High hospital occupancy is associated with increased risk for patients boarding in the emergency department

A New Approach for Understanding International Hospital Bed Numbers and Application to Local Area Bed Demand and Capacity Planning

Three models/methods are given to understand the extreme international variation in available and occupied hospital bed numbers. These models/methods all rely on readily available data. In the first, occupied beds (rather than available beds) are used to measure the expressed demand for hospital beds. The expressed occupied bed demand for three countries was in the order Australia > England > USA. Next, the age-standardized mortality rate (ASMR) has dual functions. Less developed countries/regions have low access to healthcare, which results in high ASMR, or a negative slope between ASMR versus available/occupied beds. In the more developed countries, high ASMR can also be used to measure the 'need' for healthcare (including occupied beds), a positive slope among various social (wealth/lifestyle) groups, which will include Indigenous peoples. In England, a 100-unit increase in ASMR (European Standard population) leads to a 15.3-30.7 (feasible range) unit increase in occupied beds per 1000 deaths. Higher ASMR shows why the Australian states of the Northern Territory and Tasmania have an intrinsic higher bed demand. The USA has a high relative ASMR (for a developed/wealthy country) because healthcare is not universal in the widest sense. Lastly, a method for benchmarking the whole hospital's average bed occupancy which enables them to run at optimum efficiency and safety. English hospitals operate at highly disruptive and unsafe levels of bed occupancy, manifesting as high 'turn-away'. Turn-away implies bed unavailability for the next arriving patient. In the case of occupied beds, the slope of the relationship between occupied beds per 1000 deaths and deaths per 1000 population shows a power law function. Scatter around the trend line arising from year-to-year fluctuations in occupied beds per 1000 deaths, ASMR, deaths per 1000 population, changes in the number of persons hidden in the elective, outpatient and diagnostic waiting lists, and local area variation in births affecting maternity, neonatal, and pediatric bed demand. Additional variation will arise from differences in the level of local funding for social care, especially elderly care. The problems associated with crafting effective bed planning are illustrated using the English NHS as an example.

Clinicians' Insights on Emergency Department Boarding: An Explanatory Mixed Methods Study Evaluating Patient Care and Clinician Well-Being

BACKGROUND

The aim of this study was to describe clinicians' insights into the quality and safety of patient care delivered to emergency department (ED) boarding patients, as well as clinician safety and satisfaction related to ED boarding.

METHODS

This was a single-site, mixed methods sequential explanatory study. Quantitative data were obtained from a cross-sectional survey sent to ED attending physicians, resident physicians, advanced practice providers, and nurses. Semistructured focus group interviews with a subsample of participants sought to add depth to the interpretation of survey data and identify areas of improvement in boarding care. Chi-square and Wilcoxon rank sum tests were used to evaluate for response differences between groups. Qualitative data were thematically coded and analyzed.

RESULTS

A total of 94 questionnaires were obtained for a response rate of 34.1%. Clinicians reported that boarding highly contributed to the perception of burnout. All groups reported high rates of perceived verbal and/or physical abuse from boarding patients (86.8% of nurses, 41.1% of providers, p = 0.0002). A total of 39 clinicians participated in focus groups regarding boarding care, and six themes were identified, including patient safety concerns, lack of knowledge/resources/training, and poor communication. Key themes identified as possible solutions to improve care included standardization of care, proactive planning, and culture change.

CONCLUSION

Clinicians identified many concerns regarding patient safety and the quality of care delivered to boarding patients and identified several areas for improvement. Clinicians also felt that boarding negatively affected their satisfaction and safety.

Perceived health-care quality in China: a comparison of second- and third-tier hospitals

OBJECTIVES

To evaluate disparity in service quality between second- and third-tier hospitals and explore factors that affect patients' perception of service quality in China.

DESIGN

Cross sectional study.

SETTING

Twelve hospitals in China.

PARTICIPANTS

5714 patients.

INTERVENTION

None.

MAIN OUTCOME MEASURE

Total score of the SERVQUAL scale and each of its five dimensions.

