Yolanda (Yoli) Otero Inman
Staffing effectiveness in any organization can be a challenge. The inability to directly match patient needs with nursing resources has been a chronic problem in hospitals, and there is no single solution that will lead to success in all organizations. Multiple factors related to the management of staff for to meet scheduling, census, and acuity needs while balancing retention through flexible scheduling have an impact on financial performance. Too often, when organizations are faced with the need to cut costs, they often look to nursing resources, one of the highest-cost areas in a hospital. Improving staffing effectiveness is therefore vital for improved outcomes as well as financial viability.
There are multiple strategies aimed at addressing staffing effectiveness. Some researchers and clinicians have stressed the need for real-time data reporting through a dashboard for making informed staffing decisions which ultimately can be linked to patient outcomes (Frith, K., Anderson, F., and Swell, J., "Accessing and Selecting Data for a Nursing Services Dashboard," JONA, January 2010). The components that drive cost savings are related to the ability to fill staffing needs earlier. The potential for improved employee satisfaction is high because it gives nurses autonomy in creating their work schedules (Every, A., "Best Practices for Controlling Labor Costs," Healthcare Cost Containment, 2008). Online shift-bidding systems also decrease costs for overtime and contract labor by filling staffing needs with noncontract staff, so that less resource time is spent in placing calls to fill.
The implementation of a modified staffing model paired with automation has proved successful as well (Lauw, C., and Gares, D., "Resources Management: What's Right for You," Nursing Management, December 2005). Authors Lauw and Gares found that nurse manager accountability for staffing, combined with employee autonomy for self-scheduling, reduced manager workload and improved employee satisfaction. The accuracy of the data provided through the automated tool enables resource departments to readily identify needs due to the accuracy of the information and assists teams in tracking expenses to decrease overtime.
Optimizing practice and policy also is essential in meeting this challenge. For example, at one organization, an existing, nonproactive process had resulted in the need for crisis management and frustration over not meeting volume and staffing needs (Kirkby, M., et al, "Improving Staffing with a Resource Management Plan, JONA, November 1998). In collaborating with a consulting company, the organization created multiple work teams comprised of nursing leaders and finance staff to review specific objectives for improved performance. The outcome of their efforts yielded an improved resource management plan along with a better understanding of the root causes of the issues and improved problem solving processes.
A current project brings promise of a break-through in matching resources to patient needs. Catholic Health Initiatives, in partnership with the University of Alabama, is engaged in a project that utilizes software for predicting staffing needs according to the percentage of risk in harming a patient (Sanford, K., "Nurse Staffing: Finding the Right Number and Mix," hfm, September 2010). Though this study is still in progress, this evidence-based approach to staffing will likely revolutionize how to staff appropriately (e.g., meet quality and financial needs).
Data related to nursing satisfaction and success Johnson City Medical Center in Tennessee has experienced as a result of redesigning its nurse staffing methods and using software tools to support staffing decisions. Nursing satisfaction related to nurse-to-nurse interactions increased from about 65 percent in 2007 to 70 percent in 2010, while nurse satisfaction related to decision making also increased by more than 5 percent during the same time period. Meanwhile, the average hourly rates for nurses at Johnson City Medical Center decreased by more than $10 per hour from May 2009 to November 2010.
For more information, see Yolanda (Yoli) Otero Inman, Patricia Niday, Lisa Smithgall, Shane Hilton, Sharon Grindstaff and Debbie McInturff's "Redesigning Nurse Staffing Plans for Acute Care Hospitals," hfm, June 2012
Publication Date: Friday, June 01, 2012