scholarly journals Use of the SONET Score to Evaluate High Volume Emergency Department Overcrowding: A Prospective Derivation and Validation Study

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Hao Wang ◽  
Richard D. Robinson ◽  
John S. Garrett ◽  
Kellie Bunch ◽  
Charles A. Huggins ◽  
...  
Keyword(s):  
Emergency Department ◽  
Patient Care ◽  
Care Delivery ◽  
Average Length ◽  
High Volume ◽  
Patient Acuity ◽  
Factors Affecting ◽  
Left Without Being Seen ◽  
Ed Overcrowding ◽  
Care Outcomes

Background. The accuracy and utility of current Emergency Department (ED) crowding estimation tools remain uncertain in EDs with high annual volumes. We aimed at deriving a more accurate tool to evaluate overcrowding in a high volume ED setting and determine the association between ED overcrowding and patient care outcomes.Methods. A novel scoring tool (SONET: Severely overcrowded-Overcrowded-Not overcrowded Estimation Tool) was developed and validated in two EDs with both annual volumes exceeding 100,000. Patient care outcomes including the number of left without being seen (LWBS) patients, average length of ED stay, ED 72-hour returns, and mortality were compared under the different crowding statuses.Results. The total number of ED patients, the number of mechanically ventilated patients, and patient acuity levels were independent risk factors affecting ED overcrowding. SONET was derived and found to better differentiate severely overcrowded, overcrowded, and not overcrowded statuses with similar results validated externally. In addition, SONET scores correlated with increased length of ED stay, number of LWBS patients, and ED 72-hour returns.Conclusions. SONET might be a better fit to determine high volume ED overcrowding. ED overcrowding negatively impacts patient care operations and often produces poor patient perceptions of standardized care delivery.

scholarly journals Bringing the Nurse Back to the Bedside

2021 ◽  
Author(s):  
Gordon Bingham ◽  
Paul Ross ◽  
Susan Poole ◽  
Naomi Dobroff ◽  
Larnie Wright ◽  
...  
Keyword(s):  
Health Services ◽  
Patient Care ◽  
Care Delivery ◽  
Nursing Profession ◽  
Australian Health ◽  
Care Outcomes ◽  
The Way

As digitisation continues to increase across Australian health services, the nursing profession has focused on analysing and measuring the way care is provided to the patients. Focus on optimising nursing workflows and improved care delivery has presented challenges but this is now demonstrating improvements in patient care outcomes and time for care.

scholarly journals P130: Cumulative daily boarding time: a new way to measure emergency department congestion and hospital-wide flow

CJEM ◽  
2018 ◽  
Vol 20 (S1) ◽  
pp. S103-S103
Author(s):  
L. Salehi ◽  
V. Jegatheeswaran ◽  
P. Phalpher ◽  
R. Valani ◽  
M. Mercuri
Keyword(s):  
Emergency Department ◽  
Negative Impact ◽  
Linear Regression Analysis ◽  
Positive Association ◽  
High Volume ◽  
Initial Assessment ◽  
Process Time ◽  
Alternative Measure ◽  
Ed Overcrowding ◽  
Number Percentage