RESULTS

Patients from third-tier hospitals rated significantly higher scores overall and in all the five dimensions of the SERVQUAL scale. Those with lower education, urban residents and those who had higher degree of life satisfaction and attention paid to health perceived higher service quality. Inpatients perceived higher service quality compared with outpatients.

CONCLUSION

We found a significant gap in patient's perceived service quality between second- and third-tier hospitals in China. A variety of demographic and personality factors were found to significantly influence patient's perceived service quality.

Factors related to fear of movement after acute cardiac hospitalization

Background

Fear of movement (kinesiophobia) after an acute cardiac hospitalization (ACH) is associated with reduced physical activity (PA) and non-adherence to cardiac rehabilitation (CR).

Purpose

To investigate which factors are related to kinesiophobia after an ACH, and to investigate the support needs of patients in relation to PA and the uptake of CR.

Methods

Patients were included 2–3 weeks after hospital discharge for ACH. The level of kinesiophobia was assessed with the Tampa Scale for Kinesiophobia (TSK-NL Heart). A score of > 28 points is defined as ‘high levels of kinesiophobia’ (HighKin) and ≤ 28 as ‘low levels of kinesiophobia’ (LowKin). Patients were invited to participate in a semi-structured interview with the fear avoidance model (FAM) as theoretical framework. Interviews continued until data-saturation was reached. All interviews were analyzed with an inductive content analysis.

Results

Data-saturation was reached after 16 participants (median age 65) were included in this study after an ACH. HighKin were diagnosed in seven patients. HighKin were related to: (1) disrupted healthcare process, (2) negative beliefs and attitudes concerning PA. LowKin were related to: (1) understanding the necessity of PA, (2) experiencing social support. Patients formulated ‘tailored information and support from a health care provider’ as most important need after hospital discharge.

Conclusion

This study adds to the knowledge of factors related to kinesiophobia and its influence on PA and the uptake of CR. These findings should be further validated in future studies and can be used to develop early interventions to prevent or treat kinesiophobia and stimulate the uptake of CR.

Type of facility influences lengths of stay of children presenting to high volume emergency departments

BACKGROUND

Emergency department crowding may impact patient and provider outcomes. We describe emergency department crowding metrics based on presentations by children to different categories of high volume emergency departments in Alberta, Canada.

METHODS

This population-based retrospective study extracted all presentations made by children (age < 18 years) during April 2010 to March 2015 to 15 high volume emergency departments: five regional, eight urban, and two academic/teaching. Time to physician initial assessment, and length of stay for discharges and admissions were calculated based on the start of presentation and emergency department facility. Multiple metrics, including the medians for hourly, facility-specific time to physician initial assessment and length of stay were obtained.

RESULTS

About half (51.2%) of the 1,124,119 presentations were made to the two academic/teaching emergency departments. Males presented more than females (53.6% vs 46.4%) and the median age was 5 years. Pediatric presentations to the three categories of emergency departments had mostly similar characteristics; however, urban and academic/teaching emergency departments had more severe triage scores and academic/teaching emergency departments had higher admissions. Across all emergency departments, the medians of the metrics for time to physician initial assessment, length of stay for discharges and for admission were 1h11min, 2h21min, and 6h29min, respectively. Generally, regional hospitals had shorter times than urban and academic/teaching hospitals.

CONCLUSIONS

Pediatric presentations to high volume emergency departments in this province suggest similar delays to see providers; however, length of stay for discharges and admissions were shorter in regional emergency departments. Crowding is more common in urban and especially academic emergency departments and the impact of crowding on patient outcomes requires further study.

