scholarly journals Implementation of Electronic Patient Discharge: A Successful Strategy to Increase Hospital Bed Capacity During the COVID-19 Pandemic

2021 ◽  
Keyword(s):  
Six Sigma ◽  
Patient Discharge ◽  
Management Tool ◽  
Discharge Process ◽  
Care Hospital ◽  
Discharge Time ◽  
Post Intervention ◽  
Hospital Bed Capacity ◽  
Hospital Bed ◽  
Bed Capacity

Background: The ongoing COVID-19 pandemic increased the need for inpatient beds, indicating the need for hospitals to increase the efficiency of beds. Objectives: This study aimed to increase hospital bed capacity using the implementation of Electronic Patient Discharge (EPD). Methods: This qualitative-quantitative study was conducted in a tertiary care hospital using the pre-and post-intervention designs, and the main outcome was patient discharge time. By applying the Six Sigma model, including definition, measurement, analysis, improvement, and control, the patient discharge process was assessed and improved by some interventions such as EPD. All hospitalized patients with COVID-19 from 21 March 2020 to 22 July 2021 were examined for the post-intervention. In addition, data were collected from the hospital information system (HIS). Results: By the use of EPD, patient discharge time decreased to 47.70% (from 10.19 h to 5.33 h) (P < 0.000). According to the Sigma level, the yield and defects per million opportunities of the discharge process also increased to 55%. Conclusion: Six Sigma methodology can be an effective change management tool to improve discharge time to cover the demand created during pandemics. According to the results of the present study and the obtained saved time, one bed is added to the hospital capacity for every five discharges.

scholarly journals Strengthening Hospital Capacity for the COVID-19 Pandemic: Implementation of Electronic Patient Discharge

2021 ◽  
Vol 11 (5) ◽  
pp. 305-312
Author(s):  
Mohaddeseh Sabethosseini Dokht ◽  
◽  
Mehdi Yousefi ◽  
Hamid Hedarian Miri ◽  
Somayeh Fazaeli ◽  
...  
Keyword(s):  
Six Sigma ◽  
Sigma Model ◽  
Low Cost ◽  
Patient Discharge ◽  
Discharge Process ◽  
Discharge Time ◽  
Post Intervention ◽  
Hospital Capacity ◽  
Sigma Level ◽  
And Control

Background: Increasing hospital capacity to cover the service demands is an important priority during an epidemic or a pandemic. The aim of this study was to increase hospital capacity using the Six Sigma method to improve the patient discharge process. Methods: This was a quantitative study. The Pre- and post-intervention study was conducted in a big hospital designated for COVID-19 patients. The patient discharge process was evaluated and improved based on seven sub-processes and following the Six Sigma model, including defining the problem, measuring time in each of the discharge stations, analysis times and process, improvement process, and control. Results: Implementation of the electronic patient discharge led to a 51.9% decrease in discharge time from 7.3  h during the pre-intervention period to 3.8 h post-intervention (P< 0.0001). According to the Sigma level, the yield and defects per million opportunities of the discharge process also improved to 55%. Conclusion: Increasing hospital capacity by improving the discharge time is a quick action to cover the demand created during pandemics. Also, about 32 beds can be obtained by applying the Six Sigma model to improve the discharge process in a short time and at a very low cost.

scholarly journals Implementation of Six Sigma Method To Improve Hospital Discharge Process: A Before-And- After Study With The Control Group In A Large Hospital

2021 ◽  
Author(s):  
Somayeh Fazaeli ◽  
Mehdi Yousefi ◽  
Mohadeseh Sabethoseini Dokht ◽  
Hamidreza Heidarian
Keyword(s):  
Hospital Discharge ◽  
Waiting Time ◽  
Six Sigma ◽  
Management Tool ◽  
Control Group ◽  
Discharge Process ◽  
Control Groups ◽  
Discharge Time ◽  
Post Intervention ◽  
And Control

Abstract Background: Delayed hospital discharge is a complex process that can impact hospital and service delivery capacity. The improvement of this process requires structural reforms and coordination with different wards, individuals, and the hospital.The present study aimed to use the Six Sigma method to reduce hospital discharge time. Methods: This pre-post study was conducted based on an experimental design from 2016 to 2020. A series of Six Sigma-driven interventions based on the Define-Measure-Analyze-Improve-Control (DMAIC) cycle was employed in a 1,000 bed tertiary care hospital to decrease discharge waiting time. Two wards in the hospital were allocated to the intervention and control groups. Three months of pre-intervention data were compared with 16 months of post-intervention in each group. The data were analyzed in Stata software (version 14.1). The level of statistical significance was set at 0.000.Results: There was a significant difference (P<0.000) between pre and post-intervention, as well as experimental and control groups. The discharge time points in the intervention and control groups before the intervention were reported as 438 and 411 min, respectively. After the intervention, the discharge time reached 246 min (3.20 h decrease) in the intervention group (P<0.000) and 475 min in the control group (P<0.574). The waiting time in stations 2, 3, and 4 reached zero after the intervention(P<0.000). The trend of discharge time after the intervention from October 2017 to March 2020 demonstrated that the changes were stable (184±25.56 min).Conclusions: As evidenced by the obtained results, the Six Sigma methodology can be an effective change management tool for the improvement of discharge time. The findings suggested that the use of electronic discharge and focusing on physician readiness for writing a discharge order would have the greatest impact.

