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Patients increasingly rely on online physician ratings to select their physicians and make health care decisions. However, it is unclear whether online physician ratings signal physician quality information and affect patients' physician choices. By combining physician rating data from Yelp with data from Medicare, which covers a large elderly patient group, the authors find that ratings are positively associated with important measures of physician quality, including physicians' credentials, adherence to clinical guidelines, and patients' health outcomes. They introduce novel instrumental variables, where reviewers' leniency in rating other businesses is employed as an instrument for physicians' ratings. They find that an increase in physicians' average rating increases physicians' patient flow. To understand the quality signals that patients respond to, the authors also use the latent Dirichlet allocation model and extract topics from review texts. Patients respond differentially to different information and respond most to information about physicians' interpersonal and clinical skills. In addition, rating credibility, accessibility, and strength of other existent signals moderate the positive effects of online ratings on patient flow. Overall, online physician rating platforms can promote efficiency by disseminating important quality information to patients and directing patients to higher-quality physicians. [ABSTRACT FROM AUTHOR]

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Spontaneous epistaxis is a common cause of emergency department's (ED) visit. Considering ED's overcrowding, it seems interesting to study risk factors of hospitalisation or long length of stay to increase triage's quality. Thus, we performed a prospective analysis to assess average length of stay of patients with spontaneous epistaxis. Secondary objectives were to find putative risk factor of longer length of stay. From February 13th, 2023, to August 31st, 2023, a prospective observational study was performed in five EDs among patients who consult for spontaneous epistaxis. We collected the following time items – arrival, first contact with triage nurse, first medical contact, and discharged or admission time. We also collected sociodemographic, medical history, daily medications, and care in the ED. Among 106 patients, median length of stay in the ED was 144 min. No patient was discharged before 28 min and the longest duration was 625 min (10 h and 25 min. Half epistaxis was already dried up before their arrival in the ED. Main risks factors to long ED length of stay were the hour of admission between midnight and eight am, the need of a blood sample and a consult with an ORL. We did not find any impact of the location of care, hypertension, age, or blood thinners. Half of patient presenting in the ED for spontaneous epistaxis was discharged in 144 min. This duration is significantly prolonged during night shift, if blood was sampled, or if an ORL consult was needed. Key Messages: Length of stay in the ED for a patient that consult for spontaneous anterior epistaxis is 2 h and 20 min. Night and ORL consults increase this duration. Hypertension, age, or blood thinners do not increase this duration. [ABSTRACT FROM AUTHOR]

Background: Emergency department (ED) overcrowding has formed a significant barrier to timely emergency care in Korea for the past 30 years; an associated problem, the shortage of on-call specialists, has persisted for the past 10 years. Current Concepts: ED overcrowding has gradually improved since controls were imposed on the length of ED stay times. Improving hospital efficiency and patient flow can increase the number of patients treated while minimizing treatment delays and improving patient care quality. Provision of critical care in hospitals after emergency treatment in the ED is essential for critically ill emergent patients. Many specialists have difficulty getting paid for their ED services as emergency care costs are very low. Specialists may also be deterred by the additional liability risks of working in the ED. Discussion and Conclusion: Many residents have withdrawn from emergent critical care in Korea due to conflicts between the government and doctors. Therefore, the government has recommended that patients with mild emergencies be prohibited from using the ED. However, there are more effective solutions to the emergency medicine crisis. Management of emergency patient flow through an "input--throughput--output" process that encompasses pre-hospital and in-hospital emergency medical services, regional emergency care, and interregional emergencies, should be effectively overseen. Additionally, the government should provide support for any resource deficiencies. To ensure a hopeful future for emergency care in Korea, both the government and doctors should strive to build an emergency care network that will operate through pre-hospital and hospital emergency care, inter-ED, and inter-regional emergency care systems. [ABSTRACT FROM AUTHOR]

Abstract Introduction Biological Events affect large populations depending on transmission potential and propagation. A recent example of a biological event spreading globally is the COVID-19 pandemic, which has had severe effects on the economy, society, and even politics,in addition to its broad occurrence and fatalities. The aim of this scoping review was to look into patient flow management techniques and approaches used globally in biological incidents. Methods The current investigation was conducted based on PRISMA-ScR: Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews. All articles released until March 31, 2023, about research question were examined, regardless of the year of publication. The authors searched in databases including Scopus, Web of Science, PubMed, Google scholar search engine, Grey Literature and did hand searching. Papers with lack of the required information and all non-English language publications including those with only English abstracts were excluded. Data extraction checklist has been developed Based on the consensus of authors.the content of the papers based on data extraction, analyzed using content analysis. Results A total of 19,231 articles were retrieved in this study and after screening, 36 articles were eventually entered for final analysis. Eighty-four subcategories were identified,To facilitate more precise analysis and understanding, factors were categorised into seven categories: patient flow simulation models, risk communication management, integrated ICT system establishment, collaborative interdisciplinary and intersectoral approach, systematic patient management, promotion of health information technology models, modification of triage strategies, and optimal resource and capacity management. Conclusion Patient flow management during biological Events plays a crucial role in maintaining the performance of the healthcare system. When public health-threatening biological incidents occur, due to the high number of patients, it is essential to implement a holistic,and integrated approach from rapid identification to treatment and discharge of patients.

Abstract Background Outpatient Clinics (OCs) are under pressure because of increasing patient volumes and provider shortages. At the same time, many patients with chronic diseases receive routine follow-up consultations that are not always necessary. These patients block access to care for patients that are in actual need for care. Pre-assessing patient charts has shown to reduce unnecessary outpatient visits. However, the resulting late cancellations due to the pre-assessment, challenge efficient alignment of capacity with actual patient demand, leading to either empty slots or overtime. This study aims to develop a method to analyse the effect of pre-assessing patients before inviting them to the OC. This involves 1) to select who should come and 2) to optimize the impact of pre-assessment on the schedule and efficient use of OC staff. Methods This prospective mixed-methods evaluation study consists of 1) an expert meeting to determine a pre-assessment strategy; 2) a retrospective cohort study to review the impact of this strategy (12 months of a Dutch nephrology OC); 3) mathematical optimization to develop an optimal criteria-based scheduling strategy; and 4) a computer simulation to evaluate the developed strategy. Primary outcomes are the staff idle time and staff overtime. Secondary outcomes evaluate the number of weekly offered appointments. Results The expert group reached consensus about the pre-assessment criteria. 875 (18%) of the realized appointments in 2022 did not meet the OC visit pre-assessment criteria. In the best performing scheduling strategy, 94 slots (87% of the available capacity) should be scheduled on a weekly basis. For this schedule, 26.8% of the OC weeks will experience idle time ( $$\mu$$ μ =2.51, $$\sigma$$ σ =1.44 appointment slots), and 21% of the OC weeks will experience overtime ( $$\mu$$ μ =2.26, $$\sigma$$ σ =1.65 appointment slots) due to the variation in patient appointment requests. Using the pre-assessment strategy combined with the best performing scheduling strategy under full capacity (108 slots), up to 20% increase in patient demand can be handled with equal operational performance. Conclusions This evaluation study allows OC managers to virtually test operational impact of pre-assessment strategies on the capacity of their OC, and shows the potential of increasing efficient use of scarce healthcare capacity. Trial registration Not applicable.

