Patient Flow Management Research Articles

P135: TriagED: A serious game for mass casualty triage and field disaster management

Innovation Concept: Mass Casualty Incidents (MCI) are complex events that most paramedics encounter only a few times in their careers. Triaging and managing multiple patients during an incident requires different skills than typically practiced by prehospital providers. Simulation and drills can provide an opportunity to practice those skills, but are costly and resource intensive while only allowing a few providers to be in a triage or leadership role. It is important to find engaging and less expensive methods for teaching MCI triage and initial scene management. Methods: The authors have developed and are testing a card game based on the previously published GridlockED board game. The game was developed utilizing an iterative process previously described. This game was tested with paramedics as well as other emergency medicine learners to determine usability, engagement, fidelity, as well as usefulness in teaching MCI triage and patient-flow concepts. Curriculum, Tool or Material: The card game provides a focused learning experience to allow providers to practice initial triage of multiple injured patients as well as manage patient flow from the scene to area hospitals when faced with limited prehospital resources and capabilities. Players work together in various simulated scenarios to correctly triage injured patients and send them to the correct healthcare facility. Conclusion: Serious gaming has gained momentum in medical education. Developing novel curriculae around low frequency, high stakes situations using a game like TriagED may hold the key to ensure prehospital care providers are trained for these incidents. In the future, games which integrate an element of Incident Command or receiving hosptials (e.g. full integration with GridlockED game) may help to further explore the relationship between scene management and patient flow within receiving hospitals.

Effective triage in the Pacific region: The development and implementation of the Solomon Islands Triage Scale.

The ED at the National Referral Hospital in Honiara, Solomon Islands, receives approximately 50 000 patients per year. A 2014 review of ED functioning identified deficiencies in triage processes. Placement of Australian volunteer advisors provided an opportunity to develop and implement a purpose-designed triage system. Action research methodology and the 'plan, act, observe, reflect' cycle was employed, leading to the development of a three-tier triage system based on the South African Triage Scale. ED patient flow and data management processes were simultaneously updated, and staff were trained in the new system. After a pilot period, the Solomon Islands Triage Scale was implemented in August 2017. Evaluation after 3 months of operation included predictive validity (using admission and case fatality rates as surrogate markers of urgency) and reliability (based on inter-rater agreement at retrospective chart review by an independent nurse). In the period 1 August to 31 October, there were 10 905 presentations, of which 97.1% were allocated a triage category (1% category 1, 21.3% category 2 and the remainder category 3). Admission rates correlated closely with triage category (P < 0.01). The case fatality rate was 22.1% for category 1 patients, 0.09% for category 2 and 0.01% for category 3 (P < 0.01). An audit of 96 records conducted in October 2017 revealed 88.4% agreement for triage category allocation. Solomon Islands Triage Scale is the first three-tier triage scale to be implemented in the Pacific region and appears to have adequate validity and reliability. The partnership between Australian volunteers and local clinicians is a positive example of capacity development and represents a model that could be implemented in other resource-limited settings.

Transforming hospital capacity management: Experience from two academic medical centres

Historically, capacity has been ‘undermanaged’ in health systems. Traditional mechanisms that rely on single departments to solve these problems are inadequate. New governance and managerial mechanisms are needed for redesigning care at the hospital and health system level. On the basis of our collective experience at two large academic medical centres, we identified four important elements of effective capacity management: a dedicated leadership role with a hospital-level view, centralised analytics defining universal metrics, aligned incentives across the institution and an engaged front-line staff. This paper shares case studies from two different academic medical centres, highlighting tools developed to manage patient flow and streamline operations while operating at high capacity.

Coloured Petri net for modelling and improving emergency department based on the simulation model

Emergency department (ED) is one of the most complex systems, due to its unstable environment and the stochastic characteristics of patient flows, pathologies, and limited resources, which lead to a long waiting time. Effective management of patient flows for 'ED' services has become a critical matter for most hospital supervisors. Many authors have tried to solve those issues based on different methodologies, with shared aims represented in the optimisation of patient care, by minimising patient waiting time at different levels in 'ED'. Modern studies mainly focus on limiting these issues by proposing a solution based on extending 'ED' resources. The case study was realised at the 'ED' of the hospital Chalabi Abdelkader, Mascara, Algeria. Then, the system was modelled by a coloured Petri net framework. Afterward, we performed simulations of numerous improvement scenarios. As a result, patient waiting times encountered in 'ED' were reduced, thus patient length of stay.

