Safety and feasibility of a nurse-led ambulatory abdominal paracentesis service.

2021 ◽  
Vol 39 (28_suppl) ◽  
pp. 63-63
Author(s):  
Kim Hua Lee
Keyword(s):  
Length Of Stay ◽  
Adverse Events ◽  
Average Length ◽  
Symptom Relief ◽  
Bleeding Complications ◽  
Inpatient Setting ◽  
Bed Occupancy ◽  
Abdominal Drain ◽  
Hospital Bed ◽  
Abdominal Paracentesis

63 Background: Ascites is a common complication of cancer. Symptomatic ascites contributes to cancer-related morbidity and is distressing for patients (pts). Therapeutic abdominal paracentesis (TAP) provides symptom relief but requires specialized procedural knowledge and is usually performed in the inpatient setting with several days of hospitalization. Additionally, high hospital bed occupancy during the COVID-19 pandemic prevented timely admission for TAP. An Advanced Practice Nurse (APN)-led ambulatory TAP service was introduced at our center, with the aim of improving access to TAP and reducing hospital bed occupancy. Methods: A multidisciplinary team developed workflows and safety guidelines for TAP to enable right-siting of pts in a cancer day care unit. Pts were scheduled for radiologically guided insertion of abdominal drains in the morning before 10am to allow adequate time for drainage. Pre-procedure clinical examination and safety checks were performed by APNs in the day unit. Following the procedure, abdominal fluid was drained with concurrent administration of 20% IV albumin. Drains were removed by the APN and pts were examined before discharge on the same day. Data for all cancer pts requiring TAP in the day unit and hospital from 1 Jan to 30 Nov 2020 were extracted from the electronic medical record system. The primary outcome was length-of-stay (LOS). The primary safety outcome was adverse events in the day unit. Continuous data were compared using the t-test. Data analysis was done in SPSS version 22. Results: The number of TAPs performed in the day unit and general ward requiring hospitalization were 102 and 133, respectively. There was a significant reduction in average LOS with TAPs performed in the day unit vs. hospitalization (1.48 vs. 5.82 days, p<0.001) (Table). The mean difference was 4.34 (95% confidence interval 3.33 - 5.34) days saved per pt, or a saving of 443 inpatient bed days. The TAP day unit service encountered 10 adverse events (AEs) requiring admission to the ward for continued drainage. AEs were borderline baseline blood pressure, pt frailty and inability to care for an indwelling catheter. There were no infective or bleeding complications. The majority of TAPs (86.8%) were performed in one day, with the remainder over 2-days with the abdominal drain left in-situ and reattendance at the day unit the next day for further drainage. Differences in average length-of-stay with TAP in the hospital vs. day unit. Conclusions: An APN-led ambulatory abdominal paracentesis service is a safe alternative to inpatient paracentesis. Optimal utilization of a day unit enabled reduced LOS for pts with advanced cancer. This reduction in LOS was critical during a pandemic where bed demand was high. This was possible from advanced scheduling and control over the day unit capacity.[Table: see text]

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 Better care: reducing length of stay and bed occupancy on an older adult psychiatric ward

2018 ◽  
Vol 7 (4) ◽  
pp. e000149 ◽  
Author(s):  
Katherine Adlington ◽  
Juliette Brown ◽  
Laura Ralph ◽  
Alan Clarke ◽  
Tim Bhoyroo ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Length Of Stay ◽  
Older Adult ◽  
Average Length ◽  
Psychiatric Ward ◽  
Bed Occupancy ◽  
Care Needs ◽  
Bed Days ◽  
Community Team ◽  
The Impact

BackgroundLength of stay and bed occupancy are important indicators of quality of care. Admissions are longer on older adult psychiatric wards as a result of physical comorbidity and complex care needs. The recommended bed occupancy is 85%; levels of 95% or higher are associated with violent incidents on inpatient wards.MethodsWe aimed to reduce length of stay and bed occupancy on Leadenhall ward, a functional older adult psychiatric ward serving a population of just under 40 000 older adults in two of the most deprived areas of the UK.At baseline in October 2015, the average length of stay was 47 days, and bed occupancy was at 77%. We approached the problem using quality improvement methods, established a project team and proceeded to test a number of changes over time in line with the driver diagram we produced.ResultsIn 12 months, length of stay was reduced from an average 47 to an average 30 days and bed occupancy from 77% to 54%.At the end of 2016, the closure of some beds effected this calculation and we added an additional outcome measure of occupied bed days (OBD) better to assess the impact of the work. OBD data show a decrease over the course of the project from 251 to 194 bed days (a reduction of 23%).ConclusionThe most effective interventions to address length of stay and bed occupancy on an older adult functional mental health ward were the daily management round and the high-level management focus on longer-stay patients. The work depended on an effective community team and on the support of the quality improvement programme in the trust, which have led to sustained improvements.

