scholarly journals Visualization of Amsterdam Airbnb Business Performance using Customer Reviews

2021 ◽  
Vol 5 (2) ◽  
pp. 142-152
Author(s):  
Irwan Setiawan ◽  
◽  
Fitri Diani ◽  
Keyword(s):  
Length Of Stay ◽  
Business Performance ◽  
Average Length ◽  
Annual Income ◽  
Occupancy Rate ◽  
Customer Reviews ◽  
Average Length Of Stay ◽  
Average Occupancy

This article focuses on Airbnb that was one of the most popular sharing models in Economics. This study investigates the Airbnb business performance using customer reviews to calculate the monthly occupancy rate and a yearly income of Airbnb hosts in Amsterdam between 2015 and 2019. This study uses modest and optimistic estimates for the review rate with 0.6 percent and 0.4 percent, respectively, and 3.9 for the average length of stay in Amsterdam. Findings reveal that the visitors increase from May to June, then again in September and October. The monthly occupancy rate of the super host has a higher occupancy rate rather than the regular host at every district. The yearly income of the super hosts in Centrum-West and Centrum-Oost was higher than in other districts, while annual income was most deficient in Gaasperdam - Driemond. In term of average occupancy and number of maximum people per accommodation, accommodations which accommodate more than eleven people have more occupancy rate than others. Customer reviews can be used to calculate the monthly occupancy rate and a yearly income of Airbnb hosts.

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 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 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

scholarly journals Penilaian Tingkat Efisiensi Pengelolaan Rumah Sakit Denganaplikasi Grafik Barber-Johnson Di Rumah Sakit Usada Sidoarjo

2015 ◽  
Vol 1 (1) ◽  
pp. 74
Author(s):  
Dyan Angesti
Keyword(s):  
Length Of Stay ◽  
Average Length ◽  
Visual Basic ◽  
Occupancy Rate ◽  
Bed Occupancy ◽  
Average Length Of Stay ◽  
Turn Over ◽  
Visual Basic 6.0

ABSTRAKUpaya pemberian pelayanan terbaik kepada customer oleh pihak manajemen rumah sakit tidak dapat dipungkiri apabila membutuhkan cost yang tidak sedikit. Langkah ataupun kebijakan yang akan diambil pihak manajemen haruslah merupakan langkah yang bijak. Disinilah informasi yang dihasilkan oleh unit rekam medis memegang peranan penting. Informasi yang berkualitas menjadi bermanfaat bagi pengambil keputusan baik keperluan internal maupun eksternal rumah sakit tersebut. Penelitian ini dilakukan pada bulan Maret sampai dengan Juli 2010 bertempat di Rumah Sakit Usada Sidoarjo.Variabel pada penelitian ini adalah Bed Occupancy Rate (BOR), Bed Turn Over (BTO), Average Length of Stay (AvLOS), Turn Over Interval (TOI). Penelitian ini merupakan penelitian pengembangan dengan tujuan mengembangkan laporan rumah sakit menjadi sebuah grafik Barber Johnson menggunakan Microsoft Visual Basic 6.0 sehingga dapat dipergunakan sebagai alat bantu pengambilan keputusan bagi pihak manajemen.

The Health Sector Evolution Plan and the Technical Efficiency of Public Hospitals in IranBackground: Iranian public hospitals have been excessively changing during the healthcare reform since 2014. This study aimed to examine the technical efficiency of p

2020 ◽  
Author(s):  
Edris KAKEMAM ◽  
Hossein DARGAHI
Keyword(s):  
Length Of Stay ◽  
Technical Efficiency ◽  
Healthcare Reform ◽  
Average Length ◽  
Health Sector ◽  
Public Hospitals ◽  
Occupancy Rate ◽  
Bed Occupancy ◽  
Tobit Regression ◽  
Average Length Of Stay

Background: Iranian public hospitals have been excessively changing during the healthcare reform since 2014. This study aimed to examine the technical efficiency of public hospitals during before and after the implementation of Health Sector Evolution Plan (HSEP) and to determine whether, and how, efficiency is affected by various factors. Methods: Forty-two public hospitals were selected in Tehran, Iran, from 2012 to 2016. Data envelopment analysis was employed to estimate the technical and scale efficiency sample hospitals. Tobit regression was used to relate the technical efficiency scores to seven explanatory variables in 2016, the last year. Results: Overall, 24 (57.1%), 26 (61.9%), 26 (61.9%), 24 (57.1%) and 21 (50%) of the 42 sample hospitals ran inefficiently in 2012 to 2016, with average technical efficiency of 0.859, 0.836, 0.845, 0.905 and 0.934, respectively. The average pure technical efficiency in sample hospitals increased from 0.860 in 2010 (before the HSEP) to 0.944 in 2012 (after the HSEP). Tobit regression showed that average length of stay had a negative impact on technical efficiency of hospitals. In addition, bed occupancy rate, ratio of beds to nurses and ratio of nurses to physicians assumed a positive sign with technical efficiency. Conclusion: Despite government support, public hospitals operated relatively inefficien. Managers can enhance technical efficiency by increasing bed occupancy rate through shortening the average length of stay, proportioning the number of doctors, nurses, and beds along with service quality assurance.

