Improving service in an emergency department by designing the health production flow

2019 ◽  
Vol 33 (2) ◽  
pp. 76-85
Author(s):  
Oscar Barros ◽  
Rodrigo Riffo ◽  
Inti Paredes
Keyword(s):  
Emergency Department ◽  
Length Of Stay ◽  
Average Length ◽  
Conservative Estimate ◽  
Health Production ◽  
Production Flow ◽  
Large Hospital ◽  
Direct Evaluation ◽  
Average Length Of Stay ◽  
Formal Design

Background Most emergency departments have overcapacity with poor service measured by length of stay. We hypothesized that a formal design of the emergency department production flows will improve service. Thus, we propose a methodology that was tested in a large hospital, including new flow implementation. Results We implemented new workflows during June to July 2017. A comparison of the patients’ average length of stay from June to September shows a decrease of 26%. Additionally, a comparison with 2016 shows a decrease of 50%. Direct evaluation of the value generated reveals an emergency department admissions increase of 540 monthly, equivalent of a savings of approximately US$250.000 annually. This savings is a very conservative estimate because the most significant value of this work is fast service that diminishes the patients’ risks. Conclusions Production design is an important problem in health services in terms of potential service improvements, executable with a formal, systemic, replicable method founded on several disciplines. Thus, we are replicating the approach at other hospitals with extensions to other services.

Improving Emergency Department Time to Provider, Left-Without-Treatment Rates, and Average Length of Stay

2013 ◽  
Vol 45 (3) ◽  
pp. 426-432 ◽  
Author(s):  
Ghazala Q. Sharieff ◽  
Lori Burnell ◽  
Matt Cantonis ◽  
Valerie Norton ◽  
Juan Tovar ◽  
...  
Keyword(s):  
Emergency Department ◽  
Length Of Stay ◽  
Average Length ◽  
Average Length Of Stay

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 Emergency Surgery in A Tertiary Hospital: The Covid-19 Experience

2020 ◽  
Author(s):  
Gennaro Perrone ◽  
Mario Giuffrida ◽  
Elena Bonati ◽  
Paolo Del Rio ◽  
Vittoria Pattonieri ◽  
...  
Keyword(s):  
Emergency Department ◽  
Length Of Stay ◽  
Acute Appendicitis ◽  
Acute Cholecystitis ◽  
Emergency Surgery ◽  
Average Length ◽  
Medical Science ◽  
University Hospital ◽  
Average Length Of Stay ◽  
The Impact

Objective: Evaluate the impact of Covid-19 in a critical area and analyze the changes in the daily activities in an Emergency Department of a tertiary COVID-Hospital. Methods: We reported and compared the surgical procedures performed for acute appendicitis and acute cholecystitis between two periods (March and April 2019 and March and April 2020) at Emergency Surgery Department of Parma University Hospital, a tertiary COVID-Hospital. Results: A total of 72 patients underwent surgery between March and April 2019 and 36 between March and April 2020 for acute appendicitis and cholecystitis. The average length of stay was comparable in the two considered years for LA (4.23±1.69 days in 2019 versus 4.5±2.33 days in 2020). The average length of stay in patients with acute cholecystitis was 5.9±3.8 days in 2019 and 8.23±5.5 days in 2020(P=0.038). The average hospitalization was comparable with 2019 data (5.62±3.77 days)n March 2020;whereas, April 2020 was statistically significantly longer 10.5±6 days (P= 0.023). Conclusions: Half of the emergency centers reported a drop in the overall number of urgent cases as confirmed in our department, where the number of total appendicectomy and cholecystectomy was halved comparing the two months in 2019 and 2020, 72 operations in 2019 versus 36 operations in 2020.During the pandemic, the confidence of the population to the healthcare systems was poor, and this can explain the delayed access to the emergency department of patients who suffered from an acute illness. Bangladesh Journal of Medical Science Vol.19(0) 2020 p. S 66-S 68

scholarly journals Colonization and Infection With MRSA and CRKP and Its Result in an Increased Mortality Rate Within the Intensive Care and High-Dependency Units in Barbados

2020 ◽  
Vol 41 (S1) ◽  
pp. s173-s174
Author(s):  
Keisha Gustave
Keyword(s):  
Intensive Care ◽  
Length Of Stay ◽  
High Mortality ◽  
Average Length ◽  
Cohort Analysis ◽  
Health Concern ◽  
Queen Elizabeth Hospital ◽  
Surveillance Program ◽  
Average Length Of Stay ◽  
High Dependency