Association between long boarding time in the emergency department and hospital mortality: a single-center propensity score-based analysis

Once diagnostic work-up and first therapy are completed in patients visiting the emergency department (ED), boarding them within the ED until an in-hospital bed became available is a common practice in busy hospitals. Whether this practice may harm the patients remains a debate. We sought to determine whether an ED boarding time longer than 4 h places the patients at increased risk of in-hospital death. This retrospective, propensity score-matched analysis and propensity score-based inverse probability weighting analysis was conducted in an adult ED in a single, academic, 1136-bed hospital in France. All patients hospitalized via the adult ED from January 1, 2013 to March 31, 2018 were included. Hospital mortality (primary outcome) and hospital length of stay (LOS) were assessed in (1) a matched cohort (1:1 matching of ED visits with or without ED boarding time longer than 4 h but similar propensity score to experience an ED boarding time longer than 4 h); and (2) the whole study cohort. Sensitivity analysis to unmeasured confounding and analyses in pre-specified cohorts of patients were conducted. Among 68,632 included ED visits, 17,271 (25.2%) had an ED boarding time longer than 4 h. Conditional logistic regression performed on a 10,581 pair-matched cohort, and generalized estimating equations with adjustment on confounders and stabilized propensity score-based inverse probability weighting applied on the whole cohort showed a significantly increased risk of hospital death in patients experiencing an ED boarding time longer than 4 h: odds ratio (OR) of 1.13 (95% confidence interval [95% CI] 1.05-1.22), P = 0.001; and OR of 1.12 (95% CI 1.03-1.22), P = 0.007, respectively. Sensitivity analyses showed that these findings might be robust to unmeasured confounding. Hospital LOS was significantly longer in patients exposed to ED boarding time longer than 4 h: median difference 2 days (95% CI 1-2) (P < 0.001) in matched analysis and mean difference 1.15 days (95% CI 1.02-1.28) (P < 0.001) in multivariable unmatched analysis. In this single-center propensity score-based cohort analysis, patients experiencing an ED boarding time longer than 4 h before being transferred to an in-patient bed were at increased risk of hospital death.

'See and Treat' Clinic Service Evaluation at a Tertiary Care Hospital in Abu Dhabi

Objectives

We sought to evaluate the performance provided at a ‘See and Treat’ (ST) clinic at a tertiary hospital emergency department (ED) in Abu Dhabi, UAE, and to assess its impact on ED crowding.

Methods

We conducted a retrospective electronic medical chart review and database analyses. We included patients triaged as triage level 4 (T4) and triage level 5 (T5) as per the Emergency Severity Index treated at ED in the ST clinic and other ED areas, including the off-site Urgent Care Centre (UCC) between 1 June 2016 and 30 June 2017. We analyzed a group of process and outcome measures at our ST clinic and compared them to the same measures in other areas of our ED and the co-located UCC. The process measure analyzed was the door-to-doctor time. In addition, the outcome measures analyzed were the door-to-door time, unplanned return within 72 hours, and feedback from T4 and T5 triaged patients treated at the clinic.

Results

The number of patients enrolled in the study was 43 109. Of these, 11 329 (26.3%) patients were treated at the ST clinic, 6328 (14.7%) were treated at the UCC, and 25 452 (59.0%) were treated at the main ED. The door-to-doctor time was within 30 minutes for 89.0% of ST clinic patients, and 94.0% of patients experienced a door-to-door time of within two hours; 2.1% of these patients returned within 72 hours. Among these, 78.7% returned for an issue related to their first visit. However, none of the patients were admitted on their return visit. For patients presenting to UCC and other parts of our ED, we recorded a door-to-doctor time of within 30 minutes for 80.5% of patients and a door-to-door time of within two hours for 73.0% of patients. We found the difference in waiting times (i.e., door-to-doctor times between ST clinic patients and the rest of ED) to be statistically significant (p < 0.001, 95% confidence interval (CI): 0.56–0.63). However, on comparing door-to-door times, we found the difference between ST clinic patients and the rest of ED patients was not statistically significant.

Conclusions

Door-to-doctor times were shorter in ST clinics compared to other parts of our ED, but there was no statistically significant difference in door-to-door times when comparing ST clinics to the rest of the ED. ST clinic patients had a lower rate of unplanned return within 72 hours, of which, none required admission on the return attendance. We believe ST clinics have a positive impact on reducing ED crowding but acknowledge they are one of the many plausible solutions attributing to optimized patient flow in the ED.

