Literature DB >> 35051249

How much is enough? Finding the minimum annual surgical volume threshold for total knee replacement.

Per-Henrik Randsborg1,2, Amanda C Chen3.   

Abstract

Entities:  

Keywords:  device safety; health services research; outcome assessment (health care); prostheses and implants

Year:  2021        PMID: 35051249      PMCID: PMC8647569          DOI: 10.1136/bmjsit-2021-000092

Source DB:  PubMed          Journal:  BMJ Surg Interv Health Technol        ISSN: 2631-4940


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There is compelling evidence that the outcome of total knee replacement (TKR) depends on the annual caseload of the surgeon and the institution.1–3 The fact that high-volume centres have better outcomes is so well known that patients themselves increasingly seek treatment at high-volume institutions.4 But how do we determine the surgical volume threshold that constitutes an acceptable risk? In the recent article by Okoro et al, data from nearly 170 000 TKR recipient in Ontario, Canada, were analysed using a state of the art restricted cubic spline (RCS) analysis.5 The authors identified an inflection point for increased probability for early revision or infection at 70 annual cases, after which the risk of complications plateaued. However, risk reduction continued even beyond an annual caseload of 70, highlighting the value of treatment by high-volume surgeons. This method of identifying the surgical volume threshold differs from previous studies conducted in the last 10 years (table 1). While some papers fail to mention their methods for defining the volume groups, others have largely split the data by quartiles. This results in more or less arbitrary thresholds that are more dependent on local healthcare structure and population size than providing clinical meaningful volume categories. Due to varying methods for defining the volume groups, the lowest volume category in one study6 would have been defined as the highest volume category in another.7 Clearly, if the goal is to identify the annual caseload that reduces complications and produce meaningful thresholds that surgeons and institutions can aim to achieve, the volume categories should not be defined a priori. This methodological flaw is corrected by the RCS analysis, which uses the dataset to identify the inflection point to identify the actual caseload threshold where the risk of complications is reduced.
Table 1

A literature review of publications in English from 2011 to 2021, with a minimum of 20 000 patients included, evaluating the effect of surgeon and/or hospital volume on total knee replacement outcome

Surgeon–volume relationship
StudyNSettingVolume thresholdsDefinition of thresholdOutcomeResultOR (95 % CI)P value
Author yearNo of TKRsData source, countryLowMedium lowMedium highHighVery High(Method)TypeLow versus high volume
Namba etal 12 2013a64 017Total Joint Replacement Registry, USA1–910–49≥50Not explainedAseptic revisionNo difference1.11(0.66 to1.12)0.690
Namba13 2013b56 216Total Joint Replacement Registry, USA<2020–49≥50Not explainedSurgical site infectionNo difference1.30(0.90 to 1.88)0.160
Wilson2 2016289 976Statewide Planning and Research Cooperative System (SPARCS), New York, USA0–1213–5960–145≥146SSLRCR and revisionHigher risk for low volume1.85(1.75 to 1.97)NR
Yu8 201930 828Taiwan National Health Insurance Research Data base, Taiwan1–49≥50RCSRReadmissionHigher risk for low volume1.44(1.22 to 1.69)<0.001
Hospital–volume relationship
de la Torre etal 14 201936 316Catalan Arthroplasty Registry, Spain<125>125Previous studiesRevisionHigher risk for low volume1.29(1.16 to 1.44)NR
Badawy etal 7 201326 698Norwegian Arthroplasty Register, Norway<2525–4950–99100–149≥150Previous studiesRevisionNo difference0.81*0.68
D’apuzzo etal 15 2017377 705Statewide Planning and Research Cooperative System (SPARCS), New York, USA1–8990–235236–644≥645SSLRReadmissionHigher risk for low volume1.32(1.16 to 1.51) <0.001
Kurtz6 2016952 593Medicare 100% claims, USA150–299300–499450–599≥600Not explainedReadmissionHigher readmissions for low volume51.2%†
Meyer etal 16 201143 180Krankenhaus- Infektions-Surveillance System, Germany1–5051–99>100Previous studiesSurgical site infectionsHigher risk for low volume2.04NR
Namba et al 12 2013a64 017Total Joint Replacement Registry, USA<100100–199≥200Not explainedAseptic revisionNo difference0.93(0.59 to 1.48)0.769
Namba13 2013b56 216Total Joint Replacement Registry, USA<100100–199≥200Not explainedSurgical site infectionlower risk for low volume0.33(0.12 to 0.90)0.030
Pamilo et al 17 201559 696Perfect Knee Replacement database, Finland1–99100–249250–449>450chosen arbitrarilyLOS, Readmission, MUA, revisionHigher readmission risk for low volume, no difference for revisionReadmission:1.11(1.03 to 1.19)NRRevision:1.08(0.93 to 1.26)NR
Singh et al 18 201119 418Pennsylvania Healthcare Cost Containment Council database, USA1–2526–100101–200>200Not explainedCR and MRHigher risk for low volumeCR:1.1(0.8 to 1.6)NRMR:1.0 (0.4 to 2.6)NR
Wilson2 2016289 976Statewide Planning and Research Cooperative System (SPARCS), New York, USA0–8990–235236–644>645SSLRCR and revisionHigher risk for low volume1.37(1.32 to 1.42)NR
Yu8 201930 828Taiwan National Health Insurance Research Data base, Taiwan1–74 >75RCSRReadmissionNo association1.07(0.90 to 1.28)0.435

