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Abstract: Poster Presentations |

IMPLEMENTATION OF THE INSTITUTE FOR HEALTHCARE IMPROVEMENT GLOBAL TRIGGER TOOL IN AN ONCOLOGICAL ICU: PILOT DATA FREE TO VIEW

Selvaraj E. Pravinkumar, MD*; Mary Lou Warren, CCRN; Jeffrey J. Bruno, PharmD; Catherine Nwankwo, APN; Clarence G. Finch, MBA; Shubhra Ghosh, MD; Kristen J. Price, MD
Author and Funding Information

The University of Texas M.D. Anderson Cancer Center, Houston, TX


Chest


Chest. 2009;136(4_MeetingAbstracts):27S. doi:10.1378/chest.136.4_MeetingAbstracts.27S-b
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Abstract

PURPOSE:  Traditional efforts to detect adverse events have focused on voluntary reporting and tracking of errors. However, only 10 to 20 percent of errors are reported and, of those, 90 to 95 percent cause no harm to patients. The Institute for Healthcare Improvement (IHI) released a white paper titled ‘IHI Global Trigger Tool for Measuring Adverse Events’ providing methodology and guidance in detecting and recording adverse event triggers (AET) and adverse events (AE). A multidisciplinary critical care team was established to implement the IHI tool for capturing AET and AE in an oncological ICU.

METHODS:  A total of 10 ICU patient discharges were randomly selected over a period of 1 month (Medical ICU, n = 5; Surgical ICU, n = 5). Patient charts were reviewed systematically by a multidisciplinary critical care team in accordance with IHI recommendations. AET and AE were captured based on IHI tool criteria. If AE was noted, harm to patient was then evaluated. Time taken to perform chart review was recorded. This was a quality improvement project, exempt from IRB approval.

RESULTS:  Of the 10 charts reviewed a total of 41 AET (Table 1) and 3 AE were identified. The median ICU length of stay (LOS) was 1.65 days (range: 1 day to 7.3 days). The median time taken for chart review was 30 minutes (range: 10 to 45 minutes). Increased ICU LOS was associated with increased AET's and time utilization for chart review but not necessarily an increase in AE. Of the three AE, two were related to infection and one was related to medication.

CONCLUSION:  The IHI model is effective in identifying AET and AE. This data will be valuable in implementing process changes related to patient safety. However, successful implementation of the IHI Global Trigger tool needs a dedicated multidisciplinary team and an effective data collection process.

CLINICAL IMPLICATIONS:  The IHI Global Trigger Tool can lead to identification of modifiable adverse event triggers, leading to implementation of processes for prevention of AE, thereby improving patient safety.

DISCLOSURE:  Selvaraj Pravinkumar, No Financial Disclosure Information; No Product/Research Disclosure Information

Tuesday, November 3, 2009

12:45 PM - 2:00 PM


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