Customization of a Severity of Illness Score Using Local Electronic Medical Record Data

Journal of Intensive Care Medicine

Volumn 32, Issue 1, 2017, Pages 38-47

  Lee, Joon ^a   Maslove, David M ^b  

^a UNIVERSITY OF WATERLOO   (Canada)

^b QUEEN S UNIVERSITY   (Canada)

Author keywords

clinical outcome prediction; critical care; data mining; electronic medical records; severity of illness index

Indexed keywords

ADULT; AGED; APACHE; AREA UNDER THE PRECISION RECALL CURVE; AREA UNDER THE RECEIVER OPERATING CHARACTERISTICS CURVE; ARTICLE; ASSESSMENT OF HUMANS; BREATHING RATE; CARDIOVASCULAR SURGERY; DATA BASE; DATA MINING; DISEASE SEVERITY; ELECTRONIC MEDICAL RECORD; GLASGOW COMA SCALE; HEART RATE; HUMAN; INTENSIVE CARE UNIT; LENGTH OF STAY; LEUKOCYTE COUNT; MAJOR CLINICAL STUDY; MORTALITY; PARAMETERS; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; SEQUENTIAL ORGAN FAILURE ASSESSMENT SCORE; SEVERITY OF ILLNESS SCORE; SIMPLIFIED ACUTE PHYSIOLOGY SCORE; SYSTOLIC BLOOD PRESSURE; ELECTRONIC HEALTH RECORD; HEALTH CARE QUALITY; INTENSIVE CARE; MASSACHUSETTS; MIDDLE AGED; ORGANIZATION AND MANAGEMENT; PROGNOSIS; REPRODUCIBILITY; RETROSPECTIVE STUDY; SEVERITY OF ILLNESS INDEX; STATISTICS AND NUMERICAL DATA;

BOSTON; CRITICAL CARE; ELECTRONIC HEALTH RECORDS; HUMANS; INTENSIVE CARE UNITS; MIDDLE AGED; PROGNOSIS; QUALITY ASSURANCE, HEALTH CARE; REPRODUCIBILITY OF RESULTS; RETROSPECTIVE STUDIES; SEVERITY OF ILLNESS INDEX;

EID: 85001085996     PISSN: 08850666     EISSN: 15251489     Source Type: Journal    
DOI: 10.1177/0885066615585951     Document Type: Article

References (25)

1. Zimmerman JE, Kramer AA, McNair DS, Malila FM,. Acute Physiology and Chronic Health Evaluation (APACHE) IV: Hospital mortality assessment for today's critically ill patients. Crit Care Med. 2006; 34 (5): 1297-1310. doi:10.1097/01.CCM.0000215112.84523.F0.
2. Knaus WA, Draper EA, Wagner DP, Zimmerman JE,. APACHE II: a severity of disease classification system. Crit Care Med. 1985; 13 (10): 818-829.
3. Moreno R, Apolone G,. Impact of different customization strategies in the performance of a general severity score. Crit Care Med. 1997; 25 (12): 2001-2008.
4. Sibae Al MR, Cappell MS,. Accuracy of MELD scores in predicting mortality in decompensated cirrhosis from variceal bleeding, hepatorenal syndrome, alcoholic hepatitis, or acute liver failure as well as mortality after non-transplant surgery or TIPS. Digest Dis Sci. 2011; 56 (4): 977-987. doi:10.1007/s10620-010-1390-3.
5. Lim WS, van der Eerden MM, Laing R, et al. Defining community acquired pneumonia severity on presentation to hospital: an international derivation and validation study. Thorax. 2003; 58 (5): 377-382.
6. Osborn TM, Phillips G, Lemeshow S, et al. Sepsis severity score. Crit Care Med. 2014; 42 (9): 1969-1976. doi:10.1097/CCM.0000000000000416.
7. Bakhshi-Raiez F, Peek N, Bosman RJ, de Jonge E, De Keizer NF,. The impact of different prognostic models and their customization on institutional comparison of intensive care units. Crit Care Med. 2007; 35 (11): 2553-2560. doi:10.1097/01.CCM.0000288123.29559.5A.
8. Moreno RP, Metnitz PGH, Almeida E, et al. SAPS 3-From evaluation of the patient to evaluation of the intensive care unit. Part 2: Development of a prognostic model for hospital mortality at ICU admission. Intensive Care Med. 2005; 31 (10): 1345-1355. doi:10.1007/s00134-005-2763-5.
9. Strand K, Flaatten H,. Severity scoring in the ICU: a review. Acta Anaesthesiol Scand. 2008; 52 (4): 467-478. doi:10.1111/j.1399-6576.2008.01586.x.
10. Lemeshow S, Teres D, Klar J, Avrunin JS, Gehlbach SH, Rapoport J,. Mortality Probability Models (MPM II) based on an international cohort of intensive care unit patients. JAMA. 1993; 270 (20): 2478-2486.
11. Nassar AP, Malbouisson LM, Moreno R,. Evaluation of simplified acute physiology score 3 performance: a systematic review of external validation studies. Crit Care. 2014; 18 (3): R117. doi:10.1186/cc13911.
12. Saeed M, Villarroel M, Reisner AT, et al. Multiparameter Intelligent Monitoring in Intensive Care II: a public-access intensive care unit database. Crit Care Med. 2011; 39 (5): 952-960. doi:10.1097/CCM.0b013e31820a92c6.
13. Gall J-R, Loirat P, Alperovitch A,. Simplified acute physiological score for intensive care patients. Lancet. 1983; 322 (8352): 741-741. doi:10.1016/S0140-6736(83)92278-X.
14. Vincent JL, Moreno R, Takala J, et al. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine. In: Vol 22. 1996: 707-710.
15. Elixhauser A, Steiner C, Harris DR, Coffey RM,. Comorbidity measures for use with administrative data. Med Care. 1998; 36 (1): 8-27.
16. Le Gall JR, Loirat P, Alperovitch A, et al. A simplified acute physiology score for ICU patients. Crit Care Med. 1984; 12 (11): 975-977.
17. Davis J, Goadrich M,. The relationship between Precision-Recall and ROC curves. Proceedings of the 23rd International Conference on Machine learning-ICML'06. 2006; 233-240.
18. David W Hosmer J, Lemeshow S, Sturdivant RX,. Applied Logistic Regression. Hoboken, NJ: John Wiley & Sons; 2013.
19. Kohane IS,. Secondary use of health information: are we asking the right question? JAMA Intern Med. 2013; 173 (19): 1806-1807. doi:10.1001/jamainternmed.2013.8276.
20. Pollack MM,. It is what it was. Pediatr Crit Care Med. 2011; 12 (2): 228-229. doi:10.1097/PCC.0b013e3181f2669f.
21. Celi LA, Galvin S, Davidzon G, Lee J, Scott D, Mark R,. A database-driven decision support system: customized mortality prediction. J Pers Med. 2012; 2 (4): 138-148. doi:10.3390/jpm2040138.
22. Wiens J, Guttag J, Horvitz E,. A study in transfer learning: leveraging data from multiple hospitals to enhance hospital-specific predictions. J Am Med Inform Assoc. 2014; 21 (4): 699-706. doi:10.1136/amiajnl-2013-002162.
23. National Research Council (US) Committee on A Framework for Developing a New Taxonomy of Disease. Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease. Washington (DC): National Academies Press (US); 2011.
24. America COTLHCSI, Institute of Medicine. Best Care at Lower Cost. Washington (DC): National Academies Press; 2013.
25. Schneeweiss S,. Learning from big health care data. N Engl J Med. 2014; 370 (23): 2161-2163. doi:10.1056/NEJMp1401111.