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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, Ontario Canada
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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