scholarly journals SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN RUMAH SAKIT DENGAN PELAYANAN RAWAT INAP TERBAIK

2020 ◽  
Vol 6 (4) ◽  
pp. 55-62
Author(s):  
Chintya Puspa Dewi ◽  
Mustika Mentari
Keyword(s):  
Length Of Stay ◽  
Average Length ◽  
Ideal Solution ◽  
Bed Occupancy ◽  
Average Length Of Stay ◽  
Order Preference ◽  
Simple Additive Weighting ◽  
Topsis Technique ◽  
Turn Over

Rumah sakit adalah tempat pelayanan kesehatan yang pasti sangat diperlukan oleh masyarakat.Pelayanan tersebut dilihat dari efisiensi, sarana dan prasarana yang memadai, dan faktor lainnya. Efisiensi pelayanan rawat inap juga termasuk hal yang penting bagi pasien, khususnya yang harus dirawat di rumah sakit. Pihak rumah sakit melakukan sensus harian untuk meninjau dan meningkatkan kualitas pelayanan rawat inap. Kriteria pelayanan rawat inap adalah BOR (Bed Occupancy Ratio), BTO (Bed Turn Over), TOI (Turn Over Interval), dan AVLOS (Average Length of Stay). Untuk kemudahan dalam memilih, maka dibutuhkan sistem pendukung keputusan sebagai alat. Rumah sakit yang akan dijadikan pilihan oleh peneliti adalah rumah sakit yang ada di wilayah Kota Batu. Metode yang digunakan adalah gabungan SAW (Simple Additive Weighting) dan TOPSIS (Technique For Order Preference By Similiarity To Ideal Solution). Metode ini dipilih karena menggunakan persamaan matematis yang lebih sederhana untuk mendapatkan solusi terbaik. Hasil pengujian dapat digunakan untuk membantu masyarakat dalam pemilihan rumah sakit.

scholarly journals The efficient of beds used based on graphic Barber Johnson at Semen Padang Hospital in 2017

2019 ◽  
Vol 6 (12) ◽  
pp. 5071
Author(s):  
Sayati Mandia
Keyword(s):  
Statistical Analysis ◽  
Length Of Stay ◽  
Medical Record ◽  
Medical Records ◽  
Average Length ◽  
Sampling Technique ◽  
Occupancy Rate ◽  
Bed Occupancy ◽  
Average Length Of Stay

Background: Quality of hospital services can be seen from the bed usage. Statistical analysis of efficiency bed usage can be mesured based on inpatient medical records. To determine the efficiency requires four parameters namely bed occupancy rate (BOR), average length of stay (ALoS), turnover interval (TI), and bed turnover (BTR). parameters can be presented using Graphic Barber Johnson. This study aims to determine the efficiency of bed usage at Semen Padang Hospital in 2017.Methods: This research was conducted at Semen Padang Hospital, West Sumatera, Indonesia from January to December 2017. The study used a descriptive method with a qualitative approach. The data was collected from medical records department. The population is all abstraction data of in-patient medical record in 2017, 9796 medical record used total sampling technique. Data analysis was performed by calculating the values of ALoS, BOR, BTR, and TI. Data will be presented based on graphic Barber Johnson. Excel 2010 and graphic Barber Johnson method were applied for data analysis.Results: Number of daily inpatient censuses in 2017 are 31227 and number of service days are 31362. Number of beds 144. Statistical analysis results obtained total BOR 60%, BTR 67 times, TI 2 days and ALoS 3 days. The highest value of bed occupancy rate is 66% on August.Conclusions: Based on statistical, value of bed occupancy rate (60%) and turnover interval (2 days) are efficient at Semen Padang Hospital in 2017. Average length of stay (3 days) and bed turnover rate (67 times) are not efficient.

