Methods to Analyze the Bottleneck Capacity Planning

Hospitals unfortunately throughout the evening hours have a situations called bottlenecking occur.   “Bottlenecking is a choke point or a point in a process where demand exceeds available capacity.   In other words, a bottleneck can occur at any point where capacity is insufficient to meet demand due to physical or logical constraints” (Langabeer, 2008).
      Methods to analyze the bottlenecking include many areas to plan for capacity planning and eliminate wait time in the ER department or any other area in a hospital.   “Forecasting patient demand and volumes is the first step to thoroughly understand changes in activity levels over time (Langabeer, 2008).   Forecasting make a prediction or estimates what the future hold.   Clinics or hospitals need to forecast how many staff members need to be on the schedule for a specific time area.   It also allows management to minimize unproductive wait time, increase customer service, and improves operational management.
      Two types of forecasting include: qualitative and quantitative.   “Qualitative forecasting methods include mainly market research or Delphi methods to make subjective or judgmental decisions about the future without relating demand to historical performance quantitatively (Langabeer, 2008).
      Quantitative methods should be primarily used in the hospital settings.   Quantitative forecast is broken down into two types: univariate and multivariate methods. Univariate is dependence on a single variable.   This method attempts to forecast by looking at the history of data relative to a single variable.   Inside this method is a number of different statistical models that often used to assess patterns in the data.
      • Moving Average Forecast-   This calculates an average historical figure for a specific time period.
      • Trend Forecasting- This trend analysis looks fort linear upward or downward movement in the data and extrapolates them going forward.
Multivariate methods attempt to use more than...