Introduction: Bed boarding of admitted patients in the Emergency Department (ED) is one of the major contributors to ED overcrowding, and an indicator of hospital-wide deficiencies in capacity and flow. Most indicators of ED overcrowding have measured either counts or percentages of patient subgroups (e.g. number/percentage of patients waiting in triage or number/percentage of admitted patients as compared to full ED census), or specific process time intervals related to patient movement through the hospital (e.g. Physician to Initial Assessment (PIA) time or total ED Length of Stay (EDLOS)). We sought to 1) devise an alternative measure of ED overcrowding that captured the dynamic and disproportionate resource utilization of admitted versus non-admitted patients in the ED, and to 2) determine the association of this measure with selected ED quality metrics for non-admitted patients. Methods: We conducted a retrospective multi-centre observational study at three very high-volume community hospitals in the Greater Toronto Area. Data on all patients visiting the ED during the period between January 1, 2015 and December 31, 2016 were included in the study. We calculated the total daily cumulative boarding time - or time to bed (TTB) - for each day of the study duration. The daily cumulative TTB was calculated as the time from decision to admit to transfer from the ED for all admitted patients within a 24-hour period. We conducted linear regression analysis to determine the association between our measured daily cumulative TTB and daily median and 90th percentile PIA and EDLOS times for non-admitted patients. Results: Preliminary results for 2015 indicate a total cumulative TTB time ranging from 50,973 hours to 191,093 patient-hours for the year, with daily mean cumulative TTB ranging from 140 524 patient-hours/day among the three hospitals. In all three hospitals, there was a statistically significant (p<0.01) positive association between daily cumulative TTB and both median and 90th percentile PIA times for all patients, and median EDLOS times for non-admitted CTAS 1 -3 patients. There was a statistically significant (p<0.05) positive association between daily cumulative TTB and 90th percentile EDLOS for non-admitted CTAS 1-3 patients in two of the three hospitals, with the third hospital showing a positive but non-significant association. Conclusion: Bed boarding constitutes a significant resource cost for EDs, and has a negative impact on timeliness of ED care for the general ED population, particularly more complex (CTAS 1-3) non-admitted patients.

scholarly journals MP12: Emergency department boarding: predictors and outcomes

CJEM ◽  
2018 ◽  
Vol 20 (S1) ◽  
pp. S44-S44
Author(s):  
L. Salehi ◽  
V. Jegatheeswaran ◽  
J. Herman ◽  
P. Phalpher ◽  
R. Valani ◽  
...  
Keyword(s):  
Critical Care ◽  
Patient Care ◽  
High Volume ◽  
Patient Characteristics ◽  
Patient Specific ◽  
Medicine Service ◽  
Comorbidity Burden ◽  
Ed Overcrowding ◽  
Ed Visits ◽  
The Impact

Introduction: Delays in transfer to an in-patient bed of admitted patients boarded in the ED has been identified as one of the chief drivers of ED overcrowding. Our study aims to replicate findings from a previous study in identifying patient characteristics associated with increased boarding time, and the impact of increased boarding time on in-patient length of stay (IPLOS). Methods: We conducted a retrospective single-centre observational study during the period between January 1, 2015 December 31, 2015 at a very high volume community hospital (~ 75,000 ED visits/year). All patients admitted from the ED to Medicine, Pediatrics, Surgery, and Critical Care were identified. The mean time to in-patient bed (TTB), as well as patient-specific and institutional factors that were associated with prolonged boarding times ( 12 hours) were identified. Mean IP LOS was calculated for those with prolonged boarding times and compared to those without prolonged boarding times. Results: There were 8,096 unique admissions during the study period. Patients admitted to the Medicine service exhibited significantly higher boarding times than those admitted to other services, with a mean boarding time of 17.4 hrs, as compared to 4.2 hrs, 5.7 hrs, and 4.0 hrs for those admitted to Surgery, Critical Care and Pediatrics respectively. Within Medicine patients, there was a statistically significant greater odds of prolonged boarding time for patients who were older, had a greater comorbidity burden, and required more specialized in-patient care (i.e. an isolation bed or telemetry bed). Medicine patients with prolonged boarding times also experienced 0.7 days longer IP LOS, even after correcting for age and comorbidity (mean adjusted IP LOS 10.6 days versus 11.3 days). Conclusion: Within our study period, older, sicker patients and those patients requiring more resource-intensive in-patient care have the longest ED boarding times. These prolonged ‘boarding’ times are associated with significantly increased IP LOS.