Forecasting Patient Discharge Before Noon: A Comparison Between Holt's and Box-Jenkins' Models

BACKGROUND

The uncertainty and ambiguity of not knowing how many patients will be discharged impact patient throughput in hospitals, causing concerns for responding to demand for admissions. Understanding the potential number of patients to be discharged can support caregivers, ability to concentrate on the range of interactions that patients require to ensure early discharge. Accurate forecasting of patients expected to be discharged by noon is beneficial in accommodating patients who need services and in achieving sustainable patient satisfaction.

METHOD

Models to predict patient discharge before noon (DBN) were formulated using Holt's double exponential smoothing and Box-Jenkins' methods with the aim of achieving minimal errors in each model. The models are applied to 24 months of weekly patient discharge historic data in a medical observation unit and a short-stay clinical unit of a health care hospital system located on the East Coast of United States.

RESULTS

DBN prediction outcomes were more accurate when applying Box-Jenkins' method than Holt's method. Analysis revealed that the model of ARIMA(3,1,2) is most suitable for forecasting. Upon the outcomes of forecast error metrics, the study identifies the mean absolute percent error for the ARIMA model is 14%.

CONCLUSION

Box-Jenkins forecasting performance is superior in predicting DBN with the least forecast error. Predicted values are significant to decision-making interventions aimed at taking new patients, improving quality patient care, and meeting patient throughput performance goals.

Ambulance diversions following public hospital emergency department closures

OBJECTIVE

To examine whether hospitals are more likely to temporarily close their emergency departments (EDs) to ambulances (through ambulance diversions) if neighboring diverting hospitals are public vs private.

DATA SOURCES/STUDY SETTING

Ambulance diversion logs for California hospitals, discharge data, and hospital characteristics data from California's Office of Statewide Health Planning and Development and the American Hospital Association (2007).

STUDY DESIGN

We match public and private (nonprofit or for-profit) hospitals by distance and size. We use random-effects models examining diversion probability and timing of private hospitals following diversions by neighboring public vs matched private hospitals.

DATA COLLECTION/EXTRACTION METHODS

N/A.

PRINCIPAL FINDINGS

Hospitals are 3.6 percent more likely to declare diversions if neighboring diverting hospitals are public vs private (P < 0.001). Hospitals declaring diversions have lower ED occupancy (P < 0.001) after neighboring public (vs private) hospitals divert. Hospitals have 4.2 percent shorter diversions if neighboring diverting hospitals are public vs private (P < 0.001). When the neighboring hospital ends its diversion first, hospitals terminate diversions 4.2 percent sooner if the neighboring hospital is public vs private (P = 0.022).

CONCLUSIONS

Sample hospitals respond differently to diversions by neighboring public (vs private) hospitals, suggesting that these hospitals might be strategically declaring ambulance diversions to avoid treating low-paying patients served by public hospitals.

Emergency department crowding: A systematic review of causes, consequences and solutions

BACKGROUND

Emergency department crowding is a major global healthcare issue. There is much debate as to the causes of the phenomenon, leading to difficulties in developing successful, targeted solutions.

AIM

The aim of this systematic review was to critically analyse and summarise the findings of peer-reviewed research studies investigating the causes and consequences of, and solutions to, emergency department crowding.

METHOD

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. A structured search of four databases (Medline, CINAHL, EMBASE and Web of Science) was undertaken to identify peer-reviewed research publications aimed at investigating the causes or consequences of, or solutions to, emergency department crowding, published between January 2000 and June 2018. Two reviewers used validated critical appraisal tools to independently assess the quality of the studies. The study protocol was registered with the International prospective register of systematic reviews (PROSPERO 2017: CRD42017073439).

RESULTS

From 4,131 identified studies and 162 full text reviews, 102 studies met the inclusion criteria. The majority were retrospective cohort studies, with the greatest proportion (51%) trialling or modelling potential solutions to emergency department crowding. Fourteen studies examined causes and 40 investigated consequences. Two studies looked at both causes and consequences, and two investigated causes and solutions.