Search performed in Medline 9 April 2021 yielded 72 papers for screening.

*Relative risk,.

†Percentage difference.

CR, complication rate; LOS, length of stay; MR, mortality rate; MUA, manipulation under anaesthesia; NR, not reported; RCSR, Restricted Cubic Spline Regression; SSLR, Stratum-specific likelihood ratio.

A literature review of publications in English from 2011 to 2021, with a minimum of 20 000 patients included, evaluating the effect of surgeon and/or hospital volume on total knee replacement outcome Search performed in Medline 9 April 2021 yielded 72 papers for screening. *Relative risk,. †Percentage difference. CR, complication rate; LOS, length of stay; MR, mortality rate; MUA, manipulation under anaesthesia; NR, not reported; RCSR, Restricted Cubic Spline Regression; SSLR, Stratum-specific likelihood ratio. However, it is unlikely that the threshold of 70 annual cases to reduce risk of complications is universal. Like any surgery, TKR surgery is composed of teamwork and environmental factors, such as healthcare structure and population demographics, which influence the outcome. Okoro et al suggest that all communities with available real-world data perform similar RCS analysis to identify the caseload threshold relevant to their population. It should therefore be mentioned that Yu et al published a similar RCS analysis from Taiwan in 2019.8 They found the inflection point to be somewhat lower in their population, at 50 cases per year, proving the point that the caseload threshold varies between populations. Differences in specialty training practices and best practices across nations affect volume threshold estimates. We predict that future research will produce new and different surgical volume thresholds to reduce complications, and it is unlikely that a definite answer will be possible to find. It is more likely that the true annual caseload threshold varies over time, as surgical training, implant design and population characteristics change. Another challenge in determining acceptable caseload thresholds is that different complications will have different volume thresholds. Existing literature on the effect of surgical volume has used a spectrum of different outcomes, including 30-day readmission, revision rate, radiological implant alignment,9 surgical site infection and length of hospital stay (table 1). Different complications will have different etiologies, not all related to the experience of the surgeon. Hospital environment, population characteristics, postoperative care and rehabilitation facilities all play a part in securing a good outcome after arthroplasty surgery. For example, length of stay is dependent on multiple factors, not least the hospital capacity and the proximity of a potential rehabilitation facility or the home of the patient. A longer hospital stay in a rural hospital with low surgical volume may therefore not be an indication of poor quality. Furthermore, not all of these complications necessarily constitute a clinically meaningful difference for the patient (eg, implant alignment may not have clinical relevance). As such, the revision rate is probably the best outcome measure, representing a hard end-point with a clear consequence for the patient. However, even revision rates are subject to individual variation thresholds by the revision surgeon, and local traditions such as patella resurfacing or not. Defining the minimal surgical volume threshold is clearly not an easy task. However, the true surgical volume threshold is perhaps not that important. The point is that there is little doubt that surgical volume matters, and the crucial question is what to do with this knowledge. Some authors have suggested that low-volume surgeons should either stop doing the procedure, or do more of it.10 There are many arguments for centralisation, as TKR are nearly always an elective procedure that may be postponed. However, travelling for hours to receive care is not always possible, and removing TKR service from local hospitals reduces both the availability and the quality of care. Caring for patients operated by other surgeons is difficult, especially if the patient has had a type of surgery you do not perform yourself, and interrupts the continuity of a patient’s care. Furthermore, patients treated at high-volume institutions differ from those of low-volume institutions,11 meaning that changing the population flow might affect the caseload thresholds, which are probably constantly changing anyway. Still, there is no denying the effect of surgical volume on outcome quality. The improved, and likely more accurate, caseload thresholds estimated by Okoro et al and Yu et al provide valuable information that can guide decision-makers when organising the arthroplasty service in the community. An effort to reach a minimum of caseload in most centres should be combined with efforts to improve the quality of the care in low-volume institutions, so that uniform healthcare and equity can be reached while preserving access to care.
  17 in total