scholarly journals Percent Bed occupancy rate in a selected specialized tertiary care hospital in Dhaka city

1970 ◽  
Vol 11 (1) ◽  
pp. 18-24 ◽  
Author(s):  
H Rahman ◽  
SME Haque ◽  
MA Hafiz
Keyword(s):  
Length Of Stay ◽  
Tertiary Care Hospital ◽  
Average Length ◽  
Tertiary Care ◽  
Calculated Data ◽  
Care Hospital ◽  
Dhaka City ◽  
Occupancy Rate ◽  
Bed Occupancy ◽  
Average Length Of Stay

Background and Aims: Providing a necessary care for a sick person outside home 'in hospes or hospital' dates back to nearly 300 century BC. In the present day hospital care facilities has been taken an institutional shape both in public and private sector. A hospital bed is both a scarce and expensive commodity in healthcare. Administrators running hospitals are in a dire need of objective measures and methods for efficient management of their limited financial resources. Bed utilization rates can be of immense help in realistic and effective decision making. The present study was undertaken to explore utilization of bed in a specialized tertiary care hospital in the Dhaka city. Methods: Hospital records of the year were reviewed- age, gender, disease profile, duration of hospital stay, outcome of treatment were recorded and bed occupancy rate was calculated. Data were presented as number, percentage and/ or mean SD, as appropriate. The dada were managed by Statistical Package for Social Science (SPSS) for Windows Version 10. Results: The results showed in the year 2001 total number of admissions were 13,305 of which 9953 (74.8%) were male and 3352 (25.2%) female. Average monthly admission was 1109. Maximum number of admissions (1304) was observed in the month of September of that year. Male admission rate was higher than female admission throughout the year. Among all the admission 27.2% were of road traffic accident cases. Among the admitted patients there was 57.3% discharge with advice, 1.9% death, 14.6% discharge on request bond, 12.7% discharge on request. Of all the admission there 12.5% found to be absconded. Bed occupancy rate was 79.75% and average length of stay in the hospital 18.47 days. Conclusions: The present data suggest that (i) in terms of bed occupancy rate the NITOR found to run in optimal capacity which, however, might be attributed to the relative high rate of ascendance and discharges on requests; (ii) average length of stay of patients appeared to be relatively longer and (iii) the management need to look into the issue and take appropriate measures to reduce patients unwanted long duration of stay and make the tertiary care hospital improve the quality of services. DOI: http://dx.doi.org/10.3329/bjms.v11i1.9817 BJMS 2012; 11(1): 18-24

scholarly journals Analysis of statistic health care as indicators of efficiency service in Semen Padang Hospital through Barber Johnson graph

2020 ◽  
Vol 7 (2) ◽  
pp. 427
Author(s):  
Nurhasanah Nasution
Keyword(s):  
Length Of Stay ◽  
Turnover Rate ◽  
Statistical Data ◽  
Average Length ◽  
Level Of Service ◽  
Occupancy Rate ◽  
Bed Occupancy ◽  
Johnson Graph ◽  
Average Length Of Stay ◽  
Service Efficiency

Background: The efficiency of service delivery is very important for hospitals. One measurement of service indicators that can be used is the Barber Johnson graph (GBJ). GBJ is needed to see and measure the level of service efficiency in hospitals. The indicators used are bed occupancy rate (BOR), bed turnover rate (BTR), turnover interval (TI), and length of stay (LOS). This graph can also be used to compare or view hospital developments at different times, and to increase the likelihood of changes in one variable by changing other variables. This research was conducted at Semen Padang Hospital (SPH), Padang, West Sumatera, Indonesia.Methods: The purpose of this study was to determine the statistical value of hospital and hospital service efficiency levels by using the Barber Johnson graphic. This research method is descriptive by direct observation of the medical record file of inpatients since the January to December 2017 period.Results: Statistical data obtained from SPH in 2018 showed the value of service days 30132, and the Number of beds 144 units. From the data processing results obtained a total bed occupancy rate 60.83%, bed turnover rate 6.86 times, turnover interval 2 days and average length of stay 3 days.Conclusions: Statistical data obtained from SPH in 2018 shows the value of BOR, TI is in an efficient, while BTR and LOS are inefficient.

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).

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