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Reduction in Average Length-of-Stay in Emergency Department of a Low-Income Country's Cancer Hospital.
INTRODUCTION: Prolonged length of stay (LOS) in emergency departments (ED) is a widespread problem in every hospital around the globe. Multiple factors cause it and can have a negative impact on the quality of care provided to the patients and the patient satisfaction rates. This project aimed to ensure that the average LOS of patients in a tertiary care cancer hospital stays below 3 hours.
MATERIALS AND METHODS: The Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control) approach was followed.
RESULTS: The average LOS was 166 minutes before implementing interventions. The two primary reasons for the increased length of stay were delays secondary to physician assessment and diagnostic lab reports. Strategies were defined to control these factors, which helped reduce the average length of stay to 142 minutes, a 30% reduction.
CONCLUSION: A process improvement model similar to this project is recommended to enhance the quality of hospital services. It will provide valuable insights into the process flow and assist in gathering precise data on the various steps involved. The data collected can then be analyzed to identify potential causes and make informed decisions that can significantly improve hospital processes.
MATERIALS AND METHODS: The Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control) approach was followed.
RESULTS: The average LOS was 166 minutes before implementing interventions. The two primary reasons for the increased length of stay were delays secondary to physician assessment and diagnostic lab reports. Strategies were defined to control these factors, which helped reduce the average length of stay to 142 minutes, a 30% reduction.
CONCLUSION: A process improvement model similar to this project is recommended to enhance the quality of hospital services. It will provide valuable insights into the process flow and assist in gathering precise data on the various steps involved. The data collected can then be analyzed to identify potential causes and make informed decisions that can significantly improve hospital processes.
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