PMID- 21228072
OWN - NLM
STAT- MEDLINE
DCOM- 20120820
LR  - 20220309
IS  - 2044-5423 (Electronic)
IS  - 2044-5415 (Linking)
VI  - 20
IP  - 1
DP  - 2011 Jan
TI  - Large-scale deployment of the Global Trigger Tool across a large hospital system: 
      refinements for the characterisation of adverse events to support patient safety 
      learning opportunities.
PG  - 25-30
LID - 10.1136/bmjqs.2008.029181 [doi]
AB  - BACKGROUND: The Institute for Healthcare Improvement encourages use of the Global 
      Trigger Tool to objectively determine and monitor adverse events (AEs). SETTING: 
      Baylor Health Care System (BHCS) is an integrated healthcare delivery system in 
      North Texas. The Global Trigger Tool was applied to BHCS's eight general acute 
      care hospitals, two inpatient cardiovascular hospitals and two 
      rehabilitation/long-term acute care hospitals. STRATEGY: Data were collected from 
      a monthly random sample of charts for each facility for patients discharged 
      between 1 July 2006 and 30 June 2007 by external professional nurse auditors 
      using an MS Access Tool developed for this initiative. In addition to the data 
      elements recommended by Institute for Healthcare Improvement, BHCS developed 
      fields to permit further characterisation of AEs to identify learning 
      opportunities. A structured narrative description of each identified AE 
      facilitated text mining to further characterise AEs. INITIAL FINDINGS: Based on 
      this sample, AE rates were found to be 68.1 per 1000 patient days, or 50.8 per 
      100 encounters, and 39.8% of admissions were found to have >/=1 AE. Of all AEs 
      identified, 61.2% were hospital-acquired, 10.1% of which were associated with a 
      National Coordinating Council - Medical Error Reporting and Prevention harm score 
      of "H or I" (near death or death). FUTURE DIRECTION: To enhance learning 
      opportunities and guide quality improvement, BHCS collected data-such as 
      preventability and AE source-to characterise the nature of AEs. Data are provided 
      regularly to hospital teams to direct quality initiatives, moving from a general 
      focus on reducing AEs to more specific programmes based on patterns of harm and 
      preventability.
FAU - Good, V S
AU  - Good VS
AD  - Baylor Health Care System, Office of Patient Safety, 8080 North Central 
      Expressway, Suite 500, Dallas, TX 75206, USA.
FAU - Saldana, M
AU  - Saldana M
FAU - Gilder, R
AU  - Gilder R
FAU - Nicewander, D
AU  - Nicewander D
FAU - Kennerly, D A
AU  - Kennerly DA
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
PL  - England
TA  - BMJ Qual Saf
JT  - BMJ quality & safety
JID - 101546984
MH  - Cardiac Rehabilitation
MH  - Data Mining/*methods
MH  - Delivery of Health Care, Integrated
MH  - Hospital Information Systems/*organization & administration
MH  - Humans
MH  - Length of Stay
MH  - Medical Errors/*prevention & control/statistics & numerical data
MH  - Patient Admission/statistics & numerical data
MH  - Patient Discharge
MH  - Patient Safety/*standards
MH  - Postoperative Care/education
MH  - *Quality Indicators, Health Care
MH  - Retrospective Studies
MH  - Risk Management
MH  - Software
MH  - Texas/epidemiology
EDAT- 2011/01/14 06:00
MHDA- 2012/08/21 06:00
CRDT- 2011/01/14 06:00
PHST- 2011/01/14 06:00 [entrez]
PHST- 2011/01/14 06:00 [pubmed]
PHST- 2012/08/21 06:00 [medline]
AID - 20/1/25 [pii]
AID - 10.1136/bmjqs.2008.029181 [doi]
PST - ppublish
SO  - BMJ Qual Saf. 2011 Jan;20(1):25-30. doi: 10.1136/bmjqs.2008.029181.