Capturing diagnosis-timing in ICD-coded hospital data: Recommendations from the WHO ICD-11 topic advisory group on quality and safety

International Journal for Quality in Health Care

Volumn 27, Issue 4, 2015, Pages 328-333

  Sundararajan, Vijaya ^a   Romano, P S ^b   Quan, H ^c   Burnand, B ^d   Drosler S E ^e   Brien, S ^f   Pincus, H A ^g   Ghali, W A ^c,h  

^a UNIVERSITY OF MELBOURNE   (Australia)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF CALGARY   (Canada)

^d UNIVERSITY OF LAUSANNE   (Switzerland)

^e NIEDERRHEIN UNIVERSITY OF APPLIED SCIENCES   (Germany)

^f Health Council of Canada   (Canada)

^g New York Presbyterian Columbia University Medical Center   (United States)

^h UNIVERSITY OF CALGARY   (Canada)

Author keywords

Condition onset flag; Diagnosis timing indicators; Hospital performance; International classification of diseases; Patient safety; Present on admission flag; World health organization

Indexed keywords

ADULT; ARTICLE; CODING; CONSENSUS DEVELOPMENT; CONTROLLED STUDY; HEALTH CARE QUALITY; HIP FRACTURE; HOSPITAL ADMISSION; HOSPITAL CARE; HOSPITAL INFORMATION SYSTEM; HUMAN; ICD-11; INFORMATION PROCESSING; MAJOR CLINICAL STUDY; MEASUREMENT ACCURACY; MEDICAL RECORD; MORTALITY; PATIENT SAFETY; PNEUMONIA; PRIORITY JOURNAL; RELIABILITY; SURGICAL PATIENT; VOLUNTARY REPORTING; ADVISORY COMMITTEE; DIAGNOSIS; HOSPITAL; HOSPITAL MORTALITY; INTERNATIONAL CLASSIFICATION OF DISEASES; PROCEDURES; STANDARDS; STATISTICS AND NUMERICAL DATA; TIME FACTOR; TOTAL QUALITY MANAGEMENT;

ADVISORY COMMITTEES; DATA COLLECTION; DIAGNOSIS; HOSPITAL MORTALITY; HOSPITALS; HUMANS; INTERNATIONAL CLASSIFICATION OF DISEASES; PATIENT SAFETY; QUALITY IMPROVEMENT; QUALITY OF HEALTH CARE; TIME FACTORS;

EID: 84939640170     PISSN: 13534505     EISSN: 14643677     Source Type: Journal    
DOI: 10.1093/intqhc/mzv037     Document Type: Article

References (36)