Introduction: Biological Events affect large populations depending on transmission potential and propagation. A recent example of a biological event spreading globally is the COVID-19 pandemic, which has had severe effects on the economy, society, and even politics,in addition to its broad occurrence and fatalities. The aim of this scoping review was to look into patient flow management techniques and approaches used globally in biological incidents. Methods: The current investigation was conducted based on PRISMA-ScR: Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews. All articles released until March 31, 2023, about research question were examined, regardless of the year of publication. The authors searched in databases including Scopus, Web of Science, PubMed, Google scholar search engine, Grey Literature and did hand searching. Papers with lack of the required information and all non-English language publications including those with only English abstracts were excluded. Data extraction checklist has been developed Based on the consensus of authors.the content of the papers based on data extraction, analyzed using content analysis. Results: A total of 19,231 articles were retrieved in this study and after screening, 36 articles were eventually entered for final analysis. Eighty-four subcategories were identified,To facilitate more precise analysis and understanding, factors were categorised into seven categories: patient flow simulation models, risk communication management, integrated ICT system establishment, collaborative interdisciplinary and intersectoral approach, systematic patient management, promotion of health information technology models, modification of triage strategies, and optimal resource and capacity management. Conclusion: Patient flow management during biological Events plays a crucial role in maintaining the performance of the healthcare system. When public health-threatening biological incidents occur, due to the high number of patients, it is essential to implement a holistic,and integrated approach from rapid identification to treatment and discharge of patients. [ABSTRACT FROM AUTHOR]

Background: Outpatient Clinics (OCs) are under pressure because of increasing patient volumes and provider shortages. At the same time, many patients with chronic diseases receive routine follow-up consultations that are not always necessary. These patients block access to care for patients that are in actual need for care. Pre-assessing patient charts has shown to reduce unnecessary outpatient visits. However, the resulting late cancellations due to the pre-assessment, challenge efficient alignment of capacity with actual patient demand, leading to either empty slots or overtime. This study aims to develop a method to analyse the effect of pre-assessing patients before inviting them to the OC. This involves 1) to select who should come and 2) to optimize the impact of pre-assessment on the schedule and efficient use of OC staff. Methods: This prospective mixed-methods evaluation study consists of 1) an expert meeting to determine a pre-assessment strategy; 2) a retrospective cohort study to review the impact of this strategy (12 months of a Dutch nephrology OC); 3) mathematical optimization to develop an optimal criteria-based scheduling strategy; and 4) a computer simulation to evaluate the developed strategy. Primary outcomes are the staff idle time and staff overtime. Secondary outcomes evaluate the number of weekly offered appointments. Results: The expert group reached consensus about the pre-assessment criteria. 875 (18%) of the realized appointments in 2022 did not meet the OC visit pre-assessment criteria. In the best performing scheduling strategy, 94 slots (87% of the available capacity) should be scheduled on a weekly basis. For this schedule, 26.8% of the OC weeks will experience idle time (μ =2.51, σ =1.44 appointment slots), and 21% of the OC weeks will experience overtime (μ =2.26, σ =1.65 appointment slots) due to the variation in patient appointment requests. Using the pre-assessment strategy combined with the best performing scheduling strategy under full capacity (108 slots), up to 20% increase in patient demand can be handled with equal operational performance. Conclusions: This evaluation study allows OC managers to virtually test operational impact of pre-assessment strategies on the capacity of their OC, and shows the potential of increasing efficient use of scarce healthcare capacity. Trial registration: Not applicable. [ABSTRACT FROM AUTHOR]

• Inappropriate in-hospital settings increase clinical risk for acute medical patients. • A Medical Admission Unit run by Internists redesigned the acute patient flow. • MAU ensured a high turn-over downsizing the outlying phenomenon. • MAU centralised unstable medical patients reducing in-hospital mortality. • A patient-centred and problem-oriented approach lowers clinical risk. the burden of acute complex patients, increasingly older and poli-pathological, accessing to Emergency Departments (ED) leads up hospital overcrowding and the outlying phenomenon. These issues highlight the need for new adequate patients' management strategies. The aim of this study is to analyse the effects on in-hospital patient flow and clinical outcomes of a high-technology and time-limited Medical Admission Unit (MAU) run by internists. all consecutive patients admitted to MAU from Dec-2017 to Nov-2019 were included in the study. The admissions number from ED and hospitalization rate, the overall in-hospital mortality rate in medical department, the total days of hospitalization and the overall outliers bed days were compared to those from the previous two years. 2162 patients were admitted in MAU, 2085(95.6%) from ED, 476(22.0%) were directly discharged, 88(4.1%) died and 1598(73.9%) were transferred to other wards, with a median in-MAU time of stay of 64.5 [0.2–344.2] hours. Comparing the 24 months before, despite the increase in admissions/year from ED in medical department (3842 ± 106 in Dec2015–Nov2017 vs 4062 ± 100 in Dec2017-Nov2019, p <0.001), the number of the outlier bed days has been reduced, especially in surgical department (11.46 ± 6.25% in Dec2015–Nov2017 vs 6.39 ± 3.08% in Dec2017-Nov2019, p =0.001), and mortality in medical area has dropped from 8.74 ± 0.37% to 7.29 ± 0.57%, p <0.001. over two years, a patient-centred and problem-oriented approach in a medical admission buffer unit run by internists has ensured a constant flow of acute patients with positive effects on clinical risk and quality of care reducing medical outliers and in-hospital mortality. [ABSTRACT FROM AUTHOR]

Introduction: The tradition of charitable medical treatment can be drawn back to the early years of Christianity when the Church growth closely related to the care for the sick as well as other charitable activities. Though its purpose is charity, free medical service should also improve the quality of service. It can be achieved through the implementation of lean six sigma tools. One of its tools is a process map. Process map in Lean Six Sigma is commonly used as a diagnostic tool to determine the possible bottlenecks in the system. Methods: This is a brief pre and post quality improvement study. Before the implementation of a process map suggested by the researcher (period I), the patient flow was not properly organized. After the lunch break, the researcher introduced a new process map and briefed it to the committee. The patients flow in the afternoon (Period II) was using the process map. Patient numbers and wait times were measured within the time interval of this study. Results: Out of 159 patients who served during the period of this study, 63 (40%) were male and 96 (60%) were female. During Period I of the medical service, 50 patients (31%) were treated with average 17 patients per hour and approximate waiting time 36 minutes. After implementation of process map (Period II) the number of patients served were 109 (69%) with an average 36 patients per hour and an approximate waiting time of 17 minutes. Conclusion: The implementation of process map in free medical service may assist in increasing the number of patients served and reduce the waiting time as a result. Apart from reducing the confusion of where the patients were to go next, the process map also help the committee to identify possible hinderances and address the impediments to efficient charitable medical care.

Background: Rising ED boarding and visit volumes are challenges to maintaining patient flow and avoiding patients leaving without being seen. Objectives: We aimed to decrease left without being seen and improve ED patient flow by minimizing time patients spent in the waiting room in the early hours of the day when treatment spaces are usually available. Methods: We implemented a “Waiting room zero before noon” campaign in our urban community emergency department. Providers and nurses were messaged about this goal and the expectation was set that patients should be brought to a room even if a nurse was not immediately available to care for them. Results: In the three months following this campaign, we experienced a significant decrease in left without being seen. This decrease persisted over the subsequent two years, despite increasing patient volume. Conclusion: A simple, cost-neutral campaign aimed at changing workflow culture was able to achieve improvements in patient flow despite continued challenges of rising boarding and volume.

Background: Admission for renal biopsy is considered the gold standard for diagnosing kidney disease. However, prolonged waiting times for admission can lead to delayed diagnosis. Despite this issue, there are currently no studies demonstrating how to improve the efficiency of renal biopsy procedures. Methods: We initiated a quality improvement project to implement pre-admission testing (PAT) for renal biopsy from 2016 to 2024 (until 15 April). Our evaluation focused on waiting times for admission, length of admission periods, hospitalization expenses, percentage of cases with no renal biopsy performed, incidence of severe bleeding due to renal biopsy, and percentage of cases with adequate tissue samples obtained. Additionally, we highlighted the time periods during the outbreak of SARS-CoV-2. Results: The highest annual case number was observed in time period 1 (168.3/year). Following the outbreak of SARS-CoV-2, there was a notable decrease in case numbers during time period 2 (119.8), which then increased to 143.0 in time period 3 (post-SARS-CoV-2 era). The mean waiting time was 13.72 ± 40.30 days for time period 1 and 10.00 ± 47.80 days for time period 2, without statistical significance. Following the implementation of PAT, patients now only need to wait approximately 0.76 days for admission, representing a significant reduction in waiting time. Subsequently, following the implementation of PAT, the waiting time decreased significantly to 2.09 ± 2.65 days. Additionally, hospitalization expenses per patient significantly decreased from approximately USD 69.62 ± 97.09 to USD 41.66 ± 52.82. The percentage of missed biopsy is significantly low (p < 0.001). Severe bleeding events (indicated as embolization and blood transfusion) were consistent across the three time periods (p = 0.617). Conclusions: The implementation of PAT can improve the pre-admission process for renal biopsy, resulting in decreased waiting times, fewer missed appointments, shorter admission durations, and reduced hospitalization expenses. We propose implementing PAT for outpatient individuals awaiting in-hospital renal biopsy procedures to mitigate delayed diagnosis, reduce pre-admission waiting periods, and streamline admission processes, thereby enhancing overall patient care efficiency. [ABSTRACT FROM AUTHOR]

