Validity of administrative data in recording sepsis: A systematic review

Critical Care

Volumn 19, Issue 1, 2015, Pages

  Jolley, Rachel J ^a   Sawka, Keri Jo ^a   Yergens, Dean W ^a   Quan, Hude ^a,c   Jetté, Nathalie ^a,c,d   Doig, Christopher J ^a,b,d  

^a UNIVERSITY OF CALGARY   (Canada)

^b UNIVERSITY OF CALGARY   (Canada)

^c UNIVERSITY OF CALGARY   (Canada)

^d UNIVERSITY OF CALGARY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BACTEREMIA; DIAGNOSTIC ACCURACY; HUMAN; ICD-10; ICD-9; INTENSIVE CARE UNIT; INTENSIVIST; MEDICAL DOCUMENTATION; PREDICTIVE VALUE; PRIORITY JOURNAL; SENSITIVITY AND SPECIFICITY; SEPSIS; SEPTICEMIA; SYSTEMATIC REVIEW; VALIDITY; INTERNATIONAL CLASSIFICATION OF DISEASES;

HUMANS; INTERNATIONAL CLASSIFICATION OF DISEASES; PREDICTIVE VALUE OF TESTS; SENSITIVITY AND SPECIFICITY; SEPSIS;

EID: 84928003693     PISSN: 13648535     EISSN: 1466609X     Source Type: Journal    
DOI: 10.1186/s13054-015-0847-3     Document Type: Article

References (40)

