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Does the Risk Assessment and Prediction Tool Predict Discharge Disposition After Joint Replacement?

  • Symposium: 2014 Hip Society Proceedings
  • Published:
Clinical Orthopaedics and Related Research®

Abstract

Background

Payers of health services and policymakers place a major focus on cost containment in health care. Studies have shown that early planning of discharge is essential in reducing length of stay and achieving financial benefit; tools that can help predict discharge disposition would therefore be of use. The Risk Assessment and Prediction Tool (RAPT) is a preoperative survey constructed to predict discharge disposition after total joint arthroplasty (TJA). The RAPT was developed and tested on a population of Australian patients undergoing joint replacement, but its validity in other populations is unknown. A low RAPT score is reported to indicate a high risk of needing any form of inpatient rehabilitation after TJA, including short-term nursing facilities.

Questions/purposes

This study attempts (1) to assess predictive accuracy of the RAPT on US patients undergoing total hip and knee arthroplasty (THA/TKA); and (2) to determine predictive accuracy of each individual score (1–12).

Methods

Between June 2006 and December 2011, RAPT scores of 3213 patients (1449 THAs; 1764 TKAs) were prospectively captured during the preoperative clinical visit. Scores were stored along with other clinical data, including discharge disposition, in a dedicated database on a secure server. The database was queried by the nursing case manager to retrieve the RAPT scores of all patients captured during this time period. Binary logistic regression was used to analyze the scores and determine predictive accuracy.

Results

Overall predictive accuracy was 78%. RAPT scores < 6 and > 10 (of 12) predicted with > 90% accuracy discharge to inpatient rehabilitation and home, respectively. Predictive accuracy was lowest for scores between 7 and 10 at 65.2% and almost 50% of patients received scores in this range. Based on our findings, the risk categories in our populations should be high risk < 7, intermediate risk 7 to 10, and low risk > 10.

Conclusions

The RAPT accurately predicted discharge disposition for high- and low-risk patients in our cohort. Based on our data, intermediate-risk patients should be defined as those with scores of 7 to 10. Predictive accuracy for these patients could potentially be improved through the identification and addition of other factors correlated to discharge disposition. The RAPT allows for identification of patients who are likely to be discharged home or to rehabilitation, which may facilitate preoperative planning of postoperative care. Additionally, it identifies intermediate-risk patients and could be used to implement targeted interventions to facilitate discharge home in this group of patients.

Level of Evidence

Level III, diagnostic study. See the Guidelines for Authors for a complete description of levels of evidence.

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References

  1. Bozic KJ, Katz P, Cisternas M, Ono L, Ries MD, Showstack J. Hospital resource utilization for primary and revision total hip arthroplasty. J Bone Joint Surg Am. 2005;87:570–576.

    PubMed  Google Scholar 

  2. Bozic KJ, Stacey B, Berger A, Sadosky A, Oster G. Resource utilization and costs before and after total joint arthroplasty. BMC Health Serv Res. 2012;12:73.

    Article  PubMed Central  PubMed  Google Scholar 

  3. Bozic KJ, Wagie A, Naessens JM, Berry DJ, Rubash HE. Predictors of discharge to an inpatient extended care facility after total hip or knee arthroplasty. J Arthroplasty. 2006;21:151–156.

    Article  PubMed  Google Scholar 

  4. Centers for Disease Control and Prevention. National Hospital Discharge Survey: 2010. Available at: www.cdc.gov/nchs/data/nhds/4procedures/2010pro4_numberprocedureage.pdf. Accessed January 23, 2014.

  5. Dauty M, Schmitt X, Menu P, Rousseau B, Dubois C. Using the Risk Assessment and Predictor Tool (RAPT) for patients after total knee replacement surgery. Ann Phys Rehabil Med. 2012;55:4–15.

    Article  CAS  PubMed  Google Scholar 

  6. Ethgen O, Bruyere O, Richy F, Dardennes C, Reginster JY. Health-related quality of life in total hip and total knee arthroplasty. A qualitative and systematic review of the literature. J Bone Joint Surg Am. 2004;86:963–974.

    PubMed  Google Scholar 

  7. Lavernia CJ, Guzman JF, Gachupin-Garcia A. Cost effectiveness and quality of life in knee arthroplasty. Clin Orthop Relat Res. 1997;345:134–139.

    PubMed  Google Scholar 

  8. Losina E, Walensky RP, Kessler CL, Emrani PS, Reichmann WM, Wright EA, Holt HL, Solomon DH, Yelin E, Paltiel AD, Katz JN. Cost-effectiveness of total knee arthroplasty in the United States: patient risk and hospital volume. Arch Intern Med. 2009;169:1113–1121; discussion 1121–1122.

    Article  PubMed Central  PubMed  Google Scholar 

  9. Malchau H, Garellick G, Eisler T, Karrholm J, Herberts P. Presidential guest address: the Swedish Hip Registry: increasing the sensitivity by patient outcome data. Clin Orthop Relat Res. 2005;441:19–29.

    Article  PubMed  Google Scholar 

  10. Maradit Kremers H, Visscher SL, Moriarty JP, Reinalda MS, Kremers WK, Naessens JM, Lewallen DG. Determinants of direct medical costs in primary and revision total knee arthroplasty. Clin Orthop Relat Res. 2013;471:206–214.

    Article  PubMed Central  PubMed  Google Scholar 

  11. Oldmeadow LB, McBurney H, Robertson VJ. Predicting risk of extended inpatient rehabilitation after hip or knee arthroplasty. J Arthroplasty. 2003;18:775–779.

    Article  PubMed  Google Scholar 

  12. Rolfson O, Strom O, Karrholm J, Malchau H, Garellick G. Costs related to hip disease in patients eligible for total hip arthroplasty. J Arthroplasty. 2012;27:1261–1266.

    Article  PubMed  Google Scholar 

  13. SooHoo NF, Lieberman JR, Ko CY, Zingmond DS. Factors predicting complication rates following total knee replacement. J Bone Joint Surg Am. 2006;88:480–485.

    Article  PubMed  Google Scholar 

  14. Tan C, Loo G, Pua YH, Chong HC, Yeo W, Ong PH, Lo NN, Allison G. Predicting discharge outcomes after total knee replacement using the Risk Assessment and Predictor Tool. Physiotherapy. 2014;100:176–181.

    Article  CAS  PubMed  Google Scholar 

  15. Tomek IM, Sabel AL, Froimson MI, Muschler G, Jevsevar DS, Koenig KM, Lewallen DG, Naessens JM, Savitz LA, Westrich JL, Weeks WB, Weinstein JN. A collaborative of leading health systems finds wide variations in total knee replacement delivery and takes steps to improve value. Health Aff (Millwood). 2012;31:1329–1338.

    Article  PubMed  Google Scholar 

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Acknowledgments

We thank Pamela Tobichuk and Robert Dorman for their assistance in preparing the manuscript.

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Authors and Affiliations

Authors

Corresponding author

Correspondence to Andrew A. Freiberg MD.

Additional information

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.

Each author certifies that his or her institution approved the human protocol for this investigation, that all investigations were conducted in conformity with ethical principles of research, and that informed consent for participation in the study was obtained.

This work was performed at the Harris Orthopaedic Laboratory, Massachusetts General Hospital, Boston, MA, USA.

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Hansen, V.J., Gromov, K., Lebrun, L.M. et al. Does the Risk Assessment and Prediction Tool Predict Discharge Disposition After Joint Replacement?. Clin Orthop Relat Res 473, 597–601 (2015). https://doi.org/10.1007/s11999-014-3851-z

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  • DOI: https://doi.org/10.1007/s11999-014-3851-z

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