As information and technology continue to expand in healthcare, nurse leaders must translate data driven reports into effective quality improvement plans and positive patient outcomes. This session will provide strategies and tools for implementing and maintaining effective indicator data collection to identify data driven process improvements and reduce unassisted patient falls in acute care facilities.   

OBJECTIVES
 
This Educational/Leadership session will; 1) provide useful tools for data driven analysis from operational dashboards, 2) describe the process for effective utilization of NDNQI reports to impact process improvement and reduce patient falls.

PURPOSE

The purpose of this session is to explore data driven analysis tools, discuss methods to increase nurse awareness and communication of at-risk patients, and provide an interactive session with data analysis case examples to demonstrate effective strategies to impact patient outcomes and reduce unassisted patient falls.   

PRESENTATION SUMMARY

NDNQI reports serve as useful tools to compare patient outcomes internally and provide external indicator benchmarks for similar patient populations. Operational dashboards of nursing sensitive indicators have migrated from the nurse executive to unit management levels, in efforts to provide quantifiable results and point of care data analysis. Since 2002, this acute care facility has participated in NDNQI reporting, which coincided with the JCAHO staffing effectiveness standard implementation. An operational dashboard was created to establish thresholds for analyzing nurse sensitive indicators and identify correlations between staffing effectiveness and patient outcomes.
This one page retrospective composite quarterly report provides an at-a-glance perspective of operational parameters and nursing sensitive indicators. Even though no direct correlations have been established related to staffing and outcomes, unassisted patient falls continued to escalate. The critical challenge for nurse leaders was to identify strategies to proactively manage this upward trend. A detailed drill-down data analysis report was compiled for clinical units that exceeded the nursing sensitive indicator threshold related to unassisted patient falls. Components of the composite report for patient falls include; 1) demographic data; age, gender, room assignment, 2) time/day of week falls occurred, 3) patient census and unit throughput, 4) planned versus actual staffing, 5) fall risk scores, and 6) unit productivity measurements.
In 2004, the adult progressive care unit, (30 bed step-down telemetry unit with multi-system diagnoses patient population) ranked as the clinical unit with the most reported patient falls, and exceeded the NDNQI mean for Total Falls. As a result of manager/staff commitment to process improvement, this care delivery team has proactively implemented practice changes that have significantly reduced unassisted patient falls in 2005 and 2006 (as compared to 2004 results).

RESULTS                            2004                2005                2006 (YTD 10/01/06)

PCU TOTAL FALLS              52                     38                      21
                                             - 27% from 2004       - 26.4% from 2005

NDNQI MEAN                     3.61                  3.59                  3.64
Bedsize 200 – 299                 

PCU MEAN                          5.67                  4.27                  2.56

IMPLICATIONS FOR PRACTICE

This interactive presentation will discuss the benefits of creating useful tools for effective data driven analysis that has demonstrated significant findings and decreased patient falls. Effective implementation of these tools and strategies may increase patient safety and improve patient outcomes for the hospitalized patient.