Healthcare Data Analytics: Methods Of Matching Scarce Resources With Uncertain Patient Demand, Data Envelopment Analysis: Comparing Productivity And Performance Of Units With Multiple Inputs And Outputs

Data envelopment analysis (DEA) is a technique that was developed to measure the multiple dimensions of performance (efficiency) of producing units. DEA allows the use of various inputs and outputs to build a single efficiency score to measure the comparative efficiency (performance) of hospital units, physicians, or group practices. Comparing the units’ efficiency can be formulated as a linear optimization problem that can easily be solved using the Excel Add-in solver. DEA is being used to compare a group of units to identify relatively inefficient ones, identify the magnitude of the inefficiencies, and, by comparing the inefficient with the efficient ones, suggest the targets to reduce those inefficiencies. The Excel spreadsheet templates are provided to illustrate all presented examples.

• Data Envelopment Analysis:  What is it? What is it for?
• A concept of the efficiency frontier and a scoring function
• DEA as a linear optimization problem
• Examples of DEA using Excel Add-in Solver with an explanation of the spreadsheet setup:
    - 6 hospitals: 2 Inputs and 2 Outputs
    - 12 medical labs: 2 Inputs and 3 Outputs
    -  A network of 8 hospitals: 5 Inputs and 3 Outputs(based on the actual project within Froedtert Health Hospital System)
• Strengths and limitations of DEA
• Available free DEA software

While one could find rich literature on various aspects of data envelopment analysis (DEA), it is typically presented as an academic mathematical development in the area of linear optimization which is challenging to apply in practice.

One should attend this webinar because it is focused on examples from actual hospital practice rather than using the complicated mathematics of linear optimization theory.

All presented examples are illustrated by the provided Excel spreadsheet using the Excel solver Add-in. The measures are taken from real hospital projects rather than presenting just academic exercises.

Nursing Managers, Chief Nursing Officers, Directors and VP of quality and operations improvements of healthcare organizations

Alexander Kolker holds a Ph.D. in applied mathematics and statistics. He is an expert in advanced data analytics for operations management, computer simulation modeling, and staffing optimization with a main focus on healthcare applications. Alexander is the lead editor and author of 2 books, 8 book chapters, 10 journal papers, and a speaker at 18 international conferences & webinars in the area of operations management and data analytics.

As an adjunct faculty at the UW-Milwaukee Lubar School of Business, he developed and taught a graduate course Business 755-Healthcare Delivery Systems-Data Analytics.

He worked 12 years for GE (General Electric) Healthcare as a Data Scientist and CT Detector design engineer, 3 years for Froedtert Hospital, the largest healthcare facility in the Southern state of Wisconsin, and 5 years for the Children’s Hospital of Wisconsin as a lead computer simulation and system improvement consultant.

Currently, he is teaching a 12-session online course “Healthcare Operations Research and Management Science” for the UK, National Health System (NHS)-Midland & Lancashire.

Alexander has also completed four business consulting projects using simulation modeling for optimal staffing and capacity analysis for Boston Consulting Group, Children’s Hospital of Wisconsin, Ohio Hospital Association, and US Bank Corporation.