CONCLUSIONS

The negative consequences of ED crowding are well established, including poorer patient outcomes and the inability of staff to adhere to guideline-recommended treatment. This review identified a mismatch between causes and solutions. The majority of identified causes related to the number and type of people attending ED and timely discharge from ED, while reported solutions focused on efficient patient flow within the ED. Solutions aimed at the introduction of whole-of-system initiatives to meet timed patient disposition targets, as well as extended hours of primary care, demonstrated promising outcomes. While the review identified increased presentations by the elderly with complex and chronic conditions as an emerging and widespread driver of crowding, more research is required to isolate the precise local factors leading to ED crowding, with system-wide solutions tailored to address identified causes.

The impact of ED crowding on early interventions and mortality in patients with severe sepsis

OBJECTIVE

Critically ill patients require significant time and care coordination in the emergency department (ED). We hypothesized that ED crowding would delay time to intravenous fluids and antibiotics, decrease utilization of protocolized care, and increase mortality for patients with severe sepsis or septic shock.

METHODS

This was a retrospective cohort study of severe sepsis patients admitted to the hospital from the ED between January 2005 and February 2010. Associations between four validated measures of ED crowding (occupancy, waiting patients, admitted patients, and patient-hours) assigned at triage, and time of day, time to antibiotics and fluids, and mortality were tested by analyzing trends across crowding quartiles.

RESULTS

During the study period, 2913 severe sepsis patients were admitted to the hospital and 1127 (38.7%) qualified for protocolized care. In-hospital mortality was 14.3% overall and 26% for patients qualifying for protocolized care. Time to IV fluids was delayed as ED occupancy rate increased and as patient hours increased. Time to antibiotics increased as occupancy rates, patient hours, and the number of boarding inpatients increased. Implementation rates of protocolized care decreased from 71.3% to 50.5% (p<0.0001, OR 0.39) as the number of ED inpatient boarders increased; initiation of protocolized care was significantly higher as occupancy increased (OR 1.52). Mortality was unaffected by crowding parameters in all analyses.

CONCLUSIONS

With increased ED crowding, time to critical severe sepsis therapies significantly increased and protocolized care initiation decreased. As crowding increases, EDs must implement systems that optimize delivery of time-sensitive therapies to critically ill patients.

The Impact of Emergency Department Census on the Decision to Admit

OBJECTIVE

We evaluated the effect of emergency department (ED) census on disposition decisions made by ED physicians.

METHODS

We performed a retrospective analysis using 18 months of all adult patient encounters seen in the main ED at an academic tertiary care center. Patient census information was calculated at the time of physician assignment for each individual patient and included the number of patients in the waiting room (waiting room census) and number of patients being managed by the patient's attending (physician load census). A multiple logistic regression model was created to assess the association between these census variables and the disposition decision, controlling for potential confounders including Emergency Severity Index acuity, patient demographics, arrival hour, arrival mode, and chief complaint.

RESULTS

A total of 49,487 patient visits were included in this analysis, of whom 37% were admitted to the hospital. Both census measures were significantly associated with increased chance of admission; the odds ratio (OR) per patient increase for waiting room census was 1.011 (95% confidence interval [CI] = 1.001 to 1.020), and the OR for physician load census was 1.010 (95% CI = 1.002 to 1.019). To put this in practical terms, this translated to a modeled rise from 35.3% to 40.1% when shifting from an empty waiting room and zero patient load to a 12-patient wait and 16-patient load for a given physician.

CONCLUSION

Waiting room census and physician load census at time of physician assignment were positively associated with the likelihood that a patient would be admitted, controlling for potential confounders. Our data suggest that disposition decisions in the ED are influenced not only by objective measures of a patient's disease state, but also by workflow-related concerns.