Application of a physical science model in the analysis of patient flow in a hospital

One of the most relevant aspects in hospital management relies on how to properly control and predict the patient flow, that is, the paths and the time sequence a whole set of patients run in their journey inside the hospital, as they look for treatment. This issue is of the utmost importance since it interferes in the quality of the healthcare delivered to a person and also has a huge impact on both the costs for the patient and the operational costs for the hospital. This work intends to collaborate with the comprehension of the patient flow analysis and to offer a mathematical model analogous to a physical model capable of, qualitatively at first sight, describing the main variables and properties of this flow. We also present the logical elements that allow the manager to develop quantitative flow evaluations adaptable to a specific institution, based on local measurements of the variables described here. This theoretical formulation can directly be applied to practical situations concerning the management of patient flow. The relevant variables and their mathematical relations can be used by the manager in order to quantify each relevant patient circuit in a hospital. This way, it is expected that recurring problems derived from the unwanted variations in the patient flow can be anticipated and corrected by the manager.

Impact of a patient-flow physician coordinator on waiting times and length of stay in an emergency department: A before-after cohort study.

ObjectiveOvercrowding is common in most emergency departments (ED). Despite the use of validated triage systems, some patients are at risk of delayed medical evaluation. The objective of this study was to assess the impact of a patient-flow physician coordinator (PFPC) on the proportion of patients offered medical evaluation within time limits imposed by the Swiss Emergency Triage Scale (SETS) and on patient flow within the emergency department of a teaching urban hospital.MethodsIn this before-after retrospective cohort study, we compared the proportions of patients who received their first medical contact within SETS-imposed time limits, mean waiting times before first medical consultation, mean length of stay, and number of patients who left without being seen by a physician, between two periods before and after introducing a PFPC. The PFPC was a senior physician charged with quickly assessing in the waiting area patients who could not immediately be seen and managing patient flow within the department.ResultsBefore introducing the PFPC position, 33,605 patients were admitted, versus 36,288 after. Introducing a PFPC enabled the department to increase the proportion of patients seen within the SETS-imposed time limits from 60.1% to 69.0% (p <0.0001). Waiting times until first medical consultation were reduced on average by 27.7 minutes (95% confidence interval [95% CI]: 25.9–29.5, p < .0001). No significant differences were observed as to length of stay or number of patients who left without being seen between the two study periods.ConclusionsIntroducing a physician dedicated to managing patient flow enabled waiting times until first medical consultation to be reduced, yet had no significant benefit for patient flow within the ED, nor did it reduce the number of patients who left without being seen.

A categorisation of problems and solutions to improve patient referrals from primary to specialty care

BackgroundImproving access to specialty care has been identified as a critical issue in the delivery of health services, especially given an increasing burden of chronic disease. Identifying and addressing problems that impact access to specialty care for patients referred to speciality care for non-emergent procedures and how these deficiencies can be managed via health system delivery interventions is important to improve care for patients with chronic conditions. However, the primary-specialty care interface is complex and may be impacted by a variety of potential health services delivery deficiencies; with an equal range of interventions developed to correct them. Consequently, the literature is also diverse and difficult to navigate. We present a narrative review to identify existing literature, and provide a conceptual map that categorizes problems at the primary-specialty care interface with linkages to corresponding interventions aimed at ensuring that patient transitions across the primary-specialty care interface are necessary, appropriate, timely and well communicated.MethodsWe searched MEDLINE and EMBASE databases from January 1, 2005 until Dec 31, 2014, grey literature and reference lists to identify articles that report on interventions implemented to improve the primary-specialty care interface. Selected articles were categorized to describe: 1) the intervention context, including the deficiency addressed, and the objective of the intervention 2) intervention activities, and 3) intervention outcomes.ResultsWe identified 106 articles, producing four categories of health services delivery deficiencies based in: 1) clinical decision making; 2) information management; 3) the system level management of patient flows between primary and secondary care; and 4) quality-of-care monitoring. Interventions were divided into seven categories and fourteen sub-categories based on the deficiencies addressed and the intervention strategies used. Potential synergies and trade-offs among interventions are discussed. Little evidence exists regarding the synergistic and antagonistic interactions of alternative intervention strategies.ConclusionThe categorization acts as an aid in identifying why the primary-specialty care interface may be failing and which interventions may produce improvements. Overlap and interconnectedness between interventions creates potential synergies and conflicts among co-implemented interventions.

