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REFERENCES

  • 1
    Wallace KL, Riedel AA, Joseph-Ridge N, Wortmann R. Increasing prevalence of gout and hyperuricemia over 10 years among older adults in a managed care population. J Rheumatol 2004; 31: 15827.
  • 2
    Iezzoni LI. Assessing quality using administrative data [review]. Ann Intern Med 1997; 127: 66674.
  • 3
    Petersen LA, Wright S, Normand SL, Daley J. Positive predictive value of the diagnosis of acute myocardial infarction in an administrative database. J Gen Intern Med 1999; 14: 5558.
  • 4
    Harrold LR, Yood RA, Andrade SE, Reed JI, Cernieux J, Strauss W, et al. Evaluating the predictive value of osteoarthritis diagnoses in an administrative database. Arthritis Rheum 2000; 43: 18815.
  • 5
    Rawson NS, D'Arcy C. Assessing the validity of diagnostic information in administrative health care utilization data: experience in Saskatchewan. Pharmacoepidemiol Drug Saf 1998; 7: 38998.
  • 6
    Wallace SL, Robinson H, Masi AT, Decker JL, McCarty DJ, Yu TF. Preliminary criteria for the classification of the acute arthritis of primary gout. Arthritis Rheum 1977; 20: 895900.
  • 7
    KellgrenJH, JeffreyMR, BallJ, editors. The epidemiology of chronic rheumatism. Oxford: Blackwell; 1963. p. 327.
  • 8
    Bennett PH, Wood PH, editors. Population studies of the rheumatic diseases: proceedings of the third international symposium, New York, Jun 510, 1966. Amsterdam: Excerpta Medica Foundation; 1968. p. 457–8.
  • 9
    Platt R, Davis R, Finkelstein J, Go AS, Gurwitz JH, Roblin D, et al. Multicenter epidemiologic and health services research on therapeutics in the HMO Research Network Center for Education and Research on Therapeutics. Pharmacoepidemiol Drug Saf 2001; 10: 3737.
  • 10
    Chan KA and the HMO Research Network CERTs Patient Safety Study Investigators. Development of a multipurpose dataset to evaluate potential medication errors in ambulatory setting. In: HenriksenK, BattlesJB, MarksES, LewinDI, editors. Advances in patient safety: from research to implementation. Vol. 2. Rockville (MD): Agency for Healthcare Research and Quality; 2005.
  • 11
    Sackett DL, Haynes RB, Guyatt GH, Tugwell P. Clinical Epidemiology: a basic science for clinical medicine. 2nd ed. Boston: Little, Brown and Company; 1991. p. 30.
  • 12
    Gabriel SE, Crowson CS, O'Fallon WM. A mathematical model that improves the validity of osteoarthritis diagnoses obtained from a computerized diagnostic database. J Clin Epidemiol 1996; 49: 10259.
  • 13
    Gabriel SE. The sensitivity and specificity of computerized databases for the diagnosis of rheumatoid arthritis. Arthritis Rheum 1994; 37: 8213.
  • 14
    Terkeltaub RA. Gout: epidemiology, pathology and pathogenesis. In: KlippelJH, CroffordL, StoneJH, WeyandCM, editors. Primer on the rheumatic disease. 12th ed. Atlanta: Arthritis Foundation; 2001. p. 30712.
  • 15
    Quam L, Ellis LB, Venus P, Clouse J, Taylor CG, Leatherman S. Using claims data for epidemiologic research: the concordance of claims-based criteria with the medical record and patient survey for identifying a hypertensive population. Med Care 1993; 131: 498507.
  • 16
    Katz JN, Barrett J, Liang MH, Bacon AM, Kaplan H, Kieval RI, et al. Sensitivity and positive predictive value of Medicare Part B physician claims for rheumatologic diagnoses and procedures. Arthritis Rheum 1997; 40: 1594600.