Modeling the Emergency Care Delivery System Using a Queueing Approach

This thesis considers a regional emergency care delivery system that has a common emergency medical service (EMS) provider and two hospitals, each with a single emergency department (ED) and an inpatient department (ID). Patients arrive at one of the hospital EDs either by ambulance or self-transportation, and we assume that an ambulance patient has preemptive priority over a walk-in patient. Both types of patients can potentially be admitted into the ID or discharged directly from the ED. An admitted patient who cannot access the ID due to the lack of available inpatient beds becomes a boarding patient and blocks an ED server. An ED goes on diversion, e.g., requests the EMS provider to divert incoming ambulances to the neighboring facility, if the total number of its ambulance patients and boarding patients exceeds its capacity (the total number of its servers). The EMS provider will accept the diversion request if the neighboring ED is not on diversion. Both EDs choose its capacity as its diversion threshold and never change the threshold value strategically, and hence they never game. Although the network could be an idealized model of an actual operation, it can be thought of as the simplest network model that is rich enough to reproduce the variety of interactions among different system components. In particular, we aim to highlight the bottleneck effect of inpatient units on ED overcrowding and the network effects resulting from ED diversions. A continuous time Markov chain is introduced for the network model. We show that the chain is irreversible and hence its stationary distribution is difficult to characterize analytically. We identify an alternative solution that builds on queueing decomposition and matrix-analytic methods. We demonstrate through discrete-event simulations the effectiveness of this solution on deriving various performance measures of the original network model. Moreover, by conducting extensive numerical experiments, we provide potential explanations for the overcrowding and delays in a network of hospitals. We suggest remedies from a queueing perspective for the operational challenges facing emergency care delivery systems

Patient Experience Informs Health Care Strategies in Irish Hospitals

Patients are central to health care facilities and institutions; therefore, a dire need arises to include feedback of their experience in the decision-making process. Patient experience is increasingly recognised as one of the three pillars of quality in healthcare alongside clinical effectiveness and patient safety. A comprehensive literature review (more than 2500 peer-reviewed articles) has identified five key frameworks for patient experience including: UK Picker Institute Principles and US H-CAHPS. The frameworks have enabled the identification of a potential range of patient experience dimensions and helped in grouping them into nine categories. However, there are still opportunities to address research gaps in developing a unified index to represent patient experience, and offering a practical framework to inform quality improvement strategies in hospitals. An extensive exploratory study is developed to complement the literature review. This study aims to confirm the importance of the identified nine dimensions from patients’ views, explore staff perceptions of patient experience, then compare patients’ views and staff’s perceptions. Semistructured interviews with 77 participants (26 senior staff members and 51patients) across three major acute Irish hospitals are conducted. Five important dimensions are highlighted from patients’ responses such as: staff communication and being treated with respect. While dimensions such as: continuity of care and involving family members are identified as less important. While staff in this study perceive dimensions such as quicker access to care and informing the patient with their status updates as more significant in shaping the patient experience. Both the exploratory study and literature review outcomes have contributed to the design of a patient experience questionnaire which examine dimensions that matter most to patient experience. The questionnaire is included as a component of a multi-method framework that integrated data analytics, simulation modelling, and optimisation. With an ultimate objective to improve patient experience, the proposed framework has been piloted in an Emergency Department of one of the leading and busiest university hospitals in Dublin. Fifty-eight patients responded to the questionnaire and their responses are analysed using a Partial Least Squares (PLS) model. PLS results have identified access to care as a negative predictor to patient experience. Improvement strategies such as increasing the internal capacity of the department are proposed by the management team to improve the Length of Stay (LOS) and provide better access to care. To examine and assess the impact of proposed strategies on LOS, a simulation model has complemented the solution framework. Results have showed that internal capacity of an ED has no direct impact on LOS and does not act as a performance constraint. However, other factors such as increasing downstream department’s capacity and the staffing levels can lead to a reduction in LOS (up to 25%)