Intelligent Patient Flow Management System at a Primary Healthcare Center - The Effect on Service Use and Costs.

An intelligent patient flow management system (IPFM) was piloted at a large primary healthcare center in Finland in August 2017. The goals of the system are to help patients avoid unnecessary calls and visits to their health center and to enhance the use of professional resources through more streamlined patient pathways and the re-allocation of professionals from assessment tasks to actual patient care. These goals should be reflected in the decreased service costs through optimized contact forms. Using multiple regression analysis, we studied the associations between IPFM and patients' service utilization (17,943 patients; 73,038 service contacts) during the first five months of the pilot in 2017. The results indicated that the use of IPFM by the patient was associated with a decrease of EUR 31 in the total service costs of the patient in the study period. This decrease is 14% of patient's average total service cost.

A hybrid ARIMA-SVR approach for forecasting emergency patient flow

The goal of this study is to explore and evaluate the use of a hybrid ARIMA-SVR approach to forecast daily radiology emergency patient flow. Owing to the fact that emergency patient flow is highly uncertain and dynamic, the forecasting problem is regarded as a complicated task. As the emergency patient flow may have both linear and nonlinear patterns, this paper presents a hybrid ARIMA-SVR approach, which hybridizes autoregressive integrated moving average (ARIMA) model and support vector regression (SVR) model to predict emergency patient arrivals. The proposed model is applied to 4 years of daily emergency visits data in the radiology department of a large hospital to justify the performance of the hybrid model against single models. The MAPE, RMSE and MAE of the hybrid model are 7.02%, 19.20 and 14.97, respectively. Furthermore, the hybrid model achieves better prediction performance than its competitors because it can capture the linear and nonlinear patterns simultaneously. Experimental results indicate that the proposed hybrid ARIMA-SVR approach is a promising alternative for forecasting emergency patient flow. These findings are beneficial for efficient patient flow management and scheduling decisions optimization.

Distributed Situation Awareness in Patient Flow Management: An Admission Case Study

Managing patient flow can be an effective strategy to reduce idling hospital beds, thereby lowering the healthcare cost without sacrificing quality of care. However, improving patient flow can be a major challenge due to the complex patterns of communication across diverse hospital staff. To identify improvement opportunities, this paper investigates whether the Distributed Situation Awareness (DSA) framework can feasibly and meaningfully model Situation Awareness (SA) in patient flow. The investigation involved a case study on modeling the DSA of the admission phase in patient flow for a level 1 trauma center. A DSA model combining task, knowledge, and social networks was created, showing feasibility of the framework in depicting the distribution and transaction of knowledge across workers and information systems. Further, a true elective admission case was mapped onto the DSA model, verifying its practical merits.

Inpatient flow management: a systematic review

PurposeIn hospitals, several patient flows compete for access to shared resources. Failure to manage these flows result in one or more disruptions within a hospital system. To ensure continuous care delivery, solving flow problems must not be limited to one unit, but should be extended to other departments – a prerequisite for solving flow problems in the entire hospital. Since most current studies focus solely on overcrowding in emergency units, additional insights are needed on system-wide patient flow management. The purpose of this paper is to look at the information available in system-wide patient flow management studies, which were also systematically evaluated to demonstrate which interventions improve inpatient flow.Design/methodology/approachThe authors searched PubMed and Web of Science (Core Collection) literature databases and collected full-text articles using two selection and classification stages. Stage 1 was used to screen articles relating to patient flow management for inpatient settings with typical characteristics. Stage 2 was used to classify the articles selected in Stage 1 according to the interventions and their impact on patient flow within a hospital system.FindingsIn Stage 1, 107 studies were selected. Although a growing trend was observed, there were fewer studies on patient flow management in inpatient than studies in emergency settings. In Stage 2, 61 intervention studies were classified. The authors found that most interventions were about creating and adding supply resources. Since many hospital managers these days cannot easily add capacity owing to cost and resource constraints, using existing capacity efficiently is important – unfortunately not addressed in many studies. Furthermore, arrival variability was the factor most frequently mentioned as affecting flow. Of all interventions addressed in this review, the most prominent for advancing patient access to inpatient units was employing a specialized individual or team to maintain patient flow and bed placement across hospital units.Originality/valueThis study provides the first patient flow management systematic overview within an inpatient setting context.

