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Diagnosis of Periprosthetic Joint Infection in Medicare Patients: Multicriteria Decision Analysis

  • Symposium: 2013 Musculoskeletal Infection Society
  • Published:
Clinical Orthopaedics and Related Research®

Abstract

Background

In the setting of finite healthcare resources, developing cost-efficient strategies for periprosthetic joint infection (PJI) diagnosis is paramount. The current levels of knowledge allow for PJI diagnostic recommendations based on scientific evidence but do not consider the benefits, opportunities, costs, and risks of the different diagnostic alternatives.

Questions/purposes

We determined the best diagnostic strategy for knee and hip PJI in the ambulatory setting for Medicare patients, utilizing benefits, opportunities, costs, and risks evaluation through multicriteria decision analysis (MCDA).

Methods

The PJI diagnostic definition supported by the Musculoskeletal Infection Society was employed for the MCDA. Using a preclinical model, we evaluated three diagnostic strategies that can be conducted in a Medicare patient seen in the outpatient clinical setting complaining of a painful TKA or THA. Strategies were (1) screening with serum markers (erythrocyte sedimentation rate [ESR]/C-reactive protein [CRP]) followed by arthrocentesis in positive cases, (2) immediate arthrocentesis, and (3) serum markers requested simultaneously with arthrocentesis. MCDA was conducted through the analytic hierarchy process, comparing the diagnostic strategies in terms of benefits, opportunities, costs, and risks.

Results

Strategy 1 was the best alternative to diagnose knee PJI among Medicare patients (normalized value: 0.490), followed by Strategy 3 (normalized value: 0.403) and then Strategy 2 (normalized value: 0.106). The same ranking of alternatives was observed for the hip PJI model (normalized value: 0.487, 0.405, and 0.107, respectively). The sensitivity analysis found this sequence to be robust with respect to benefits, opportunities, and risks. However, if during the decision-making process, cost savings was given a priority of higher than 54%, the ranking for the preferred diagnostic strategy changed.

Conclusions

After considering the benefits, opportunities, costs, and risks of the different available alternatives, our preclinical model supports the American Academy of Orthopaedic Surgeons recommendations regarding the use of serum markers (ESR/CRP) before arthrocentesis as the best diagnostic strategy for PJI among Medicare patients.

Level of Evidence

Level II, economic and decision analysis. See Instructions to Authors for a complete description of levels of evidence.

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References

  1. Alijanipour P, Bakhshi H, Parvizi J. Diagnosis of periprosthetic joint infection: the threshold for serological markers. Clin Orthop Relat Res. 2013;471:3186–3195.

    Article  PubMed  Google Scholar 

  2. Banuelas R, Antony J. Modified analytic hierarchy process to incorporate uncertainty and managerial aspects. Int J Prod Res.. 2004;42:3851–3872.

    Article  Google Scholar 

  3. Barrack RL, Jennings RW, Wolfe MW, Bertot AJ. The Coventry Award. The value of preoperative aspiration before total knee revision. Clin Orthop Relat Res. 1997:345:8–16.

    Article  PubMed  Google Scholar 

  4. Büyükyazıcı M, Sucu M. The analytic hierarchy and analytic network processes. CRITERION. 2003;1:c1.

    Google Scholar 

  5. Deirmengian C, Hallab N, Tarabishy A, Della Valle C, Jacobs JJ, Lonner J, Booth RE Jr. Synovial fluid biomarkers for periprosthetic infection. Clin Orthop Relat Res. 2010;468:2017–2023.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Della Valle C, Parvizi J, Bauer TW, Dicesare PE, Evans RP, Segreti J, Spangehl M, Watters WC 3rd, Keith M, Turkelson CM, Wies JL, Sluka P, Hitchcock K. Diagnosis of periprosthetic joint infections of the hip and knee. J Am Acad Orthop Surg. 2010;18:760–770.

