PMID- 23370221
OWN - NLM
STAT- MEDLINE
DCOM- 20140707
LR  - 20211021
IS  - 1549-8425 (Electronic)
IS  - 1549-8417 (Print)
IS  - 1549-8417 (Linking)
VI  - 9
IP  - 2
DP  - 2013 Jun
TI  - Development and testing of tools to detect ambulatory surgical adverse events.
PG  - 96-102
LID - 10.1097/PTS.0b013e31827d1a88 [doi]
AB  - OBJECTIVES: Numerous health-care systems in the United States, including the 
      Veterans Health Administration (VA), use the National Surgical Quality 
      Improvement Program (NSQIP) to detect surgical adverse events (AEs). VASQIP 
      sampling methodology excludes many routine ambulatory surgeries from review. 
      Triggers, algorithms derived from clinical logic to flag cases where AEs have 
      most likely occurred, could complement VASQIP by detecting a higher yield of 
      ambulatory surgeries with a true surgical AE. METHODS: We developed and tested a 
      set of ambulatory surgical AE trigger algorithms using a sample of fiscal year 
      2008 ambulatory surgeries from the VA Boston Healthcare System. We used VA Boston 
      VASQIP-assessed cases to refine triggers and VASQIP-excluded cases to test how 
      many trigger-flagged surgeries had a nurse chart review-detected surgical AE. 
      Chart review was performed using the VA electronic medical record. We calculated 
      the ratio of cases with a true surgical AE over flagged cases (i.e., the positive 
      predictive value [PPV]), and the 95% confidence interval for each trigger. 
      RESULTS: Compared with the VASQIP rate (9 AEs, or 2.8%, of the 322 charts 
      assessed), nurse chart review of the 198 trigger-flagged surgeries yielded more 
      cases with at least 1 AE (47 surgeries with an AE, or 6.0%, of the 782 
      VASQIP-excluded ambulatory surgeries). Individual trigger PPVs ranged from 12.4% 
      to 58.3%. CONCLUSIONS: In comparison with VASQIP, our set of triggers identified 
      a higher rate of surgeries with AEs in fewer chart-reviewed cases. Because our 
      results are based on a relatively small sample, further research is necessary to 
      confirm these findings.
FAU - Mull, Hillary J
AU  - Mull HJ
AD  - Center for Organization, Leadership, and Management Research, VA Boston 
      Healthcare System, Boston, MA 02130, USA. hjmull@bu.edu
FAU - Borzecki, Ann M
AU  - Borzecki AM
FAU - Hickson, Kathleen
AU  - Hickson K
FAU - Itani, Kamal M F
AU  - Itani KM
FAU - Rosen, Amy K
AU  - Rosen AK
LA  - eng
GR  - VA999999/ImVA/Intramural VA/United States
PT  - Comparative Study
PT  - Evaluation Study
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
PL  - United States
TA  - J Patient Saf
JT  - Journal of patient safety
JID - 101233393
SB  - IM
MH  - Algorithms
MH  - Ambulatory Surgical Procedures/*adverse effects/standards
MH  - *Data Mining/methods
MH  - Electronic Health Records
MH  - Humans
MH  - *Patient Safety
MH  - Postoperative Complications/*etiology/prevention & control
MH  - *Quality Indicators, Health Care
MH  - Reproducibility of Results
MH  - Risk Factors
MH  - Time Factors
MH  - United States
MH  - United States Department of Veterans Affairs
PMC - PMC4559857
MID - NIHMS718934
EDAT- 2013/02/02 06:00
MHDA- 2014/07/08 06:00
PMCR- 2015/09/04
CRDT- 2013/02/02 06:00
PHST- 2013/02/02 06:00 [entrez]
PHST- 2013/02/02 06:00 [pubmed]
PHST- 2014/07/08 06:00 [medline]
PHST- 2015/09/04 00:00 [pmc-release]
AID - 10.1097/PTS.0b013e31827d1a88 [doi]
PST - ppublish
SO  - J Patient Saf. 2013 Jun;9(2):96-102. doi: 10.1097/PTS.0b013e31827d1a88.