Capacity Audit Tool: identifying inpatient delays to maximise service improvement

2010 ◽  
Vol 34 (4) ◽  
pp. 395 ◽  
Author(s):  
Kathryn M. Zeitz ◽  
Katie Tucker
Keyword(s):  
Acute Care ◽  
Compliance Rate ◽  
Tertiary Hospital ◽  
Service Improvement ◽  
Care Hospital ◽  
Audit Tool ◽  
Audit Process ◽  
Hospital Bed ◽  
Improvement Strategies ◽  
Bed Capacity

Objective. This case study describes the development of a process and tool, the ‘Capacity Audit’, to quantify key inpatient delays in an acute care tertiary hospital setting. Method. The Capacity Audit Tool is an adaption of an existing Wasted Capacity Audit Tool supported by a systematic process to assess and quantify the status of patients in a cohort of inpatient beds. This paper reports on the application of the tool for all inpatient beds in an acute tertiary hospital assessed twice a day for a 15-day period. Results. In total, 820 surveys were completed. This represents 9126 beds assessed in the morning shift and 9261 in the afternoon shift over the 15-day period. The simplicity of the Capacity Audit Tool and the process to collect data resulted in a 95% compliance rate. The audit revealed that 76% of beds audited were being used appropriately for acute care. The top three delays were patients awaiting a post-acute care, the bed being empty and awaiting a patient to be allocated, and patients awaiting discharge transport. Conclusions. The Capacity Audit Tool facilitates a high level of compliance, providing a comprehensive understanding of the use of hospital bed stock and bed capacity. In addition, the process reveals key inpatient delays to target critical improvement strategies. What is known about the topic? There is only one known tool available to assess acute care hospital bed capacity. The Institute of Health Care Improvement describes a wasted capacity audit tool but there are minimal supporting materials to facilitate application of this tool more broadly. What does this paper add? This paper describes the application of an audit process, ‘Capacity Audit’, that can assist hospitals to measure bed capacity and reveal the key inpatient delays to bed turnover. What are the implications for practitioners? The application of the Capacity Audit process enables practitioners to systematically assess key inpatient delays, reveal wasted capacity in bed usage and target improvement strategies in an evidenced versus anecdotal way.

Managing Hospital Bed Capacity Through Partitioning Care into Focused Wings

2012 ◽  
Author(s):  
Thomas J Best ◽  
Burhaneddin Sandikci ◽  
Donald D. Eisenstein ◽  
David Owen Meltzer
Keyword(s):  
Hospital Bed Capacity ◽  
Hospital Bed ◽  
Bed Capacity

A network flow approach to optimizing hospital bed capacity decisions

2006 ◽  
Vol 9 (4) ◽  
pp. 391-404 ◽  
Author(s):  
Elif Akcali ◽  
Murray J Côté ◽  
Chin Lin
Keyword(s):  
Network Flow ◽  
Hospital Bed Capacity ◽  
Capacity Decisions ◽  
Hospital Bed ◽  
Bed Capacity

Successful Hospital Evacuation After the Kumamoto Earthquakes, Japan, 2016

2017 ◽  
Vol 11 (5) ◽  
pp. 517-521 ◽  
Author(s):  
Takashi Nagata ◽  
Shinkichi Himeno ◽  
Akihiro Himeno ◽  
Manabu Hasegawa ◽  
Alan Kawarai Lefor ◽  
...  
Keyword(s):  
Public Health ◽  
Adverse Events ◽  
Natural Disaster ◽  
Disaster Response ◽  
Timely Manner ◽  
Public Health Preparedness ◽  
Hospital Bed Capacity ◽  
Hospital Bed ◽  
The Future ◽  
Bed Capacity

AbstractTwo major earthquakes struck Kumamoto Prefecture in Japan in April 2016. Disaster response was immediately provided, including disaster medical services. Many hospitals were damaged and patients needed immediate evacuation to alternative facilities. The hospital bed capacity of Kumamoto Prefecture was overwhelmed, and transportation of more than 100 patients was needed. Hospital evacuation was carried out smoothly with the coordinated efforts of multiple agencies. The overall operation was deemed a success because patients were transported in a timely manner without any significant adverse events. Upon repair of facilities in Kumamoto Prefecture, patients were returned safely to their previous facilities. The management of inpatients after this natural disaster in Kumamoto Prefecture can serve as a model for hospital evacuation with multi-agency coordination in the future. Future efforts are needed to improve interfacility communications immediately following a natural disaster. (Disaster Med Public Health Preparedness. 2017;11:517–521)

scholarly journals EVALUATING THE USE OF HOSPITAL BED CAPACITY IN MEDICAL ORGANIZATIONS

2018 ◽  
Vol 10 (4) ◽  
pp. 37-43
Author(s):  
I. A. Zheleznyakova ◽  
L. A. Kovaleva ◽  
T. A. Khelisupali ◽  
M. A. Voinov ◽  
V. V. Omel’yanovskii
Keyword(s):  
Hospital Bed Capacity ◽  
Hospital Bed ◽  
Bed Capacity
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