Chart documentation quality and its relationship to the validity of administrative data discharge records

Health Informatics Journal

Volumn 16, Issue 2, 2010, Pages 101-113

  So, Lawrence ^a   Beck, Cynthia A ^a   Brien, Susan ^a   Kennedy, James ^b   Feasby, Thomas E ^a   Ghali, William A ^a   Quan, Hude ^a  

^a UNIVERSITY OF CALGARY   (Canada)

^b UNIVERSITY OF OXFORD   (United Kingdom)

Author keywords

administrative data; carotid endarterectomy; ICD 9 CM; validity

Indexed keywords

ARTICLE; DOCUMENTATION; HOSPITAL DISCHARGE; HUMAN; MEDICAL RECORD; NURSE; REPRODUCIBILITY; STANDARD;

DOCUMENTATION; HUMANS; MEDICAL RECORDS; NURSES; PATIENT DISCHARGE; REPRODUCIBILITY OF RESULTS;

EID: 77953897376     PISSN: 14604582     EISSN: 17412811     Source Type: Journal    
DOI: 10.1177/1460458210364784     Document Type: Article

References (26)

1. Drösler SE, Klazinga NS, Romano PS, et al. 2009. Application of patient safety indicators internationally: a pilot among seven countries. Int J Qual Health Care 2009 April; 1-7, 10.1093/intqhc/mzp018 (epub ahead of print).
2. Quan H., Drösler S., Sundararajan V., et al., 2008. Adaptation of AHRQ patient safety indicators for use in ICD-10 administrative data by an international consortium. Advances in Patient Safety: New Directions and Alternative Approaches August. Download at http://www.ahrq.gov/downloads/pub/ advances2/vol1/Advances-Quan-52.pdf.
3. Reed WC CIOs and the D.R.I.P. (data-rich, information-poor) syndrome. Hosp Health Netw 1995; 69: 82.
4. Wu L., Ashton CM Chart review: a need for reappraisal. Eval Health Prof 1997; 20 (2). 146-163.
5. O'Malley KJ, Cook KF, Price MD, Wildes KR, Hurdle JF, Ashton CM Measuring diagnoses: ICD code accuracy. BMC Health Serv Res 2005; 40 (5). 1620-1639.
6. Beard CM, Yunginger JW, Reed CE, O'Connell EJ, Silverstein MD, 1992. Interobserver variability in medical record review: an epidemiological study of asthma. J Clin Epidemiol 1992; 45 (9). 1013-1020.
7. Roos LL, Gupta S., Soodeen RA, Jebamani L. Data quality in an information-rich environment: Canada as an example. Can J Aging 2005; 24 (supplement 1). 153-170.
8. Horwitz RJ, Yu EC Assessing the reliability of epidemiologic data obtained from medical records. J Chronic Dis 1984; 3 (11). 825-831.
9. Kennedy J., Quan H., Ghali WA, Feasby TE Variations in rates of appropriate and inappropriate carotid endarterectomy for stroke prevention in 4 Canadian provinces. Can Med Assoc J 2004; 171 (5). 455-459.
10. Feasby TE, Quan H., Ghali WA Hospital and surgeon determinants of carotid endarterectomy outcomes. Arch Neurol 2002; 59: 1877-1881.
11. I Kennedy J., Quan H., Ghali WA, Feasby TE An audit tool for assessing the appropriateness of carotid endarterectomy. BMC Health Serv Res 2004; 4 (17).
12. Charlson ME, Pompei P., Ales KL, Mackenzie CR A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. 1987; 40 (5). 373-383.
13. Quan H., Sundararajan V., Halfon P., et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 2005; 43 (11). 1130-1139.
14. Davidson R., Mackinnon JG Econometric Theory and Methods. New York: Oxford University Press, 2004.
15. Dresselhaus TR, Peabody JW, Luck J., Bertenthal D. An evaluation of vignettes for predicting variation in the quality of preventive care. J Gen Intern Med 2004; 19: 1013-1018. (Pubitemid 39431137)
16. Luck J., Peabody JW, Dresselhaus TR, Lee M., Glassman P. How well does chart abstraction measure quality? A prospective comparison of standardized patients with the medical record. Am J Med 2000; 108: 642-649.
17. Peabody JW, Luck J., Glassman P., Dresselhaus TR, Lee M. Comparison of vignettes, standardized patients, and chart abstraction. J Am Med Assoc 2000; 283 (13). 1715-1722.
18. Rethans J., Martin E., Metsemakers J. To what extent do clinical notes by general practitioners reflect actual medical performance? A study using simulated patients. Br J Gen Pract 1994; 44: 153-156.
19. Dresser MVB, Feingold L., Rosenkranz SL, Coltin KL Clinical quality measurement: compar ing chart review and automated methodologies. Med Care 1997; 35 (6). 539-552.
20. Schneeweiss S., Avorn J. A review of uses of health care utilization databases for epidemiologic research on therapeutics. J Clin Epidemiol 2005; 58: 323-337.
21. Fry DE, Pine MB, Jordan HS, Hoaglin DC, Jones B., Meimban R. The hazards of using administrative data to measure surgical quality. Am Surg 2006; 72: 1031-1037; discussion 1061-1069, 1133-1148.
22. Linder JA, Ma J., Bates DW, Middleton B., Stafford RS Electronic health record use and the qual ity of ambulatory care in the United States. Arch Intern Med 2007; 9 July; 167 (13). 1400-1405.
23. Keyhani S., Hebert PL, Ross JS, Federman A., Zhu CW, Siu AL Electronic health record components and the quality of care. Med Care December 2008; 46 (12). 1267-1272.
24. Holt T.A., Stables D., Hippisley-Cox J., O'Hanlon S., Majeed A. Identifying undiagnosed diabetes: cross-sectional survey of 3.6 million patients' electronic records. Br J Gen Pract March 2008; 58 (548). 192-196.
25. Mitiku TF, Tu K. Using data from electronic medical records: theory versus practice. Health Care Qual 2008; 11 (4). 23-25.
26. Jordan K., Porcheret M., Croft P., 2004. Quality of morbidity coding in general practice computerized medical records: a systematic review. Fam Pract August 2004; 21 (4). 396-412. Review.