Background: Methicillin-resistant Staphylococcus aureus(MRSA) and carbapenem-resistant Klebsiella pneumoniae (CRKP) are a growing public health concern in Barbados. Intensive care and critically ill patients are at a higher risk for MRSA and CRKP colonization and infection. MRSA and CRKP colonization and infection are associated with a high mortality and morbidly rate in the intensive care units (ICUs) and high-dependency units (HDUs). There is no concrete evidence in the literature regarding MRSA and CRKP colonization and infection in Barbados or the Caribbean. Objectives: We investigated the prevalence of MRSA and CRKP colonization and infection in the patients of the ICU and HDU units at the Queen Elizabeth Hospital from 2013 to 2017. Methods: We conducted a retrospective cohort analysis of patients admitted to the MICU, SICU, and HDU from January 2013 through December 2017. Data were collected as part of the surveillance program instituted by the IPC department. Admissions and weekly swabs for rectal, nasal, groin, and axilla were performed to screen for colonization with MRSA and CRKP. Follow-up was performed for positive cultures from sterile isolates, indicating infection. Positive MRSA and CRKP colonization or infection were identified, and patient notes were collected. Our exclusion criteria included patients with a of stay of <48 hours and patients with MRSA or CRKP before admission. Results: Of 3,641 of persons admitted 2,801 cases fit the study criteria. Overall, 161 (5.3%) were colonized or infected with MRSA alone, 215 (7.67%) were colonized or infected with CRKP alone, and 15 (0.53%) were colonized or infected with both MRSA and CRKP. In addition, 10 (66.6%) of patients colonized or infected with MRSA and CRKP died. Average length of stay of patients who died was 50 days. Conclusions: The results of this study demonstrate that MRSA and CRKP cocolonization and coinfection is associated with high mortality in patients within the ICU and HDU units. Patients admitted to the ICU and HDU with an average length of stay of 50 days are at a higher risk for cocolonization and coinfection with MRSA and CRKP. Stronger IPC measures must be implemented to reduce the spread and occurrence of MRSA and CRKP.Funding: NoneDisclosures: None

scholarly journals Temporal Changes in Central-Line–Associated Bloodstream Infection Time Between Events, 2017–2018 Versus 2015–2016

2020 ◽  
Vol 41 (S1) ◽  
pp. s403-s404
Author(s):  
Jonathan Edwards ◽  
Katherine Allen-Bridson ◽  
Daniel Pollock
Keyword(s):  
Length Of Stay ◽  
Patient Care ◽  
Average Length ◽  
Bloodstream Infections ◽  
Central Line ◽  
Significant Shift ◽  
Care Hospital ◽  
Average Length Of Stay ◽  
Period 2 ◽  
Hospital Bed

Background: The CDC NHSN surveillance coverage includes central-line–associated bloodstream infections (CLABSIs) in acute-care hospital intensive care units (ICUs) and select patient-care wards across all 50 states. This surveillance enables the use of CLABSI data to measure time between events (TBE) as a potential metric to complement traditional incidence measures such as the standardized infection ratio and prevention progress. Methods: The TBEs were calculated using 37,705 CLABSI events reported to the NHSN during 2015–2018 from medical, medical-surgical, and surgical ICUs as well as patient-care wards. The CLABSI TBE data were combined into 2 separate pairs of consecutive years of data for comparison, namely, 2015–2016 (period 1) and 2017–2018 (period 2). To reduce the length bias, CLABSI TBEs were truncated for period 2 at the maximum for period 1; thereby, 1,292 CLABSI events were excluded. The medians of the CLABSI TBE distributions were compared over the 2 periods for each patient care location. Quantile regression models stratified by location were used to account for factors independently associated with CLABSI TBE, such as hospital bed size and average length of stay, and were used to measure the adjusted shift in median CLABSI TBE. Results: The unadjusted median CLABSI TBE shifted significantly from period 1 to period 2 for the patient care locations studied. The shift ranged from 20 to 75.5 days, all with 95% CIs ranging from 10.2 to 32.8, respectively, and P < .0001 (Fig. 1). Accounting for independent associations of CLABSI TBE with hospital bed size and average length of stay, the adjusted shift in median CLABSI TBE remained significant for each patient care location that was reduced by ∼15% (Table 1). Conclusions: Differences in the unadjusted median CLABSI TBE between period 1 and period 2 for all patient care locations demonstrate the feasibility of using TBE for setting benchmarks and tracking prevention progress. Furthermore, after adjusting for hospital bed size and average length of stay, a significant shift in the median CLABSI TBE persisted among all patient care locations, indicating that differences in patient populations alone likely do not account for differences in TBE. These findings regarding CLABSI TBEs warrant further exploration of potential shifts at additional quantiles, which would provide additional evidence that TBE is a metric that can be used for setting benchmarks and can serve as a signal of CLABSI prevention progress.Funding: NoneDisclosures: None

scholarly journals Biased and unbiased estimation of the average length of stay in intensive care units in the Covid-19 pandemic

