Simulation of 48-Hour Queue Dynamics for A Semi-Private Hospital Ward Considering Blocked Beds

This thesis study evaluates access to care at an internal medicine unit with solely semi-private rooms at Baystate Medical Center (BMC). Patients are divided into two types: Type I patient consumes one bed; Type II patient occupies two beds or an entire semi-private room as a private space for clinical reasons, resulting in one empty but unavailable (blocked) bed per Type II patient. Because little data is available on blocked beds and Type II patients, unit-level hospital bed planning studies that consider blocked beds have been lacking. This thesis study bridges that gap by building a single-stream and a two-stream discrete micro-simulation model in Excel VBA to describe unit-level bed queue dynamics at hourly granularity in the next 48-hour time horizon, using historical arrival rates and census-dependent discharge rates, supplemented with qualitative results on complexity of patient-level discharge prediction. Results showed that while we increase additional semiprivate beds, there was notable difference between the traditional single-stream model and the two-stream model concerning improvement in bed queue size. Possible directions for future research include patient-level discharge prediction considering both clinical and nonclinical milestones, and strategic redesign of hospital unit(s) considering overflows and internal transfers

The impact of the emergency department crowding on acutely ill patient experience and hospital performance

Background: ED Crowding is stated as one of the biggest problems in healthcare services that is compromising the quality of care and the performance of EDs and raising problems for patients. Objectives: to expand and provide an updated critical analysis of the findings of peerreviewed research studies, exploring the impact of ED crowding on patient experience and hospital performance. Methods: a systematic literature review was applied, and it includes Englishlanguage scientific articles and primary studies. Inclusion criteria: articles with crowding measure/scale identified and with sufficient scientific evidence to support its impact on one or both affected strands. Search terms: 'Emergency Department', 'ED', 'Emergency Room', 'Emergency Service', 'Crowding', 'Overcrowding', 'Patient Satisfaction', 'Patient Experience' and 'Hospital Performance'. Results: all identified studies revealed an association between ED crowding and patient satisfaction and perceived quality of care. It was, also, identified an association between ED crowding and several KPIs, demonstrating that it has a negative impact on hospital productivity, quality and operational, logistic and financial performance. Conclusions: Literature revealed that ED crowding contributed to a poor patient experience, once it had impact on several domains of healthcare system, such as: safety, efficiency, timeliness, patient-centred care delivery and patient’s perceived quality of care and overall satisfaction. In the future, it would be interesting to develop a primary study about this subject in Portugal, once ED crowding is point out as one of the biggest problems in the Portuguese healthcare sector and there is a lack of studies investigating the Portuguese reality on this matter.Enquadramento: a sobrelotação do serviço de urgência é identificada como um dos maiores problemas na área da saúde, que está a comprometer a qualidade dos cuidados prestados e o desempenho dos Serviços de Urgência (SUs) e a prejudicar o doente agudo. Objetivos: expandir e facultar uma análise crítica e atualizada de resultados encontrados na revisão da literatura dos artigos científicos, sobre o impacto da sobrelotação do serviço de urgência na experiência do doente agudo e no desempenho do hospital. Metodologia: foi aplicada uma revisão sistemática da literatura, que inclui artigos científicos em inglês e estudos primários. Critérios de inclusão: artigos onde foi identificada um indicador de sobrelotação e com evidência científica suficiente que fundamente o impacto deste fenómeno numa ou nas duas vertentes afetadas. Termos de pesquisa: 'Serviço de Urgência', 'SU', 'Sobrelotação', 'Satisfação do Doente', 'Experiência do Doente', e 'Desempenho do Hospital'. Resultados: todos os artigos incluídos na revisão sistemática da literatura revelaram que existe uma associação entre a sobrelotação do SU e a satisfação e perceção do doente sobre a qualidade de cuidados e vários indicadores de desempenho, demonstrando que esta tem um impacto negativo na qualidade, produtividade e desempenho do hospital. Conclusão: esta revisão revelou que a sobrelotação do SU contribuí para que o doente tenha uma experiência pobre no SU, uma vez que tem impacto em vários domínios do sistema de saúde, tais como: segurança, eficiência, pontualidade, prestação de cuidados centrada no doente, satisfação geral e perceção que o doente tem da qualidade dos cuidados. No futuro, seria interessante desenvolver um estudo primário sobre este tema em Portugal, uma vez que a sobrelotação do SU é apontada como um dos maiores problemas do sistema de saúde português e que existe uma escassez de estudos que investiguem a realidade portuguesa sobre esta matéria. Palavras-chave: gestão de saúde, sobrelotação, serviço de urgência, indicadores de desempenho, experiência do doente agudo ou satisfação do doente agudo e desempenho do hospital

