Background: Loosening is a major cause for failure of total hip and total knee arthroplasties (THAs/TKAs). Preemptive diagnostics of asymptomatic loosening could open strategies to prevent gross loosening. A multitude of biomarkers may discriminate between loosened and stable implants, but it is unknown which have the best performance. The present systematic review aimed to assess which biomarkers have shown the most promising results in discriminating between stable and aseptic loosened THAs and TKAs. Methods: PubMed, Embase, Web of Science, Cochrane Library, and Academic Search Premier were systematically searched up to January 2020 for studies including THA/TKA and biomarkers to assess loosening. Two reviewers independently screened records, extracted data, and assessed the risk of bias using the ICROMS tool to classify the quality of the studies.Results: Twenty-eight (three high-quality) studies were included, reporting on a median of 48 patients (interquartile range 28–69). Serum and urine markers were evaluated in 22 and 10 studies, respectively. Tumor necrosis factor α and osteocalcin were significantly higher in loosened compared with stable implants. Urinary N-terminal telopeptide had significantly elevated levels in loosened prostheses.Conclusion: Several serum and urine markers were promising in discriminating between loosened and stable implants. We recommend future studies to evaluate these biomarkers in a longitudinal fashion to assess whether progression of loosening is associated with a change in these biomarkers. In particular, high-quality studies assessing the usability of these biomarkers are needed.@en

Objective To assess the effectiveness of a prospective multifaceted quality improvement intervention on patient outcomes after total hip and knee arthroplasty (THA and TKA). Design Cluster randomised controlled trial nested in a national registry. From 1 January 2018 to 31 May 2020 routinely submitted registry data on revision and patient characteristics were used, supplemented with hospital data on readmission, complications and length of stay (LOS) for all patients. Setting 20 orthopaedic departments across hospitals performing THA and TKA in The Netherlands. Participants 32 923 patients underwent THA and TKA, in 10 intervention and 10 control hospitals (usual care). Intervention The intervention period lasted 8 months and consisted of the following components: (1) monthly updated feedback on 1-year revision, 30-day readmission, 30-day complications, long (upper quartile) LOS and these four indicators combined in a composite outcome; (2) interactive education; (3) an action toolbox including evidence-based quality improvement initiatives (QIIs) to facilitate improvement of above indicators; and (4) bimonthly surveys to report on QII undertaken. Main outcome measures The primary outcome was textbook outcome (TO), an all-or-none composite representing the best outcome on all performance indicators (ie, the absence of revision, readmissions, complications and long LOS). The individual indicators were analysed as secondary outcomes. Changes in outcomes from pre-intervention to intervention period were compared between intervention versus control hospitals, adjusted for case-mix and clustering of patients within hospitals using random effect binary logistic regression models. The same analyses were conducted for intervention hospitals that did and did not introduce QII. Results 16,314 patients were analysed in intervention hospitals (12,475 before and 3,839 during intervention) versus 16,609 in control hospitals (12,853 versus 3,756). After the intervention period, the absolute probability to achieve TO increased by 4.32% (95% confidence interval (CI) 4.30-4.34) more in intervention than control hospitals, corresponding to 21.6 (95%CI 21.5-21.8), i.e., 22 patients treated in intervention hospitals to achieve one additional patient with TO. Intervention hospitals had a larger increase in patients achieving TO (ratio of adjusted odds ratios 1.24, 95%CI 1.05-1.48) than control hospitals, a larger reduction in patients with long LOS (0.74, 95%CI 0.61-0.90) but also a larger increase in patients with reported 30-day complications (1.34, 95%CI 1.00-1.78). Intervention hospitals that introduced QII increased more in TO (1.32, 95%CI 1.10-1.57) than control hospitals, with no effect shown for hospitals not introducing QII (0.93, 95%CI 0.67-1.30). Conclusion The multifaceted QI intervention including monthly feedback, education, and a toolbox to facilitate QII effectively improved patients achieving TO. The effect size was associated with the introduction of (evidence-based) QII, considered as the causal link to achieve better patient outcomes. Trial registration number NCT04055103.@en