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Nathanael Lapidus ◽  
Xianlong Zhou ◽  
Fabrice Carrat ◽  
Bruno Riou ◽  
Yan Zhao ◽  
...  
Keyword(s):  
Intensive Care ◽  
Length Of Stay ◽  
Average Length ◽  
Parametric Method ◽  
Estimation Methods ◽  
Unbiased Estimation ◽  
Bed Occupancy ◽  
Average Length Of Stay ◽  
Discharged Patients ◽  
First Admission

Abstract Background The average length of stay (LOS) in the intensive care unit (ICU_ALOS) is a helpful parameter summarizing critical bed occupancy. During the outbreak of a novel virus, estimating early a reliable ICU_ALOS estimate of infected patients is critical to accurately parameterize models examining mitigation and preparedness scenarios. Methods Two estimation methods of ICU_ALOS were compared: the average LOS of already discharged patients at the date of estimation (DPE), and a standard parametric method used for analyzing time-to-event data which fits a given distribution to observed data and includes the censored stays of patients still treated in the ICU at the date of estimation (CPE). Methods were compared on a series of all COVID-19 consecutive cases (n = 59) admitted in an ICU devoted to such patients. At the last follow-up date, 99 days after the first admission, all patients but one had been discharged. A simulation study investigated the generalizability of the methods' patterns. CPE and DPE estimates were also compared to COVID-19 estimates reported to date. Results LOS ≥ 30 days concerned 14 out of the 59 patients (24%), including 8 of the 21 deaths observed. Two months after the first admission, 38 (64%) patients had been discharged, with corresponding DPE and CPE estimates of ICU_ALOS (95% CI) at 13.0 days (10.4–15.6) and 23.1 days (18.1–29.7), respectively. Series' true ICU_ALOS was greater than 21 days, well above reported estimates to date. Conclusions Discharges of short stays are more likely observed earlier during the course of an outbreak. Cautious unbiased ICU_ALOS estimates suggest parameterizing a higher burden of ICU bed occupancy than that adopted to date in COVID-19 forecasting models. Funding Support by the National Natural Science Foundation of China (81900097 to Dr. Zhou) and the Emergency Response Project of Hubei Science and Technology Department (2020FCA023 to Pr. Zhao).

scholarly journals Times of change in complex environments - Evaluating hospital co-payments in Palestine refugee camps

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
S V Valente de Almeida ◽  
H Ghattas ◽  
G Paolucci ◽  
A Seita
Keyword(s):  
Length Of Stay ◽  
Policy Change ◽  
Negative Binomial ◽  
Negative Impact ◽  
Average Length ◽  
Lessons Learned ◽  
Policy Impact ◽  
Average Length Of Stay ◽  
Ex Post ◽  
The Impact

Abstract We measure the impact introducing a of 10% co-payment component on hospitalisation costs for Palestine refugees from Lebanon in public and private hospitals. This ex-post analysis provides a detailed insight on the direction and magnitude of the policy impact in terms of demand and supply for healthcare. The data was collected by the United Nations Relief and Works Agency for Palestine Refugees in the Near East and include episode level information from all public, private and Red Crescent Hospitals in Lebanon, between April 2016 and October 2017. This is a complete population episode level dataset with information from before and after the policy change. We use multinomial logit, negative binomial and linear models to estimate the policy impact on demand by type of hospital, average length of stay and treatment costs for the patient and the provider. After the new policy was implemented patients were 18% more likely to choose a (free-of-charge) PRCS hospital for secondary care, instead of a Private or Public hospital, where the co-payment was introduced. This impact was stronger for episodes with longer stays, which are also the more severe and more expensive cases. Average length of stay decreased in general for all hospitals and we could not find a statistically significant impact on costs for the provider nor the patient. We find evidence that the introduction of co-payments is hospital costs led to a shift in demand, but it is not clear to what extent the hospitals receiving this demand shift were prepared for having more patients than before, also because these are typically of less quality then the others. Regarding costs, there is no evidence that the provider managed to contain costs with the new policy, as the demand adapted to the changes. Our findings provide important information on hospitalisation expenses and the consequences of a policy change from a lessons learned perspective that should be taken into account for future policy decision making. Key messages We show that in a context of poverty, the introduction of payment for specific hospital types can be efficient for shifting demand, but has doubtable impact on costs containment for the provider. The co-payment policy can have a negative impact on patients' health since after its implementation demand increased at free-of-charge hospitals, which typically have less resources to treat patients.