Abstract Background The continual increase in patient attendance at the emergency department (ED) is a worldwide health issue. The aim of this study was to determine whether the use of a secondary prioritization software reduces the patients’ median length of stay (LOS) in the pediatric ED. Methods A randomized, controlled, open-label trial was conducted over a 30-day period between March 15th and April 23rd 2021 at Lille University Hospital. Work days were randomized to use the patient prioritization software or the pediatric ED’s standard dashboard. All time intervals between admission and discharge were recorded prospectively by a physician not involved in patient care during the study period. The study’s primary endpoint was the LOS in the pediatric ED, which was expected to be 15 min shorter in the intervention group than in the control group. The secondary endpoints were specific time intervals during the stay in the pediatric ED and levels of staff satisfaction. Results 1599 patients were included: 798 in the intervention group and 801 in the control group. The median [interquartile range] LOS was 172 min [113–255] in the intervention group and 167 min [108–254) in the control group (p = 0.46). In the intervention group, the time interval between admission to the first medical evaluation for high-priority patients and the time interval between the senior physician’s final evaluation and patient discharge were shorter (p

Abstract Background Globally, emergency departments (EDs) are overcrowded and unable to meet an ever-increasing demand for care. The aim of this study is to comprehensively review and synthesise literature on potential solutions and challenges throughout the entire health system, focusing on ED patient flow. Methods An umbrella review was conducted to comprehensively summarise and synthesise the available evidence from multiple research syntheses. A comprehensive search strategy was employed in four databases alongside government or organisational websites in March 2023. Gray literature and reports were also searched. Quality was assessed using the JBI critical appraisal checklist for systematic reviews and research syntheses. We summarised and classified findings using qualitative synthesis, the Population-Capacity-Process (PCP) model, and the input/throughput/output (I/T/O) model of ED patient flow and synthesised intervention outcomes based on the Quadruple Aim framework. Results The search strategy yielded 1263 articles, of which 39 were included in the umbrella review. Patient flow interventions were categorised into human factors, management-organisation interventions, and infrastructure and mapped to the relevant component of the patient journey from pre-ED to post-ED interventions. Most interventions had mixed or quadruple nonsignificant outcomes. The majority of interventions for enhancing ED patient flow were primarily related to the 'within-ED' phase of the patient journey. Fewer interventions were identified for the 'post-ED' phase (acute inpatient transfer, subacute inpatient transfer, hospital at home, discharge home, or residential care) and the 'pre-ED' phase. The intervention outcomes were aligned with the aim (QAIM), which aims to improve patient care experience, enhance population health, optimise efficiency, and enhance staff satisfaction. Conclusions This study found that there was a wide range of interventions used to address patient flow, but the effectiveness of these interventions varied, and most interventions were focused on the ED. Interventions for the remainder of the patient journey were largely neglected. The metrics reported were mainly focused on efficiency measures rather than addressing all quadrants of the quadruple aim. Further research is needed to investigate and enhance the effectiveness of interventions outside the ED in improving ED patient flow. It is essential to develop interventions that relate to all three phases of patient flow: pre-ED, within-ED, and post-ED.

Abstract Background To determine the effectiveness of applying the Sydney Triage to Admission Risk Tool (START) in conjunction with senior early assessment in different Emergency Departments (EDs). Methods This multicentre implementation study, conducted in two metropolitan EDs, used a convenience sample of ED patients. Patients who were admitted, after presenting to both EDs, and were assessed using the existing senior ED clinician assessment, were included in the study. Patients in the intervention group were assessed with the assistance of START, while patients in the control group were assessed without the assistance of START. Outcomes measured were ED length of stay and proportion of patients correctly identified as an in-patient admission by START. Results A total of 773 patients were evaluated using the START tool at triage across both sites (Intervention group n = 355 and control group n = 418 patients). The proportion of patients meeting the 4-hour length of stay thresholds was similar between the intervention and control groups (30.1% vs. 28.2%; p = 0.62). The intervention group was associated with a reduced ED length of stay when compared to the control group (351 min, interquartile range (IQR) 221.0–565.0 min versus 383 min, IQR 229.25–580.0 min; p = 0.85). When stratified into admitted and discharged patients, similar results were seen. Conclusion In this extension of the START model of care implementation study in two metropolitan EDs, START, when used in conjunction with senior early assessment was associated with some reduced ED length of stay.

Abstract Background Movement of patients through a health establishment is a complex activity reliant upon multi-actor co-ordination across departments. The challenge of enhancing service delivery to meet the needs of a growing and aging population, whilst minimizing expense, is a global concern. There is an urgent need to understand and quantify systemic gaps in the efficient delivery of healthcare services. Stagnation of patient flow has negative impacts on both staff and patients by increasing risks of adverse outcomes, staff frustration and job dissatisfaction. An inefficient discharge process can be a significant barrier to timely patient movement. Methods A retrospective cohort study was conducted at a tertiary, academic hospital in the Western Cape, South Africa to assess the journey of medical patients from admission to discharge across the five different medical teams (firms) within the general medicine department. Consecutive sampling was used to capture all eligible adult medical in-patients admitted from the emergency department (ED) to general medicine from the 11th – 20th April 2023 and discharged up until the 30th of April 2023. We reviewed the patient notes (folders) of these individuals using a data-extraction tool to ascertain reasons for admission and barriers to timely discharge. Results Among 86 patient folders reviewed, cumulatively accounting for 596 in-patient days, a difference in the median length of in-patient stay between medical firms (p = 0.042) was noted. The shortest length of stay corresponded to firms with the greatest proportion of daily senior staff oversight (defined as documented patient reviews by a registrar, medical officer and/or consultant independently or in addition to reviews done for the day by interns and/or students). While 52% of patients vacated their beds between 14:00 and 17:00, 66% of patients were admitted after 20:00. Reasons for prolonged admission were variable, and attributable to a range of different disciplines across the multidisciplinary team. Conclusion Whilst this study did not evaluate the appropriateness of chosen medical management but rather systemic drivers affecting patient movement and barriers to timely discharge, the delays in discharge were noted to be multi-factorial including facets across the efficient delivery of medical care, availability of resources and the internal operational frameworks for the institution. Understanding the need to optimize internal process efficiencies with regards to prompt acquisition of investigations, improvement of senior staff oversight and the creation of a standardized discharge process, could enhance efficient patient movement.

Objective Methods Results Conclusion To determine whether undertaking procedural sedation in the low‐acuity fast‐track area is safe and effective in improving patient flow.A retrospective cohort study reviewed patients who underwent procedural sedation in the Royal Brisbane and Women's Hospital Emergency and Trauma Centre between December 2020 and December 2021.A total of 411 cases were included. Performing sedation in the fast‐track area was not associated with increased complication rates but was associated with reduced time to sedation (difference = 44.24 min, P < 0.001) and length of stay (difference = 60.64 min, P < 0.01).The sedation of patients outside a high‐acuity area is safe and significantly improves patient flow. [ABSTRACT FROM AUTHOR]

BACKGROUND: Poor patient flow or patient movement through a healthcare organisation can lead to adverse outcomes for patients and organisational inefficiency. Many hospitals have addressed suboptimal patient flow by increasing resources, such as bed stock and staffing; however, this is an unsustainable approach. In determining the nature of poor patient flow issues, it is important to collect data from healthcare professionals who manage patient flow daily. Doing so provides insights into the current state of patient flow management in its entirety, whilst also helping with the development of sustainable solutions. METHODS: Thirteen semi-structured interviews were conducted with healthcare professionals who were directly involved with patient flow at a referring hospital in Tasmania, Australia. RESULTS: Using a thematic analysis method, four major themes were developed. The first major theme was: 'managing patient flow' which centered around known and unknown demands on bed availability. The second theme, 'communication for decisions', highlighted the essential role of communication in maintaining patient flow. The third theme, 'tools as enablers and barriers, relates to the number of software programs which can both help and hinder patient flow. The final theme of 'increasing complexity' is related to an apparent trend towards greater numbers of patients requiring care of an increasingly specialised nature. CONCLUSIONS: The findings of this study provide great insights into patient flow issues, with potential solutions identified to address them. [ABSTRACT FROM AUTHOR]

