Operating theatre modelling: integrating social measures

Hospital resource modelling literature is primarily focussed on productivity and efficiency measures. In this paper, our focus is on the alignment of the most valuable revenue factor, the operating room (OR) with the most valuable cost factor, the staff. When aligning these economic and social decisions, respectively, into one sustainable model, simulation results justify the integration of these factors. This research shows that integrating staff decisions and OR decisions results in better solutions for both entities. A discrete event simulation approach is used as a performance test to evaluate an integrated and an iterative model. Experimental analysis show how our integrated approach can benefit the alignment of the planning of the human resources as well as the planning of the capacity of the OR based on both economic related metrics (lead time, overtime, number of patients rejected) and social related metrics (personnel preferences, aversions, roster quality)

Providing Language Services in Small Health Care Provider Settings: Examples From the Field

Assesses recent innovations in language service programs and activities at healthcare provider settings with ten or fewer clinicians. Includes an eight-step plan to help providers develop a strategy to meet the needs of their patients

Mercy Medical Center: Reducing Readmissions Through Clinical Excellence, Palliative Care, and Collaboration

Outlines strategies and practices behind low readmissions rates for heart attack, heart failure, and pneumonia patients, such as investing in advanced practice nurses who help incorporate evidence-based standards into patient care. Lists lessons learned

Barnes Hospital Bulletin

https://digitalcommons.wustl.edu/bjc_barnes_bulletin/1150/thumbnail.jp

Business Process Redesign in the Perioperative Process: A Case Perspective for Digital Transformation

This case study investigates business process redesign within the perioperative process as a method to achieve digital transformation. Specific perioperative sub-processes are targeted for re-design and digitalization, which yield improvement. Based on a 184-month longitudinal study of a large 1,157 registered-bed academic medical center, the observed effects are viewed through a lens of information technology (IT) impact on core capabilities and core strategy to yield a digital transformation framework that supports patient-centric improvement across perioperative sub-processes. This research identifies existing limitations, potential capabilities, and subsequent contextual understanding to minimize perioperative process complexity, target opportunity for improvement, and ultimately yield improved capabilities. Dynamic technological activities of analysis, evaluation, and synthesis applied to specific perioperative patient-centric data collected within integrated hospital information systems yield the organizational resource for process management and control. Conclusions include theoretical and practical implications as well as study limitations

An analytical comparison of the patient-to-doctor policy and the doctor-to-patient policy in the outpatient clinic

Outpatient clinics traditionally organize processes such that the doctor remains in a consultation room, while patients visit for consultation, we call this the Patient-to-Doctor policy. A different approach is the Doctor-to-Patient policy, whereby the doctor travels between multiple consultation rooms, in which patients prepare for their consultation. In the latter approach, the doctor saves time by consulting fully prepared patients. We compare the two policies via a queueing theoretic and a discrete-event simulation approach. We analytically show that the Doctor-to-Patient policy is superior to the Patient-to-Doctor policy under the condition that the doctor’s travel time between rooms is lower than the patient’s preparation time. Simulation results indicate that the same applies when the average travel time is lower than the average preparation time. In addition, to calculate the required number of consultation rooms in the Doctor-to-Patient policy, we provide an expression for the fraction of consultations that are in immediate succession; or, in other words, the fraction of time the next patient is prepared and ready, immediately after a doctor finishes a consultation.We apply our methods for a range of distributions and parameters and to a case study in a medium-sized general hospital that inspired this research

Analytical models to determine room requirements in outpatient clinics

Outpatient clinics traditionally organize processes such that the doctor remains in a consultation room while patients visit for consultation, we call this the Patient-to-Doctor policy (PtD-policy). A different approach is the Doctor-to-Patient policy (DtP-policy), whereby the doctor travels between multiple consultation rooms, in which patients prepare for their consultation. In the latter approach, the doctor saves time by consulting fully prepared patients. We use a queueing theoretic and a discrete-event simulation approach to provide generic models that enable performance evaluations of the two policies for different parameter settings. These models can be used by managers of outpatient clinics to compare the two policies and choose a particular policy when redesigning the patient process.We use the models to analytically show that the DtP-policy is superior to the PtD-policy under the condition that the doctor’s travel time between rooms is lower than the patient’s preparation time. In addition, to calculate the required number of consultation rooms in the DtP-policy, we provide an expression for the fraction of consultations that are in immediate succession; or, in other words, the fraction of time the next patient is prepared and ready, immediately after a doctor finishes a consultation. We apply our methods for a range of distributions and parameters and to a case study in a medium-sized general hospital that inspired this research

How can patient journey in surgical wards of a referral hospital be improved?

Background: We studied the patient journey in surgical wards in order to find an effective and efficient way of scheduling in surgical wards.Methods: We applied Root cause analysis (RCA) model within three months in a referral hospital. After understanding root causes of the events occurred through a focus discussion group, required interventions were proposed according to literatures, experiences, and preference of the stakeholders. Possible interventions were also analyzed based on its ability to reduce contributing factors in the events and the belief of process-owner that if interventions can be implemented.Results: The results were provided for five main steps: 1) the most important root cause was “not prioritizing patients and pre-scheduling the number of surgical procedures in the days before”. 2) Constraints indicated that workforce weren't allocated proportionally to the number of surgical operations in varying shift lengths, increased numbers of on-calls physicians increased related costs, the admission of patients in VIP wards have been getting a high priority, and surgeon compensation based on fee for service method was challenging. 3) The current situation of allocating three rooms on average for each physician can be changed depending on numbers of surgeries. 4) Proposed interventions are establishing a computer registration system, reforming payment methods, setting up an electronic waiting list, development of scheduling guidelines, and Applying MIP model.Conclusions: Implementing of scheduling reforms requires a comprehensive action plan system and predefined functional indicators. These should be achieved with considering comments of all clinical and technical groups to ensure the feasibility of an operating room schedule.Keywords: patient journey, surgery, scheduling, Root cause analysis (RCA), patient transfe