Demand and capacity imbalance in the emergency department, and patient outcomes

Background An emergency department (ED) is always open and continuously needs to balance the inflow and demand for emergency service with available capacity. When demand exceeds the available capacity of an ED, it is referred to as crowding. Crowding is a critical concern for EDs worldwide, and there is evidence that it is associated with increased mortality, morbidity, and an unsustainable working environment. One of the most critical factors impacting crowding is the access to hospital beds at the right level of care to allow for a timely admission of patients. The long-term trend across the OECD countries is that the number of hospital beds per capita is declining. This development is mainly positive and driven by improvements in diagnostics and clinical care, resulting in more efficient use of resources. However, reducing hospital beds without a concurrent innovation that leads to a reduction in the demand for inpatient care will likely lead to an increased bed occupancy that could result in crowding and poor outcomes for patients. Aims This doctoral thesis aims to improve the knowledge of demand and capacity imbalance in the ED and how this impacts patient outcomes. More specifically: 1. Is hospital bed occupancy associated with increased mortality? 2. Is hospital bed occupancy associated with crowding? 3. Is crowding associated with increased mortality? Methods The thesis includes four studies, three large retrospective cohort studies, analyzing around 2 million adult ED visits in each study using survival analysis. Hazard ratios are estimated using a cox proportional hazards model. The model is adjusted for potential confounding factors such as case-mix and arrival time. The model allows for differences between hospitals in the underlying risk, and seasonal trends are considered using calendar time as the underlying time scale. The remaining study is a descriptive study of the developments of crowding and key input, throughput, and output factors during the first wave of COVID-19 at a university hospital. Results Aim 1: Study I found no statistically significant association between hospital bed occupancy and 30-day mortality. Aim 2: In Study I, there was an association between bed occupancy and crowding. For each 10% increase in bed occupancy, the length of stay in the ED increased by 16 minutes for all patients and 28 minutes for admitted patients. In Study III, there was an association between emergency ward occupancy and crowding with an estimated correlation (95% CI) between mean ED LOS and mean emergency ward bed occupancy of 0.94 (0.55 – 0.99). Aim 3: Study II identified a statistically significant association between crowding and 30-day mortality with an estimated HR (95% CI) of 1.08 (1.03-1.14) in the high category of crowding, which included the top 5% of ED visits most exposed to crowding. The study included visits from Stockholm County during 2012-2016. Study IV used the same methodology but included visits to 14 EDs in four counties during 2015-2019. The results were mixed, and only Stockholm county had robust associations between crowding and mortality. Estimated HRs for 30-day mortality in Stockholm county in the subgroup analysis for admitted patients was 1.06 (1.01-1.12) in the moderate category and 1.11 (1.01-1.22) in the high. During the study period, the average hospital bed occupancy in Stockholm was 101% compared to 92% in Skåne and 81% in Östergötland. Conclusions A relative increase in hospital bed occupancy is not necessarily associated with increased mortality among patients seeking care at the ED. It is, however, associated with additional workload and increased crowding in the ED. The association between crowding and mortality varies by hospital, and there are statistically significant associations in some, but not all. Since the association is not universal, it may potentially be avoidable. An additional finding is that there are signs that a high hospital bed occupancy may modify and reinforce the association between crowding and mortality. If this would be the case, patients exposed to a combination of boarding and crowding may be at risk of poor outcomes. Investigating outcomes and mechanisms for this patient group should be a priority in future research

Stochastic Models for Capacity Planning in Healthcare Delivery: Case Studies in an Outpatient, Inpatient and Surgical Setting

U.S. healthcare system has become far too complex and costly to sustain and operations research has much to contribute in improving health systems by addressing a large spectrum of problems. We study capacity planning in healthcare while considering the case-mix of patients, using stochastic modeling in different application areas: primary care, inpatient bed allocation and (spine) surgery scheduling. This body of work was developed over four years of collaborative research with hospitals and healthcare providers. The main objective of our research in primary care is to optimize the patient mix of primary care physicians in a group practice to maximize patient-clinician continuity and access. To model case-mix, we use the number of simultaneous chronic conditions (comorbidities) a patient has as a predictor of the number of appointment requests. We later extend the optimization framework and use queuing theory to develop methodologies to quantify and evaluate access to care and continuity of care for patient visits with different urgencies. From an inpatient care perspective, we develop an empirically calibrated simulation model to represent a time-varying multi-server queuing network model with multiple patient classes. Our main focus has been on quantifying the impact of discharge profiles to alleviate inpatient bed congestions. The main objective of our research in surgical care is to create better patient access and improve revenue as a result of increased surgical capacity with more efficient schedules and an improved patient mix, using a multi-stage mixed integer optimization

