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Identification of prosthetic hip and knee joint infections using administrative databases—A validation study

Published online by Cambridge University Press:  30 September 2020

Christopher E. Kandel*
Affiliation:
Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
Richard Jenkinson
Affiliation:
Division of Orthopaedic Surgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada Division of Orthopaedic Surgery, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
Jessica Widdifield
Affiliation:
Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada Sunnybrook Research Institute, Holland Bone & Joint Program, Toronto, Ontario, Canada Institute for Clinical Evaluative Sciences (ICES), Toronto, Ontario, Canada
Bettina E. Hansen
Affiliation:
Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada Division of Gastroenterology, Toronto General Hospital, University Health Network, Toronto, Ontario, Canada
J. Roderick Davey
Affiliation:
Division of Orthopaedic Surgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada Division of Orthopaedic Surgery, University Health Network, Toronto, Ontario, Canada
Matthew P. Muller
Affiliation:
Unity Health Network, University of Toronto, Toronto, Ontario, Canada
Nick Daneman
Affiliation:
Division of Infectious Diseases, Sunnybrook Health Sciences Centre, Toronto, OntarioCanada
Allison McGeer
Affiliation:
Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada Sinai Health System, University of Toronto, Ontario, Canada
*
Author for correspondence: Christopher E. Kandel, E-mail: christopher.kandel@mail.utoronto.ca

Abstract

Objective:

To determine whether combinations of diagnosis and procedures codes can improve the detection of prosthetic hip and knee joint infections from administrative databases.

Design:

We performed a validation study of all readmissions from January 1, 2010, until December 31, 2016, following primary arthroplasty comparing the diagnosis and procedure codes obtained from an administrative database based upon the International Classification of Disease, Tenth Revision (ICD-10) to the reference standard of chart review.

Setting:

Four tertiary-care hospitals in Toronto, Canada, from 2010 to 2016.

Participants:

Individuals who had a primary arthroplasty were identified using procedure codes.

Intervention:

Chart review of readmissions identified the presence of a prosthetic joint infection and, if present, the surgical procedure performed.

Results:

Overall, 27,802 primary arthroplasties were performed. Among 8,844 readmissions over a median follow-up of 669 days (interquartile range, 256–1,249 days), a PJI was responsible for or present in 586 of 8,844 (6.6%). Diagnosis codes alone exhibited a sensitivity of 0.88 (95% CI, 0.85–0.92) and positive predictive value (PPV) of 0.78 (95% CI, 0.74–0.82) for detecting a PJI. Combining a PJI diagnosis code with procedure codes for an arthroplasty and the insertion of a peripherally inserted central catheter improved detection: sensitivity was 0.92 (95% CI, 0.88–0.94) and PPV was 0.78 (95% CI, 0.74–0.82). However, procedure codes were unable to identify the specific surgical approach to PJI treatment.

Conclusions:

Compared to PJI diagnosis codes, combinations of diagnosis and procedure codes improve the detection of a PJI in administrative databases.

Type
Original Article
Copyright
© 2020 by The Society for Healthcare Epidemiology of America. All rights reserved.

