Diagnostic accuracy of administrative data algorithms in the diagnosis of osteoarthritis: a systematic review
Tóm tắt
Administrative health care data are frequently used to study disease burden and treatment outcomes in many conditions including osteoarthritis (OA). OA is a chronic condition with significant disease burden affecting over 27 million adults in the US. There are few studies examining the performance of administrative data algorithms to diagnose OA. The purpose of this study is to perform a systematic review of administrative data algorithms for OA diagnosis; and, to evaluate the diagnostic characteristics of algorithms based on restrictiveness and reference standards. Two reviewers independently screened English-language articles published in Medline, Embase, PubMed, and Cochrane databases that used administrative data to identify OA cases. Each algorithm was classified as restrictive or less restrictive based on number and type of administrative codes required to satisfy the case definition. We recorded sensitivity and specificity of algorithms and calculated positive likelihood ratio (LR+) and positive predictive value (PPV) based on assumed OA prevalence of 0.1, 0.25, and 0.50. The search identified 7 studies that used 13 algorithms. Of these 13 algorithms, 5 were classified as restrictive and 8 as less restrictive. Restrictive algorithms had lower median sensitivity and higher median specificity compared to less restrictive algorithms when reference standards were self-report and American college of Rheumatology (ACR) criteria. The algorithms compared to reference standard of physician diagnosis had higher sensitivity and specificity than those compared to self-reported diagnosis or ACR criteria. Restrictive algorithms are more specific for OA diagnosis and can be used to identify cases when false positives have higher costs e.g. interventional studies. Less restrictive algorithms are more sensitive and suited for studies that attempt to identify all cases e.g. screening programs.
Tài liệu tham khảo
Iezzoni LI. Assessing quality using administrative data. Ann Intern Med. 1997;127(8):666–74. Epub 1998/02/12.
Riley GF. Administrative and claims records as sources of health care cost data. Med Care. 2009;47(7 Suppl 1):S51–5. doi:10.1097/MLR.0b013e31819c95aa. Epub 2009/06/19.
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(8):821–9. doi:10.1016/j.jclinepi.2010.10.006. Epub 2011/01/05.
Bernatsky S, Lix L, O’Donnell S, Lacaille D, Network C. Consensus statements for the use of administrative health data in rheumatic disease research and surveillance. J Rheumatol. 2013;40(1):66–73. doi:10.3899/jrheum.120835. Epub 2012/11/03.
Saczynski JS, Andrade SE, Harrold LR, Tjia J, Cutrona SL, Dodd KS, et al. A systematic review of validated methods for identifying heart failure using administrative data. Pharmacoepidemiol Drug Saf. 2012;21 Suppl 1:129–40. doi:10.1002/pds.2313. PubMed PMID: 22262599, PubMed Central PMCID: PMC3808171, Epub 2012/01/25.
De Coster C, Quan H, Finlayson A, Gao M, Halfon P, Humphries KH, et al. Identifying priorities in methodological research using ICD-9-CM and ICD-10 administrative data: report from an international consortium. BMC Health Serv Res. 2006;6:77. doi:10.1186/1472-6963-6-77. Epub 2006/06/17. PubMed PMID: 16776836; PubMed Central PMCID: PMC1513221.
Carnahan RM, Moores KG. Mini-Sentinel’s systematic reviews of validated methods for identifying health outcomes using administrative and claims data: methods and lessons learned. Pharmacoepidemiol Drug Saf. 2012;21 Suppl 1:82–9. doi:10.1002/pds.2321. Epub 2012/01/25.
Nguyen M, Ball R, Midthun K, Lieu TA. The Food and Drug Administration’s post-licensure rapid immunization safety monitoring program: strengthening the federal vaccine safety enterprise. Pharmacoepidemiol Drug Saf. 2012;21 Suppl 1:291–7. doi:10.1002/pds.2323. Epub 2012/01/25.
Lawrence RC, Felson DT, Helmick CG, Arnold LM, Choi H, Deyo RA, et al. Estimates of the prevalence of arthritis and other rheumatic conditions in the United States. Part II Arthritis Rheum. 2008;58(1):26–35. doi:10.1002/art.23176. PubMed PMID: 18163497, PubMed Central PMCID: PMC3266664, Epub 2008/01/01.
World Health Organization. The global burden of disease: 2004 update. Geneva: WHO Press; 2008.
Solomon DH, Avorn J, Wang PS, Vaillant G, Cabral D, Mogun H, et al. Prescription opioid use among older adults with arthritis or low back pain. Arthritis Rheum. 2006;55(1):35–41. doi:10.1002/art.21697. Epub 2006/02/08.
Harrold LR, Yood RA, Straus W, Andrade SE, Reed JI, Cernieux J, et al. Challenges of estimating health service utilization for osteoarthritis patients on a population level. J Rheumatol. 2002;29(9):1931–6. Epub 2002/09/18.
Kopec JA, Rahman MM, Sayre EC, Cibere J, Flanagan WM, Aghajanian J, et al. Trends in physician-diagnosed osteoarthritis incidence in an administrative database in British Columbia, Canada, 1996–1997 through 2003–2004. Arthritis Rheum. 2008;59(7):929–34. doi:10.1002/art.23827. Epub 2008/06/26.
Katz JN, Barrett J, Mahomed NN, Baron JA, Wright RJ, Losina E. Association between hospital and surgeon procedure volume and the outcomes of total knee replacement. J Bone Joint Surg Am. 2004;86-A(9):1909–16. Epub 2004/09/03.
Katz JN, Losina E, Barrett J, Phillips CB, Mahomed NN, Lew RA, et al. Association between hospital and surgeon procedure volume and outcomes of total hip replacement in the United States medicare population. J Bone Joint Surg Am. 2001;83-A(11):1622–9. Epub 2001/11/10.