Potential Savings Involved in the Purchase of Low-Cost, High-Volume Medical Commodities as Established from a Community Hospital Survey

1996 ◽  
Vol 9 (4) ◽  
pp. 24-29
Author(s):  
San W. Ng ◽  
Rosmin Esmail ◽  
William J. Sibbald ◽  
Gordon S. Doig
Keyword(s):  
Patient Care ◽  
Community Hospital ◽  
Care Delivery ◽  
Low Cost ◽  
Cost Savings ◽  
Improve Patient Care ◽  
High Volume ◽  
Health Technology ◽  
Substantial Cost ◽  
Improve Patient

Health technology refers to the instruments, equipment, drugs and procedures used in health care delivery, as well as the organizations supporting it. Health technology assessment, which is the process of conducting investigations to establish the criteria for efficacious, effective and efficient patient care, is becoming increasingly important in an era of diminishing resources. This survey of 39 community hospitals in southwestern Ontario found that improved purchasing strategies can result in substantial cost savings which can in turn be used to improve patient care. The study shows that optimizing the price of basic hospital commodities could save an average community hospital as much as $625,000 per year.

scholarly journals LO67: A variation on Triage Liaison Physicians (TLP): a comparative analysis of the Emergency Department Disposition and Care Consultant (EDC) concept

CJEM ◽  
2018 ◽  
Vol 20 (S1) ◽  
pp. S30-S30
Author(s):  
B. H. Rowe ◽  
A. Haponiuk ◽  
J. Lowes ◽  
W. Sevcik ◽  
C. Villa-Roel ◽  
...  
Keyword(s):  
Emergency Department ◽  
Tertiary Care ◽  
Pilot Project ◽  
Chi Square ◽  
Left Without Being Seen ◽  
Ed Overcrowding ◽  
Discharged Patients ◽  
Level 3 ◽  
Dichotomous Outcomes ◽  
And Control

Introduction: Despite evidence that triage liaison physicians (TLP) effectively reduce emergency department (ED) overcrowding, support for these interventions is patchy. The aim of this study was to evaluate the implementation of a TLP-like ED Disposition and Care Consultant (EDC) shift at an academic tertiary care ED. Methods: A 24-week pilot project was conducted 11/16-04/17. Physicians worked 8- hour day (07-15:00) and/or evening (15:00-23:00) EDC shifts and performed immediate triage and patient care when needed, assisted triage RNs, answered all incoming calls, and managed administrative matters. Due to their voluntary nature, not all shifts were filled. This study compared active (EDC) and control (C) shifts on the following ED metrics: length of stay (LOS), proportions of patients who left without being seen (LWBS), and safety (return visits to ED). Descriptive (median and interquartile range {IQR} and proportions) and simple (Wilcoxson-Mann-Whitney, chi-square, z-proportion) tests are presented for continuous and dichotomous outcomes, respectively. Multiple linear regression identified factors associated with LOS. Results: Of 112 possible EDC shifts, 58 (52%) were filled involving 4289 patients and compared to 276 C shifts involving 21,358 patients. ED volume, patient age (49; IQR: 31, 66), mode of arrival (~30% EMS), triage levels (~51% level 3), and complaints were similar between the groups. Overall, the EDC group reduced LWBS by 16% (8.7% vs. 10.4%; p=0.001), ED LOS for discharged patients by 30 minutes (5.5 vs. 6.0 hours; p<0.001), and ED LOS for admitted patients by 42 minutes (9.7 vs. 10.4 hours; p=0.02). The EDC increased the proportion discharged <4 hours by 28% (20.1 vs. 15.7%; p<0.001) and increased the proportion admitted <8 hours by 17% (8.2% vs. 9.6%, p=0.002). ED relapses <72 hours were similar (9.3% vs. 8.9%; p=0.4); however, admissions were higher in the EDC shifts (25.3% vs. 23.8%; p=0.04). In addition to EDC coverage status, LOS was influenced by triage level (1.7%, p<0.001), disposition (19.6%, p<0.001), and age (4.8%, p<0.001). Conclusion: Our results indicate that an EDC shift, while unpopular with many physicians, provides valuable services to an overcrowded ED and that the implementation of this type of shift could reduce LOS and LWBS statistics in a tertiary care institution. Additional evaluations to examine this and other front-end interventions in other ED centers are indicated.