Sustaining critical care: using evidence-based simulation to evaluate ICU management policies

Intensive Care Units (ICU) are costly yet critical hospital departments that should be available to care for patients needing highly specialized critical care. Shortage of ICU beds in many regions of the world and the constant fire-fighting to make these beds available through various ICU management policies motivated this study. The paper discusses the application of a generic system dynamics model of emergency patient flow in a typical hospital, populated with empirical evidence found in the medical and hospital administration literature, to explore the dynamics of intended and unintended consequences of such ICU management policies under a natural disaster crisis scenario. ICU management policies that can be implemented by a single hospital on short notice, namely premature transfer from ICU, boarding in ward, and general ward admission control, along with their possible combinations, are modeled and their impact on managerial and health outcome measures are investigated. The main insight out of the study is that the general ward admission control policy outperforms the rest of ICU management policies under such crisis scenarios with regards to reducing total mortality, which is counter intuitive for hospital administrators as this policy is not very effective at alleviating the symptoms of the problem, namely high ED and ICU occupancy rates that are closely monitored by hospital management particularly in times of crisis. A multivariate sensitivity analysis on parameters with diverse range of values in the literature found the superiority of the general ward admission control to hold true in every scenario.

Patterns and predictors of early mortality among emergency department patients in Addis Ababa, Ethiopia

Background

Ethiopian emergency department (ED) patients have a considerable burden of illness and injury for which all-cause mortality rates have not previously been published. This study sought to characterize the burden of and to identify predictors for early all-cause mortality among patients presenting to the Tikur Anbessa Specialized Hospital ED (TASH-ED) in Ethiopia.

Methods

Data was prospectively collected from the records of all patients who died within 72 h of ED presentation. Pearson’s Chi square and Fisher’s exact tests were used to investigate associations between two outcome variables: (a) time to death and (b) immediate cause of death in relation to specific demographic and clinical factors. Time from ED presentation to death was dichotomized as ‘very early’ mortality within ≤6 h and death >6–72 h and logistic regression was used to assess the adjusted impact of these demographic and clinical variables on the probability of dying within 6 h of ED presentation.

Results

Between October 2012 and May 2013, 9956 patients visited the ED and 220 patients died within 72 h of admission. After excluding patients dead on arrival (n = 34), the average age of death was 43.1 years and the overall mortality rate was 1.9 %. Head injury (21.5 %) and sepsis (18.8 %) were the most common causes of death. Relative to medical patients, trauma patients were more likely to be male (p < 0.01), less likely to have had prior recent ED visits (p < 0.01) and more likely to be triaged as higher acuity (p = 0.04). The sole statistically significant predictor of death within 6 h from our multivariable logistic regression model was symptom duration less than 4 h (4–48 h vs. <4 h: OR = 0.20, 95 % CI 0.07, 0.53, p < 0.01; >48 h vs. <4 h: OR = 0.27, 95 % CI 0.09, 0.81, p = 0.02).

Conclusions

The mortality burden of trauma and sepsis in the TASH-ED is substantial, and mortality patterns differ between these groups. As emergency medicine develops as a specialty in the Ethiopian health system, the potential impact of context-specific clinical care protocol development, trauma prevention advocacy and ED care re-organization initiatives to reduce mortality among these young, previously well patients warrants exploration.

A quality improvement project to decrease emergency department and medical intensive care unit transfer times

OBJECTIVE

To reduce transfer time of critically ill patients from the emergency department (ED) to the medical intensive care unit (MICU).

DESIGN

A prospective, observational study assessing preimplementation and postimplementation of quality improvement interventions in a tertiary academic medical center.

INTERVENTIONS

A team of frontline health care professional including ED, MICU, and supporting services using the clinical microsystems approach mapped out existing practice patterns, determined causes for delays, and used the Plan-Do-Study-Act to test changes. Measurements and Main Results The team identified multiple issues that contributed to delays. These included poor coordination between transport services, respiratory therapy, and nursing in transferring patients from the ED as well delays in identification and transfer of stable MICU patients. These interventions reduced transfer time from 4.2 (3.4-5.7) hours to 2.2 (1.4-3.1) hours (median [interquartile range]; P<.001). Hospital length of stay decreased from 9.9±9 to 8.3±7 days (P<.03).