Timing it Right: Balancing Inpatient Congestion Versus Readmission Risk at Discharge

When to discharge a patient plays an important role in hospital patient flow management as well as the quality of care and patient outcomes. In this work, we develop and implement a data-integrated decision support framework to aid hospitals in managing the delicate balance between readmission risk at discharge and ward congestion. We formulate a large-scale Markov Decision Process (MDP) that integrates a personalized readmission prediction model to dynamically prescribe both how many and which patients to discharge on each day. Due to patient heterogeneity and the fact that length-of-stay is not memoryless, the MDP suffers the curse of dimensionality. We leverage structural properties and analytical solutions for a special cost setting to transform the MDP into a univariate optimization; this leads to a novel, efficient dynamic heuristic. Further, for our decision framework to be implementable in practice, we build a unified prediction model that integrates several statistical methods and provides key inputs to the decision framework; existing off-the-shelf readmission prediction models alone could not adequately parametrize our decision support. Through extensive counterfactual analyses, we demonstrate the value of our discharge decision tool over our partner hospital's historical discharge behavior. We also obtain generalizable insights by applying the tool to a broad range of hospital types through a high-fidelity simulation. Lastly, we showcase an implementation of our tool at our partner hospital, to demonstrate broader applicability through our framework's plug-and-play design for integration with general hospital data-systems and workflows.

Developing a telemedicine triage system to manage patient flow at a high volume cancer center urgent care.

e18517Background: MSKCC sees a high volume of patients with acute presentations at its 21 bed Urgent Care Center (UCC). We examined the incidence and underlying reasons for unplanned inpatient admi...

P073: The GridlockED board game: using serious games for medical education

Introduction: The management of patient flow in the emergency department (ED) is crucial for the practice of emergency medicine (EM). However, this skill is difficult to teach didactically and is learned implicitly in the latter half of residency training. To help expedite the learning process, we developed the GridlockED board game as an educational tool to simulate ED patient flow. By having junior medical trainees play this game, we believe that they will develop a greater understanding of patient flow and resource management in the ED. Additionally, since GridlockED is a cooperative game, players may also benefit by improving their communication and teamwork skills. Methods: GridlockED was developed over twenty months of iterative gameplay and review. Feedback from attending emergency physicians, residents, and medical students was integrated into the game through a Plan-Do-Study-Act (PDSA) model. Emergency medicine nurses, physicians and residents at McMaster University were recruited to play GridlockED. Each player completed a pre-survey to collect demographic data and to assess their prior experience with playing board games. All play sessions were recorded for data collection purposes. Following each game session, a member of the research team conducted an exit interview with the players to gather information about their play experience and the educational value of the game. A post-survey was also sent to each participant for further feedback. Results: Eighteen gameplay sessions were conducted from June to August 2017. A total of thirty-two participants played the game (13 emergency physicians, 15 residents, and four nurses). Overall responses to the post-gameplay survey showed that players endorsed GridlockED as a useful potential teaching tool (75%, n=24/32) and the majority felt that it had the potential to improve patient flow in the ED (56%, n=18/32). Most participants found that the game was easy to play (91%, n=27/29), and that the instructions were clear (87.5%, n=28/32). Respondents also felt that the game reflected real life scenarios (56%, n=18) and that cases reflected the types of patients that they saw in the ED (78%, n=25). Conclusion: Our results have shown an overall positive response to GridlockED, with most participants supporting it as both an engaging board game and potential teaching tool. We believe that future studies with larger sample sizes and medical students will further validate the use of serious games in medical education.

A Two-Stage Model to Predict Surgical Patients' Lengths of Stay From an Electronic Patient Database.

