PMID- 28095173
OWN - NLM
STAT- MEDLINE
DCOM- 20171025
LR  - 20211201
IS  - 1935-469X (Electronic)
IS  - 1554-7477 (Print)
IS  - 1554-7477 (Linking)
VI  - 13
IP  - 3
DP  - 2017 Mar
TI  - Performance of a Trigger Tool for Identifying Adverse Events in Oncology.
PG  - e223-e230
LID - 10.1200/JOP.2016.016634 [doi]
AB  - PURPOSE: Although patient safety is a priority in oncology, few tools measure 
      adverse events (AEs) beyond treatment-related toxicities. The study objective was 
      to assemble a set of clinical triggers in the medical record and assess the 
      extent to which triggered events identified AEs. METHODS: We performed a 
      retrospective cohort study to assess the performance of an oncology medical 
      record screening tool at a comprehensive cancer center. The study cohort included 
      400 patients age 18 years or older diagnosed with breast (n = 128), colorectal (n 
      = 136), or lung cancer (n = 136), observed as in- and outpatients for up to 1 
      year. RESULTS: We identified 790 triggers, or 1.98 triggers per patient (range, 
      zero to 18 triggers). Three hundred four unique AEs were identified from medical 
      record reviews and existing AE databases. The overall positive predictive value 
      (PPV) of the original tool was 0.40 for total AEs and 0.15 for preventable or 
      mitigable AEs. Examples of high-performing triggers included return to the 
      operating room or interventional radiology within 30 days of surgery (PPV, 0.88 
      and 0.38 for total and preventable or mitigable AEs, respectively) and elevated 
      blood glucose (> 250 mg/dL; PPV, 0.47 and 0.40 for total and preventable or 
      mitigable AEs, respectively). The final modified tool included 49 triggers, with 
      an overall PPV of 0.48 for total AEs and 0.18 for preventable or mitigable AEs. 
      CONCLUSION: A valid medical record screening tool for AEs in oncology could offer 
      a powerful new method for measuring and improving cancer care quality. Future 
      improvements could optimize the tool's efficiency and create automated electronic 
      triggers for use in real-time AE detection and mitigation algorithms.
FAU - Lipitz-Snyderman, Allison
AU  - Lipitz-Snyderman A
AD  - Memorial Sloan Kettering Cancer Center; Columbia University; AIG, New York, NY; 
      Pascal Metrics, Washington, DC; University of Utah School of Medicine, Salt Lake 
      City, UT; and Tufts Medical Center and Tufts University School of Medicine, 
      Boston, MA.
FAU - Classen, David
AU  - Classen D
AD  - Memorial Sloan Kettering Cancer Center; Columbia University; AIG, New York, NY; 
      Pascal Metrics, Washington, DC; University of Utah School of Medicine, Salt Lake 
      City, UT; and Tufts Medical Center and Tufts University School of Medicine, 
      Boston, MA.
FAU - Pfister, David
AU  - Pfister D
AD  - Memorial Sloan Kettering Cancer Center; Columbia University; AIG, New York, NY; 
      Pascal Metrics, Washington, DC; University of Utah School of Medicine, Salt Lake 
      City, UT; and Tufts Medical Center and Tufts University School of Medicine, 
      Boston, MA.
FAU - Killen, Aileen
AU  - Killen A
AD  - Memorial Sloan Kettering Cancer Center; Columbia University; AIG, New York, NY; 
      Pascal Metrics, Washington, DC; University of Utah School of Medicine, Salt Lake 
      City, UT; and Tufts Medical Center and Tufts University School of Medicine, 
      Boston, MA.
FAU - Atoria, Coral L
AU  - Atoria CL
AD  - Memorial Sloan Kettering Cancer Center; Columbia University; AIG, New York, NY; 
      Pascal Metrics, Washington, DC; University of Utah School of Medicine, Salt Lake 
      City, UT; and Tufts Medical Center and Tufts University School of Medicine, 
      Boston, MA.
FAU - Fortier, Elizabeth
AU  - Fortier E
AD  - Memorial Sloan Kettering Cancer Center; Columbia University; AIG, New York, NY; 
      Pascal Metrics, Washington, DC; University of Utah School of Medicine, Salt Lake 
      City, UT; and Tufts Medical Center and Tufts University School of Medicine, 
      Boston, MA.
FAU - Epstein, Andrew S
AU  - Epstein AS
AD  - Memorial Sloan Kettering Cancer Center; Columbia University; AIG, New York, NY; 
      Pascal Metrics, Washington, DC; University of Utah School of Medicine, Salt Lake 
      City, UT; and Tufts Medical Center and Tufts University School of Medicine, 
      Boston, MA.
FAU - Anderson, Christopher
AU  - Anderson C
AD  - Memorial Sloan Kettering Cancer Center; Columbia University; AIG, New York, NY; 
      Pascal Metrics, Washington, DC; University of Utah School of Medicine, Salt Lake 
      City, UT; and Tufts Medical Center and Tufts University School of Medicine, 
      Boston, MA.
FAU - Weingart, Saul N
AU  - Weingart SN
AD  - Memorial Sloan Kettering Cancer Center; Columbia University; AIG, New York, NY; 
      Pascal Metrics, Washington, DC; University of Utah School of Medicine, Salt Lake 
      City, UT; and Tufts Medical Center and Tufts University School of Medicine, 
      Boston, MA.
LA  - eng
GR  - P30 CA008748/CA/NCI NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
PT  - Research Support, Non-U.S. Gov't
DEP - 20170117
PL  - United States
TA  - J Oncol Pract
JT  - Journal of oncology practice
JID - 101261852
SB  - IM
MH  - Adult
MH  - Aged
MH  - Aged, 80 and over
MH  - Cohort Studies
MH  - Drug-Related Side Effects and Adverse Reactions/*diagnosis
MH  - Female
MH  - Humans
MH  - Longitudinal Studies
MH  - Male
MH  - Medical Oncology/*methods
MH  - Middle Aged
MH  - Quality Improvement
MH  - Retrospective Studies
PMC - PMC5482407
EDAT- 2017/01/18 06:00
MHDA- 2017/10/27 06:00
PMCR- 2017/12/01
CRDT- 2017/01/18 06:00
PHST- 2017/01/18 06:00 [pubmed]
PHST- 2017/10/27 06:00 [medline]
PHST- 2017/01/18 06:00 [entrez]
PHST- 2017/12/01 00:00 [pmc-release]
AID - 016634 [pii]
AID - 10.1200/JOP.2016.016634 [doi]
PST - ppublish
SO  - J Oncol Pract. 2017 Mar;13(3):e223-e230. doi: 10.1200/JOP.2016.016634. Epub 2017 
      Jan 17.