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Effects of Staffing Matrix on Clinical outcomes

Effects of Staffing Matrix on Clinical outcomes

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Effects of Staffing Matrix on Clinical outcomes

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  1. Effects of Staffing Matrix on Clinical outcomes Karen Loden, MN, RNDr. Linda Corson Jones Memorial ResearchDayApril 11, 2008

  2. Learner Objective • Discuss the relationship of the current staffing matrix to clinical patient outcomes

  3. Staffing Matrix • Definition: a mathematical model that shows the number of patients and required staff by skill level for a 24 hour period

  4. Development • Staffing matrix developed • To achieve appropriate skill mix on in patient care units • To achieve realistic and reliable staffing within budget parameters and professional standards

  5. Staffing Matrix Sample

  6. Application in clinical area • Does not supersede professional judgment in staffing • Matrix facilitates staffing decisions 3 times daily based on available staff, patient acuity and activity and census.

  7. Research Question asked • Is there a relationship between the staffing matrix to patient outcomes of • Length of stay • Falls • Medication Errors • MET calls • Code Blue • Patient satisfaction (pain control, loyalty, personal needs, care and concern.

  8. Data Collection sources • Data was collected for a six month period (July 2007- December 2007) from the staffing software, Performance Improvement, Patient Satisfaction questionnaires and Financial services • Used HPPD by skill level (hours worked not total hours) (hours per patient day = # hours worked by skill level/patient days or census for time period)

  9. Relationship of clinical outcomes • There was no relationship between the variables of LOS, MET calls, and Code Blue and the HPPD. • There was not a statistical difference when comparing the matrix HPPD and the actual HPPD. • There was an inverse relationship between RN HPPD and falls, and medication errors, but it was not statistically significant. • There is a relationship between the RN, LPN and UAP HPPD to patient outcomes of pain control, loyalty, personal needs, care and concern.

  10. Correlation *** r = 0.55, this was put into the regression model ** correlation is significant at the 0.01 level * correlation is significant at the 0.05 level

  11. Regression: Pain Perception A great deal of effort has surrounded our communication related to pain management which may be why there is not predictive relationship.

  12. Regression: Loyalty

  13. Regression: Personal Needs

  14. Regression: Care and Concern

  15. Implications for Nursing Administration • The matrix offers a guide to help consistency in number of hours provided by skill level. • Review and adjust matrix at regular intervals during fiscal year • Skill mix needs to be evaluated when staffing, to achieve positive patient outcomes. • Value all skill levels in nursing to achieve positive patient outcomes.

  16. Recommendations • Identification of how to utilize the staff we have on duty to meet patient needs • Ask the nursing staff what works, then act on it. • Provide adequate support for RNs. • Investigate the LPN role in patient care and patient satisfaction. • Develop scripting using solution starters. • Continue data collection for next 6 months

  17. Questions • kloden@ololrmc.com • kloden@bellsouth.net