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References

Kurtz, S, Ong, K, Lau, E, Mowat, F, Halpern, M. Projections of primary and revision hip and knee arthroplasty in the United States from 2005 to 2030. J Bone Joint Surg Am 2007;89:780785.CrossRefGoogle ScholarPubMed
Kurtz, SM, Lau, EC, Son, M-S, Chang, ET, Zimmerli, W, Parvizi, J. Are we winning or losing the battle with periprosthetic joint infection: trends in periprosthetic joint infection and mortality risk for the Medicare population. J Arthroplasty 2018;33:32383245.CrossRefGoogle ScholarPubMed
Bozic, KJ, Grosso, LM, Lin, Z, et al. Variation in hospital-level risk-standardized complication rates following elective primary total hip and knee arthroplasty. J Bone Joint Surg Am 2014;96:640647.CrossRefGoogle ScholarPubMed
Lacny, S, Bohm, E, Hawker, G, Powell, J, Marshall, DA. Assessing the comparability of hip arthroplasty registries in order to improve the recording and monitoring of outcome. Bone Jt J 2016;98-B:442451.CrossRefGoogle Scholar
Rusk, A, Bush, K, Brandt, M, et al. Improving surveillance for surgical site infections following total hip and knee arthroplasty using diagnosis and procedure codes in a provincial surveillance network. Infect Control Hosp Epidemiol 2016;37:699703.CrossRefGoogle Scholar
Bolon, MK, Hooper, D, Stevenson, KB, et al. Improved surveillance for surgical site infections after orthopedic implantation procedures: extending applications for automated data. Clin Infect Dis 2009;48:12231229.CrossRefGoogle ScholarPubMed
Rennert-May, E, Manns, B, Smith, S, et al. Validity of administrative data in identifying complex surgical site infections from a population-based cohort after primary hip and knee arthroplasty in Alberta, Canada. Am J Infect Control 2018;46:11231126.CrossRefGoogle ScholarPubMed
Curtis, M, Graves, N, Birrell, F, et al. A comparison of competing methods for the detection of surgical-site infections in patients undergoing total arthroplasty of the knee, partial and total arthroplasty of hip and femoral or similar vascular bypass. J Hosp Infect 2004;57:189193.CrossRefGoogle ScholarPubMed
Marang-van de Mheen, PJ, Bragan Turner, E, et al. Variation in prosthetic joint infection and treatment strategies during 4.5 years of follow-up after primary joint arthroplasty using administrative data of 41397 patients across Australian, European, and United States hospitals. BMC Musculoskelet Disord 2017;18:207.CrossRefGoogle ScholarPubMed
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;64:821829.CrossRefGoogle ScholarPubMed
Juurlink, D, Preyra, C, Croxford, R, et al. Canadian Institute for Health Information discharge abstract database: a validation study. Institute for Clinical Evaluative Sciences website. https://www.ices.on.ca/Publications/Atlases-and-Reports/2006/Canadian-Institute-for-Health-Information. Published 2006. Accessed September 11, 2020.Google Scholar
ICD-10-CA and CCI evolution tables. Canadian Institute for Health Information (CIHI) website. https://secure-cihi-ca.myaccess.library.utoronto.ca/estore/productSeries.htm?pc=PCC217. Accessed June 11, 2020.Google Scholar
Parvizi, J, Gehrke, T, International Consensus Group on Periprosthetic Joint Infection. Definition of periprosthetic joint infection. J Arthroplasty 2014;29:1331.CrossRefGoogle Scholar
Breiman, L, Friedman, J, Olshen, R, Stone, C. Classification and Regression Trees. Pacific Grove, CA: Wadsworth; 1984.Google Scholar
Calderwood, MS, Ma, A, Khan, YM, et al. Use of Medicare diagnosis and procedure codes to improve detection of surgical site infections following hip arthroplasty, knee arthroplasty, and vascular surgery. Infect Control Hosp Epidemiol 2012;33:4049.CrossRefGoogle ScholarPubMed
Fillingham, YA, Della Valle, CJ, Suleiman, LI, et al. Definition of successful infection management and guidelines for reporting of outcomes after surgical treatment of periprosthetic joint infection: from the work group of the Musculoskeletal Infection Society (MSIS). J Bone Joint Surg Am 2019;101(14):e69.CrossRefGoogle Scholar
Tan, TL, Goswami, K, Fillingham, YA, Shohat, N, Rondon, AJ, Parvizi, J. Defining treatment success after 2-stage exchange arthroplasty for periprosthetic joint infection. J Arthroplasty 2018;33:35413546.CrossRefGoogle ScholarPubMed
Gundtoft, PH, Pedersen, AB, Schønheyder, HC, Overgaard, S. Validation of the diagnosis “prosthetic joint infection” in the Danish Hip Arthroplasty Register. Bone Jt J 2016;98B:320325.CrossRefGoogle Scholar
Baker, AW, Haridy, S, Salem, J, et al. Performance of statistical process control methods for regional surgical site infection surveillance: a 10-year multicentre pilot study. BMJ Qual Saf 2018;27:600610.CrossRefGoogle ScholarPubMed
Yokoe, DS, Avery, TR, Platt, R, Huang, SS. Reporting surgical site infections following total hip and knee arthroplasty: impact of limiting surveillance to the operative hospital. Clin Infect Dis 2013;57:12821288.CrossRefGoogle ScholarPubMed
Ravi, B, Pincus, D, Wasserstein, D, et al. Association of overlapping surgery with increased risk for complications following hip surgery: a population-based, matched cohort study. JAMA Intern Med 2018;178:7583.CrossRefGoogle ScholarPubMed
Parvizi, J, Tan, TL, Goswami, K, et al. The 2018 definition of periprosthetic hip and knee infection: an evidence-based and validated criteria. J Arthroplasty 2018;33:13091314.e2.CrossRefGoogle ScholarPubMed
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