Use of Hospital Capacity Command Centers to Improve Patient Flow and Safety: A Scoping Review

Overnight stay in Spanish emergency departments and mortality in older patients

To assess whether older adults who spend a night in emergency departments (ED) awaiting admission are at increased risk of mortality. This was a retrospective review of a multipurpose cohort that recruited all patients ≥ 75 years who visited ED and were admitted to hospital on April 1 to 7, 2019, at 52 EDs across Spain. Study groups were: patients staying in ED from midnight until 8:00 a.m. (ED group) and patients admitted to a ward before midnight (ward group). The primary endpoint was in-hospital mortality, truncated at 30 days, and secondary outcomes assessed length of stay for the index episode. The sample comprised 3,243 patients (median [IQR] age, 85 [81-90] years; 53% women), with 1,096 (34%) in the ED group and 2,147 (66%) in the ward group. In-hospital mortality for patients spending the night in the ED the ED group was 10.7% and 9.5% for patients transferred to a ward bed before midnight the ward group (adjusted OR: 1.12, 95%CI: 0.80-1.58). Sensitivity analyses rendered similar results (ORs ranged 1.06-1.13). Interaction was only detected for academic/non-academic hospitals (p < 0.001), with increased mortality risk for the latter (1.01, 0.33-3.09 vs 2.86, 1.30-6.28). There were no differences in prolonged hospitalization (> 7 days), with adjusted OR of 1.16 (0.94-1.43) and 1.15 (0.94-1.42) depending on whether time spent in the ED was or was not taken into consideration. No increased risk of in-hospital mortality or prolonged hospitalization was found in older patients waiting overnight in the ED for admission. Nonetheless, all estimations suggest a potential harmful effect of staying overnight, especially if a proper bedroom and hospitalist ward bed and hospitalized care are not provided.

Application of a Human Factors Systems Approach to Healthcare Control Centres for Managing Patient Flow: A Scoping Review

Over the past decade, healthcare systems have started to establish control centres to manage patient flow, with a view to removing delays and increasing the quality of care. Such centres-here dubbed Healthcare Capacity Command/Coordination Centres (HCCCs)-are a challenge to design and operate. Broad-ranging surveys of HCCCs have been lacking, and design for their human users is only starting to be addressed. In this review we identified 73 papers describing different kinds of HCCCs, classifying them according to whether they describe virtual or physical control centres, the kinds of situations they handle, and the different levels of Rasmussen's [1] risk management framework that they integrate. Most of the papers (71%) describe physical HCCCs established as control centres, whereas 29% of the papers describe virtual HCCCs staffed by stakeholders in separate locations. Principal functions of the HCCCs described are categorised as business as usual (BAU) (48%), surge management (15%), emergency response (18%), and mass casualty management (19%). The organisation layers that the HCCCs incorporate are classified according to the risk management framework; HCCCs managing BAU involve lower levels of the framework, whereas HCCCs handling the more emergent functions involve all levels. Major challenges confronting HCCCs include the dissemination of information about healthcare system status, and the management of perspectives and goals from different parts of the healthcare system. HCCCs that take the form of physical control centres are just starting to be analysed using human factors principles that will make staff more effective and productive at managing patient flow.

Boarding in the emergency department: challenges and mitigation strategies

PURPOSE OF REVIEW

Herein, we conducted a review of the literature to better understand the issue of prolonged emergency department (ED) boarding by providing an overview of the current evidence on the available causes, consequences, and mitigation strategies.

RECENT FINDINGS

Severely ill patients awaiting transfer to intensive care units (ICU) imposes additional burdens on the emergency care team from both a clinical and management perspective. The reasons for prolonged ED boarding are multifactorial. ED boarding compromises patients' safety and outcomes, and is associated with increased team burnout and dissatisfaction. Mitigation strategies include the optimization of patients' flow, the establishment of resuscitative care units, deployment of mobile critical care teams, and improvements in training. Staffing adjustments, changes in hospital operations, and quality improvement initiatives are required to improve this situation, while active bed management and implementation of capacity command centers may also help.

SUMMARY

Considering the characteristics of healthcare systems, such as funding mechanisms, organizational structures, delivery models, access and quality of care, the challenge of ED boarding of critically ill patients requires a nuanced and adaptable approach. Solutions are complex but must involve the entirety of the hospital system, emergency department, staff adjustment, and education.

Patient Outcomes Compared Between Admissions Coordinated by the Transfer Center and Emergency Department at a U.S. Tertiary Care Hospital

BACKGROUND

Patient admissions at a U.S. tertiary care hospital occur via the emergency department (ED), or transfer center. We aim to compare the clinical outcomes of patients admitted from the ED to admissions coordinated by the transfer center.

METHODS

Admissions to Mayo Clinic Hospital, Rochester, MN, between July 2019 to June 2021 were identified in this retrospective study and categorized into two cohorts-transfer center and ED. The two cohorts were then matched for age, sex, admitting service, and Charlson Comorbidity Index. Univariate and multivariate analyses were performed to compare hospital length of stay (LOS), mortality, 30-day mortality, and 30-day readmissions between the two cohorts.

RESULTS

73,685 admissions were identified, of which 24,262 (33%) were transfer center admissions. In the matched cohorts (n = 19,093, each), in-hospital mortality (2.4% versus 1.9%), 30-day mortality (5.4% versus 3.9%), 30-day readmission (12.7% versus 7.2%), and LOS (6.4 days versus 5.1 days) were significantly higher (P < 0.001) among the admissions coordinated by transfer center. A higher palliative care consultation rate (9.4% versus 6.2%, P < 0.001), and a lower proportion of home discharges home (76.2% versus 82.5%, P < 0.001) among transfer center admissions was observed. Similar findings were noted in multivariate analysis, even when adjusting for LOS.

