Management Engineering

Management Engineering, A Guide to Best Practices for Industrial Engineering in Healthcare, edited by Dr. Jean Ann Larson, CRC Press, 2014.Healthcare professionals are really, really, really smart – at least that’s what I noticed at the Lean Healthcare Summit in Orlando.  They’ve got degrees and data and they can pore over reams of research and somehow make sense of it.  So that’s why this engineering collection for healthcare may be a very useful tool – no one expects busy healthcare pros, especially physicians, to sign up for a B.S. in engineering – and there are not enough trained engineers in the system right now – but the some appropriate and very useful engineering tools we were trained in for manufacturing are easily learned and tested -.  Value-stream mapping, for instance, or Poisson distributions.  We recommend these chapters for immediate application to healthcare problems and information flows:

          Chapter 19, Data Collection, Analysis and Presentation

          Chapter 16, Six Sigma

          Chapter 17, Flowcharting, Spaghetti Diagrams, etc.

          Chapter 26, Value Stream Mapping

          Chapter 27, Statistical and Mathematical Analysis in a Healthcare Setting – It’s good to review formula first even if the team uses a software package to manipulate patient data.

          Chapter 30, Throughput and Cycle Time Reduction

          Chapter 31, Simulation in Healthcare

          Authors Flint and Troy show the example of how data is used to analyze patient wait times and illustrate basic data gathering decisions, tools, and analysis.  The questions that narrow down which data to gather are so important at the beginning of any problem-solving project.  Here the questions include:  At what points in the process do patients have particularly long waits? Under what circumstances do patients have particularly long waits? Do average patient waiting times differ significantly for different providers? Do average patient waiting times differ significantly by day of the week? Do average patient waiting times vary by appointment time? Are average patient waiting times long for physicians than for nurse practitioners or other providers? Do new patient visits take longer than return or post-op patient visits?                                                                   

Data gathering and analysis stages contain a number of sensible warnings from the authors.  In Analysis, the authors recommend using a simple spreadsheet to study the distribution of the data.  One can learn as much from the outliers as the steady state curves.  Finally, the authors recommend using SAS, SPSS, Minitab or Excel for advanced modeling and more detailed analysis.   Further, simulation is a great tool to use and test various project solutions.  Chapter 31 covers simulation modeling in more detail that will allow team members to build models of the clinic processes.