Proactive control of hospital processes significantly influences patient performance and satisfaction. The objective of the research is to develop a dashboard for the evaluation of patient flow management in hospital institutions. Descriptive quantitative study was developed and previous methodologies were analyzed. A procedure was developed for the preparation of a dashboard for the evaluation of patient flow management in hospital institutions, structured in five stages and nine steps, including procedures for the identification of key variables and aggregation of indicators. A dashboard was prepared for the General Surgery service of a Clinical Surgical Teaching Hospital, which is composed of 18 indicators, 6 synthetic indexes and an integral indicator. The integral indicator obtained a value of 0.79 (4), which shows the effectiveness of the actions implemented during the deployment of the improvement model. Among the positive implications for health managers is the possibility of monitoring strategies with a process vision. [ABSTRACT FROM AUTHOR]

This study focuses on mitigating patient congestion in healthcare departments by employing an M/G/1 queue. The system comprises of two crucial servers, HR (Human Resource) and nurse and investigates the flow of patients between them. The HR department's role in managing staffing and generating daily census reports significantly reduces nursing demand and congestion, directing patients to the nursing unit for intensive medical care. The system demonstrates stability when the HR's arrival rate is lower than its service rate, effectively reducing congestion. Utilizing the Matrix-Geometric method ensures system stability, crucial for efficient healthcare operations. The hidden Markov model, supported by the Viterbi algorithm, facilitates the determination of the most efficient HR and nurse sequencing and necessary staffing levels, accommodating sequences of any length. The novelty of the work lies in the choice of Viterbi algorithm in modelling as its computational complexity O(n)=O(6)=O(1). The hidden Markov model and Baum-Welch algorithm offer a comprehensive analysis of patient flow dynamics, unveiling hidden states and transitions that influence system performance. This comprehensive understanding aids in managing overcrowding and optimizing resource utilization. Presenting the results numerically in tables provides a holistic view of healthcare department dynamics, contributing to effective process improvements and resource allocation. This study's innovative integration of methodologies offers a sophisticated approach to understanding and optimizing the dynamics of patient flow in healthcare departments. [ABSTRACT FROM AUTHOR]

Background Globally, emergency departments (EDs) are overcrowded and unable to meet an ever-increasing demand for care. The aim of this study is to comprehensively review and synthesise literature on potential solutions and challenges throughout the entire health system, focusing on ED patient fow. Methods An umbrella review was conducted to comprehensively summarise and synthesise the available evidence from multiple research syntheses. A comprehensive search strategy was employed in four databases alongside government or organisational websites in March 2023. Gray literature and reports were also searched. Quality was assessed using the JBI critical appraisal checklist for systematic reviews and research syntheses. We summarised and classifed fndings using qualitative synthesis, the Population-Capacity-Process (PCP) model, and the input/ throughput/output (I/T/O) model of ED patient fow and synthesised intervention outcomes based on the Quadruple Aim framework. Results The search strategy yielded 1263 articles, of which 39 were included in the umbrella review. Patient fow interventions were categorised into human factors, management-organisation interventions, and infrastructure and mapped to the relevant component of the patient journey from pre-ED to post-ED interventions. Most interventions had mixed or quadruple nonsignifcant outcomes. The majority of interventions for enhancing ED patient fow were primarily related to the ’within-ED’ phase of the patient journey. Fewer interventions were identifed for the ’post-ED’ phase (acute inpatient transfer, subacute inpatient transfer, hospital at home, discharge home, or residential care) and the ’pre-ED’ phase. The intervention outcomes were aligned with the aim (QAIM), which aims to improve patient care experience, enhance population health, optimise efciency, and enhance staf satisfaction. Conclusions This study found that there was a wide range of interventions used to address patient fow, but the efectiveness of these interventions varied, and most interventions were focused on the ED. Interventions for the remainder of the patient journey were largely neglected. The metrics reported were mainly focused on efciency measures rather than addressing all quadrants of the quadruple aim. Further research is needed to investigate and enhance the efectiveness of interventions outside the ED in improving ED patient fow. It is essential to develop interventions that relate to all three phases of patient fow: pre-ED, within-ED, and post-ED. [ABSTRACT FROM AUTHOR]

Background: To determine the effectiveness of applying the Sydney Triage to Admission Risk Tool (START) in conjunction with senior early assessment in different Emergency Departments (EDs). Methods: This multicentre implementation study, conducted in two metropolitan EDs, used a convenience sample of ED patients. Patients who were admitted, after presenting to both EDs, and were assessed using the existing senior ED clinician assessment, were included in the study. Patients in the intervention group were assessed with the assistance of START, while patients in the control group were assessed without the assistance of START. Outcomes measured were ED length of stay and proportion of patients correctly identified as an in-patient admission by START. Results: A total of 773 patients were evaluated using the START tool at triage across both sites (Intervention group n = 355 and control group n = 418 patients). The proportion of patients meeting the 4-hour length of stay thresholds was similar between the intervention and control groups (30.1% vs. 28.2%; p = 0.62). The intervention group was associated with a reduced ED length of stay when compared to the control group (351 min, interquartile range (IQR) 221.0–565.0 min versus 383 min, IQR 229.25–580.0 min; p = 0.85). When stratified into admitted and discharged patients, similar results were seen. Conclusion: In this extension of the START model of care implementation study in two metropolitan EDs, START, when used in conjunction with senior early assessment was associated with some reduced ED length of stay. [ABSTRACT FROM AUTHOR]

Lack of timeliness and capacity are seen as fundamental problems that jeopardise healthcare delivery systems everywhere. Many believe the shortage of medical providers is causing this timeliness problem. This action research presents how one doctor implemented the theory of constraints (TOC) to improve the throughput (quantity of patients treated) of his ophthalmology imaging practice by 64% in a few weeks with little to no expense. The five focusing steps (5FS) guided the TOC implementation – which included the drum-buffer-rope scheduling and buffer management – and occurred in a matter of days. The implementation provided significant bottom-line results almost immediately. This article explains each step of the 5FS in general terms followed by specific applications to healthcare services, as well as the detailed use in this action research. Although TOC successfully addressed the practice problems, this implementation was not sustained after the TOC champion left the organisation. However, this drawback provided valuable knowledge. The article provides insightful knowledge to help readers implement TOC in their environments to provide immediate and significant results at little to no expense. [ABSTRACT FROM AUTHOR]

