Office for Technology Commercialization

Patient-to-Nurse Ratio Workload Management System

Technology #20130305

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Nursing Hours per Patient DayNurse Workload ManagementPatient-to-Nurse Ratio
Diwakar Gupta, PhD
Professor, Industrial and Systems Engineering, College of Science and Engineering
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Managed By
Andrew Morrow
Technology Licensing Officer

Nurse Workload Management

A more accurate nurses’ workload forecasting system has been created by researchers collaborating with nurse managers working in hospitals. The system is based on software that eliminates the need to manually estimate the demand for nurses for a future shift and their workload. This system uses a predictive algorithm that accounts for the number of patient admissions, discharges, transfers, and various activities performed by the nurses when determining an optimal shift schedule. This approach helps hospitals integrate three key decisions: (i) how many nurses are needed to staff a future shift, (ii) how to assign the available cohort of nurses to different future shifts, and (iii) which patients should be assigned to which nurses to balance workload within a shift.

MN-IP Try and Buy
  • Trial period of 6 to 12 months. $5000/6 months.
  • Fee waived for MN-based companies or if sponsoring $50,000+ in research.
  • Exclusive license for a $15,000 conversion payment.
  • No patent costs.
  • Royalty rate of 2% (1% for MN company) after first $1 million in product sales.

** View the Term Sheet **
** Contact Andrew Morrow for more information.

Nursing Hours per Patient Day Systems

Within hospitals, it is extremely important to effectively manage the workload of nurses. Many hospitals currently utilize target ‘nursing hours per patient day’, (NHPPD) to monitor the effectiveness of their staffing approach. The target NHPPDs are based on a survey of nursing hours used by similar hospitals for similar types of patients. The NHPPD system is meant to streamline scheduling processes and ensure adequate nurse staffing per patient without over-staffing. However, according to nurse managers, the currently available systems have flaws associated with them, including the fact that they are subject to human error in how workloads are forecast. For example in many systems, nurse managers manually enter the number of hours they predict are needed for each patient which can vary from manager to manager.  These inconsistencies result in NHPPD systems that are not able to accurately forecast future needs, or assign nurses to shifts as well as patients to nurses in a fair manner so that workloads are balanced across shifts and among employees within a shift.

Optimize Patient-to-Nurse Ratio

Nursing managers benefit from the nurse workload management software because it is more accurate than other software packages and it produces a more balanced workload among nurses. Accuracy is achieved because the algorithm is based on actual hospital data such as patient admissions, discharges, transfers, available doctors’ orders and various activities performed by the nurses. Balancing of workload is achieved by making optimal patient assignments that are determined via a genetic algorithm. As a result, the software produces more balanced patient-to-nurse ratio, ensuring optimal staffing conditions.


  • Offers a prediction system that forecasts future shifts’ requirements for nurses based on actual hospital data
  • Optimally schedules shifts to minimize the gap between the target and assigned NHPPD
  • Assigns patients to nurses in each shift to balance workload across nurses
  • Removes guessing game from scheduling processes found in current systems
  • Produces consistent results through the use of a constant set of variables

Product Details

A predictive algorithm system that automates the process of estimating future workload, optimizing shift schedules, and assigning patients to nurses to achieve a more balanced workload for nurses.

Fulfillment Details

Licensee will receive rights to further develop the software as a product.

Phase of Development

Prototype exists and has been tested