Soaring healthcare costs and the growing demand for services require us to use healthcare resources more efficiently. Randomness in resource requirements makes the care delivery process less efficient. Our aim is to reduce the uncertainty in patients' resource requirements, and we achieve that objective by classifying patients into similar resource user groups. In this article, we develop a two-stage classification model to classify patients into lower variability resource user groups by using electronic patient records. There are various statistical tools for classifying patients into lower variability resource user groups. However, classification and regression tree (CART) analysis is a more suitable method for analyzing healthcare data because it has some distinct features. For example, it can handle the interaction between predictor variables naturally, it is nonparametric in nature, and it is relatively insensitive to the curse of dimensionality. We found that the CART analysis is also useful for determining the patient attributes that can explain the variability in resource requirements. Furthermore, we observed that some of the covariates, such as the principal prescribed procedure code, the admission point, and the operating surgeon, were able to explain up to 53.43% of the variability in patients' lengths of stay (LoS). Reducing the uncertainty in patients' LoS predictions helps us manage patient flow efficiently and subsequently obtain a better throughput.

Assessing the Online Outpatient Booking System

Background: Appointment scheduling is considered as one of the important aspects of patient flow management. Today, the advent of Internet into the realm of health care has paved the way for employing an internet-based booking system for visiting physicians. Therefore, this study aimed at assessing the online outpatient booking system in Iranian hospitals. Methods: The present study was an applied descriptive study. In this study, all outpatient appointment booking websites in Iranian hospitals were evaluated. The methods of outpatients booking in the hospitals (N = 598) were determined based on information available at their active websites. Finally, 31 active online booking systems were identified and investigated using a localized checklist, including 59 items in 6 sections. Results: The results showed that only 13.03% of Iranian hospitals had an active online booking system. All the online booking systems had a weak quality based on the total score percentage (17.10%). The highest score percentages were related to sections of online security features (45%) and details of health insurance (42%), while the clinical data section received the lowest score (7.25%). The most frequent item was the patient’s name in the patient demographics section (27 websites). Conclusions: The outpatient appointment system in Iranian hospitals is done more traditionally through walk-ins to the health centers. The online outpatient booking systems have poor quality. Hence, codification and communication of national standards for designing hospital websites, periodical evaluation of appointment booking websites by ministry of health, and survey of the users of this method can enhance the qualitative level of these websites.

A proactive transfer policy for critical patient flow management.

Hospital emergency departments are often overcrowded, resulting in long wait times and a public perception of poor attention. Delays in transferring patients needing further treatment increases emergency department congestion, has negative impacts on their health and may increase their mortality rates. A model built around a Markov decision process is proposed to improve the efficiency of patient flows between the emergency department and other hospital units. With each day divided into time periods, the formulation estimates bed demand for the next period as the basis for determining a proactive rather than reactive transfer decision policy. Due to the high dimensionality of the optimization problem involved, an approximate dynamic programming approach is used to derive an approximation of the optimal decision policy, which indicates that a certain number of beds should be kept free in the different units as a function of the next period demand estimate. Testing the model on two instances of different sizes demonstrates that the optimal number of patient transfers between units changes when the emergency patient arrival rate for transfer to other units changes at a single unit, but remains stable if the change is proportionally the same for all units. In a simulation using real data for a hospital in Chile, significant improvements are achieved by the model in key emergency department performance indicators such as patient wait times (reduction higher than 50%), patient capacity (21% increase) and queue abandonment (from 7% down to less than 1%).

L’infermiere nel DEA: una risorsa strategica per la gestione dell’overcrowding e della customer satisfaction

Introduction: The overcrowding is one of the main problems that every day has to face most of the Emergency Rooms; it is found when there is an excessive, and non-programmable, inflow of patients. Overcrowding generates consequences that involve the entire hospital: despite the phenomenon has been the subject of numerous studies, to date, international literature does not seem to be able to provide a univocal solution to the problem, because of its complex and multifaceted characteristics; nor it was possible to propose an organizational model that can readily contain the problem to provide safe and quality care. Aim: The purpose of this study is to investigate the real situation of a specific emergency room and understand whether the introduction of a nurse dedicated to the management of flows may reduce the overcrowding. Material and method: An observational retrospective study was conducted on data from Emergency Rooms of Salerno’s University Hospital (period 2012-2017); were therefore considered the activities useful for an effective and efficient control of overcrowding and some possible solutions. Results: The synergistic implementation of planned strategies, even if not completely solving overcrowding, may permit a reduction and/or a redistribution of the work overload. Conclusions: The implementation of a methodology that engages the ED staff in the management of patient flows, with the supervision and control by a nurse flow coordinator, may lead to a better management of the value and the customer satisfaction.

