PMID- 21921867
OWN - NLM
STAT- MEDLINE
DCOM- 20120127
LR  - 20110916
IS  - 1549-8425 (Electronic)
IS  - 1549-8417 (Linking)
VI  - 7
IP  - 1
DP  - 2011 Mar
TI  - Applying trigger tools to detect adverse events associated with outpatient 
      surgery.
PG  - 45-59
LID - 10.1097/PTS.0b013e31820d164b [doi]
AB  - OBJECTIVE: The objective of this study is to evaluate the performance of 5 
      triggers to detect adverse events (AEs) associated with outpatient surgery. 
      Triggers use surveillance algorithms derived from clinical logic to flag cases 
      where AEs have most likely occurred. Current efforts to detect AEs have focused 
      primarily on the inpatient setting, despite the increase in outpatient surgery in 
      all health care settings. METHODS: Using trigger logic, we retrospectively 
      evaluated data from 3 large health care systems' electronic medical records. 
      Patients were eligible for inclusion if they had an outpatient (same-day) surgery 
      in 2007 and at least 1 clinical note in the 6 months after the surgery. Two nurse 
      abstractors reviewed a sample of trigger-flagged cases from each health care 
      system. After reaching interrater reliability targets (kappa > 0.60), we calculated 
      the positive predictive value (PPV) of each trigger and the confidence interval 
      of the estimate. RESULTS: The surgical triggers flagged between 1% and 22% of the 
      outpatient surgery cases, with a wide range in PPVs (6.0%-62.0%). The pulmonary 
      embolism and deep vein thrombosis and emergency department triggers had the 
      lowest proportion of flagged cases along with the highest PPVs, showing the most 
      promise for screening cases with a high probability of AE occurrence. 
      CONCLUSIONS: Triggers may be useful in identifying a narrow set of surgeries for 
      further review to determine if a surgical AE occurred, complementing existing 
      tools and initiatives used to detect AEs. Improved detection of AEs in outpatient 
      surgery should help target potential areas for quality improvement.
FAU - Rosen, Amy K
AU  - Rosen AK
AD  - Center for Organization, Leadership, Management Research, a VA Center of 
      Excellence, VA Boston Healthcare System, Boston, Massachusetts 02130, USA. 
      akrosen@bu.edu
FAU - Mull, Hillary J
AU  - Mull HJ
FAU - Kaafarani, Haytham
AU  - Kaafarani H
FAU - Nebeker, Jonathan
AU  - Nebeker J
FAU - Shimada, Stephanie
AU  - Shimada S
FAU - Helwig, Amy
AU  - Helwig A
FAU - Nordberg, Brian
AU  - Nordberg B
FAU - Long, Brenna
AU  - Long B
FAU - Savitz, Lucy A
AU  - Savitz LA
FAU - Shanahan, Christopher W
AU  - Shanahan CW
FAU - Itani, Kamal
AU  - Itani K
LA  - eng
GR  - HHSA290200600012/PHS HHS/United States
PT  - Journal Article
PT  - Research Support, U.S. Gov't, P.H.S.
PL  - United States
TA  - J Patient Saf
JT  - Journal of patient safety
JID - 101233393
SB  - IM
MH  - Algorithms
MH  - Ambulatory Surgical Procedures/*adverse effects/statistics & numerical data
MH  - Delphi Technique
MH  - Humans
MH  - Iatrogenic Disease/*prevention & control
MH  - Monitoring, Physiologic/*instrumentation/methods
MH  - Postoperative Complications/*prevention & control
MH  - Predictive Value of Tests
MH  - Program Evaluation
MH  - Retrospective Studies
MH  - United States
EDAT- 2011/09/17 06:00
MHDA- 2012/01/28 06:00
CRDT- 2011/09/17 06:00
PHST- 2011/09/17 06:00 [entrez]
PHST- 2011/09/17 06:00 [pubmed]
PHST- 2012/01/28 06:00 [medline]
AID - 01209203-201103000-00008 [pii]
AID - 10.1097/PTS.0b013e31820d164b [doi]
PST - ppublish
SO  - J Patient Saf. 2011 Mar;7(1):45-59. doi: 10.1097/PTS.0b013e31820d164b.