In order to improve care for total hip and knee arthroplasties (THA/TKA), hospitals may want to compare their performance with hospitals in other countries. Pooling data across countries also enable early detection of infrequently occurring safety issues. We therefore aimed to assess the between-hospital variation and definitions used for revision, readmission, and complications across countries. • PubMed, Embase, Web of Science, Cochrane library, Emcare, and Academic Search Premier were searched from January 2009 to August 2020 for studies reporting on: (i) primary THA/ TKA; (ii) revision, readmission, or complications; and (iii) between-hospital variation. Most recent registry reports of Network of Orthopedic Registries of Europe members were also reviewed. Two reviewers independently screened records, extracted data, and assessed the risk of bias using the Integrated quality Criteria for the Review Of Multiple Study designs tool for studies and relevant domains for registries. We assessed agreement for the following domains: (i) outcome definition; (ii) follow-up and starting point; (iii) case-mix adjustment; and (iv) type of patients and hospitals included. • Between-hospital variation was reported in 33 (1 high-quality, 13 moderate-quality, and 19 low-quality) studies and 8 registry reports. The range of variation for revision was 0-33% for THA and 0-27% for TKA varying between assessment within hospital admission until 10 years of follow-up; for readmission, 0-40% and 0-32% for THA and TKA, respectively; and for complications, 0-75% and 0-50% for THA and TKA, respectively. Indicator definitions and methodological variables varied considerably across domains. • The large heterogeneity in definitions and methods used likely explains the considerable variation in between-hospital variation reported for revision, readmission, and complications, making it impossible to benchmark hospitals across countries or pool data for earlier detection of safety issues. It is necessary to collaborate internationally and strive for more uniformity in indicator definitions and methods in order to achieve reliable international benchmarking in the future.@en

In order to improve care for total hip and knee arthroplasties (THA/TKA), hospitals may want to compare their performance with hospitals in other countries. Pooling data across countries also enable early detection of infrequently occurring safety issues. We therefore aimed to assess the between-hospital variation and definitions used for revision, readmission, and complications across countries. • PubMed, Embase, Web of Science, Cochrane library, Emcare, and Academic Search Premier were searched from January 2009 to August 2020 for studies reporting on: (i) primary THA/ TKA; (ii) revision, readmission, or complications; and (iii) between-hospital variation. Most recent registry reports of Network of Orthopedic Registries of Europe members were also reviewed. Two reviewers independently screened records, extracted data, and assessed the risk of bias using the Integrated quality Criteria for the Review Of Multiple Study designs tool for studies and relevant domains for registries. We assessed agreement for the following domains: (i) outcome definition; (ii) follow-up and starting point; (iii) case-mix adjustment; and (iv) type of patients and hospitals included. • Between-hospital variation was reported in 33 (1 high-quality, 13 moderate-quality, and 19 low-quality) studies and 8 registry reports. The range of variation for revision was 0-33% for THA and 0-27% for TKA varying between assessment within hospital admission until 10 years of follow-up; for readmission, 0-40% and 0-32% for THA and TKA, respectively; and for complications, 0-75% and 0-50% for THA and TKA, respectively. Indicator definitions and methodological variables varied considerably across domains. • The large heterogeneity in definitions and methods used likely explains the considerable variation in between-hospital variation reported for revision, readmission, and complications, making it impossible to benchmark hospitals across countries or pool data for earlier detection of safety issues. It is necessary to collaborate internationally and strive for more uniformity in indicator definitions and methods in order to achieve reliable international benchmarking in the future.@en

In order to improve care for total hip and knee arthroplasties (THA/TKA), hospitals may want to compare their performance with hospitals in other countries. Pooling data across countries also enable early detection of infrequently occurring safety issues. We therefore aimed to assess the between-hospital variation and definitions used for revision, readmission, and complications across countries. • PubMed, Embase, Web of Science, Cochrane library, Emcare, and Academic Search Premier were searched from January 2009 to August 2020 for studies reporting on: (i) primary THA/ TKA; (ii) revision, readmission, or complications; and (iii) between-hospital variation. Most recent registry reports of Network of Orthopedic Registries of Europe members were also reviewed. Two reviewers independently screened records, extracted data, and assessed the risk of bias using the Integrated quality Criteria for the Review Of Multiple Study designs tool for studies and relevant domains for registries. We assessed agreement for the following domains: (i) outcome definition; (ii) follow-up and starting point; (iii) case-mix adjustment; and (iv) type of patients and hospitals included. • Between-hospital variation was reported in 33 (1 high-quality, 13 moderate-quality, and 19 low-quality) studies and 8 registry reports. The range of variation for revision was 0-33% for THA and 0-27% for TKA varying between assessment within hospital admission until 10 years of follow-up; for readmission, 0-40% and 0-32% for THA and TKA, respectively; and for complications, 0-75% and 0-50% for THA and TKA, respectively. Indicator definitions and methodological variables varied considerably across domains. • The large heterogeneity in definitions and methods used likely explains the considerable variation in between-hospital variation reported for revision, readmission, and complications, making it impossible to benchmark hospitals across countries or pool data for earlier detection of safety issues. It is necessary to collaborate internationally and strive for more uniformity in indicator definitions and methods in order to achieve reliable international benchmarking in the future.@en