    PubMed  Google Scholar 

  7. Della Valle CJ, Parvizi J, Bauer TW, DiCesare PE, Evans RP, Segreti J, Spangehl M. American Academy of Orthopaedic Surgeons: the diagnosis of periprosthetic joint infections of the hip and knee. Guideline and evidence report. 2010. Available at: http://www.aaos.org/research/guidelines/PJIguideline.pdf. Accessed July 15, 2011.

  8. Dolan JG. Multi-criteria clinical decision support: aprimer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare. Patient. 2010;3:229–248.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Dolan JG, Boohaker E, Allison J, Imperiale TF. Patients’ preferences and priorities regarding colorectal cancer screening. Med Decis Making. 2013;33:59–70.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Ebell M. AHRQ White Paper. Use of clinical decision rules for point-of-care decision support. Med Decis Making. 2010;30:712–721.

    Article  PubMed  Google Scholar 

  11. Erkut E, Tarimcilar M. On sensitivity analysis in the analytic hierarchy process. IMA J Management Math. 1991;3:61–83.

    Article  Google Scholar 

  12. Ijzerman MJ, van Til JA, Bridges JF. A comparison of analytic hierarchy process and conjoint analysis methods in assessing treatment alternatives for stroke rehabilitation. Patient. 2012;5:45–56.

    Article  PubMed  Google Scholar 

  13. Kurtz SM, Ong KL, Lau E, Bozic KJ, Berry D, Parvizi J. Prosthetic joint infection risk after TKA in the Medicare population. Clin Orthop Relat Res. 2010;468:52–56.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Liberatore MJ, Nydick RL. The analytic hierarchy process in medical and health care decision making: a literature review. European Journal of Operational Research. 2008;189:194–207.

    Article  Google Scholar 

  15. Love C, Marwin SE, Palestro CJ. Nuclear medicine and the infected joint replacement. Semin Nucl Med. 2009;39:66–78.

    Article  PubMed  Google Scholar 

  16. Ong KL, Kurtz SM, Lau E, Bozic KJ, Berry DJ, Parvizi J. Prosthetic joint infection risk after total hip arthroplasty in the Medicare population. J Arthroplasty. 2009;24:105–109.

    Article  PubMed  Google Scholar 

  17. Parvizi J, Della Valle CJ. AAOS Clinical Practice Guideline: diagnosis and treatment of periprosthetic joint infections of the hip and knee. J Am Acad Orthop Surg. 2010;18:771–772.

    PubMed  Google Scholar 

  18. Parvizi J, Ghanem E, Menashe S, Barrack RL, Bauer TW. Periprosthetic infection: what are the diagnostic challenges? J Bone Joint Surg Am. 2006;88(suppl 4):138–147.

    Article  PubMed  Google Scholar 

  19. Parvizi J, Jacovides C, Antoci V, Ghanem E. Diagnosis of periprosthetic joint infection: the utility of a simple yet unappreciated enzyme. J Bone Joint Surg Am. 2011;93:2242–2248.

    PubMed  Google Scholar 

  20. Parvizi J, McKenzie JC, Cashman JP. Diagnosis of periprosthetic joint infection using synovial C-reactive protein. J Arthroplasty. 2012;27:12–16.

    Article  PubMed  Google Scholar 

  21. Parvizi J, Zmistowski B, Berbari EF, Bauer TW, Springer BD, Della Valle CJ, Garvin KL, Mont MA, Wongworawat MD, Zalavras CG. New definition for periprosthetic joint infection: from the Workgroup of the Musculoskeletal Infection Society. Clin Orthop Relat Res. 2011;469:2992–2994.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Saaty RW. The analytic hierarchy process—what it is and how it is used. Math Model.. 1987;9:161–176.

    Article  Google Scholar 

  23. Saaty TL, Özdemir MS. The Encyclicon: A Dictionary of Decisions with Dependence and Feedback Based on the Analytic Network Process. Pittsburgh, PA: RWS Publications; 2005.

