Taxonomic classification of planning decisions in health care: a review of the state of the art in OR/MS

We provide a structured overview of the typical decisions to be made in resource capacity planning and control in health care, and a review of relevant OR/MS articles for each planning decision. The contribution of this paper is twofold. First, to position the planning decisions, a taxonomy is presented. This taxonomy provides health care managers and OR/MS researchers with a method to identify, break down and classify planning and control decisions. Second, following the taxonomy, for six health care services, we provide an exhaustive specification of planning and control decisions in resource capacity planning and control. For each planning and control decision, we structurally review the key OR/MS articles and the OR/MS methods and techniques that are applied in the literature to support decision making

A system dynamics-based simulation study for managing clinical governance and pathways in a hospital

This paper examines the development of clinical pathways in a hospital in Australia based on empirical clinical data of patient episodes. A system dynamics (SD)-based decision support system (DSS) is developed and analyzed for this purpose. System dynamics was used as the simulation modeling tool because of its rigorous approach in capturing interrelationships among variables and in handling dynamic aspects of the system behavior in managing healthcare. The study highlights the scenarios that will help hospital administrators to redistribute caseloads amongst admitting clinicians with a focus on multiple Diagnostic Related Groups (DRG’s) as the means to improve the patient turnaround and hospital throughput without compromising quality patient care. DRG’s are the best known classification system used in a casemix funding model. The classification system groups inpatient stays into clinically meaningful categories of similar levels of complexity that consume similar amounts of resources. Policy explorations reveal various combinations of the dominant policies that hospital management can adopt. The analyses act as a scratch pad for the executives as they understand what can be feasibly achieved by the implementation of clinical pathways given a number of constraints. With the use of visual interfaces, executives can manipulate the DSS to test various scenarios. Experimental evidence based on focus groups demonstrated that the DSS can enhance group learning processes and improve decision making. The simulation model findings support recent studies of CP implementation on various DRG’s published in the medical literature. These studies showed substantial reductions in length of stay, costs and resource utilization

A survey of health care models that encompass multiple departments

In this survey we review quantitative health care models to illustrate the extent to which they encompass multiple hospital departments. The paper provides general overviews of the relationships that exists between major hospital departments and describes how these relationships are accounted for by researchers. We find the atomistic view of hospitals often taken by researchers is partially due to the ambiguity of patient care trajectories. To this end clinical pathways literature is reviewed to illustrate its potential for clarifying patient flows and for providing a holistic hospital perspective

Simulation methods in the healthcare systems

International audienceHealthcare systems can be considered as large-scale complex systems. They need to be well managed in order to create the desired values for its stakeholders as the patients, the medical staff and the industrials working for healthcare. Many simulation methods coming from other sectors have already proved their added value for healthcare. However, based on our experience in the French heath sector (Jean et al. 2012), we found these methods are not widely used in comparison with other areas as manufacturing and logistic. This paper presents a literature review of the healthcare issue and major simulations methods used to address them. This work is design to suggest how more systematic creation of solutions may be performed using complementary methods to resolve a common issue. We believe that this first work can help to better understand the simulation approaches used for health workers, deciders or researchers of any responsibility level

A decision support simulation model for bed management in healthcare

In order to provide access to care in a timely manner, it is necessary to effectively manage the allocation of limited resources such as beds. Bed management is key to the effective delivery of high-quality and low-cost healthcare. An efficient utilization of beds requires a detailed understanding of the hospital\u27s operational behavior. It is necessary to understand the behavior of a hospital in order to make necessary adjustments to its resources, and policies, which can improve patient\u27s access to care. The aim of this research was to develop a discrete event simulation to assist in planning and staff scheduling decisions. Each department\u27s performance measures were taken into consideration separately to understand and quantify the behavior of individual departments, and the hospital system as a whole. Several scenarios were analyzed to determine the impact on reducing the number of patients waiting in queue, waiting time for patients, and length of stay of patients. From the results, the departments that have long queues of patients, waiting times, and lengths of stay are detailed to predict how the hospital reacts to patient flow --Abstract, page iv