An Analysis of the Concept of Patient Flow Management

Aim: To analyze the concept of patient flow management. Background: Patient flow has a significant impact on the provision of patient care. The term “patient flow” is widely used, but the related concept of patient flow management has been poorly defined. The ability to differentiate and clarify the term patient flow management has implications on strategies to improve patient flow. Design: Rodgers evolutionary method of concept analysis. Data Source: Literature published between 2000 and 2021 in the PubMed, CINAHL, and Business Source databases. Review Methods: Inductive analysis of the literature was performed to identify the usage and features of the concept. Results: Patient flow management is defined as the application of holistic perspectives, dynamic data, and complex considerations of multiple priorities to enable timely, efficient, and high‐quality patient care. Patient flow management requires the identification of a patient, care processes, a flow manager, and frontline staff. It has profound consequences on patient, staff, and hospital system outcomes. Conclusions: Literature should more carefully delineate between “patient flow” and patient flow management. Effective patient flow management increases the speed and quality of patient care, improves employee satisfaction, and reduces healthcare costs. Strategies to improve patient flow management should focus on understanding the role and interventions of flow management nurses

A Grounded Theory of Patient Flow Management within the Emergency Department

Background: Emergency department (ED) crowding is an urgent threat to patient safety and negatively impacts healthcare staff and institutions. Patient flow researchers have employed a range of methods to address this crisis, including an increase in the use of operations research and operations management strategies. However, identified patient flow solutions are inadequate. Research describing the complexities of patient flow processes and investigating the work and contributions of ED nurses is needed. Purposes: The purposes of this study were to explore how ED nurses perform patient flow management and to develop a constructivist grounded theory of patient flow management within the ED. Methods: A conceptual foundation for patient flow management was first established using evolutionary concept analysis and expanded concept analysis approaches. This study then employed constructivist grounded theory and situational analysis methodologies to examine the work of ED nurses. Data was collected through 29 focus groups and interviews with 27 participants and 64 hours of participant observations across four EDs. Data analysis relied on coding, constant comparative analysis, and memo-writing to identify emergent themes and develop a substantive theory. Findings: Concept analyses defined patient flow management as the application of ED experience, holistic perspectives, dynamic data, and complex considerations of multiple priorities by ED nurses to promote patient safety within their scope of responsibility. The study offers three main contributions: a theoretical model of the work of ED patient flow management, a theoretical framework to describe holistic considerations of factors that impact departmental capacity and nurse engagement in patient flow management, and a grounded theory of patient flow management capacity and engagement that describes how ED nurses adapt patient flow management strategies according to patient burden. Conclusion: This study offers a new conceptual and theoretical foundation to understand the work of patient flow management. This novel perspective centralizes the work of ED nurses as active agents in patient flow processes and describes their strategies and contributions to meet patient care needs. Several practical considerations are offered to engage and support nurses in their roles as patient flow managers, improve patient flow processes, and further investigate ED nurse patient flow management

Essays on patient-flow in the emergency department

Emergency department (ED) overcrowding is a global concern. To help mitigate this issue, this thesis studies impediments to efficient patient flow in the ED caused by suboptimal worker behaviors and patient routing policies. I focus on three issues: (i) admission batching, (ii) hallway placement and (iii) under-triage behavior, and empirically demonstrate their impact on patient flow and quality of care. These studies are summarized as follows. Admissions batching: We study the behavior of admitting patients back-to-back (i.e., batching) by ED physicians. Using data from a large hospital, we show that the probability of batching admissions is increasing in the hour of an ED physician’s shift, and that batched patients experience a longer delay from hospital admission to receiving an inpatient bed. We further show that this effect is partially due to the increase in the coefficient of variation of inpatient bed-requests caused by batching. However, we also find that batching admissions is associated with a higher shift-level productivity. An important implication of our work is that workers may induce delays in downstream stages, caused by practices that increase their productivity. Hallway utilization: A common practice in busy EDs is to admit patients from the waiting area to hallway beds as the regular beds fill up. Using data from a large ED, we first perform a causal analysis to quantify the impact of hallway placement on wait times and quality of care – as defined by disposition time, room-to-departure (R2D) time and likelihood of adverse outcomes. We find that patients admitted to the hallway experience a significantly lower door-to-doctor time at the cost of longer disposition and R2D times. Hallway patients are also substantially more likely to experience an adverse outcome. Next, using a counterfactual analysis we show that a pooling policy, where hallway beds are used only if all regular beds are full, significantly reduces wait times, albeit at the cost of a slightly higher hallway utilization. Also, too little or too much wait tolerance for rooming patients may result in under- or over-utilization of the hallway space, both of which are detrimental to overall ED length of stay (LOS) and wait times. Under-triage behavior: Triaging ED patients upon arrival to the ED and assessing their urgency for treatment is crucial for timely service to all patients. Despite the standard patient classification algorithm by which all nurses are trained, we hypothesize, and show, that the ED’s workload impacts the perceived patient urgency, and subsequently, patient severity scores. We first use a predictive model to predict a patient’s true triage level using information collected at triage and define under-triage, accordingly. We find that under-triage is decreasing up to a certain point of workload but increasing after (U-shape). We also quantify the impact of under-triage on disposition time, room-to-departure time and risk of readmission. Collectively, this thesis demonstrates how patient-flow may be improved without the need to increase explicit physical capacity in the ED (e.g., beds). It offers practical solutions to managers and contributes to the operations management literature

