incorporated. Then, 2 kinds of uncertainty; that is, the symmetric and bounded uncertainties have been investigated. Therefore, the issue of scheduling under uncertainty has been considered wherein unknown problem factors could be illustrated via a given probability distribution function. In this regard, Lin, Janak, and Floudas (2004) introduced one of the newly developed strong optimisation protocols. Hence, computers as well as the chemical engineering [1069-1085] has been developed for considering uncertainty illustrated through a given probability distribution. Finally, our accurate optimisation protocol has been on the basis of a min-max framework and in a case of application to the (MILP) problems it produced a precise solution that has immunity to uncertain data

    Prioritization of patients' access to health care services

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    L'accĂšs aux services de santĂ© et les longs dĂ©lais d'attente sont l’un des principaux problĂšmes dans la plupart des pays du monde, dont le Canada et les États-Unis. Les organismes de soins de santĂ© ne peuvent pas augmenter leurs ressources limitĂ©es, ni traiter tous les patients simultanĂ©ment. C'est pourquoi une attention particuliĂšre doit ĂȘtre portĂ©e Ă  la priorisation d'accĂšs des patients aux services, afin d’optimiser l’utilisation de ces ressources limitĂ©es et d’assurer la sĂ©curitĂ© des patients. En fait, la priorisation des patients est une pratique essentielle, mais oubliĂ©e dans les systĂšmes de soins de santĂ© Ă  l'Ă©chelle internationale. Les principales problĂ©matiques que l’on retrouve dans la priorisation des patients sont: la prise en considĂ©ration de plusieurs critĂšres conflictuels, les donnĂ©es incomplĂštes et imprĂ©cises, les risques associĂ©s qui peuvent menacer la vie des patients durant leur mise sur les listes d'attente, les incertitudes prĂ©sentes dans les dĂ©cisions des cliniciens et patients, impliquant l'opinion des groupes de dĂ©cideurs, et le comportement dynamique du systĂšme. La priorisation inappropriĂ©e des patients en attente de traitement a une incidence directe sur l’inefficacitĂ© des prestations de soins de santĂ©, la qualitĂ© des soins, et surtout sur la sĂ©curitĂ© des patients et leur satisfaction. InspirĂ©s par ces faits, dans cette thĂšse, nous proposons de nouveaux cadres hybrides pour prioriser les patients en abordant un certain nombre de principales lacunes aux mĂ©thodes proposĂ©es et utilisĂ©es dans la littĂ©rature et dans la pratique. Plus prĂ©cisĂ©ment, nous considĂ©rons tout d'abord la prise de dĂ©cision collective incluant les multiples critĂšres de prioritĂ©, le degrĂ© d'importance de chacun de ces critĂšres et de leurs interdĂ©pendances dans la procĂ©dure d'Ă©tablissement des prioritĂ©s pour la priorisation des patients. Puis, nous travaillons sur l'implication des risques associĂ©s et des incertitudes prĂ©sentes dans la procĂ©dure de priorisation, dans le but d'amĂ©liorer la sĂ©curitĂ© des patients. Enfin, nous prĂ©sentons un cadre global en se concentrant sur tous les aspects mentionnĂ©s prĂ©cĂ©demment, ainsi que l'implication des patients dans la priorisation, et la considĂ©ration des aspects dynamiques du systĂšme dans la priorisation. À travers l'application du cadre global proposĂ© dans le service de chirurgie orthopĂ©dique Ă  l'hĂŽpital universitaire de Shohada, et dans un programme clinique de communication augmentative et alternative appelĂ© PACEC Ă  l'Institut de rĂ©adaptation en dĂ©ficience physique de QuĂ©bec (IRDPQ), nous montrons l'efficacitĂ© de nos approches en les comparant avec celles actuellement utilisĂ©es. Les rĂ©sultats prouvent que ce cadre peut ĂȘtre adoptĂ© facilement et efficacement dans diffĂ©rents organismes de santĂ©. Notamment, les cliniciens qui ont participĂ© Ă  l'Ă©tude ont conclu que le cadre produit une priorisation prĂ©cise et fiable qui est plus efficace que la mĂ©thode de priorisation actuellement utilisĂ©e. En rĂ©sumĂ©, les rĂ©sultats de cette thĂšse pourraient ĂȘtre bĂ©nĂ©fiques pour les professionnels de la santĂ© afin de les aider Ă : i) Ă©valuer la prioritĂ© des patients plus