PMID- 28411291
OWN - NLM
STAT- MEDLINE
DCOM- 20171116
LR  - 20220928
IS  - 1553-5606 (Electronic)
IS  - 1553-5592 (Linking)
VI  - 12
IP  - 4
DP  - 2017 Apr
TI  - Automating Venous Thromboembolism Risk Calculation Using Electronic Health Record 
      Data upon Hospital Admission: The Automated Padua Prediction Score.
PG  - 231-237
LID - 10.12788/jhm.2714 [doi]
AB  - BACKGROUND: Venous thromboembolism (VTE) risk scores assist providers in 
      determining the relative benefit of prophylaxis for individual patients. While 
      automated risk calculation using simpler electronic health record (EHR) data is 
      feasible, it lacks clinical nuance and may be less predictive. Automated 
      calculation of the Padua Prediction Score (PPS), requiring more complex input 
      such as recent medical events and clinical status, may save providers time and 
      increase risk score use. OBJECTIVE: We developed the Automated Padua Prediction 
      Score (APPS) to auto-calculate a VTE risk score using EHR data drawn from prior 
      encounters and the first 4 hours of admission. We compared APPS to standard 
      practice of clinicians manually calculating the PPS to assess VTE risk. DESIGN: 
      Cohort study of 30,726 hospitalized patients. APPS was compared to manual 
      calculation of PPS by chart review from 300 randomly selected patients. 
      MEASUREMENTS: Prediction of hospital-acquired VTE not present on admission. 
      RESULTS: Compared to manual PPS calculation, no significant difference in average 
      score was found (5.5 vs. 5.1, P = 0.073), and area under curve (AUC) was similar 
      (0.79 vs. 0.76). Hospital- acquired VTE occurred in 260 (0.8%) of 30,726 
      patients. Those without VTE averaged APPS of 4.9 (standard deviation [SD], 2.6) 
      and those with VTE averaged 7.7 (SD, 2.6). APPS had AUC = 0.81 (confidence 
      interval [CI], 0.79-0.83) in patients receiving no pharmacologic prophylaxis and 
      AUC = 0.78 (CI, 0.76- 0.82) in patients receiving pharmacologic prophylaxis. 
      CONCLUSIONS: Automated calculation of VTE risk had similar ability to predict 
      hospital-acquired VTE as manual calculation despite differences in how often 
      specific scoring criteria were considered present by the 2 methods. Journal of 
      Hospital Medicine 2017;12: 231- 237.
CI  - (c) 2017 Society of Hospital Medicine
FAU - Elias, Pierre
AU  - Elias P
AD  - Department of Medicine, Columbia University Medical Center, New York, New York, 
      USA.
AD  - Division of Hospital Medicine, University of California San Francisco, San 
      Francisco, CA, USA.
FAU - Khanna, Raman
AU  - Khanna R
AD  - Division of Hospital Medicine, University of California San Francisco, San 
      Francisco, CA, USA.
FAU - Dudley, Adams
AU  - Dudley A
AD  - Philip R. Lee Institute for Health Policy Studies, University of California, San 
      Francisco, San Francisco, CA, USA.
FAU - Davies, Jason
AU  - Davies J
AD  - Department of Neurological Surgery, University of California, San Francisco, San 
      Francisco, CA, USA.
FAU - Jacolbia, Ronald
AU  - Jacolbia R
AD  - Division of Hospital Medicine, University of California San Francisco, San 
      Francisco, CA, USA.
FAU - McArthur, Kara
AU  - McArthur K
AD  - Abramson Center for the Future of Health, University of Houston, Houston, TX, 
      USA.
FAU - Auerbach, Andrew D
AU  - Auerbach AD
AD  - Division of Hospital Medicine, University of California San Francisco, San 
      Francisco, CA, USA.
LA  - eng
GR  - K24 HL098372/HL/NHLBI NIH HHS/United States
GR  - U54 GM104941/GM/NIGMS NIH HHS/United States
PT  - Journal Article
PL  - United States
TA  - J Hosp Med
JT  - Journal of hospital medicine
JID - 101271025
RN  - 0 (Anticoagulants)
SB  - IM
MH  - Anticoagulants/*therapeutic use
MH  - Cohort Studies
MH  - Electronic Health Records/*statistics & numerical data
MH  - Hospitalization
MH  - Humans
MH  - Male
MH  - Middle Aged
MH  - *Patient Admission
MH  - Risk Assessment/methods
MH  - Venous Thromboembolism/*prevention & control
EDAT- 2017/04/16 06:00
MHDA- 2017/11/29 06:00
CRDT- 2017/04/16 06:00
PHST- 2017/04/16 06:00 [entrez]
PHST- 2017/04/16 06:00 [pubmed]
PHST- 2017/11/29 06:00 [medline]
AID - 10.12788/jhm.2714 [doi]
PST - ppublish
SO  - J Hosp Med. 2017 Apr;12(4):231-237. doi: 10.12788/jhm.2714.