1.  Influence of hospital volume on revision rate after total knee arthroplasty with cement.

Authors:  Mona Badawy; Birgitte Espehaug; Kari Indrekvam; Lars B Engesæter; Leif I Havelin; Ove Furnes
Journal:  J Bone Joint Surg Am       Date:  2013-09-18       Impact factor: 5.284

2.  Impact of department volume on surgical site infections following arthroscopy, knee replacement or hip replacement.

Authors:  Elisabeth Meyer; Doris Weitzel-Kage; Dorit Sohr; Petra Gastmeier
Journal:  BMJ Qual Saf       Date:  2011-07-18       Impact factor: 7.035

3.  All-Cause Versus Complication-Specific Readmission Following Total Knee Arthroplasty.

Authors:  Michele D'Apuzzo; Geoffrey Westrich; Chisa Hidaka; Ting Jung Pan; Stephen Lyman
Journal:  J Bone Joint Surg Am       Date:  2017-07-05       Impact factor: 5.284

4.  The Impact of Surgeon Volume and Training Status on Implant Alignment in Total Knee Arthroplasty.

Authors:  Gregory S Kazarian; Charles M Lawrie; Toby N Barrack; Matthew J Donaldson; Gary M Miller; Fares S Haddad; Robert L Barrack
Journal:  J Bone Joint Surg Am       Date:  2019-10-02       Impact factor: 5.284

5.  Risk factors for total knee arthroplasty aseptic revision.

Authors:  Robert S Namba; Guy Cafri; Monti Khatod; Maria C S Inacio; Timothy W Brox; Elizabeth W Paxton
Journal:  J Arthroplasty       Date:  2013-08-15       Impact factor: 4.757

6.  Hospital volume and operative mortality in the modern era.

Authors:  Bradley N Reames; Amir A Ghaferi; John D Birkmeyer; Justin B Dimick
Journal:  Ann Surg       Date:  2014-08       Impact factor: 12.969

7.  Which Hospital and Clinical Factors Drive 30- and 90-Day Readmission After TKA?

Authors:  Steven M Kurtz; Edmund C Lau; Kevin L Ong; Edward M Adler; Frank R Kolisek; Michael T Manley
Journal:  J Arthroplasty       Date:  2016-04-04       Impact factor: 4.757

8.  Trend Toward High-Volume Hospitals and the Influence on Complications in Knee and Hip Arthroplasty.

Authors:  Nicholas C Laucis; Mohammed Chowdhury; Abhijit Dasgupta; Timothy Bhattacharyya
Journal:  J Bone Joint Surg Am       Date:  2016-05-04       Impact factor: 5.284

9.  Risk factors associated with deep surgical site infections after primary total knee arthroplasty: an analysis of 56,216 knees.

Authors:  Robert S Namba; Maria C S Inacio; Elizabeth W Paxton
Journal:  J Bone Joint Surg Am       Date:  2013-05-01       Impact factor: 5.284

10.  Hospital volume affects outcome after total knee arthroplasty.

Authors:  Konsta J Pamilo; Mikko Peltola; Juha Paloneva; Keijo Mäkelä; Unto Häkkinen; Ville Remes
Journal:  Acta Orthop       Date:  2014-10-17       Impact factor: 3.717

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