Stochastic Models of Patient Access Management in Healthcare

abstract: This dissertation addresses access management problems that occur in both emergency and outpatient clinics with the objective of allocating the available resources to improve performance measures by considering the trade-offs. Two main settings are considered for estimating patient willingness-to-wait (WtW) behavior for outpatient appointments with statistical analyses of data: allocation of the limited booking horizon to patients of different priorities by using time windows in an outpatient setting considering patient behavior, and allocation of hospital beds to admitted Emergency Department (ED) patients. For each chapter, a different approach based on the problem context is developed and the performance is analyzed by implementing analytical and simulation models. Real hospital data is used in the analyses to provide evidence that the methodologies introduced are beneficial in addressing real life problems, and real improvements can be achievable by using the policies that are suggested. This dissertation starts with studying an outpatient clinic context to develop an effective resource allocation mechanism that can improve patient access to clinic appointments. I first start with identifying patient behavior in terms of willingness-to-wait to an outpatient appointment. Two statistical models are developed to estimate patient WtW distribution by using data on booked appointments and appointment requests. Several analyses are conducted on simulated data to observe effectiveness and accuracy of the estimations. Then, this dissertation introduces a time windows based policy that utilizes patient behavior to improve access by using appointment delay as a lever. The policy improves patient access by allocating the available capacity to the patients from different priorities by dividing the booking horizon into time intervals that can be used by each priority group which strategically delay lower priority patients. Finally, the patient routing between ED and inpatient units to improve the patient access to hospital beds is studied. The strategy that captures the trade-off between patient safety and quality of care is characterized as a threshold type. Through the simulation experiments developed by real data collected from a hospital, the achievable improvement of implementing such a strategy that considers the safety-quality of care trade-off is illustrated.Dissertation/ThesisDoctoral Dissertation Industrial Engineering 201

Missed Nursing Care Reported by Medical-Surgical RNs in a Community Hospital

Background: Missed nursing care is defined as any lapse in essential patient care. It is a previously studied, persistent phenomenon. If unrecognized, it can compromise patients’ recoveries, trigger adverse events, and increase healthcare costs. Objectives: To examine the prevalence of missed nursing care reported by medical-surgical registered nurses (RNs) and contributing factors for its occurrence. Methods: The project used a cross-sectional, correlational design. A convenience sample of 96 RNs, recruited from three medical-surgical units, completed the MISSCARE Survey between September and October 2017. An analysis of survey responses quantified the frequency, nature, and common contributing factors for care omissions. The project was set in a small, Northeast, Pathway to Excellence® designated hospital. Results: Fifty-two RNs completed surveys, most who were female (94.2%), held a Bachelor’s in Nursing degree (53.8%), and had 10+ years of work experience (34.6%). Over 1 in 5 respondents reported five nursing tasks were “frequently” or “always” missed: care conferences (46.1%), scheduled ambulation (36.5%), turning (34.6%), monitoring intake and output (23.1%), and timely medications administration (23.1%). Significant contributors to care omissions were: heavy admission/discharge activity (57.7%), fewer assistive personnel (55.8%), staff shortages (50.0%), and unbalanced patient assignments (40.4%). Conclusions: RNs identified the top five missed nursing care items in a small, community hospital and cited patient turnover, labor resource shortages, and unbalanced assignments as key, contributing factors. Inter-professional communication and teamwork effectiveness were not reported as contributing factors. Project results should inform nurse leaders’ efforts to devise interventions to safeguard patients, improve quality, and decrease cost