Background: To assess the extent of between-hospital variation in revision following primary shoulder arthroplasty (SA), both overall and for specific revision indications to guide quality improvement initiatives, and to assess whether revision rates are suitable as quality indicators to reliably rank hospital performance. Methods: All primary SAs performed between 2014 and 2018 were included from the Dutch Arthroplasty Register to examine 1-year revision and all primary SAs performed between 2014 and 2016 for 1- and 3-year revisions. For each hospital, the observed number (O) of revisions was compared with that expected (E) based on case-mix and depicted in funnel plots with 95% control limits to identify outlier hospitals. The rankability (ie, the reliability of ranking hospitals) was calculated as the percentage of total hospital variation due to true between-hospital differences rather than chance and categorized as low (<50%), moderate (50%-75%), and high (>75%). Results: A total of 13,104 primary SAs (87 hospitals) in 2014-2018 were included, of which 7213 were performed between 2014 and 2016. Considerable between-hospital variation was found in 1-year revision in 2014-2016 (median 1.6%, interquartile range 0.0%-3.1%), identifying 3 outlier hospitals having overall significantly more revisions than expected (O/E range 1.9-2.3) and for specific indications (cuff pathology and infection). Results for 2014-2018 were similar. For 3-year revision, 3 outlier hospitals were identified (O/E range 1.7-3.3). Rankabilities for all outcomes were low. Conclusions: Considerable between-hospital variation was observed for 1- and 3-year revision rates following primary SA, where outlier hospitals could be identified based on large differences in revision for specific indications to direct quality improvement initiatives. However, rankabilities were low, meaning that much of the other (smaller) variation in performance could not be detected, rendering revisions unsuitable to rank hospital performances following primary SA.@en

Background: To assess the extent of between-hospital variation in revision following primary shoulder arthroplasty (SA), both overall and for specific revision indications to guide quality improvement initiatives, and to assess whether revision rates are suitable as quality indicators to reliably rank hospital performance. Methods: All primary SAs performed between 2014 and 2018 were included from the Dutch Arthroplasty Register to examine 1-year revision and all primary SAs performed between 2014 and 2016 for 1- and 3-year revisions. For each hospital, the observed number (O) of revisions was compared with that expected (E) based on case-mix and depicted in funnel plots with 95% control limits to identify outlier hospitals. The rankability (ie, the reliability of ranking hospitals) was calculated as the percentage of total hospital variation due to true between-hospital differences rather than chance and categorized as low (<50%), moderate (50%-75%), and high (>75%). Results: A total of 13,104 primary SAs (87 hospitals) in 2014-2018 were included, of which 7213 were performed between 2014 and 2016. Considerable between-hospital variation was found in 1-year revision in 2014-2016 (median 1.6%, interquartile range 0.0%-3.1%), identifying 3 outlier hospitals having overall significantly more revisions than expected (O/E range 1.9-2.3) and for specific indications (cuff pathology and infection). Results for 2014-2018 were similar. For 3-year revision, 3 outlier hospitals were identified (O/E range 1.7-3.3). Rankabilities for all outcomes were low. Conclusions: Considerable between-hospital variation was observed for 1- and 3-year revision rates following primary SA, where outlier hospitals could be identified based on large differences in revision for specific indications to direct quality improvement initiatives. However, rankabilities were low, meaning that much of the other (smaller) variation in performance could not be detected, rendering revisions unsuitable to rank hospital performances following primary SA.@en

Background and purpose — Most arthroplasty registers give hospital-specific feedback on revision rates after total hip and knee arthroplasties (THA/TKA). However, due to the low number of events per hospital, multiple years of data are required to reliably detect worsening performance, and any single indicator provides only part of the quality of care delivered. Therefore, we developed an ordered composite outcome including revision, readmission, complications, and long length-of-stay (LOS) for a more comprehensive view on quality of care and assessed the ability to reliably differentiate between hospitals in their performance (rankability) with fewer years of data. Methods — All THA and TKA performed between 2017 and 2019 in 20 Dutch hospitals were included. All combi-nations of the 4 indicators were ranked from best to worst to create the ordinal composite outcome for THA and TKA separately. Between-hospital variation for the composite outcome was compared with individual indicators standard-ized for case-mix differences, and we calculated the statisti-cal rankability using fixed and random effects models. Results — 22,908 THA and 20,423 TKA were included. Between-hospital variation for the THA and TKA composite outcomes was larger when compared with revision, readmis-sion, and complications, and similar to long LOS. Rankabili-ties for the composite outcomes were above 80% even with 1 year of data, meaning that largely true hospital differences were detected rather than random variation. Interpretation — The ordinal composite outcome gives a more comprehensive overview of quality of delivered care and can reliably differentiate between hospitals in their performance using 1 year of data, thereby allowing earlier intro-duction of quality improvement initiatives.@en

