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

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 2R44NR011129-02
Agency Tracking Number: NR011129
Amount: $551,839.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: NINR
Solicitation Number: PHS2010-2
Solicitation Year: 2010
Award Year: 2010
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
United States
DUNS: 803679364
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 (216) 391-7400
Business Contact
Phone: (216) 391-7400
Research Institution

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 staff 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 rigid 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 successfully 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 simulation, 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 scheduling 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 medical 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 worker 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 worker 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 employ a simple but powerful technology, Monte-Carlo Simulation, to automatically build the staff schedule, minimize periods of overstaffing, and significantly reduce healthcare labor costs.

* Information listed above is at the time of submission. *

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