scholarly journals Length of stay following percutaneous left atrial appendage occlusion: Data from the prospective, multicenter Amplatzer Amulet Occluder Observational Study

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0255721
Author(s):  
Kerstin Piayda ◽  
Shazia Afzal ◽  
Jens Erik Nielsen-Kudsk ◽  
Boris Schmidt ◽  
Patrizio Mazzone ◽  
...  
Keyword(s):  
Length Of Stay ◽  
Adverse Events ◽  
Observational Study ◽  
Hospital Stay ◽  
Left Atrial ◽  
Left Atrial Appendage ◽  
Atrial Appendage ◽  
Bleeding Complications ◽  
Serious Adverse Events ◽  
Left Atrial Appendage Occlusion

Aims To evaluate factors influencing the length of stay in patients undergoing percutaneous left atrial appendage occlusion (LAAO). Methods and results Patient characteristics, procedural data and the occurrence of serious adverse events were analyzed from the AmplatzerTM AmuletTM Occluder Observational Study. Patients were divided into three groups: same day (S, 0day, n = 60, 5.6%) early (E, 1day, n = 526, 48.9%), regular (R, 2-3days, n = 338, 31.4%) and late (L, ≥4days, n = 152, 14.1%) discharge and followed up for 60 days. Procedure and device related SAE during the in-hospital stay (S: 0.0% vs. E: 1.0% vs. R: 2.1% vs. L: 23%, p<0.0001) were a major trigger for a prolonged in-hospital stay. Of the 37 subjects in the late discharge group with an SAE prior to discharge, cardiac or bleeding complications were the most common underlying conditions, occurring in 26 subjects. Multinomial logistic analysis only identified HAS-BLED score as an independent influencing factor (p = 0.04) for a late discharge. After 60 days, mortality tended to be greatest in the late discharge group (S: 0.0% vs. E: 1.0% vs. R: 1.2% vs. L: 3.3%, p = 0.1066). Conclusion Over half of the subjects receiving an Amplatzer Amulet occluder were discharged within 1 day of the implant procedure. Serious adverse events were a major trigger for a late discharge after LAAO. Increased HAS-BLED score was associated with a prolonged in-hospital stay.

scholarly journals ANALISIS KINERJA KEUANGAN DAN NON KEUANGAN RUMAH SAKIT SEBELUM DAN SESUDAH BADAN LAYANAN UMUM DAERAH

ProBank ◽  
2017 ◽  
Vol 2 (2) ◽  
pp. 25-35
Author(s):  
Khairana Amalia Chrishartoyo ◽  
Sri Rahayu ◽  
Djusnimar Zutilisna
Keyword(s):  
Length Of Stay ◽  
Death Rate ◽  
Average Length ◽  
T Test ◽  
Occupancy Rate ◽  
Bed Occupancy ◽  
Paired Sample ◽  
Average Length Of Stay ◽  
Turn Over

Diterbitkannya Peraturan Menteri Dalam Negeri Nomor 61 Tahun 2007 tentang Pedoman teknis Pola Pengelolaan Keuangan Badan Layanan Umum Daerah mengharuskan Pemerintah Daerah menganut PPK - BLUD dalam manajemen Rumah Sakit dalam rangka meningkatkan pelayanan kesehatan bagi masyarakat. Penelitian ini bertujuan untuk melihat perbedaan kinerja keuangan dan non keuangan RSUD Dr Moewardi sebelum dan sesudah berstatus BLUD. Kinerja keuangan diukur dengan rasio likuiditas, rasio aktivitas, rasio profitabilitas, dan rasio struktur modal. Sedangkan kinerja non keuangan diukur dengan rasio efisiensi pelayanan yaitu Bed Occupancy Rate, Bed Turn Over, Turn Over Interval, Average Length Of Stay, Gross Death Rate dan Net Death Rate. Teknik analisis yang digunakan adalah Paired Sample T Test. Hasil uji statistik menunjukkan tiga dari empat kelompok rasio keuangan yang diuji memiliki nilai Asymp. Sig. (2-tailed) kurang dari 0,05 sehingga dapat disimpulkan terdapat perbedaan signifikan pada kinerja keuangan RSUD Dr Moewardi sebelum dan sesudah BLUD, sedangkan pada rasio efiseiensi pelayanan hanya dua dari enam rasio yang memiliki nilai Asymp. Sig. (2-tailed) kurang dari 0,05 sehingga dapat disimpulkan tidak terdapat perbedaan signifikan pada kinerja efisiensi pelayananRSUD Dr Moewardi sebelum dan sesudah BLUD.Kata kunci :BLUD, kinerja keuangan, kinerja efisiensi pelayanan, rasio keuangan