scholarly journals P17 An audit of Trakcare discharge times for Laparoscopic Cholecystectomy

BJS Open ◽  
2021 ◽  
Vol 5 (Supplement_1) ◽  
Author(s):  
Jacob Rapier ◽  
Steven Hornby ◽  
Jacob Rapier
Keyword(s):  
Laparoscopic Cholecystectomy ◽  
Length Of Stay ◽  
Initial Data ◽  
Best Practice ◽  
Average Length ◽  
Accurate Data ◽  
Day Case ◽  
Average Length Of Stay ◽  
Number Of Patients ◽  
Elective Laparoscopic Cholecystectomy

Abstract Introduction Nationally 61,220 Laparoscopic Cholecystectomies are carried out annually. Those carried out as day-cases reduce providers’ costs and increase income through the best practice tariff. The system in our trust to record discharges is ‘Trakcare’. The aim of this audit was to accurately measure the discharge times of patients undergoing elective Laparoscopic Cholecystectomies, to try and reduce the number of patients recorded as having an overnight stay by accurate data collection. Methods Initial data was collected for all elective Laparoscopic Cholecystectomy discharge times on Trakcare, over a 1 month period. This data was then re-audited prospectively both from Trakcare and discharges reported by nurses/patients. A comparison was then made of Trakcare against reported discharge times. Results Initially 54 operations were recorded, with 30 completed as day cases (55.6%). The re-audited data (on Trakcare) recorded 47 operations, with 15 completed as day cases (37.91%). Of these discharges we were able to capture 26 (55.32%) manually, and 11 were completed as day cases (42.31%). Measuring these 26 with the same operations on Trakcare we were unable to show a difference in the number of cases completed as a day case (11 vs 11), with only a 33 minute decrease in the average length of stay. Conclusion Trakcare is a reliable tool for measuring the date of discharge for patients. The recommendations in are: scheduling surgery for a time pre-13:00 shows a higher proportion of patients discharged the same day, and continue to use Trakcare to record discharge times.

Total Population Estimate of Newborn Special-Care Bed Needs

PEDIATRICS ◽  
1985 ◽  
Vol 75 (6) ◽  
pp. 993-996
Author(s):  
August L. Jung ◽  
Nan Sherman Streeter
Keyword(s):  
Length Of Stay ◽  
Total Population ◽  
Average Length ◽  
Special Care ◽  
Care Hospital ◽  
Total Hospital ◽  
Live Births ◽  
Average Length Of Stay ◽  
Study Results ◽  
Hospital Days

In 1977, 7% of the 38,855 infants born in Utah were estimated to have required a total of 27,439 special-care hospital days. About half (53%) were mildly ill; their average length of stay was 4.6 days, or 24% of the total hospital-days. Another 20% of the infants had intermediate illness, with a 12-day average stay, or 23% of the total hospital-days. The remaining 27% of the infants required intensive care and used 53% of the total hospital-days; their average length of stay was 20 days. As a total population, the state's 38,855 births generated a need for two beds per 1,000 annual live births in special-care facilities. The estimated bed need was: mild illness (Level I), 0.5 beds per 1,000 annual live births; intermediate illness (Level II), 0.5 beds per 1,000 annual live births; and intense illness (Level III), one bed per 1,000 annual live births. Results are based on the assumption that nonstudy births, 30% of the total, have needs proportionate to study births. The following considerations are necessary to extrapolate these bed needs to other populations: (1) convalescence of intensely ill babies may require that up to 50% of their bed needs may be shifted to intermediate care; (2) compliance with criteria for transport to the next level of care may not be 100% as assumed in the study, thus redistributing bed needs; (3) census characteristically fluctuates in special-care nurseries (study results are reported for an unchanging daily census); and (4) the low birth rate of a population is intimately related to the bed needs.

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