    Google Scholar 

  24. Saaty TL, Vargas LG. Uncertainty and rank order in the analytic hierarchy process. Eur. J. Oper. Res.. 1987;32:107–117.

    Article  Google Scholar 

  25. Sajjad Zahir M. Incorporating the uncertainty of decision judgements in the analytic hierarchy process. Eur. J. Oper. Res. 1991;53:206–216.

    Article  Google Scholar 

  26. Shearer DW, Kramer J, Bozic KJ, Feeley BT. Is hip arthroscopy cost-effective for femoroacetabular impingement? Clin Orthop Relat Res. 2012;470:1079–1089.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Sloane EB, Liberatore MJ, Nydick RL. Medical decision support using the Analytic Hierarchy Process. J Healthc Inf Manag. 2002;16:38–43.

    PubMed  Google Scholar 

  28. Wang YM, Elhag TM. An approach to avoiding rank reversal in AHP. Decis. Support Syst.. 2006;42:1474–1480.

    Article  Google Scholar 

  29. Ward DT, Hansen EN, Takemoto SK, Bozic KJ. Cost and effectiveness of postoperative fever diagnostic evaluation in total joint arthroplasty patients. J Arthroplasty. 2010;25:43–48.

    Article  PubMed  Google Scholar 

  30. Wetters NG, Berend KR, Lombardi AV, Morris MJ, Tucker TL, Della Valle CJ. Leukocyte esterase reagent strips for the rapid diagnosis of periprosthetic joint infection. J Arthroplasty. 2012;27:8–11.

    Article  PubMed  Google Scholar 

  31. Wijnmalen DJ. Analysis of benefits, opportunities, costs, and risks (BOCR) with the AHP-ANP: a critical validation. Math Comput Model.. 2007;46:892–905.

    Article  Google Scholar 

  32. Williams JL, Norman P, Stockley I. The value of hip aspiration versus tissue biopsy in diagnosing infection before exchange hip arthroplasty surgery. J Arthroplasty. 2004;19:582–586.

    Article  PubMed  Google Scholar 

  33. Zahedi F. Group consensus function estimation when preferences are uncertain. Oper Res.. 1986;34:883–894.

    Article  Google Scholar 

  34. Zahedi F. The Analytic Hierarchy Process—a survey of the method and its applications. Interfaces. 1986;16:96–108.

    Article  Google Scholar 

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Authors and Affiliations

  1. The Rothman Institute at Thomas Jefferson University, Philadelphia, PA, USA

    Claudio Diaz-Ledezma MD & Paul M. Lichstein MD, MS

  2. Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, USA

    James G. Dolan MD

  3. The Rothman Institute at Thomas Jefferson University, The Sheridan Building, 125th South 9th Street, Suite 1000, Philadelphia, PA, 19107, USA

    Javad Parvizi MD, FRCS

Authors
  1. Claudio Diaz-Ledezma MD
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  2. Paul M. Lichstein MD, MS
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  3. James G. Dolan MD
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  4. Javad Parvizi MD, FRCS
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Corresponding author

Correspondence to Javad Parvizi MD, FRCS.

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Each author certifies that he or she, or a member of his or her immediate family, has no funding or commercial associations (eg, consultancies, stock ownership, equity interest, patent/licensing arrangements, etc) that might pose a conflict of interest in connection with the submitted article.

All ICMJE Conflict of Interest Forms for authors and Clinical Orthopaedics and Related Research editors and board members are on file with the publication and can be viewed on request.

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Diaz-Ledezma, C., Lichstein, P.M., Dolan, J.G. et al. Diagnosis of Periprosthetic Joint Infection in Medicare Patients: Multicriteria Decision Analysis. Clin Orthop Relat Res 472, 3275–3284 (2014). https://doi.org/10.1007/s11999-014-3492-2

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  • DOI: https://doi.org/10.1007/s11999-014-3492-2

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