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 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 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 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 PENGARUH KELENGKAPAN PENGISIAN FORMULIR TRANSFER PASIEN INTERNAL TERHADAP MUTU REKAM MEDIS

2021 ◽  
Vol 10 (2) ◽  
pp. 124-131
Author(s):  
Indar Farwanti Wahyuni
Keyword(s):  
Medical Record ◽  
Medical Records ◽  
Random Sampling ◽  
Health Workers ◽  
Sampling Technique ◽  
Simple Random Sampling ◽  
Patient Transfer ◽  
Literature Study ◽  
Number Of Patients

Abstract Internal patient transfer is the process of transferring patients from one room to another in a hospital while still being oriented towards quality and patient safety. The results of the observations showed that the filling of the internal patient transfer form was not optimal so that there were still incomplete forms due to the large number of patients and the weak coordination between health workers. To determine the effect of the completeness of filling out the internal patient transfer form on the quality of medical records. The research method used is quantitative with a descriptive approach. Data collection techniques used are observation, questionnaires and literature study. The sampling technique was simple random sampling technique so as to obtain a sample of 91 internal patient transfer forms. From the results of observations, 22% of the internal patient transfer forms were found that were not completely filled in, especially in the signature and clear name. The two variables have a strong relationship. The effect of the variable completeness of the internal patient transfer form on the medical record quality variable is 90.1% and the remaining 9.9% is influenced by other factors. Based on these studies, it can be concluded that the lack of accuracy and coordination of nurses, doctors and other officers in filling out internal patient transfer forms so that this affects the quality of medical records in the aspect of accuracy. Keyword : Completeness, Internal Patient Transfer Form, Medical Record Quality   Abstrak Transfer pasien internal merupakan proses pemindahan pasien dari satu ruangan ke ruangan yang lain di dalam satu rumah sakit dengan tetap berorientasi pada mutu dan keselamatan pasien. Hasil observasi menunjukkan bahwa belum optimalnya pengisian formulir transfer pasien internal sehingga masih terdapat formulir yang tidak lengkap disebabkan oleh faktor dari banyaknya pasien dan lemahnya koordinasi antara tenaga kesehatan. Untuk mengetahui pengaruh kelengkapan pengisian formulir transfer pasien internal terhadap mutu rekam medis. Metode penelitian yang digunakan yaitu kuantitatif dengan pendekatan deskriptif. Teknik pengumpulan data yang digunakan adalah observasi, kuesioner dan studi pustaka. Teknik pengambilan sampel adalah teknik simple random sampling sehingga memperoleh sampel sebanyak  91 formulir transfer pasien internal. Dari hasil observasi ditemukannya formulir transfer pasien internal yang belum terisi lengkap sebanyak 22% terutama pada tandatangan dan nama jelas. Kedua variabel memiliki hubungan yang kuat. Pengaruh variabel kelengkapan formulir transfer pasien internal terhadap variabel mutu rekam  medis sebesar 90,1% dan sisanya 9,9% dipengaruhi oleh faktor lain. Berdasarkan penelitian tersebut dapat disimpulkan bahwa kurangnya ketelitian dan koordinasi perawat, dokter dan petugas lain dalam pengisian formulir transfer pasien internal sehingga hal ini mempengaruhi mutu rekam medis pada aspek keakuratan. Kata kunci: Kelengkapan, Formulir Transfer Pasien Internal, Mutu Rekam Medis

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