Determining Care Delivery Model Feasibility Using Discrete-Event-Simulation

Background: The need for inpatient pediatric psychiatric services to address the growing issue of pediatric mental health in a multi-state integrated hospital enterprise is straining the system’s capacity to provide timely mental health care. Local Problem: Lack of access to specialty pediatric psychiatric treatment for dual diagnosis medi-psychiatric care management is a patient quality and safety issue. Insufficient capacity contributes to longer emergency room boarding times and inpatient length of stay for patients who have a mental illness. Methods: Use of digital simulation methodology to analyze the behavior of a dynamic event-driven care delivery workflow and to optimize quality patient outcomes by implementing a hub and spoke model of care. Interventions: A discrete event simulation model was built using retrospective data to evaluate existing resources and “what if” scenarios based on patient movement through a hub-and-spoke regional patient transfer structure. Results: Simulation of the patient flow determined that a decentralized hub-and-spoke model for management of pediatric dual diagnosis patient volume was unnecessary. Simulation modeling results revealed an average daily census of five indicating an ability to centralize all pediatric dual diagnosis volume into one hub hospital instead of three. Conclusions: Simulation was a cost effective, predictive, and innovative approach to evaluating alternative care models at the nurse executive level. The project demonstrated that prudent strategy for use of capital project resources can be enhanced at the beginning of the design phase in project management and clarity of scope realized at the macro, meso, and micro levels every project, every time

Triumph of hope over experience: learning from interventions to reduce avoidable hospital admissions identified through an Academic Health and Social Care Network.

BACKGROUND: Internationally health services are facing increasing demands due to new and more expensive health technologies and treatments, coupled with the needs of an ageing population. Reducing avoidable use of expensive secondary care services, especially high cost admissions where no procedure is carried out, has become a focus for the commissioners of healthcare. METHOD: We set out to identify, evaluate and share learning about interventions to reduce avoidable hospital admission across a regional Academic Health and Social Care Network (AHSN). We conducted a service evaluation identifying initiatives that had taken place across the AHSN. This comprised a literature review, case studies, and two workshops. RESULTS: We identified three types of intervention: pre-hospital; within the emergency department (ED); and post-admission evaluation of appropriateness. Pre-hospital interventions included the use of predictive modelling tools (PARR - Patients at risk of readmission and ACG - Adjusted Clinical Groups) sometimes supported by community matrons or virtual wards. GP-advisers and outreach nurses were employed within the ED. The principal post-hoc interventions were the audit of records in primary care or the application of the Appropriateness Evaluation Protocol (AEP) within the admission ward. Overall there was a shortage of independent evaluation and limited evidence that each intervention had an impact on rates of admission. CONCLUSIONS: Despite the frequency and cost of emergency admission there has been little independent evaluation of interventions to reduce avoidable admission. Commissioners of healthcare should consider interventions at all stages of the admission pathway, including regular audit, to ensure admission thresholds don't change

Leveraging discrete event simulation modeling to evaluate design and process improvements of an emergency department

This study exemplifies the practical application of the Discrete Event Simulation (DES) approach for evaluating the effectiveness of suggested processes and design modifications in improving the existing bottlenecks of an Emergency Department. EDs are under escalating pressure to deliver efficient care while handling considerable challenges, such as overcrowding, delays, length of stay, safety risks, or staffing. Many ED appointments are non-urgent and can be treated in an alternative outpatient setting. Suitable demand-capacity matching and adjusted admission protocols reduce ED patients' Length of Stay (LOS) and improve boarding times. Alternatively, new design suggestions include applying results-pending areas where lower acuity patients wait for their pending lab or imaging results. In this study, DES assesses underlying conditions and existing bottlenecks in an existing ED. The current ED flow involved a "pull-until-full" for exam room boarding and bedside registration after triage fulfillment. Nonetheless, the ED experienced boarding delays for patients waiting to be admitted into the hospital. This study explored two scenarios in DES as potential alternatives for reducing LOS: the implication of a "rapid-admit" protocol and a "results-pending" area. Findings showed that the Rapid-Admit process reduced the admitted patient's LOS by 16%. On average, the results-pending implication reduced the admit LOS by an average of 32% across all ESI levels. These findings suggest the importance of process, staffing, and spatial modifications to achieve ED operational improvements. DES enabled a data-driven approach to evaluate bottlenecks, enhance architect-owner communication, and optimize the system for future design and process improvement alternatives