In a hospital, keeping track of patients and their needs is a multi-faceted nightmare. Each department has its own intake and check-out process, and all of this information must be in one central place. That’s why there are so many hospitals that are struggling to confirm the organization of patient data. There are several of Machine Learning algorithms that can help to optimize patient flow in hospitals, provide a real-time presentation of department workflow. This editorial will examine some of the most effective ML algorithms to solve these issues. Before we dive directly into the solutions, it is important to understand how ML can help specifically in the healthcare industry. The increased adoption of ML stipulates a wide range of new technologies and applications that would transform medicine. These healthcare developments would help providers to offer care tailored to the individual needs of patients, making treatment more effective and affordable. Although the actual impact of the algorithms on healthcare is still a subject of future research, the expected outcomes are huge. Before analyzing how they work, it is important to explain the terminology. Specifically: data mining is the manner of discovering new data or knowledge from huge amounts of data. The major focus of data mining is made on unstructured data, as e.g. medical records, social media posting or images. Machine learning implies a computer program that is trained on data to find patterns and make predictions.1 There are many types of ML algorithms, but they all have three steps in common: • Training: create a model using the data. • Use the model to make predictions. • Tune the model to get the best results. Natural Language Processing (NLP) is a type of machine learning that allows computers to understand human language.2 Health care providers use NLP to meet patients’ needs, goals, and expectations. One of the many problems in hospitals is the inability to manage patient flows through various departments and check-out points. The problem is that when patients arrive at a hospital, they can be instructed to go to the Emergency Department. They can also be told to go to a different department based on the results. In spite of the fact that it is necessary for there to be a single source of information, regardless of the department, in order to ensure that both patients and staff have access to the same level of information.3 It would be ideal to have a centralized location that provides information on the department's current availability, wait times, and staff members' status. In order to enhance the efficiency of patient flow within the hospital, administrators and healthcare providers can utilize machine learning algorithms to gather information regarding patients' arrival, departure, and current condition. In addition, it is able to evaluate the condition of each individual patient and give staff with information in real time. This strategy makes it easier to control the flow of patients in an effective manner, which in turn enables staff members to concentrate on the activities that are most important to them. There are a great number of data sources that can be operated in order to collect information regarding the conditions of patients. To ensure that activities are carried out in the most effective manner possible, it is essential that staff members have instant access to these resources. Natural language processing, often known as NLP, is a method that is utilized for the retrieval of information that is very effective. Natural Language Processing (NLP) has made it possible for computers to grasp human language. This capability was first introduced in 2005. They are able to collect vital information from a patient's report and incorporate it into the centralized system in a seamless manner.4 Because of this, the system is able to collect and store information about the diagnoses, treatments, prescriptions, and other pertinent information pertaining to patients. In addition to providing patients and staff members with real-time updates on the situation, the data may be employed to provide precise estimations of the amount of time that patients will be required to wait. In addition to this, it is able to recognize and assess patterns and trends within the process of the department, thus allowing the required adjustments to be made in order to improve efficiency. After collecting data from patients, it is possible to analyses trends and patterns within the data. The investigation has the potential to improve patient care by highlighting areas for improvement. Using an acceptable sample size, it is possible to make reliable predictions about the likelihood of specific occurrences. The use of a machine learning algorithm allows for the assessment of the likelihood that persons with specified conditions will be discharged or admitted to a medical facility.5 The use of these algorithms is critical in giving invaluable assistance to workers in the performance of their everyday activities, as well as predicting and anticipating the state of patients. The rapid examination of data has various advantages, notably in terms of minimizing wait times. The provision of timely help is an important part of controlling patient flow because it has a direct impact on patient satisfaction and likely to recommend the healthcare institution. The implementation of an automated system for data collection and analysis can assist hospitals in attaining transparency. To augment transparency within the healthcare facility, administration may elect to employ machine learning algorithms to produce status dashboards.6 This type of dashboard has the capability to deliver instantaneous updates regarding the condition of facilities and departments. It can provide details such as staff availability, wait times, and the individual patient loads of each staff member. There are specific situations in which the implementation of a decentralized system is required to assure hospital-wide transparency. Particularly designed chatbots may be employed in such circumstances to collect data and provide immediate transparency. A chatbot that is purpose-built for the hospital environment can efficiently respond to fundamental inquiries, collect critical data, and improve patient transparency. By employing ML algorithms, the efficacy of patient flow can be significantly enhanced. Conflict of interest: None declared.

In spite of continuous medical and technological advances, there are still treatments today, e.g., infertility treatments, that have not been addressed using remote monitoring due to the absence of reliable devices and smart health monitoring systems (SHMSs). A recent European Union report highlights the need for scientific investment in remote monitoring efficiency. To expedite cost-effective real-data experiments, the scientific community emphasizes complementing SHMSs with modeling and simulation techniques, allowing the projection of comprehensive treatment scenarios and informed decision-making based on synthetic data. In this paper, we conducted simulations of patient flow in two assisted reproduction clinics, with real data, applying discrete event simulation techniques. Four simulation scenarios were run for the Alicante clinic: (i) current system organization, (ii) using SHMS with the same resources, (iii) SHMS with reduced clinical staff, and (iv) SHMS with modified staff allocation. In a large-scale clinic in Madrid, two scenarios were simulated: (i) current system organization and (ii) SHMS with the same resources. The simulation of different scenarios enabled (i) the identification of a bottleneck in an ultrasound scanning area in the current system’s organization; (ii) modelling of the relocation of the clinical staff within the clinic; and (iii) a proposal of the most optimal scenario with SHMS. Comparing the obtained results, we showed a reduction in the workload of the receptionists, in the ultrasound and blood collection areas and finally reduced the workload of physicians with first half and the second half of the working day schedules in both clinics.

Abstract Background The COVID-19 pandemic has exposed gaps and areas of need in health care systems. General practitioners (GPs) play a crucial role in the response to COVID-19 and other respiratory infectious diseases (e.g., influenza). Knowing the current flow of these patients and the real needs of GPs is necessary to implement new therapeutic and diagnostic strategies. We sought to learn about the flow of COVID-19 and flu patients in Spanish primary health centers and understand the training needs in both the diagnosis and treatment of these diseases. Methods A total of 451 regionally representative GPs completed an online survey between January and February 2022. Results Most of the GPs had available infection containment measures (79%) and access to point-of-care (POC) rapid diagnostic testing (81%) in their centers. The availability of on-the-day diagnostic tests for COVID-19 was higher than that for influenza (80% vs. 20%). Most GPs referred 1 of 10 COVID-19 or flu patients with moderate to severe disease to the emergency department (80% and 90%, respectively). Training/knowledge was considered good regarding diagnostic tests and vaccines (85%) but null or low regarding antivirals (60%) and monoclonal antibodies (80%). Conclusions This survey identified the conditions of Spanish GPs in terms of the diagnosis and treatment of COVID-19 and flu patients. Respondents’ comments suggested that quite radical system-level adjustments are needed to allow GPs to capitalize on the potential benefits of POC tests for diagnosis, reduction of referrals, and monitoring of these diseases.

Purpose: High efficiency in the operating room may significantly improve the overall performance of the hospital and the service quality provided to patients. The operating room is the de facto financial hub of the hospital and maximizing its efficiency may lead to considerable improvements. To this end, we seek ways of accelerating the patient flow in order to save time and cost in healthcare facilities.Methodology: In this study, we use agent-based simulation to simulate patient care in the operating room. After performing the required validations, a number of improvement scenarios were developed and evaluated.Findings: A hybrid scenario including modifications to the referral time of the patient by the surgeon, transfer time of the surgical set and supplies to the operating room, and the timing of anesthesia proved to have the most positive impact on the criteria i.e. activities, reducing the average Length of Stay (LOS) by 9.69 minutes. The second-most effective scenario involved modifying the referral time of the patient by the surgeon, reduced the LOS by 7.31 minutes.Originality/Value: Through this research, it became apparent that minimizing the patients' LOS improves the efficiency of the operating room as it helps reduce the overall idle time and increases the number of operations carried out in each shift. Making time even for one additional operation per day significantly increases the operating room income. Moreover, a shorter LOS means less fatigue for the medical staff and reduces the total cost of running the operating room by reducing the staff's overtime hours.