1. Angus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR. Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med. 2001;29:1303-10.
2. Martin GS, Mannino DM, Eaton S, Moss M. The epidemiology of sepsis in the United States from 1979 through 2000. N Engl J Med. 2003;348:1546-54.
3. Iwashyna TJ, Ely EW, Smith DM, Langa KM. Long-term cognitive impairment and functional disability among survivors of severe sepsis. JAMA. 2010;304:1787-94.
4. Lynn LA. The diagnosis of sepsis revisited - a challenge for young medical scientists in the 21st century. Patient Saf Surg. 2014;8:1.
5. Quach S, Hennessy DA, Faris P, Fong A, Quan H, Doig C. A comparison between the APACHE II and Charlson Index Score for predicting hospital mortality in critically ill patients. BMC Health Serv Res. 2009;9:129.
6. Zhan C, Miller MR. Administrative data based patient safety research: a critical review. Qual Saf Health Care. 2003;12:ii58-63.
7. World Health Organization. International Classification of Diseases (ICD). http://www.who.int/classifications/icd/en/. Accessed 25 Mar 2015.
8. Jetté N, Quan H, Hemmelgarn B, Drosler S, Maass C, Moskal L, et al. The development, evolution, and modifications of ICD-10: challenges to the international comparability of mortality data. Med Care. 2010;48:1105-10.
9. Odeh M. Sepsis, septicaemia, sepsis syndrome, and septic shock: the correct definition and use. Postgrad Med J. 1996;72:66.
10. Bone RC, Balk RA, Cerra FB, Dellinger RP, Fein AM, Knaus WA, et al. Definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. The ACCP/SCCM Consensus Conference Committee. American College of Chest Physicians/Society of Critical Care Medicine. Chest. 1992;101:1644-55.
11. Sands KE, Bates DW, Lanken PN, Graman PS, Hibberd PL, Kahn KL, et al. Epidemiology of sepsis syndrome in 8 academic medical centers. JAMA. 1997;278:234-40.
12. Iwashyna TJ, Odden A, Rohde J, Bonham C, Kuhn L, Malani P, et al. Identifying patients with severe sepsis using administrative claims: patient-level validation of the angus implementation of the international consensus conference definition of severe sepsis. Med Care. 2014;526:e39-43.
13. Quach S, Blais C, Quan H. Administrative data have high variation in validity for recording heart failure. Can J Cardiol. 2010;26:306-12.
14. St Germaine-Smith CS, Metcalfe A, Pringsheim T, Roberts JI, Beck CA, Hemmelgarn BR, et al. Recommendations for optimal ICD codes to study neurologic conditions a systematic review. Neurology. 2012;79:1049-55.
15. Synthesis. http://synthesis.info/. Updated 2013. Accessed 25 Mar 2015.
16. Yergens DW, Dutton DJ, Patten SB. An overview of the statistical methods reported by studies using the canadian community health survey. BMC Med Res Methodol. 2014;14:15.
17. Benchimol EI, Manuel DG, To T, Griffiths AM, Rabeneck L, Guttmann A. Development and use of reporting guidelines for assessing the quality of validation studies of health administrative data. J Clin Epidemiol. 2011;64:821-9.
18. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33:159-74.
19. Cevasco M, Borzecki AM, Chen Q, Zrelak PA, Shin M, Romano PS, et al. Positive predictive value of the AHRQ patient safety indicator "postoperative sepsis": implications for practice and policy. J Am Coll Surg. 2011;212:954-61.
20. Gedeborg R, Furebring M, Michaëlsson K. Diagnosis-dependent misclassification of infections using administrative data variably affected the incidence and mortality estimates of ICU patients. J Clin Epidemiol. 2007;60:155-62.
21. Grijalva CG, Chung CP, Stein CM, Gideon PS, Dyer SM, Mitchel EF, et al. Computerized definitions showed high positive predictive values for identifying hospitalizations for congestive heart failure and selected infections in Medicaid enrollees with rheumatoid arthritis. Pharmacoepidemiol Drug Saf. 2008;17:890-5.
22. Ibrahim I, Jacobs IG, Webb SAR, Finn J. Accuracy of International Classification of Diseases, 10th Revision codes for identifying severe sepsis in patients admitted from the emergency department. Crit Care Resusc. 2012;14:112-8.
23. Lawson EH, Louie R, Zingmond DS, Brook RH, Hall BL, Han L, et al. A comparison of clinical registry versus administrative claims data for reporting of 30-day surgical complications. Ann Surg. 2012;256:973-81.
24. Madsen KM, Schonheyder HC, Kristensen B, Nielsen GL, Sorensen HT. Can hospital discharge diagnosis be used for surveillance of bacteremia? A data quality study of a Danish hospital discharge registry. Infect Control Hosp Epidemiol. 1998;19:175-80.
25. Ollendorf DA, Fendrick AM, Massey K, Williams GR, Oster G. Is sepsis accurately coded on hospital bills? Value Health. 2002;5:79-81.
26. Quan H, Eastwood C, Cunningham CT, Liu M, Flemons W, De Coster C, et al. Validity of AHRQ patient safety indicators derived from ICD-10 hospital discharge abstract data (chart review study). BMJ Open. 2013;3:e003716.
27. Ramanathan R, Leavell P, Stockslager G, Mays C, Harvey D, Duane TM. Validity of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) screening for sepsis in surgical mortalities. Surg Infect (Larchmt). 2014;15:513-6.
28. Schneeweiss S, Robicsek A, Scranton R, Zuckerman D, Soloman DH. Veteran's Affairs hospital discharge database coded serious bacterial infections accurately. J Clin Epidemiol. 2007;60:397-409.
29. Whittaker SA, Mikkelsen ME, Gaieski DF, Koshy S, Kean C, Fuchs BD. Severe sepsis cohorts derived from claims-based strategies appear to be biased toward a more severely ill patient population. Crit Care Med. 2013;41:945-53.
30. Levy MM, Fink MP, Marshall JC, Abraham E, Angus D, Cook D, et al. International Sepsis Definitions Conference. 2001 SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference. Intensive Care Med. 2003;29:530-8.
31. Rohde JM, Odden AJ, Bonham C, Kuhn L, Malani PN, Chen LM, et al. The epidemiology of acute organ system dysfunction from severe sepsis outside of the intensive care unit. J Hosp Med. 2013;8:243-7.
32. O'Malley KJ, Cook KF, Price MD, Wildes KR, Hurdle JF, Ashton CM. Measuring diagnoses: ICD code accuracy. Health Serv Res. 2005;40:1620-39.
33. Poeze M, Ramsay G, Gerlach H, Rubulotta F, Levy M. An international sepsis survey: a study of doctors' knowledge and perception about sepsis. Crit Care. 2004;8:R409-13.
34. Assunção M, Akamine N, Cardoso GS, Mello PV, Teles JM, Nunes AL, et al. Survey on physician's knowledge of sepsis: do they recognize it promptly? J Crit Care. 2010;25:545-52.
35. Bone RC. Why new definitions of sepsis and organ failure are needed. Am J Med. 1993;95:348-50.
36. Trzeciak S, Zanotti-Cavazzoni S, Parrillo JE, Dellinger RP. Inclusion criteria for clinical trials in sepsis: did the American College of Chest Physicians/Society of Critical Care Medicine consensus conference definitions of sepsis have an impact? Chest. 2005;127:242-5.
37. Goto M, Ohl ME, Schweizer ML, Perencevich EN. Accuracy of administrative code data for the surveillance of healthcare-associated infections: a systematic review and metaanalysis. Clin Infect Dis. 2014;58:688-96.
38. Quan H, Khan N, Hemmelgarn BR, Tu K, Chen G, Campbell N, et al. Validation of a case definition to define hypertension using administrative data. Hypertension. 2009;54:1423-8.
39. Southern DA, Roberts B, Edwards A, Dean S, Norton P, Svenson LW, et al. Validity of administrative data claim-based methods for identifying individuals with diabetes at a population level. Can J Public Health. 2010;101:61-4.
40. Drösler SE, Romano PS, Sundararajan V, Burnand B, Colin C, Pincus H, et al. How many diagnosis fields are needed to capture safety events in administrative data? Findings and recommendations from the WHO ICD-11 Topic Advisory Group on Quality and Safety. Int J Qual Health Care. 2014;26:16-25.