ВОЗМОЖНОСТИ ИСПОЛЬЗОВАНИЯ ИНФОРМАЦИОННЫХ ТЕХНОЛОГИЙ В УПРАВЛЕНИИ ПРОЦЕССАМИ ОРГАНИЗАЦИИ СКОРОЙ МЕДИЦИНСКОЙ ПОМОЩИ

Objective: Improvement of the model of the automated control system to support the decision-making in the field of emergency medical care to the population of a large industrial center. Methods: The analysis of the activity of the ambulance station was studied the existing normative legal acts regulating the activity of emergency medical aid. A detailed study of software KGBUZ «KSSMP» – an automated control system (ASU) «MISS 03», working system of dispatching of vehicles – «AutoGRAPH». To create a model of its own software, the C++ programming language was used. Results: The model of the AnScor+ software and hardware complex created by us is organized as a distributed client-server system. The end devices are data collection terminals (mobile phones of ambulance crews running the Android operating system); a client-server Android application was developed for them. The interaction between mobile terminals, dispatcher terminals, and the MISS-03 automated control system is carried out centrally through the software of the AnScor+ server. Conclusion: The creation of such analytical services to ensure the solutions of the problems of transport logistics, automated patient flow management will allow realizing in practice the advanced algorithms of the medical emergency services, significantly improve the main performance indicators, such as the promptness of quality and the volume of medical care. Keywords: Ambulance, informatization, automated control system, healthcare, patient flows.

System-level mechanisms and contexts for health and social care coordination through Multi-Specialty Community Providers in England: a Realist evidence synthesis

Introduction: Current National Health Service (NHS) policy towards care coordination in England, involving the introduction of Multi-Specialty Community Providers (MCPs), assumes that repeated unplanned admissions of older people with multiple morbidity make disproportionately heavy use of hospital bed-days, that a substantial number of these admissions are preventable, and that reducing these admissions would substantially reduce cost and access pressures on hospital services. 'Integrated' (better-coordinated) care, delivered by MCPs, is intended to reduce these admissions by partly replacing hospital care with non-hospital care, hence raising the quality and reducing the cost of care. Our study synthesised existing evidence about how to integrate care at the system-level, including management of complexity and whole system patient flow. Theory/Methods: Stage 1. From grey literature, MCPs’ published logic models, and a think tank (policy makers, health-workers, patients/public), we elicited policy-assumptions ('programme theory') about what structures, working practices and services ('mechanisms') the MCPs will contain, and how these mechanisms are expected to produce the outcomes above. Stage 2. Realist review: Evidence from other ‘integrated’ care projects which related to the programme theory identified in stage 1 was synthesised to produce a revised, more strongly evidence-based explanation of how complex, MCP-like ‘integrated’ care systems function in different contexts. 3. 'Critical Analysis': The policy-makers' initial programme theory (from stage 1) was compared with the evidence from stage 2. In that way the policy-makers’ initial programme theory was elaborated, qualified and revised, better to inform the development of health and social care co-ordination in England. Results: We present 1) the initial programme theory, built from NHS England policy-makers' assumptions as to what outcomes the MCP models of care integration will produce in England, and by what means, and 2) some main findingsof how different models of care co-ordination might contribute to achieving these outcomes and under what conditions. Discussions: We discuss 1) how realist review methods were used to elaborate, qualify or challenge policy-makers' assumptions about how care co-ordination by means of MCPs would achieve the desired outcomes, and 2) how these findings can inform better care co-ordination. Conclusions: We describe the main empirical strengths and weaknesses in the assumptions underlying the models of care and care coordination which inform current NHS policy, and indicate where existing evidence is weak or lacking. Lessons learned: We discuss how we met the challenge of focusing the scope of a project that encompasses complex system-level issues across health and social care, and how far the findings and lessons might apply to other, differently-structured health systems. Limitations: Policy-makers assumptions were complex and incompletely articulated, making our findings depend, at points, upon our interpretation of what policy makers specifically intended. The complexity constrained us to focus our review on the policy makers’ most central assumptions. Future research: 1) Understanding how the logic models informed practice by evaluating the usefulness, and any future policy application, of our findings by policy makers in England. 2) Testing our findings empirically through primary research (Realist evaluation) of MCPs in practice.