Hadiki Habib,1– 3,&ast; Mondastri Korib Sudaryo4,&ast; 1Doctoral Program of Epidemiology, Epidemiology Department, Faculty of Public Health, Universitas Indonesia, Depok, Indonesia; 2Emergency Unit, Dr. Cipto Mangunkusumo Hospital/Faculty of Medicine Universitas Indonesia, Jakarta, Indonesia; 3Division of Respirology and Critical Illness, Department of Internal Medicine, Dr. Cipto Mangunkusumo Hospital/Faculty of Medicine Universitas Indonesia, Jakarta, Indonesia; 4Epidemiology Department, Faculty of Public Health, Universitas Indonesia, Depok, Indonesia&ast;These authors contributed equally to this workCorrespondence: Mondastri Korib Sudaryo, Epidemiology Department, Faculty of Public Health, Universitas Indonesia, Depok, 10430, Indonesia, Tel +62 81263488115, Email mondastri.ks@gmail.comPurpose: The number of emergency department (ED) visits and prolonged ED length of stay (LOS) are increasing worldwide. Prolonged ED LOS may be associated with a higher risk of in-hospital mortality. Here, we analysed the association between of ED LOS and the risk of in-hospital mortality in a hospital in Jakarta, Indonesia.Patients and methods: This was a single-centre retrospective cohort study performed in a referral academic hospital in Jakarta, Indonesia. Data on ED visits in 2019 were obtained from the electronic medical records. ED patient was used as the unit of the analysis. The dependent variable was all-cause in-hospital mortality during one’s visit. The main independent variable was ED LOS with respect to approval (< 8 h) and prolonged (≥ 8 h). Potential confounders were sex, age, triage categories, trauma-related case, malignancy-related case, labour-related case, and referral patients from other healthcare facilities. Multivariate logistic regression analysis was performed to evaluate the association of ED LOS and in-hospital mortality after adjusting for other confounders.Results: There were 18,553 participants included in the analysis. The in-hospital mortality was 13.5% among all participants, and 63.5% participants had an ED LOS ≥ 8 h. Multivariate analysis showed that a prolonged ED LOS was associated with an increased risk of in-hospital mortality (adjusted relative risk, 2.69; 95% confidence interval, 2.40– 3.03; P< 0.001).Conclusion: Prolonged ED LOS was associated with risk an increased of in-hospital mortality after adjusting for several confounders. In future, hospital service plans should aim to reduce ED LOS and increase patient flow from the ED to in-patient wards.Plain Language Summary: Prolonged emergency department length of stay (ED LOS) was associated with risk of in-hospital mortality in an Indonesia referral hospital; this is the first such reported association.Therefore, reduced ED LOS and increased patient flow to the inpatient ward should be a target for quality improvement in hospital service plans.Keywords: emergency department, mortality, length of stay, overcrowding, patient flow, triage

Abstract Urgent care clinics and emergency departments around the world periodically suffer from extended wait times beyond patient expectations due to surges in patient flows. The delays arising from inadequate staffing levels during these periods have been linked with adverse clinical outcomes. Previous research into forecasting patient flows has mostly used statistical techniques. These studies have also predominately focussed on short‐term forecasts, which have limited practicality for the resourcing of medical personnel. This study joins an emerging body of work which seeks to explore the potential of machine learning algorithms to generate accurate forecasts of patient presentations. Our research uses datasets covering 10 years from two large urgent care clinics to develop long‐term patient flow forecasts up to one quarter ahead using a range of state‐of‐the‐art algorithms. A distinctive feature of this study is the use of eXplainable Artificial Intelligence (XAI) tools like Shapely and LIME that enable an in‐depth analysis of the behaviour of the models, which would otherwise be uninterpretable. These analysis tools enabled us to explore the ability of the models to adapt to the volatility in patient demand during the COVID‐19 pandemic lockdowns and to identify the most impactful variables, resulting in valuable insights into their performance. The results showed that a novel combination of advanced univariate models like Prophet as well as gradient boosting, into an ensemble, delivered the most accurate and consistent solutions on average. This approach generated improvements in the range of 16%–30% over the existing in‐house methods for estimating the daily patient flows 90 days ahead.

This article explores the implementation of Lean management principles to optimize operations in healthcare facilities. Lean management, a philosophy made famous by the Toyota Motor Company, focuses on continuous improvement and the elimination of waste to maximize quality and safety for patients. The primary objective of this paper is to examine how Lean tools and techniques can be adapted to the unique environment of healthcare institutions to enhance their productivity and service quality. The article begins by outlining the core principles of Lean management, emphasizing the importance of value stream mapping, Kaizen, and the 5S methodology. Value stream mapping helps identify and visualize the flow of materials and information required to bring a product or service to a consumer, which in healthcare translates to patient care processes. Kaizen, a practice of continuous improvement, encourages small, incremental changes that collectively lead to significant enhancements in efficiency and quality. The 5S methodology—Sort, Set in order, Shine, Standardize, and Sustain—ensures a clean, organized, and efficient work environment. The paper then delves into specific Lean practices that can be applied within healthcare settings, such as reducing patient wait times, improving the flow of patients and information, and minimizing unnecessary movements and processes. By focusing on these areas, healthcare facilities can reduce bottlenecks, streamline operations, and enhance patient care delivery. For instance, implementing Lean techniques in patient scheduling can lead to more efficient use of clinical resources and reduce the time patients spend waiting for services. Furthermore, the paper provides a critical review of existing literature and studies on the application of Lean management in healthcare, highlighting successful implementations and the challenges faced during the process. It discusses real-world examples where Lean management has significantly improved operational efficiency, patient satisfaction, and overall healthcare outcomes. For example, a hospital that adopted Lean principles reported reduced patient wait times, lower operational costs, and improved staff morale. The article also addresses the potential obstacles and resistance to change that healthcare facilities might encounter when adopting Lean principles. It offers strategic recommendations for overcoming these barriers, including leadership commitment, staff training, and fostering a culture of continuous improvement. Leadership commitment is crucial as it sets the tone for organizational change and ensures that the necessary resources are allocated for Lean initiatives. Staff training is essential to equip employees with the skills and knowledge required to implement Lean practices effectively. Fostering a culture of continuous improvement involves engaging staff at all levels, encouraging open communication, and recognizing and rewarding contributions to Lean projects. In conclusion, the paper argues that Lean management principles, when effectively implemented, can lead to substantial improvements in the operational performance of healthcare facilities. It calls for further research and collaboration between healthcare professionals and Lean management experts to tailor these practices to the specific needs of the healthcare sector. The successful integration of Lean management into healthcare operations not only enhances efficiency and reduces waste but also improves patient care quality and safety. By adopting Lean principles, healthcare facilities can create a more efficient, patient-centered environment that supports high-quality care delivery. This article highlights the importance of a systematic approach to implementing Lean management, considering the unique challenges and opportunities within the healthcare sector. It underscores the need for ongoing evaluation and adaptation of Lean practices to ensure sustained improvements and long-term success.

Aim: A centralised Coordination Hub was implemented at a large tertiary health service in Queensland, Australia to address problems associated with a fragmented, reactive and manual approach to patient flow. Approach: The Hub was developed through challenging traditional ways of working, breaking down divisional silos, and developing technological enablers to manage patient flow as a whole-system issue. The Hub is a centralised space within the health service, where staff involved in patient flow are co-located and provided with real-time visibility of end-to-end data. Context: This case study describes the implementation and early operation of the Hub, outlining the critical design features and some of the early challenges and how they are being addressed. Main findings: This approach was designed to manage patient flow as a whole-system issue – co-locating staff, providing them with visibility of real time data, and accountability for decision-making to address flow blockages. Conclusions: Greater visibility of data and co-location of staff is not sufficient to manage long-standing patient flow challenges. This must be accompanied by appropriate accountability and authority to ensure that those who see and understand emergent flow issues are equipped with the authority to act and respond.

Examining medical supply–demand imbalances, as revealed through patients' cross-boundary treatment behaviors, is vital for reducing a metropolitan area's medical supply–demand gap and furthering sustainable development goals. This study, leveraging medical supply–demand and commuting data, scrutinizes medical imbalances in the Wuhan metropolitan area core. It includes a 'People-centered' theory for elucidating patients' treatment behaviors, proposes a method for constructing a regional medical supply–demand network, and explores the problem of supply–demand imbalance. The key findings include: (1) Wuhan's central area, despite its abundance of quality medical resources, fails to adequately cover the entire metropolitan area, indicating a need for broader resource distribution. (2) The Ezhou–Huangshi–Huanggang junction shows a stark contrast to Wuhan with its limited medical services and extensive hinterland connections. Future initiatives should aim to integrate resources dispersed from Wuhan, reducing regional disparities. (3) The city's periphery, influenced by resource distribution models and geographic distance, exhibits significant variance from central urban areas in medical supply–demand connectivity, particularly around Wuhan's eastern administrative boundaries. Future urban planning is needed to reinforce this area's role as a vital medical services conduit. (4) The distinguishing differences among the nine medical service communities in terms of resource recognition, service sharing, and patient mobility provide policy guidance for the allocation of medical resources. [ABSTRACT FROM AUTHOR]

