Health care systems around the country face a common staffing problem. Sometimes nurses are scheduled for more patients than actually arrive at the hospital. Other times, there aren’t enough nurses to cover patient demand. This leads to members of the clinical staff being called in on days when they aren’t supposed to work or sent home due to low patient census. In some cases, nurses are putting in overtime.
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These instances result in unpredictable schedules, difficulty matching staffing resources with patient needs, fatigue and high rates of turnover. For health care organizations, it means increased costs in overtime and incentive bonuses.
OSF HealthCare wanted to develop an innovative approach to solve these issues with the goal of placing Mission Partners at the right location at the right time at the right cost every time. The organization brought together an ecosystem of groups including clinical leadership, human resources, clinician education, performance improvement, information technology, finance and healthcare analytics with the purpose of identifying ways to optimize every clinical department within the organization.
The result is the development of the Precision Staffing Model that includes new standards around scheduling, staffing practices, position control and scheduling tools as well as variance reports. One of the tools that is core to this work involves a predictive analytics and optimization application.
Building a predictive analytics and optimization application
Advanced Analytics, a part of OSF Innovation, developed an easy-to-use predictive analytics and optimization application to better match staffing resources with patient need. The solution allows end-users to predict staffing demand based on historical patient volume data as well as benchmarking with similar institutions.
“Using the National Database of Nursing Quality Indicators, we can see how hospitals of similar size staff their clinical departments,” said Chris Franciskovich, director of Advanced Analytics. “Our clinicians in charge of scheduling can see what the data looks like across the country and compare where they fall in that spectrum.”
The application forecasts the probability of needing a certain number of nurses every hour of every day over a year-long period. All of that information goes through a two-stage optimization with the first taking into account the cost for varying levels of nurse types, including core, flexible and planned premium labor to inform staffing levels.
The second stage estimates how many members of each staff are needed to meet patient volume demands with consideration for those who might not be available due to clinical mandatory training, time-off and other issues. This helps determine how many flexible and overtime nurses may be needed.
Clinical departments are provided with the number of Mission Partners that need to be scheduled and staffing grids, allowing them to have the right amount of nurses and techs to care for their patient demand.
Phased implementation of the model
The Precision Staffing Model was first used in three of the largest hospitals within OSF HealthCare over a six-month period, primarily for inpatient care.
This resulted in a reduction in the cost of overtime, incentive shifts and traveler contracts–equating to $2 million in savings as well as the development of more consistent work schedules, improvement in work-life balance and needed workforce support from flexible staff.
“The fact that our overtime and incentive dollars have gone down means we are more closely aligning our scheduling to our needs,” said Robin Kretschman, vice president of Clinical Business Strategic Operations for OSF HealthCare. “This leads to a better quality of life for our Mission Partners.”
The Precision Staffing Model was expanded across the Ministry in February 2019 for inpatient care. In the last quarterly report, the cost of overtime, incentive shifts and traveler contracts were reduced by more than 7.5%. The model will be adopted by obstetrics and the emergency department over the next two quarters. Initial assessment work has begun in Multispecialty Services.
The estimated impact of a fully implemented Precision Staffing Model to inpatient departments is projected to be about $7.6 million. The use of the model is also expected to lead to improved quality care, the patient experience as well an increase in Mission Partner engagement.