CONCLUSION

A team made up of frontline health care professionals using a structured quality improvement process and implementing multifaceted, multistage interventions, reduced transfer delays, and length of stay. Added benefits included engagement among members of the 2 microsystems and a more cohesive approach to patient care.

Impact of opening a new emergency department on healthcare service and patient outcomes: analyses based on linking ambulance, emergency and hospital databases

BACKGROUND

Emergency department (ED) crowding caused by access block is an increasing public health issue and has been associated with impaired healthcare delivery, negative patient outcomes and increased staff workload.

AIM

To investigate the impact of opening a new ED on patient and healthcare service outcomes.

METHODS

A 24-month time series analysis was employed using deterministically linked data from the ambulance service and three ED and hospital admission databases in Queensland, Australia.

RESULTS

Total volume of ED presentations increased 18%, while local population growth increased by 3%. Healthcare service and patient outcomes at the two pre-existing hospitals did not improve. These outcomes included ambulance offload time: (Hospital A PRE: 10 min, POST: 10 min, P < 0.001; Hospital B PRE: 10 min, POST: 15 min, P < 0.001); ED length of stay: (Hospital A PRE: 242 min, POST: 246 min, P < 0.001; Hospital B PRE: 182 min, POST: 210 min, P < 0.001); and access block: (Hospital A PRE: 41%, POST: 46%, P < 0.001; Hospital B PRE: 23%, POST: 40%, P < 0.001). Time series modelling indicated that the effect was worst at the hospital furthest away from the new ED.

CONCLUSIONS

An additional ED within the region saw an increase in the total volume of presentations at a rate far greater than local population growth, suggesting it either provided an unmet need or a shifting of activity from one sector to another. Future studies should examine patient decision making regarding reasons for presenting to a new or pre-existing ED. There is an inherent need to take a 'whole of health service area' approach to solve crowding issues.

Delayed admission to ICU does not increase the mortality of patients post neurosurgery

Increasing shortage of intensive care resources is a worldwide problem. While routine postoperative admission to the intensive care unit (ICU) of patients undergoing neurosurgery is a long established practice for many hospitals. Therefore, some neurosurgical patients have to be cared in post anesthesia care unit (PACU) before ICU admission during high ICU occupancy. The aim of this study was to compare the outcome of neurosurgical patients immediately admitted to the ICU post operation with those who were required to wait for ICU bed in PACU and managed by anesthesiologists before ICU admission. All adult neurosurgical patients admitted to our ICU between January 2010 and July 2013 were retrospectively analyzed. Recorded data included demographic data, surgical categories, end time of operation, operation hours, postoperative complication, hospital/ICU length of stay and cost, Glasgow coma score (GCS) on ICU discharge and ICU mortality. A total of 989 neurosurgical patients were evaluated. Nine hundred thirty-seven (94.7%) patients were immediately admitted and 52 (5.3%) patients had delayed ICU admission. Median PACU waiting hours was 4.3 h (interquartile range: 2.0-10.2 h). Delayed ICU admission post neurosurgery was highly associated with the end time of operation (p = 0.019) and high ICU occupancy (p < 0.0001). Average GCS on ICU discharge was higher in immediately admitted group (13.0 ± 3.5 vs. 11.4 ± 4.5, p = 0.012). However, delayed admission to ICU post neurosurgery was not associated with prolonged ICU length of stay, increased ICU mortality, increased postoperative complication and hospital/ICU cost (all p > 0.05). Thus, an algorithm for appropriate disposition of neurosurgical patients is warranted so as to balance the quality of care and control of scarce intensive resources.