Hospital services need to develop management based on the phenomena that make up their environment and project themselves to the needs of their patients. In this sense, managing patient flows allows for optimizing hospital resources and increasing patient safety during the patient's journey. The objective of this article is to improve the management of patient flows in hospital institutions through the application of discrete simulation. The proposed methodology integrates the processes of planning, execution, verification, and action. Among the tools used are the process descriptions, Diagnosis Related Groups definition, and discrete simulation. Additionally, tools from manufacturing systems are adapted to hospital management in the solutions proposal. Among the main results, patient flow management is improved in the Urology service of the Faustino Pérez Hernández Clinical and Surgical Teaching Hospital in Matanzas province, Cuba. The process is described, and a simulation model is built to identify insufficiencies and check the feasibility of improvements. Discrete simulation is an operations management tool that facilitates managing and improving patient flows in hospital institutions. [ABSTRACT FROM AUTHOR]

COVID-19 led to unprecedented inpatient capacity challenges, particularly in ICUs, which spurred development of statewide or regional placement centers for coordinating transfer (load-balancing) of adult patients needing intensive care to hospitals with remaining capacity. Do Medical Operations Coordination Centers (MOCC) augment patient placement during times of severe capacity challenges? The Minnesota MOCC was established with a focus on transfer of adult ICU and medical-surgical patients; trauma, cardiac, stroke, burn, and extracorporeal membrane oxygenation cases were excluded. The center operated within one health care system's bed management center, using a dedicated 24/7 telephone number. Major health care systems statewide and two tertiary centers in a neighboring state participated, sharing information on system status, challenges, and strategies. Patient volumes and transfer data were tracked; client satisfaction was evaluated through an anonymous survey. From August 1, 2020, through March 31, 2022, a total of 5,307 requests were made, 2,008 beds identified, 1,316 requests canceled, and 1,981 requests were unable to be fulfilled. A total of 1,715 patients had COVID-19 (32.3%), and 2,473 were negative or low risk for COVID-19 (46.6%). COVID-19 status was unknown in 1,119 (21.1%). Overall, 760 were patients on ventilators (49.1% COVID-19 positive). The Minnesota Critical Care Coordination Center placed most patients during the fall 2020 surge with the Minnesota Governor's stay-at-home order during the peak. However, during the fall 2021 surge, only 30% of ICU patients and 39% of medical-surgical patients were placed. Indicators characterizing severe surge include the number of Critical Care Coordination Center requests, decreasing placements, longer placement times, and time series analysis showing significant request-acceptance differences. Implementation of a large-scale Minnesota MOCC program was effective at placing patients during the first COVID-19 pandemic fall 2020 surge and was well regarded by hospitals and health systems. However, under worsening duress of limited resources during the fall 2021 surge, placement of ICU and medical-surgical patients was greatly decreased. [ABSTRACT FROM AUTHOR]

Copyright of Económicas CUC is the property of Corporacion Universidad de la Costa, CUC and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Patient flow simulation and analysis is one of the oldest IT-based methods used to optimize patient care processes and hospital management. During the pandemic, interest in this domain suddenly increased due to the various constraints and recommendations to reduce the likelihood of further infections in the hospital. Suddenly, metrics such as the number of patients waiting in the same area, the maximum time a patient could stay in a single room, and the minimum distance between patients became important issues to monitor and optimize. Using data and modelling concepts from various hospitals, our team developed a simulation tool that used bpmn models to define an emergency department. We then modified a single day's usual patient flow with various real-world inspired edge cases to evaluate how the simulated flow would change and which stations would become bottlenecks, where the quality of patient care would deteriorate and rooms would become overcrowded. To execute the models, we developed our own tool based on the open-source Camunda modeling tool and the Business Process Model Notation (BPMN) file format. To execute the generated models, we use our own Python-based execution environment based on the SpiffWorkow library, which permits extensive logging and extensive customization of the attributes analysed. In addition, the modelling toolkit of Camunda was narrowed down and compiled so that it could be easily used by researchers who are not programmers. In the paper, we present both the modeling process and the scenario design process, as well as the results obtained through the runs, including the maximum waiting times during the model runs and the maximum number of patients waiting at once, which allowed us to validate the effectiveness of the framework. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Health Management Review is the property of International Journal of Health Management Review and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

AIM: A centralised Coordination Hub was implemented at a large tertiary health service in Queensland, Australia to address problems associated with a fragmented, reactive and manual approach to patient flow. APPROACH: The Hub was developed through challenging traditional ways of working, breaking down divisional silos, and developing technological enablers to manage patient flow as a whole-system issue. The Hub is a centralised space within the health service, where staff involved in patient flow are co-located and provided with real-time visibility of end-to-end data. CONTEXT: This case study describes the implementation and early operation of the Hub, outlining the critical design features and some of the early challenges and how they are being addressed. MAIN FINDINGS: This approach was designed to manage patient flow as a whole-system issue - co-locating staff, providing them with visibility of real time data, and accountability for decision-making to address flow blockages. CONCLUSIONS: Greater visibility of data and co-location of staff is not sufficient to manage long-standing patient flow challenges. This must be accompanied by appropriate accountability and authority to ensure that those who see and understand emergent flow issues are equipped with the authority to act and respond. [ABSTRACT FROM AUTHOR]

Despite the many examples where simulation has successfully demonstrated its capability in modelling patient flow, there is little evidence of enduring widespread use. Bespoke academic projects provide little scope for repeatable practical application and efforts to develop generic reusable solutions have neither clearly identified the end users nor fully appreciated their multifaceted requirements. Influenced by a review of existing findings and recommendations in addition to a customised survey of prospective end users, a set of practical design principles were elicited in guiding development of a new open-source and versatile tool. Capturing variability in arrivals and length of stay as well as the stochastic nature of dynamic delays in patient discharge and transfer, the PathSimR tool can be used to model various user-defined configurations of outpatient and inpatient pathways. In addition to reporting on early use and engagement initiatives to promote the tool, this study also offers a blueprint for how simulation models can be developed and deployed within the healthcare setting. [ABSTRACT FROM AUTHOR]

Emergency Medicine Departments (EMDs) are one of the busiest hospital departments in the world, as they are typically the first point of contact for health emergencies and are designed and resourced to manage them. However, due to their potential overflow, EMDs contribute to overcrowding. Overcrowding in the Emergency Department (ED) of hospitals can harm hospitals financially and have negative impacts on patient care, such as lengthening waiting times, diverting ambulances, increasing length of stays, raising medical errors, and elevating patient mortality rates. The COVID-19 pandemic has exacerbated the critical situation for EMDs, making it imperative to reduce overcrowding and improve EMD efficiency for patient welfare and safety during this pandemic. Controlling overcrowding should be carried out by the authorities responsible for regulations. This review discusses the effects of EMD crowding on patients’ health status and explores potential solutions through strategic management, including executive leadership involvement, hospital-wide coordination strategies, data-driven management, and performance accountability.

Abstract Background Delayed access to outpatient care may negatively impact on health outcomes. We aimed to evaluate implementation of the Specific Timely Appointments for Triage (STAT) model of access in an epilepsy clinic to reduce a long waitlist and waiting time. Methods This study is an intervention study using pre-post comparison and an interrupted time series analysis to measure the effect of implementation of the STAT model to an epilepsy clinic. Data were collected over 28 months to observe the number of patients on the waitlist and the waiting time over three time periods: 12 months prior to implementation of STAT, ten months during implementation and six months post-intervention. STAT combines one-off backlog reduction with responsive scheduling that protects time for new appointments based on historical data. The primary outcomes were the number of patients on the waitlist and the waiting time across the three time periods. Secondary outcomes evaluated pre- and post-intervention changes in number of appointments offered weekly, non-arrival and discharge rates. Results A total of 938 patients were offered a first appointment over the study period. The long waitlist was almost eliminated, reducing from 616 during the pre-intervention period to 11 post-intervention (p = 0.002), but the hypothesis that waiting time would decrease was not supported. The interrupted time series analysis indicated a temporary increase in waiting time during the implementation period but no significant change in slope or level in the post- compared to the pre-intervention period. Direct comparison of the cohort of patients seen in the pre- and post-intervention periods suggested an increase in median waiting time following the intervention (34 [IQR 25–86] to 46 [IQR 36–61] days (p = 0.001)), but the interquartile range reduced indicating less variability in days waited and more timely access for the longest waiters. Conclusions The STAT model was implemented in a specialist epilepsy outpatient clinic and reduced a large waitlist. Reductions in the waitlist were achieved with little or no increase in waiting time. The STAT model provides a framework for an alternative way to operate outpatient clinics that can help to ensure that all people referred are offered an appointment in a timely manner.

