USA flag logo/image

An Official Website of the United States Government

Demand Driven Healthcare Scheduling using Flexible Shifts and Monte-Carlo…

Award Information

Department of Health and Human Services
Award ID:
Program Year/Program:
2010 / SBIR
Agency Tracking Number:
Solicitation Year:
Solicitation Topic Code:
Solicitation Number:
Small Business Information
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
Phase 2
Fiscal Year: 2010
Title: Demand Driven Healthcare Scheduling using Flexible Shifts and Monte-Carlo Simulat
Agency: HHS
Contract: 2R44NR011129-02
Award Amount: $551,839.00


DESCRIPTION (provided by applicant): The shortage of nurses and medical technologists is accelerating. Shortages can be reduced by scheduling staff to precisely meet the hour-by-hour demand for medical service. Think of bank teller scheduling, where more s taff are scheduled at peak demand. Current attempts to schedule to demand are relatively primitive: a small number of quantized fixed shifts, for example: 7am-3pm, 10am-6pm, 3pm-11pm, 7am-7pm, 7pm-7am, etc. is allowed. The pre-determined fixed shifts are r igid input parameters for the scheduling process and workers are assigned to the shifts. In this innovation, fixed shifts are replaced with flexible shift parameters; specifically, a range of start times and shift durations that are harmonious with worker lifestyles. These parameters become elastic inputs for the scheduling algorithm. The actual shift assigned to a worker on any particular day is computed with the objective to have just enough workers to meet the hour-by-hour demand. Phase I research succes sfully determined the efficacy of worker-friendly, flexible shift scheduling and found savings of 4 percent are possible. Four percent can cut the current worker shortfall significantly and corresponds to annual savings of 3.5 billion in healthcare costs. Despite many scientific studies of flexible shift scheduling, there is a dearth of practical commercial applications primarily due to the complexity of technologies employed in the research. In Phase II, a simple but powerful technology, Monte-Carlo simul ation, will be employed. The hypothesis is that a Monte-Carlo simulation can be developed that uses worker-friendly, flexible shift parameters to precisely meet the hour-by-hour demand for medical service. The Specific Aim is to find an objective function that quantifies the goal of meeting hour-by-hour demand and a set of shift perturbations for the Monte-Carlo process to use during the simulation. The commercialized product will be a new module for DOCS Scheduler, Acme Express Inc.'s healthcare staff sche duling software that is already in the marketplace. The current DOCS Scheduler was designed for salaried (physicians) staff and uses fixed shifts. Using flexible shifts is an entirely different innovation and focuses on shift workers like nurses and medica l technicians. A new module that saves 4 percent in healthcare staffing costs will be a market-changing, competitive advantage for Acme Express, Inc. PUBLIC HEALTH RELEVANCE: An ageing population with increasing lifespan, coupled with healthcare wor ker retirements and high turnover, is exacerbating the shortage of healthcare workers. The USA nurse shortage of 200,000 workers in 2008 is estimated to be 1,000,000 by 2014, with similar estimates for medical technologists. Phase I found that healthcare w orker shortage can be reduced by 4 percent and healthcare worker morale improved by using flexible shifts that are harmonious with worker lifestyles to schedule staff precisely according to demand for medical service. In Phase II, Acme Express, Inc. will e mploy a simple but powerful technology, Monte-Carlo Simulation, to automatically build the staff schedule, minimize periods of overstaffing, and significantly reduce healthcare labor costs.

Principal Investigator:

Don S. Scipione

Business Contact:

Don Scipione
Small Business Information at Submission:


EIN/Tax ID: 134166430
Number of Employees: N/A
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No