scholarly journals LO56: Novel role of physician navigators on performance indicators in the emergency department

CJEM ◽  
2017 ◽  
Vol 19 (S1) ◽  
pp. S47
Author(s):  
A. Leung ◽  
G. Puri ◽  
B. Chen ◽  
Z. Gong ◽  
E. Chan ◽  
...  
Keyword(s):  
Emergency Department ◽  
Patient Care ◽  
Mixed Linear Model ◽  
Primary Objective ◽  
Initial Assessment ◽  
Direct Patient Care ◽  
Healthcare Team ◽  
Left Without Being Seen ◽  
Before And After ◽  
The Impact

Introduction: Burnout rates for emergency physicians (EP) continue to be amongst the highest in medicine. One of the commonly cited sources of stress contributing to disillusionment is bureaucratic tasks that distract EPs from direct patient care in the emergency department (ED). The novel position of Physician Navigator was created to help EPs decrease their non-clinical workload during shifts, and improve productivity. Physician Navigators are non-licensed healthcare team members that assist in activities which are often clerical in nature, but directly impact patient care. This program was implemented at no net-cost to the hospital or healthcare system. Methods: In this retrospective study, 6845 clinical shifts worked by 20 EPs over 39 months from January 1, 2012 to March 31, 2015 were evaluated. The program was implemented on April 1, 2013. The primary objective was to quantify the effect of Physician Navigators on measures of EP productivity: patient seen per hour (Pt/hr), and turn-around-time (TAT) to discharge. Secondary objectives included examining the impact of Physician Navigators on measures of ED throughput for non-resuscitative patients: emergency department length of stay (LOS), physician-initial-assessment times (PIA), and left-without-being-seen rates (LWBS). A mixed linear model was used to evaluate changes in productivity measures between shifts with and without Physician Navigators in a clustered design, by EP. Autoregressive modelling was performed to compare ED throughput metrics before and after the implementation of Physician Navigators for non-resuscitative patients. Results: Across 20 EPs, 2469 shifts before, and 4376 shifts after April 1, 2013 were analyzed. Daily patient volumes increased 8.7% during the period with Physician Navigators. For the EPs who used Physician Navigators, Pt/hr increased by 1.07 patients per hour (0.98 to 1.16, p&lt;0.001), and TAT to discharge decreased by 10.6 minutes (-13.2 to -8.0, p&lt;0.001). After the implementation of the Physician Navigators, overall LOS for non-resuscitative patients decreased by 2.6 minutes (1.0%, p=0.007), and average PIA decreased by 7.4 minutes (12.0%, p&lt;0.001). LBWS rates decreased by 43.9% (0.50% of daily patient volume, p&lt;0.001). Conclusion: The use of a Physician Navigator was associated with increased EP productivity as measured by Pt/hr, and TAT to discharge, and reductions in ED throughput metrics for non-resuscitative patients.

scholarly journals Emergency Department Overcrowding in Turkey: Reasons, Facts and Solutions

2014 ◽  
Vol 52 (195) ◽  
pp. 878-885 ◽  
Author(s):  
Oya Durmus Cakir ◽  
Sebnem Eren Cevik ◽  
Mehtap Bulut ◽  
Ozlem Guneyses ◽  
Sule Akkose Aydin
Keyword(s):  
Emergency Department ◽  
Length Of Stay ◽  
Average Length ◽  
Waiting Times ◽  
Pediatric Trauma ◽  
University Hospital ◽  
Trauma Patients ◽  
Factors Affecting ◽  
Average Length Of Stay ◽  
Bed Capacity