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

2020 ◽  
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

BackgroundThe 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.MethodsTwo 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.FindingsLOS ≥ 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.InterpretationDischarges 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.FundingSupport 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 Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Quentin J. Leclerc ◽  
Naomi M. Fuller ◽  
Ruth H. Keogh ◽  
Karla Diaz-Ordaz ◽  
Richard Sekula ◽  
...  
Keyword(s):  
Length Of Stay ◽  
Clinical Care ◽  
Clinical Information ◽  
Public Health Research ◽  
General Ward ◽  
Bed Occupancy ◽  
College Hospital ◽  
Time Model ◽  
Hospitalised Patients ◽  
Hospital Bed

Abstract Background Predicting bed occupancy for hospitalised patients with COVID-19 requires understanding of length of stay (LoS) in particular bed types. LoS can vary depending on the patient’s “bed pathway” - the sequence of transfers of individual patients between bed types during a hospital stay. In this study, we characterise these pathways, and their impact on predicted hospital bed occupancy. Methods We obtained data from University College Hospital (UCH) and the ISARIC4C COVID-19 Clinical Information Network (CO-CIN) on hospitalised patients with COVID-19 who required care in general ward or critical care (CC) beds to determine possible bed pathways and LoS. We developed a discrete-time model to examine the implications of using either bed pathways or only average LoS by bed type to forecast bed occupancy. We compared model-predicted bed occupancy to publicly available bed occupancy data on COVID-19 in England between March and August 2020. Results In both the UCH and CO-CIN datasets, 82% of hospitalised patients with COVID-19 only received care in general ward beds. We identified four other bed pathways, present in both datasets: “Ward, CC, Ward”, “Ward, CC”, “CC” and “CC, Ward”. Mean LoS varied by bed type, pathway, and dataset, between 1.78 and 13.53 days. For UCH, we found that using bed pathways improved the accuracy of bed occupancy predictions, while only using an average LoS for each bed type underestimated true bed occupancy. However, using the CO-CIN LoS dataset we were not able to replicate past data on bed occupancy in England, suggesting regional LoS heterogeneities. Conclusions We identified five bed pathways, with substantial variation in LoS by bed type, pathway, and geography. This might be caused by local differences in patient characteristics, clinical care strategies, or resource availability, and suggests that national LoS averages may not be appropriate for local forecasts of bed occupancy for COVID-19. Trial registration The ISARIC WHO CCP-UK study ISRCTN66726260 was retrospectively registered on 21/04/2020 and designated an Urgent Public Health Research Study by NIHR.

scholarly journals National University Hospital discharge survey in the Islamic Republic of Iran

2000 ◽  
Vol 6 (2-3) ◽  
pp. 402-408
Author(s):  
S. M. Reza Khatami ◽  
S. K. Kamrava ◽  
B. Ghatehbaghi ◽  
M. Mirzazadeh
Keyword(s):  
Health Care ◽  
Length Of Stay ◽  
Hospital Discharge ◽  
Average Length ◽  
Health Care Service ◽  
Health Care Facilities ◽  
University Hospital ◽  
Occupancy Rate ◽  
Bed Occupancy ◽  
Average Length Of Stay

We aimed to determine the rate of hospital discharge, average length of stay and bed occupancy rate in different hospital wards around the country. The survey consisted of health care service activities from 452 university-related hospitals in the country with a total of 59 348 beds. Because of missing data, the use of 56 315 of these beds was analysed. The countrywide discharge rate was 68.32 patients/1000 population per year with an average length of stay of 3.60 days and a bed occupancy rate of 57.44%. The data could be used to design a framework for prediction of inpatient health care facilities needed in the future

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