ÖZ: Sağlık sistemleri, birbiriyle karmaşık yollarla etkileşime giren çok sayıda paydaşı içeren insan temelli sistemlerdir. Sağlık sistemlerinin stokastik doğası ve girdilerinin, etkinliklerinin ve çıktılarının karmaşık dinamikleri ve etkileşimleri nedeniyle sağlık hizmeti sağlayıcıları, bu karmaşıklığı anlamalarını ve bu şekilde sistem performanslarını geliştirmelerini sağlayan araçlara ihtiyaç duyar. Yoğun bakım üniteleri (YBÜ), kapasite yetersizliği nedeniyle hastaları tedavi edememekte ve bazı durumlarda hastalar, başka hastanelere sevk edilmekte ve hasta bekleme süreleri uzamaktadır. YBÜ gibi kıt bir kaynağın verimli kullanımı ve yönetimi, bir hastanenin sorunsuz çalışması için kritik öneme sahiptir. Kapasite planlaması, yani gelecekteki talep ve kapasite ile ilgili mevcut bilgilere dayanarak optimal yatak konfigürasyonunun belirlenmesi hem kapasite hem de talepteki yüksek belirsizlikler nedeniyle çok zordur. Bu problemin çözümü için çalışmada, yoğun bakım yatak kapasitesi planlamasının karar verme sürecini kolaylaştırmak için simülasyon modeli önerilmektedir. Bu çalışma, Türkiye’de faaliyette bulunan 3. basamak bir üniversite eğitim araştırma hastanesindeki YBÜ’nün kapasite planlamasını geliştirmeye odaklanmaktadır. Çalışmanın amacı, YBÜ’nün kaynaklarını taleple eşleştirerek optimum yatak ihtiyacını belirlemek olarak tanımlanabilir. Çalışmanın sonucunda oluşturulan simülasyon modelleri, hastaların bekleme süreleri ve yatak sayılarına göre değerlendirilerek yoğun bakım kapasitesi hakkında öngörülerde bulunulmuştur. YBÜ’lerin hayati önemi, yönetiminde belirsizlik durumları gözönüne alındığında, farklı bölge ve hastane koşullarında kapasite kararlarının alınmasında bir araç olarak simülasyon yönteminin kullanılması, karar alıcılara kaynak tahsis stratejilerini değerlendirmelerinde yardımcı olabileceği öngörülmektedir. ABSTRACT: Health systems are human based systems comprising a high number of stakeholders who interact with each other in complex ways. Due to the stochastic nature of health systems and the complex dynamics and interactions of their inputs, processes and outputs; providers of health services require tools tat allow them to comprehend the said complexity and improve system performance. Intensive care units (ICUs) may fall short in treating patients due to insufficient capacity and patients may be transferred to other hospitals under certain circumstances, and waiting times can get longer. Efficient use and management of a scarce resource such as the ICU is of critical importance for trouble-free operation of a hospital. Capacity planning, in other words, determination of optical bed configuration based on current knowledge of future demand and capacity, is very difficult due to high uncertainty in both bed capacity and demand. The paper at hand proposes a simulation model to allow an easier decision-making process in the planning of bed capacity in ICU. The study focuses on improving the capacity planning of a level III university hospital in Turkey that specializes in education and research. The objective of the study is to determine optimal bed requirement by matching the resources of the ICU with demand. We provide forecasts of ICU capacity by evaluating the simulation models based on patient waiting times and bed quantity. Considered in the context of the vital importance of intensive care units and the uncertainties in their management, it is thought that the use of simulation modeling in the making of capacity decisions can prove useful for decision makers in assessing their resource allocation strategies under different regional and hospital conditions.

Background: The COVID-19 pandemic has exposed gaps and areas of need in health care systems. General practitioners (GPs) play a crucial role in the response to COVID-19 and other respiratory infectious diseases (e.g., influenza). Knowing the current flow of these patients and the real needs of GPs is necessary to implement new therapeutic and diagnostic strategies. We sought to learn about the flow of COVID-19 and flu patients in Spanish primary health centers and understand the training needs in both the diagnosis and treatment of these diseases. Methods: A total of 451 regionally representative GPs completed an online survey between January and February 2022. Results: Most of the GPs had available infection containment measures (79%) and access to point-of-care (POC) rapid diagnostic testing (81%) in their centers. The availability of on-the-day diagnostic tests for COVID-19 was higher than that for influenza (80% vs. 20%). Most GPs referred 1 of 10 COVID-19 or flu patients with moderate to severe disease to the emergency department (80% and 90%, respectively). Training/knowledge was considered good regarding diagnostic tests and vaccines (85%) but null or low regarding antivirals (60%) and monoclonal antibodies (80%). Conclusions: This survey identified the conditions of Spanish GPs in terms of the diagnosis and treatment of COVID-19 and flu patients. Respondents' comments suggested that quite radical system-level adjustments are needed to allow GPs to capitalize on the potential benefits of POC tests for diagnosis, reduction of referrals, and monitoring of these diseases. [ABSTRACT FROM AUTHOR]

The objective of this study was to determine the factors that increase the odds of long-stay delayed discharge in alternate level of care (ALC) patients using data collected from the Ontario Wait Time Information System (WTIS) database. Retrospective cohort study utilizing data from Niagara Health's WTIS database. WTIS includes individuals admitted to any of the Niagara Health sites that have been designated as ALC. Sample consisted of 16,429 ALC patients who received care in Niagara Health hospitals from September 2014 to September 2019 and were recorded in the WTIS database. ALC designation of 30 or more days was used as the threshold for a long-stay delayed discharge. This study used binary logistic regression modeling to analyze sex, age, admission source, and discharge destination as well needs/barriers requirements to assess the likelihood of a long-stay delayed discharge among acute care (AC) and post-acute care (PAC) patients given the presence of each variable. Sample sizes calculations and receiver operating characteristic curves were used to verify the validity of the regression model. Overall, 10.2% of the sample were considered long-stay ALC patients. Both AC and PAC long-stay ALC patients were more likely to be male [OR = 1.23, (1.06–1.43); OR = 1.28, (1.03–1.60)] and have a discharge destination of a long-term care bed [OR = 28.68, (22.83–36.04); OR = 6.22, (4.75–8.15)]. AC patients had bariatric [OR = 7.16, (3.45–14.83)], behavioral [OR = 1.89, (1.22–2.91)], infection (isolation) [OR = 2.31, (1.63–3.28)], and feeding [OR = 6.38, (1.82–22.30)] barriers hindering discharge. PAC patients had no significant barriers hindering patient discharge. Shifting the focus from ALC patient designation to short- vs long-stay ALC patients allowed this study to focus on the subset of patients that are disproportionately affecting delayed discharges. Understanding the importance of specialized patient requirements in addition to clinical factors can help hospitals become more prepared in preventing delayed discharges. [ABSTRACT FROM AUTHOR]

Rationale: Wait lists are common in the provision of publicly funded services in outpatient and community settings. Aims and Objectives: We aimed to explore the experiences of consumers on wait lists across a broad range of services and to understand the impact of delays in access to services on people's lives. Methods: Consumers with experience of being on a wait list for an outpatient or community‐based health service participated in one of three focus groups. Data were transcribed and analysed inductively using a thematic approach. Results: Waiting for healthcare has detrimental impacts on health and well‐being. Consumers on wait lists want their health needs addressed, but they also want the ability to plan, clear communication and to feel like someone cares. Instead, they feel forgotten by impersonal and inflexible systems with very little communication, with emergency departments and general practitioners often left to fill in the gaps. Conclusions: More consumer‐centred approaches are needed for access systems for outpatient and community services, featuring honesty about what services can realistically be provided, early access to initial assessment and information and clear lines of communication. [ABSTRACT FROM AUTHOR]