BACKGROUND: Variation in 1-year revision rates between Dutch hospitals after primary total hip and knee arthroplasty (THA and TKA) may direct quality-improvement initiatives if this variation accurately reflects true hospital differences. The aim of the present study was to assess the extent of variation, both overall and for specific indications, as well as the statistical reliability of ranking hospitals. METHODS: All primary THAs and TKAs that were performed between January 2014 and December 2016 were included. Observed/expected (O/E) ratios regarding 1-year revision rates were depicted in a funnel plot with 95% control limits to identify outliers based on 1 or 3 years of data, both overall and by specific indication for revision. The expected number was calculated on the basis of patient mix with use of logistic regression models. The statistical reliability of ranking hospitals (rankability) on these outcomes indicates the percentage of total variation that is explained by "true" hospital differences rather than chance. Rankability was evaluated using fixed and random effects models, for overall revisions and specific indications for revision, including 1 versus 3 years of data. RESULTS: The present study included 86,468 THAs and 73,077 TKAs from 97 and 98 hospitals, respectively. Thirteen hospitals performing THAs were identified as negative outliers (median O/E ratio, 1.9; interquartile range [IQR], 1.5-2.5), with 5 hospitals as outliers in multiple years. Eight negative outliers were identified for periprosthetic joint infection; 4, for dislocation; and 2, for prosthesis loosening. Seven hospitals performing TKAs were identified as negative outliers (median O/E ratio, 2.3; IQR, 2.2-2.8), with 2 hospitals as outliers in multiple years. Two negative outlier hospitals were identified for periprosthetic joint infection and 1 was identified for technical failures. The rankability for overall revisions was 62% (moderate) for THA and 46% (low) for TKA. CONCLUSIONS: There was large between-hospital variation in 1-year revision rates after primary THA and TKA. For most outlier hospitals, a specific indication for revision could be identified as contributing to worse performance, particularly for THA; these findings are starting points for quality-improvement initiatives.@en

BACKGROUND: Variation in 1-year revision rates between Dutch hospitals after primary total hip and knee arthroplasty (THA and TKA) may direct quality-improvement initiatives if this variation accurately reflects true hospital differences. The aim of the present study was to assess the extent of variation, both overall and for specific indications, as well as the statistical reliability of ranking hospitals. METHODS: All primary THAs and TKAs that were performed between January 2014 and December 2016 were included. Observed/expected (O/E) ratios regarding 1-year revision rates were depicted in a funnel plot with 95% control limits to identify outliers based on 1 or 3 years of data, both overall and by specific indication for revision. The expected number was calculated on the basis of patient mix with use of logistic regression models. The statistical reliability of ranking hospitals (rankability) on these outcomes indicates the percentage of total variation that is explained by "true" hospital differences rather than chance. Rankability was evaluated using fixed and random effects models, for overall revisions and specific indications for revision, including 1 versus 3 years of data. RESULTS: The present study included 86,468 THAs and 73,077 TKAs from 97 and 98 hospitals, respectively. Thirteen hospitals performing THAs were identified as negative outliers (median O/E ratio, 1.9; interquartile range [IQR], 1.5-2.5), with 5 hospitals as outliers in multiple years. Eight negative outliers were identified for periprosthetic joint infection; 4, for dislocation; and 2, for prosthesis loosening. Seven hospitals performing TKAs were identified as negative outliers (median O/E ratio, 2.3; IQR, 2.2-2.8), with 2 hospitals as outliers in multiple years. Two negative outlier hospitals were identified for periprosthetic joint infection and 1 was identified for technical failures. The rankability for overall revisions was 62% (moderate) for THA and 46% (low) for TKA. CONCLUSIONS: There was large between-hospital variation in 1-year revision rates after primary THA and TKA. For most outlier hospitals, a specific indication for revision could be identified as contributing to worse performance, particularly for THA; these findings are starting points for quality-improvement initiatives.@en