Widdifield J, Labrecque J, Lix L, Paterson JM, Bernatsky S, Tu K, et al. Systematic review and critical appraisal of validation studies to identify rheumatic diseases in health administrative databases. Arthritis Care Res (Hoboken). 2013;65(9):1490–503. doi:10.1002/acr.21993. Epub 2013/02/26.
Moher D, Liberati A, Tetzlaff J, Altman DG, Group P. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. J Clin Epidemiol. 2009;62(10):1006–12. doi:10.1016/j.jclinepi.2009.06.005. Epub 2009/07/28.
Leong A, Dasgupta K, Bernatsky S, Lacaille D, Avina-Zubieta A, Rahme E. Systematic review and meta-analysis of validation studies on a diabetes case definition from health administrative records. PLoS One. 2013;8(10):e75256. doi:10.1371/journal.pone.0075256. PubMed PMID: 24130696, PubMed Central PMCID: PMC3793995, Epub 2013/10/17.
Altman DG, Bland JM, Diagnostic tests. 1: Sensitivity and specificity. BMJ. 1994;308(6943):1552. Epub 1994/06/11. PubMed PMID: 8019315; PubMed Central PMCID: PMC2540489.
Simel DL, Samsa GP, Matchar DB. Likelihood ratios with confidence: sample size estimation for diagnostic test studies. J Clin Epidemiol. 1991;44(8):763–70. Epub 1991/01/01.
Brenner H, Gefeller O. Variation of sensitivity, specificity, likelihood ratios and predictive values with disease prevalence. Stat Med. 1997;16(9):981–91. Epub 1997/05/15.
Mikkelsen WM, Dodge HJ, Duff IF, Kato H. Estimates of the prevalence of rheumatic diseases in the population of Tecumseh, Michigan, 1959–60. J Chronic Dis. 1967;20(6):351–69. Epub 1967/06/01.
Fowles JB, Lawthers AG, Weiner JP, Garnick DW, Petrie DS, Palmer RH. Agreement between physicians’ office records and Medicare Part B claims data. Health Care Financ Rev. 1995;16(4):189–99.
Kadhim-Saleh A, Green M, Williamson T, Hunter D, Birtwhistle R. Validation of the diagnostic algorithms for 5 chronic conditions in the Canadian Primary Care Sentinel Surveillance Network (CPCSSN): a Kingston Practice-based Research Network (PBRN) report. J Am Board Fam Med. 2013;26(2):159–67. doi:10.3122/jabfm.2013.02.120183. Epub 2013/03/09.
Harrold LR, Yood RA, Andrade SE, Reed JI, Cernieux J, Straus W, et al. Evaluating the predictive value of osteoarthritis diagnoses in an administrative database. Arthritis Rheum. 2000;43(8):1881–5.
Williamson T, Green ME, Birtwhistle R, Khan S, Garies S, Wong ST, et al. Validating the 8 CPCSSN case definitions for chronic disease surveillance in a primary care database of electronic health records. Ann Fam Med. 2014;12(4):367–72. doi:10.1370/afm.1644. PubMed PMID: 25024246, PubMed Central PMCID: PMC4096475, Epub 2014/07/16.
Coleman N, Halas G, Peeler W, Casaclang N, Williamson T, Katz A. From patient care to research: a validation study examining the factors contributing to data quality in a primary care electronic medical record database. BMC Fam Pract. 2015;16:11. doi:10.1186/s12875-015-0223-z. PubMed PMID: 25649201, PubMed Central PMCID: PMC4324413, Epub 2015/02/05.
Lix L, Yogendran M, Burchill C, Metge C, McKeen N, Moore D, et al. Defining and Validating Chronic Diseases: An Administrative Data Approach. Winnipeg: Manitoba Centre for Health Policy; 2006.
Rahman JA M, Kopec JA, Cibere J. Abstract no. 342 The Validation of Administrative Osteoarthritis Diagnosis using a Clinical and Radiological Population-Based Cohort from British Columbia, Canada. Osteoarthritis Cartilage. 2014;14(Supplement 4):S150.
Birtwhistle R, Keshavjee K, Lambert-Lanning A, Godwin M, Greiver M, Manca D, et al. Building a pan-Canadian primary care sentinel surveillance network: initial development and moving forward. J Am Board Fam Med. 2009;22(4):412–22. doi:10.3122/jabfm.2009.04.090081. Epub 2009/07/10.
van Walraven C, Austin P. Administrative database research has unique characteristics that can risk biased results. J Clin Epidemiol. 2012;65(2):126–31. doi:10.1016/j.jclinepi.2011.08.002. Epub 2011/11/15.
Jencks SF, Williams DK, Kay TL. Assessing hospital-associated deaths from discharge data. The role of length of stay and comorbidities. JAMA. 1988;260(15):2240–6. Epub 1988/10/21.
Kim C, Nevitt MC, Niu J, Clancy MM, Lane NE, Link TM, et al. Association of hip pain with radiographic evidence of hip osteoarthritis: diagnostic test study. BMJ. 2015;351:h5983. doi:10.1136/bmj.h5983. Epub 2015/12/04. PubMed PMID: 26631296; PubMed Central PMCID: PMC4667842.
Hannan MT, Felson DT, Pincus T. Analysis of the discordance between radiographic changes and knee pain in osteoarthritis of the knee. J Rheumatol. 2000;27(6):1513–7. Epub 2000/06/14.
Bedson J, Croft PR. The discordance between clinical and radiographic knee osteoarthritis: a systematic search and summary of the literature. BMC Musculoskelet Disord. 2008;9:116. doi:10.1186/1471-2474-9-116. PubMed PMID: 18764949, PubMed Central PMCID: PMC2542996, Epub 2008/09/04.