Staff Schedule

Chicago,

USA

Location

September 2020 -

December 2020

Date

Andrew Patronick

Andy Balcazer

Role

Team

Optimization

Skills

Algorithm Developer

Time Series: Patient Volume

The goal is to develop a 4-week staffing schedule of full-time and part-time nurses in the Hospital Medicine Department at NMH, using a dataset containing the hourly patient counts of each day from the beginning of 2009 to mid-2012. 

To eliminate the process inefficiency's in healthcare, hospitals rely on advanced forecasting technology to create an effective nurse staffing schedule. The scheduling system gets complicated without accurately predicting the demand (hospitalized patients). Healthcare providers must adjust the staffing schedule by balancing full-time and part-time nurses.

Research

Data Analysis

Analyzed Data from the hospital regarding the number of incoming patients

Prediction Modeling

Analyzed Data from the hospital regarding the number of incoming patients

Optimizing Staff

Optimized the number of nurses needed in AMPL to balance the cost of full time, part-time and shortfall workers

Data Analysis

We began by averaging the number of patients by the days over a 24 hour period. 

How to determine the number of shifts?

Using AMPL the team determined:

  • the total number of shifts needed across the week at each time t. ​

  • the number of full-time and part-time nurses needed to be hired.

 * Full-time nurses work 12-Hour in each shift 3 shifts/week

 * Part-time nurses work 8-Hour in each shift 5 shifts/week 

 Mathematical Formulation to determine the number of nurses & shifts in AMPL

Creating a Nurse Schedule using Number of Shifts

Using AMPL we created a schedule that took into account the nurse demands for each shift start time and shift type (12-HR and 8-HR).

 

The model assigned Full-time and Part-time nurses to specific shits on specific days while minimizing costs and fitting the constraints. ​

 Mathematical Formulation to assign nurses to shifts in AMPL

Nurse to Patient Ratio

To ensure every patient will be taken care of in a timely manner, we ran the model with three values of patient-to-staff ratio.

  • 5-to-1 ratio is usually applicable to Medical/Surgical units

  • 3-to-1 ratio is suitable for step down units

  • 4-to-1 ratio is preferred for most units including Emergency Departments

The increase in cost from 5-to-1 ratio to 4-to-1 is outweighed by safety measures and a 4-to-1 ratio with a total cost of $197,400

Takeaways

  • Data Analysis helps analyze the number of incoming patients​

  • Optimization Algorithms determine the number of nurses needed per shift and minimize the cost of staffing by assessing the best combination of full-time and part-time nurses.

My Ventures

Stocks

Analyzing banks S&P 500 companies recommendations.  Surprisingly, there were no trackers following the performance of analyst picks over the long term and I decided to build one.

Logistics

Stroke Code

Redesigning the CODE stroke activation process to reduce the Door-in-door out time for stroke patients

PROJECT WILL BE AVAILABLE AUGUST 2021