effects of staffing matrix on clinical outcomes karen loden, mn, rn dr. linda corson jones memorial...
TRANSCRIPT
Effects of Staffing Matrix on Clinical outcomes
Karen Loden, MN, RNDr. Linda Corson Jones Memorial Research Day
April 11, 2008
Learner Objective
Discuss the relationship of the current staffing matrix to clinical patient outcomes
Staffing Matrix
Definition: a mathematical model that shows the number of patients and required staff by skill level for a 24 hour period
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
Days Evenings NightsCensus RN LPN NA RN LPN NA RN LPN NA
48 5.0 5.0 5.0 5.0 5.0 4.0 4.0 3.0 3.047 5.0 5.0 5.0 5.0 5.0 4.0 4.0 3.0 3.046 5.0 5.0 5.0 5.0 5.0 4.0 4.0 3.0 3.045 5.0 5.0 5.0 5.0 5.0 4.0 4.0 3.0 3.044 5.0 5.0 5.0 5.0 5.0 4.0 3.0 3.0 3.0
43 5.0 5.0 5.0 5.0 4.0 4.0 3.0 3.0 3.0
42 4.0 5.0 5.0 4.0 5.0 4.0 3.0 3.0 3.041 4.0 5.0 5.0 4.0 4.0 4.0 3.0 3.0 3.040 4.0 4.0 5.0 4.0 4.0 4.0 3.0 3.0 3.039 4.0 4.0 4.0 4.0 4.0 4.0 3.0 2.0 3.038 4.0 3.0 4.0 4.0 3.0 4.0 3.0 2.0 3.0
Staffing Matrix Sample
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.
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.
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)
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.
Correlation
Skill level HPPD
Pain control Loyalty Personal needs
Care and Concern
RH HPPD .271* .426** .461** .360**
LPN HPPD -.228* -.347** -.369** -.280**
UAP HPPD .210***
*** 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
Regression: Pain Perception
Skill level HPPD
Standardized coefficients
Betat Sig.
RN HPPD .387 1.449 .151
LPN HPPD .127 .475 .636
A great deal of effort has surrounded our communication related to pain management which may be why there is not predictive relationship.
Regression: Loyalty
Skill level HPPD
Standardized coefficients
Betat Sig.
RN HPPD .675 2.706 .008
LPN HPPD .272 1.089 .279
Regression: Personal Needs
Skill level HPPD
Standardized Coefficients
Betat Sig.
RN HPPD .697 2.884 .005
LPN HPPD .256 1.057 .294
UAP HPPD .196 2.022 .046
Regression: Care and Concern
Skill level HPPD
Standardized coefficients
Betat Sig.
RN HPPD .644 2.506 .014
LPN HPPD .310 1.206 .231
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.
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
