PMID- 29181297
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20201001
IS  - 2211-3355 (Print)
IS  - 2211-3355 (Electronic)
IS  - 2211-3355 (Linking)
VI  - 8
DP  - 2017 Dec
TI  - The ability of triggers to retrospectively predict potentially preventable 
      adverse events in a sample of deceased patients.
PG  - 250-255
LID - 10.1016/j.pmedr.2017.10.016 [doi]
AB  - Several trigger systems have been developed to screen medical records of 
      hospitalized patients for adverse events (AEs). Because it's too labor-intensive 
      to screen the records of all patients, usually a sample is screened. Our sample 
      consists of patients who died during their stay because chances of finding 
      preventable AEs in this subset are highest. Records were reviewed for fifteen 
      triggers (n = 2182). When a trigger was present, the records were scrutinized by 
      specialized medical doctors who searched for AEs. The positive predictive value 
      (PPV) of the total trigger system and of the individual triggers was calculated. 
      Additional analyses were performed to identify a possible optimization of the 
      trigger system. In our sample, the trigger system had an overall PPV for AEs of 
      47%, 17% for potentially preventable AEs. More triggers present in a record 
      increased the probability of detecting an AE. Adjustments to the trigger system 
      slightly increased the positive predictive value but missed about 10% of the AEs 
      detected with the original system. In our sample of deceased patients the trigger 
      system has a PPV comparable to other samples. However still, an enormous amount 
      of time and resources are spent on cases without AEs or with non-preventable AEs. 
      Possibly, the performance could be further improved by combining triggers with 
      clinical scores and laboratory results. This could be promising in reducing the 
      costly and labor-intensive work of screening medical records.
FAU - Klein, Dorthe O
AU  - Klein DO
AD  - Department of Clinical Epidemiology and Medical Technology Assessment, Maastricht 
      University Medical Centre, Maastricht, The Netherlands.
FAU - Rennenberg, Roger J M W
AU  - Rennenberg RJMW
AD  - Department of Internal Medicine, Maastricht University Medical Centre, 
      Maastricht, The Netherlands.
FAU - Koopmans, Richard P
AU  - Koopmans RP
AD  - Department of Internal Medicine, Maastricht University Medical Centre, 
      Maastricht, The Netherlands.
FAU - Prins, Martin H
AU  - Prins MH
AD  - Department of Epidemiology, Maastricht University, Maastricht, The Netherlands.
LA  - eng
PT  - Journal Article
DEP - 20171103
PL  - United States
TA  - Prev Med Rep
JT  - Preventive medicine reports
JID - 101643766
PMC - PMC5700821
EDAT- 2017/11/29 06:00
MHDA- 2017/11/29 06:01
PMCR- 2017/11/03
CRDT- 2017/11/29 06:00
PHST- 2017/03/22 00:00 [received]
PHST- 2017/10/19 00:00 [revised]
PHST- 2017/10/30 00:00 [accepted]
PHST- 2017/11/29 06:00 [entrez]
PHST- 2017/11/29 06:00 [pubmed]
PHST- 2017/11/29 06:01 [medline]
PHST- 2017/11/03 00:00 [pmc-release]
AID - S2211-3355(17)30159-6 [pii]
AID - 10.1016/j.pmedr.2017.10.016 [doi]
PST - epublish
SO  - Prev Med Rep. 2017 Nov 3;8:250-255. doi: 10.1016/j.pmedr.2017.10.016. eCollection 
      2017 Dec.