facilement et prĂ©cisĂ©ment, ii) dĂ©terminer les politiques et les lignes directrices pour la priorisation et planification des patients, iii) gĂ©rer les listes d'attente plus adĂ©quatement, vi) diminuer le temps nĂ©cessaire pour la priorisation des patients, v) accroĂźtre l'Ă©quitĂ© et la justice entre les patients, vi) diminuer les risques associĂ©s Ă  l’attente sur les listes pour les patients, vii) envisager l'opinion de groupe de dĂ©cideurs dans la procĂ©dure de priorisation pour Ă©viter les biais possibles dans la prise de dĂ©cision, viii) impliquer les patients et leurs familles dans la procĂ©dure de priorisation, ix) gĂ©rer les incertitudes prĂ©sentes dans la procĂ©dure de prise de dĂ©cision, et finalement x) amĂ©liorer la qualitĂ© des soins.Access to health care services and long waiting times are one of the main issues in most of the countries including Canada and the United States. Health care organizations cannot increase their limited resources nor treat all patients simultaneously. Then, patients’ access to these services should be prioritized in a way that best uses the scarce resources, and to ensure patients’ safety. In fact, patients’ prioritization is an essential but forgotten practice in health care systems internationally. Some challenging aspects in patients’ prioritization problem are: considering multiple conflicting criteria, incomplete and imprecise data, associated risks that threaten patients on waiting lists, uncertainties in clinicians’ decisions, involving a group of decision makers’ opinions, and health system’s dynamic behavior. Inappropriate prioritization of patients waiting for treatment, affects directly on inefficiencies in health care delivery, quality of care, and most importantly on patients’ safety and their satisfaction. Inspired by these facts, in this thesis, we propose novel hybrid frameworks to prioritize patients by addressing a number of main shortcomings of current prioritization methods in the literature and in practice. Specifically, we first consider group decision-making, multiple prioritization criteria, these criteria’s importance weights and their interdependencies in the patients’ prioritization procedure. Then, we work on involving associated risks that threaten patients on waiting lists and handling existing uncertainties in the prioritization procedure with the aim of improving patients’ safety. Finally, we introduce a comprehensive framework focusing on all previously mentioned aspects plus involving patients in the prioritization, and considering dynamic aspects of the system in the patients’ prioritization. Through the application of the proposed comprehensive framework in the orthopedic surgery ward at Shohada University Hospital, and in an augmentative and alternative communication (AAC) clinical program called PACEC at the Institute for Disability Rehabilitation in Physics of QuĂ©bec (IRDPQ), we show the effectiveness of our approaches comparing the currently used ones. The implementation results prove that this framework could be adopted easily and effectively in different health care organizations. Notably, clinicians that participated in the study concluded that the framework produces a precise and reliable prioritization that is more effective than the currently in use prioritization methods. In brief, the results of this thesis could be beneficial for health care professionals to: i) evaluate patients’ priority more accurately and easily, ii) determine policies and guidelines for patients’ prioritization and scheduling, iii) manage waiting lists properly, vi) decrease the time required for patients’ prioritization, v) increase equity and justice among patients, vi) diminish risks that could threaten patients during waiting time, vii) consider all of the decision makers’ opinions in the prioritization procedure to prevent possible biases in the decision-making procedure, viii) involve patients and their families in the prioritization procedure, ix) handle available uncertainties in the decision-making procedure, and x) increase quality of care
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