Caring for inpatient boarders in the emergency department: improving safety and patient and staff satisfaction

Hospital capacity constraints lead to large numbers of inpatients being held for extended periods in the emergency department. This creates concerns with safety, quality of care, and dissatisfaction of patients and staff. The aim of this quality-improvement project was to improve satisfaction and processes in which nurses provided care to inpatient boarders held in the emergency department. A quality-improvement project framework that included the use of a questionnaire was used to ascertain employee and patient dissatisfaction and identify opportunities for improvement. A task force was created to develop action plans related to holding and caring for inpatients in the emergency department. A questionnaire was sent to nursing staff in spring 2012, and responses from the questionnaire identified improvements that could be implemented to improve care for inpatient boarders. Situation-background-assessment-recommendation (SBAR) communications and direct observations were also used to identify specific improvements. Post-questionnaire results indicated improved satisfaction for both staff and patients. It was recognized early that the ED inpatient area would benefit from the supervision of an inpatient director, managers, and staff. Outcomes showed that creating an inpatient unit within the emergency department had a positive effect on staff and patient satisfaction.

Delayed admission to intensive care unit for critically surgical patients is associated with increased mortality

BACKGROUND

Shortage of beds in intensive care units (ICUs) is an increasing common phenomenon worldwide. Consequently, many critically ill patients have to be cared for in other hospital areas without specialized staff, such as general wards, emergency department, post anesthesia care unit (PACU). However, boarding critically ill patients in general wards or emergency department has been associated with higher mortality. The purpose of this study was to evaluate if a delay in ICU admission, waiting in PACU and managed by anesthesiologists, affects their ICU outcomes for critically surgical patients.

METHODS

A retrospective cohort of adult critically surgical patients admitted to our ICU between January 2010 and June 2012 were analyzed. ICU admission was classified as either immediate or delayed (waiting in PACU). A general estimation equation was used to examine the relationship of PACU waiting hours before ICU admission with ICU outcomes by adjusting for age, patient sex, comorbidities, surgical categories, end time of operation, operation hours, and clinical conditions.

RESULTS

A total of 2,279 critically surgical patients were evaluated. Two thousand ninety-four (91.9%) patients were immediately admitted and 185 (8.1%) patients had delayed ICU admission. There was a significant increase in ICU mortality rates with a delay in ICU admission (P < .001). Prolonged waiting hours in PACU (≥ 6 hours) was associated with higher ICU mortality (adjusted odds ratio 5.32; 95% confidence interval 1.25 to 22.60, P = .024). However, longer PACU waiting times was not associated with mechanical ventilation days, ICU length of stay, and ICU cost.

CONCLUSION

Prolonged waiting hours in PACU because of ICU bed shortage was associated with higher ICU mortality for critically surgical patients.

Trends in computed tomography utilization and association with hospital outcomes in a Chinese emergency department

BACKGROUND

Excessive use of computed tomography (CT) in emergency departments (EDs) has become a concern due to its expense and the potential risks associated with radiation exposure. Although studies have shown a steady increase in the number of CT scans requested by ED physicians in developed countries like the United States and Australia, few empirical data are available regarding China.

METHODS AND FINDINGS

We retrospectively analyzed a database of ED visits to a tertiary Chinese hospital to examine trends in CT utilization and their association with ED outcomes between 2005 and 2008. A total of 197,512 ED visits were included in this study. CT utilization increased from 9.8% in 2005 to 13.9% in 2008 (P<.001 for trend). The ED length of stay for visits with CT utilization was 0.6 hour longer than those in which CT was not obtained. CT utilization increased the ED cost by an average $48.2. After adjustment for patients' demographics, arrival hours and clinical condition, CT utilization during ED visits was significantly associated with high ED cost (Odds Ratio [OR]: 21.70; 95% confidence interval [CI], 17.00-27.71), long ED length of stay (OR: 1.22; 95%CI, 1.12-1.34), and more likely to receive emergency operations (OR: 2.31; 95%CI, 1.94-2.76). However, there was no significant correlation between CT use and the possibility to be admitted to inpatient wards (OR: 0.82; 95%CI, 0.65-1.04). With respect to the time-related trends, CT utilization during ED visits in all study years was significantly associated with high ED cost and more likely to receive emergency operations.

CONCLUSION

CT utilization was associated with higher ED cost, longer ED length of stay and more likely to receive emergency operations, but did not correlate with a significant change in the admission rate.