Introduction: The purpose of this study was to determine the factors affecting the long waiting times of the patients in a university hospital. Methods: This study included 3000 of the adults above 18 years and pediatric trauma patients under 18 years who applied to emergency department between February 2009 and April 2009. The examination period of the physician, length of stay, length of hospitalization, waiting times for hospitalization and follow up times in the emergency department were recorded. Moreover, the patients were divided into four groups according to the reasons for waiting. Results: In our study, the time period between 4 pm-12 pm was determined as the busiest time for the applications. Average length of stay in the emergency department for 3000 patients was 146.7±160.2 minutes. The length of stay for the patients consulted was longer than the length of stay for the ones who were not consulted. Because of the fact that our hospital did not have appropriate bed capacity, 41.1% of the patients waited less than two hours, 13. 4% of the patients waited more than 8 hours. It was also found that the waiting times of the Group two patients (206,7±145,2 minutes) was longer than Group one (95,5±73,9 minutes) patients and the waiting times of Group three patients (470,7±364,7 minutes) was longer than Group one patients. Conclusions: In conclusion, cooperation of the managers, relevant departments and a multidisciplinary approach are necessary to achieve the goals to reduce overcrowding in the emergency departments.  Keywords: bed capacity; crowding; emergency department; length of stay.  

scholarly journals LO54: A descriptive analysis of ED length of stay of admitted patients ‘boarded’ in the emergency department

CJEM ◽  
2017 ◽  
Vol 19 (S1) ◽  
pp. S46
Author(s):  
L. Salehi ◽  
P. Phalpher ◽  
R. Valani
Keyword(s):  
Emergency Department ◽  
Length Of Stay ◽  
Descriptive Analysis ◽  
High Volume ◽  
Increased Risk ◽  
Significant Difference ◽  
Ed Overcrowding ◽  
Day Of The Week ◽  
The Mean ◽  
The Impact

Introduction: Previous studies have shown a link between Emergency Department (ED) overcrowding and worse clinical outcomes, increased risk of in-hospital mortality, higher costs, and longer times to treatment. Prolonged ED Length of Stay (LoS) of admitted patients awaiting a bed on in-patient units has been identified as a major driver of ED overcrowding. The purpose of this study is to provide a descriptive analysis of ED LoS among admitted patients, and determine the impact of prolonged ED LoS on total hospital in-patient length of stay (IP LoS). Methods: We conducted a single-site retrospective study for the period between January 1-December 31, 2015 at a very high volume community hospital. All patients aged ≥18 years admitted from the ED to acute in-patient Medicine units were identified. We carried out overall descriptive analysis (including analysis of day-of-the-week variability) on ED LoS. The mean total IP LoS for those patients with ED LoS&lt;12 hours, 12-24 hours, and ≥24 hours were calculated and analyzed using ANOVA and Tukey HSD tests. Results: A total of 6,961 individuals were admitted to the medical units over the 12-month period. The median and mean ED LoS for admitted patients were 22.9 hrs (IQR: 13.9 hrs- 33.1 hrs) and 25.6 hrs respectively. Using ANOVA, there was a statistically significant difference in means of ED LoS as a function of the day of the week (p&lt;0.0001), with Mondays having the highest mean ED LoS (27.6 hrs), and Fridays having the lowest (23.1 hrs). The mean IP LoS for those with ED LoS&lt;12 hours, 12-24 hours, and ≥24 hours, were 6.8 days, 6.9 days, and 8.5 days respectively, with a statistically significant difference between group means (p&lt;0.0001). Multiple pairwise comparisons of group means showed a statistically significant (p&lt;0.05) difference between mean IP LOS of those with an EDLOS≥24 hours and those with an EDLOS&lt;24 hours. Conclusion: Preliminary results indicate that ED LoS≥24 hours among admitted patients was associated with an increase in total IP LoS.*In the next 1-2 months, we intend to explore the role of other independent variables (age, sex, comorbidity, isolation status, and telemetry) on total ED LoS, and its association with IP LoS.

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