1. Ghali WA, Pincus HA, Southern DA et al. ICD-11 for quality and safety: overview of the WHO Quality and Safety Topic Advisory Group. Int J Qual Health Care 2013;25:621-5.
2. Drosler SE, Romano PS, Sundararajan V 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.
3. Quan H, Moskal L, Forster AJ et al. International variation in the definition of 'main condition' in ICD-coded health data. Int J Qual Health Care 2014;26:511-515.
4. Canadian Institute for Health Information. Diagnosis Typing: Current Canadian and International Practices 2004. Available from: http://secure. cihi.ca/cihiweb/en/downloads/Diagnosis_Typing_Background_v1.pdf (27 March 2012, date last accessed).
5. State Government of Victoria. Victorian Additions to Australian Coding Standards 2001. Available from: http://www.health.vic.gov.au/hdss/ icdcoding/vicadditions/vicadd01.pdf (23 March 2012, date last accessed).
6. Australian Institute for Health and Welfare. Episode of Admitted Patient Care-Diagnosis Onset Type, Code N 2006. Available from: http:// meteor.aihw.gov.au/content/index.phtml/itemId/270192 (2 April 2012, date last accessed).
7. Australian Institute for Health and Welfare. Episode of Admitted Patient Care-Condition Onset Flag, Code N 2008. Available from: http://meteor. aihw.gov.au/content/index.phtml/itemId/354816 (2 April 2012, date last accessed).
8. Kassed C, Kowlessar N, Pfuntner A et al. The Case for the Presenton-Admission (POA) Indicator: Update 2011 Methods Report. HCUP Methods Series Report #2011-05. ONLINE. U.S. Agency for Healthcare Research and Quality, November 1, 2011 (2 April 2012, date last accessed).
9. Medicare Learning Network. Hospital-Acquired Conditions and Present on Admission Indicator Reporting Provision: Department of Health and Human Services Centers for Medicare & Medicaid Services; Available from: http://www.cms.gov/Outreach-and-Education/Medicare-Learning-Network-MLN/MLNProducts/Downloads/wPOAFactSheet.pdf (2 October 2014, date last accessed).
10. Centers, for, Medicare, &, Medicaid, Services. Hospital-Acquired Conditions (Present on Admission Indicator) Coding: Centers for Medicare & Medicaid Services; 2014. Available from: http://www.cms.gov/Medicare/ Medicare-Fee-for-Service-Payment/HospitalAcqCond/Coding.html (2 October 2014, date last accessed).
11. Houchens RL, Elixhauser A, Romano PS. How often are potential patient safety events present on admission? Jt Comm J Qual Patient Saf 2008;34:154-63.
12. Pine M, Fry DE, Jones B et al. Screening algorithms to assess the accuracy of present-on-admission coding. Perspect Health Inf Manag 2009;6:2.
13. Rangachari P. Coding for quality measurement: the relationship between hospital structural characteristics and coding accuracy from the perspective of quality measurement. Perspect Health Inf Manag 2007;4:3.
14. Coffey R, Milenkovic M, Andrews RM. The Case for the Presenton-Admission (POA) Indicator Report# 2006-01: U.S. Agency for Healthcare Research and Quality.; June 2006 [cited 2012 27-03-2012]. Available from: http://www.hcup-us.ahrq.gov/reports/methods/2006_1.pdf.
15. Research Triangle International. Centre for Medicare & Medicaid Services RTI Evaluation of FY 2011 Data, Chart A: Research Triangle International; 2011. Available from: http://www.rti.org/reports/cms/ (2 October 2014, date last accessed).
16. Quan H, Parsons GA, Ghali WA. Assessing accuracy of diagnosis-type indicators for flagging complications in administrative data. J Clin Epidemiol 2004;57:366-72.
17. Glance LG, Osler TM, Mukamel DB et al. Impact of the presenton- admission indicator on hospital quality measurement: experience with the Agency for Healthcare Research and Quality (AHRQ) Inpatient Quality Indicators. Med Care 2008;46:112-9.
18. Meddings J, Saint S, McMahon LF Jr. Hospital-acquired catheterassociated urinary tract infection: documentation and coding issues may reduce financial impact of Medicare's new payment policy. Infect Control Hosp Epidemiol 2010;31:627-33.
19. Haas J, Luft H,Romano PS et al. Report for the CaliforniaHospitalOutcomes Project. Community-acquired pneumonia, 1996: Model Development and Validation. Office of Statewide Health Planning and Development, 2010.
20. Goldman LE, Chu PW, Osmond D et al. The accuracy of presenton- admission reporting in administrative data. Health Serv Res 2011;46 (6pt1):1946-62.
21. RTI, International. Accuracy of Coding in the Hospital-Acquired Conditions-Present on Admission Program. Final Report. Centers for Medicare & Medicaid Services, 2012.
22. Bahl V, Thompson MA, Kau TY et al. Do the AHRQ patient safety indicators flag conditions that are present at the time of hospital admission? Med Care 2008;46:516-22.
23. Goldman LE, Chu PW, Bacchetti P et al. Effect of Present-on-Admission (POA) reporting accuracy on hospital performance assessments using risk-adjusted mortality. Health Serv Res 2014;50:922-938.
24. Ghali WA, Quan H, Brant R. Risk adjustment using administrative data: impact of a diagnosis-type indicator. J Gen Intern Med 2001;16:519-24.
25. Glance LG, Dick AW, Osler TM et al. Accuracy of hospital report cards based on administrative data. Health Serv Res 2006;41(4 Pt 1):1413-37.
26. Pine M, Jordan HS, Elixhauser A et al. Enhancement of claims data to improve risk adjustment of hospital mortality. JAMA 2007;297:71-6.
27. Roos LL, Stranc L, James RC et al. Complications, comorbidities, and mortality: improving classification and prediction. Health Serv Res 1997;32:229-38. ; discussion 39-42.
28. Stukenborg GJ, Wagner DP, Harrell FE Jr et al. Hospital discharge abstract data on comorbidity improved the prediction of death among patients hospitalized with aspiration pneumonia. J Clin Epidemiol 2004;57:522-32.
29. Stukenborg GJ, Kilbridge KL, Wagner DP et al. Present-at-admission diagnoses improve mortality risk adjustment and allow more accurate assessment of the relationship between volume of lung cancer operations and mortality risk. Surgery 2005;138:498-507.
30. AHRQ. Quality Indicators-Guide to Patient Safety Indicators. Department of Health and Human Services Agency for Healthcare Research and Quality, 2003.
31. Naessens JM, Campbell CR, Berg B et al. Impact of diagnosis-timing indicators on measures of safety, comorbidity, and case mix groupings from administrative data sources. Med Care 2007;45:781-8.
32. Scanlon MC, Harris JM II, Levy F et al. Evaluation of the agency for healthcare research and quality pediatric quality indicators. Pediatrics 2008;121: e1723-31.
33. Jackson TJ, Michel JL, Roberts R et al. Development of a validation algorithm for 'present on admission' flagging. BMC Med Inform Decis Mak 2009;9:48.
34. McConchie S, Shepheard J,Waters S et al. The AusPSIs: the Australian version of the agency of healthcare research and quality patient safety indicators. Aust Health Rev 2009;33:334-41.
35. Dalton JE, Glance LG, Mascha EJ et al. Impact of present-on-admission indicators on risk-adjusted hospital mortality measurement. Anesthesiology 2013;118:1298-306.
36. Stukenborg GJ. Hospital mortality risk adjustment for heart failure patients using present on admission diagnoses: improved classification and calibration. Med Care 2011;49:744-51.