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Wayne State University Wayne State University Dissertations January 2022Acute Coronary Syndrome Prediction: A DataDriven Machine Learning Modeling Approach In Emergency Care Joshua Oluwatobiloba Emakhu
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01
Gather necessary data: Collect historical data on patient visits, including time of day, day of the week, and seasonal variations.
02
Identify relevant metrics: Determine key metrics to analyze, such as patient wait times, number of staff on duty, and available resources.
03
Choose a forecasting method: Select an appropriate predictive model (e.g., time-series analysis, regression analysis) based on the data collected.
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Input data into the model: Enter the gathered data into the chosen predictive model for processing.
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Analyze results: Review the output of the model to understand expected patient volumes and trends.
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Adjust for external factors: Consider adjustments for events that could affect patient volume, such as local events or seasonal health trends.
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Communicate predictions: Share findings with the relevant staff and departments to prepare for anticipated patient flow.
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Monitor and refine: Continuously track real patient volumes against predictions and refine the model as necessary.

Who needs prediction of emergency department?

01
Emergency department leadership: To optimize staffing and resource allocation.
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Healthcare administrators: For strategic planning and budgeting.
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Nurses and medical staff: To prepare for fluctuating patient volumes and ensure adequate care.
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Data analysts: For ongoing analysis and improvement of predictive methods.
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Policy makers: To enhance healthcare delivery and patient outcomes in emergency services.
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The prediction of emergency department refers to an estimation or forecast related to patient volume, resource needs, and staffing requirements in an emergency department over a specific period.
Typically, healthcare administrators, emergency department managers, or designated personnel within a healthcare facility are required to file the prediction of emergency department.
To fill out the prediction of emergency department, users should gather data on historical patient visits, analyze trends, and input this information into the appropriate prediction forms or software provided by the healthcare facility.
The purpose of the prediction of emergency department is to optimize resource allocation, improve patient care, and enhance operational efficiency by anticipating the demand for services.
Information that must be reported includes expected patient volumes, peak times for admissions, required staffing levels, and any anticipated changes in capacity or services.
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