CONCLUSIONS

Transfer center admissions had higher in-hospital mortality, LOS, 30-day mortality, and 30-day readmission compared to ED admissions. This study also highlights new considerations for palliative care consultation before transfer acceptance, especially to avoid futile transfers. Additional studies analyzing factors behind the outcomes of transfer center admissions are required.

Impact of an ICU bed capacity optimisation method on the average length of stay and average cost of hospitalisation following implementation of China's open policy with respect to COVID-19: a difference-in-differences analysis based on information management system data from a tertiary hospital in southwest China

OBJECTIVES

Following the implementation of China's open policy with respect to COVID-19 on 7 December 2022, the influx of patients with infectious diseases has surged rapidly, necessitating hospitals to adopt temporary requisition and modification of ward beds to optimise hospital bed capacity and alleviate the burden of overcrowded patients. This study aims to investigate the effect of an intensive care unit (ICU) bed capacity optimisation method on the average length of stay (ALS) and average cost of hospitalisation (ACH) after the open policy of COVID-19 in China.

DESIGN AND SETTING

A difference-in-differences (DID) approach is employed to analyse and compare the ALS and ACH of patients in four modified ICUs and eight non-modified ICUs within a tertiary hospital located in southwest China. The analysis spans 2 months before and after the open policy, specifically from 5 October 2022 to 6 December 2022, and 7 December 2022 to 6 February 2023.

PARTICIPANTS

We used the daily data extracted from the hospital's information management system for a total of 5944 patients admitted by the outpatient and emergency access during the 2-month periods before and after the release of the open policy in China.

RESULTS

The findings indicate that the ICU bed optimisation method implemented by the tertiary hospital led to a significant reduction in ALS (HR -0.6764, 95% CI -1.0328 to -0.3201, p=0.000) and ACH (HR -0.2336, 95% CI -0.4741 to -0.0068, p=0.057) among ICU patients after implementation of the open policy. These results were robust across various sensitivity analyses. However, the effect of the optimisation method exhibits heterogeneity among patients admitted through the outpatient and emergency channels.

CONCLUSIONS

This study corroborates a significant positive impact of ICU bed optimisation in mitigating the shortage of medical resources following an epidemic outbreak. The findings hold theoretical and practical implications for identifying effective emergency coordination strategies in managing hospital bed resources during sudden public health emergency events. These insights contribute to the advancement of resource management practices and the promotion of experiences in dealing with public health emergencies.

Patient flow in emergency departments: a comprehensive umbrella review of solutions and challenges across the health system

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.

Increasing Hospital at Home Enrollment Through Decentralization With Agile Science

LEVEL OF EVIDENCE

4, Descriptive quality improvement project.

Can we improve healthcare with centralized management systems, supported by information technology, predictive analytics, and real-time data?: A review

This narrative review discusses the effects of implementing command centers, centralized management systems, supported by information technology, predictive analytics, and real-time data, as well as small-scale centralized operating systems, on patient outcomes, operation, care delivery, and resource utilization. Implementations of command centers and small-scale centralized operating systems have led to improvement in 3 areas: integration of both multiple services into the day-to-day operation, communication and coordination, and employment of prediction and early warning system. Additional studies are required to understand the full impact of command centers on the healthcare system.

The working experience of medical staff in the hospital-wide bed-sharing mode: A qualitative study

AIM

The purpose of this study was to provide a comprehensive understanding of the attitudes and experiences of the medical staff regarding the hospital bed-sharing model.

DESIGN

The present research was a qualitative study.

METHODS

This qualitative study used in-depth individual interviews with 7 doctors, 10 clinical nurses and 3 head nurses, which were then transcribed and analysed thematically.

RESULTS

The study identified six overall themes. Issues were raised about the efficient utilization of hospital bed resources, greater challenges for nursing work, adjustment of doctors' work modes, barriers to communication between doctors, nurses, and patients, potential medical risks, and differentiation of patients' medical experience.

IMPLICATIONS FOR NURSING MANAGEMENT

Hospital administrators and nurse managers should work together to solve the challenges that medical staff face, including strengthening nursing training, improving medical-nursing collaboration models, standardizing and effective communication strategies, and improving patient experiences.

Hospital Capacity Command Centers: A Benchmarking Survey on an Emerging Mechanism to Manage Patient Flow

BACKGROUND

Delayed hospital and emergency department (ED) patient throughput, which occurs when demand for inpatient care exceeds hospital capacity, is a critical threat to safety, quality, and hospital financial performance. In response, many hospitals are deploying capacity command centers (CCCs), which co-locate key work groups and aggregate real-time data to proactively manage patient flow. Only a narrow body of peer-reviewed articles have characterized CCCs to date. To equip health system leaders with initial insights into this emerging intervention, the authors sought to survey US health systems to benchmark CCC motivations, design, and key performance indicators.

METHODS

An online survey on CCC design and performance was administered to members of a hospital capacity management consortium, which included a convenience sample of capacity leaders at US health systems (N = 38). Responses were solicited through a targeted e-mail campaign. Results were summarized using descriptive statistics.

RESULTS

The response rate was 81.6% (31/38). Twenty-five respondents were operating CCCs, varying in scope (hospital, region of a health system, or entire health system) and number of beds managed. The most frequent motivation for CCC implementation was reducing ED boarding (n = 24). The most common functions embedded in CCCs were bed management (n = 25) and interhospital transfers (n = 25). Eighteen CCCs (72.0%) tracked financial return on investment (ROI); all reported positive ROI.

CONCLUSION

This survey addresses a gap in the literature by providing initial aggregate data for health system leaders to consider, plan, and benchmark CCCs. The researchers identify motivations for, functions in, and key performance indicators used to assess CCCs. Future research priorities are also proposed.