BACKGROUND: Variation in 1-year revision rates between Dutch hospitals after primary total hip and knee arthroplasty (THA and TKA) may direct quality-improvement initiatives if this variation accurately reflects true hospital differences. The aim of the present study was to assess the extent of variation, both overall and for specific indications, as well as the statistical reliability of ranking hospitals. METHODS: All primary THAs and TKAs that were performed between January 2014 and December 2016 were included. Observed/expected (O/E) ratios regarding 1-year revision rates were depicted in a funnel plot with 95% control limits to identify outliers based on 1 or 3 years of data, both overall and by specific indication for revision. The expected number was calculated on the basis of patient mix with use of logistic regression models. The statistical reliability of ranking hospitals (rankability) on these outcomes indicates the percentage of total variation that is explained by "true" hospital differences rather than chance. Rankability was evaluated using fixed and random effects models, for overall revisions and specific indications for revision, including 1 versus 3 years of data. RESULTS: The present study included 86,468 THAs and 73,077 TKAs from 97 and 98 hospitals, respectively. Thirteen hospitals performing THAs were identified as negative outliers (median O/E ratio, 1.9; interquartile range [IQR], 1.5-2.5), with 5 hospitals as outliers in multiple years. Eight negative outliers were identified for periprosthetic joint infection; 4, for dislocation; and 2, for prosthesis loosening. Seven hospitals performing TKAs were identified as negative outliers (median O/E ratio, 2.3; IQR, 2.2-2.8), with 2 hospitals as outliers in multiple years. Two negative outlier hospitals were identified for periprosthetic joint infection and 1 was identified for technical failures. The rankability for overall revisions was 62% (moderate) for THA and 46% (low) for TKA. CONCLUSIONS: There was large between-hospital variation in 1-year revision rates after primary THA and TKA. For most outlier hospitals, a specific indication for revision could be identified as contributing to worse performance, particularly for THA; these findings are starting points for quality-improvement initiatives.@en

BACKGROUND: Variation in 1-year revision rates between Dutch hospitals after primary total hip and knee arthroplasty (THA and TKA) may direct quality-improvement initiatives if this variation accurately reflects true hospital differences. The aim of the present study was to assess the extent of variation, both overall and for specific indications, as well as the statistical reliability of ranking hospitals. METHODS: All primary THAs and TKAs that were performed between January 2014 and December 2016 were included. Observed/expected (O/E) ratios regarding 1-year revision rates were depicted in a funnel plot with 95% control limits to identify outliers based on 1 or 3 years of data, both overall and by specific indication for revision. The expected number was calculated on the basis of patient mix with use of logistic regression models. The statistical reliability of ranking hospitals (rankability) on these outcomes indicates the percentage of total variation that is explained by "true" hospital differences rather than chance. Rankability was evaluated using fixed and random effects models, for overall revisions and specific indications for revision, including 1 versus 3 years of data. RESULTS: The present study included 86,468 THAs and 73,077 TKAs from 97 and 98 hospitals, respectively. Thirteen hospitals performing THAs were identified as negative outliers (median O/E ratio, 1.9; interquartile range [IQR], 1.5-2.5), with 5 hospitals as outliers in multiple years. Eight negative outliers were identified for periprosthetic joint infection; 4, for dislocation; and 2, for prosthesis loosening. Seven hospitals performing TKAs were identified as negative outliers (median O/E ratio, 2.3; IQR, 2.2-2.8), with 2 hospitals as outliers in multiple years. Two negative outlier hospitals were identified for periprosthetic joint infection and 1 was identified for technical failures. The rankability for overall revisions was 62% (moderate) for THA and 46% (low) for TKA. CONCLUSIONS: There was large between-hospital variation in 1-year revision rates after primary THA and TKA. For most outlier hospitals, a specific indication for revision could be identified as contributing to worse performance, particularly for THA; these findings are starting points for quality-improvement initiatives.@en

BACKGROUND: Variation in 1-year revision rates between Dutch hospitals after primary total hip and knee arthroplasty (THA and TKA) may direct quality-improvement initiatives if this variation accurately reflects true hospital differences. The aim of the present study was to assess the extent of variation, both overall and for specific indications, as well as the statistical reliability of ranking hospitals. METHODS: All primary THAs and TKAs that were performed between January 2014 and December 2016 were included. Observed/expected (O/E) ratios regarding 1-year revision rates were depicted in a funnel plot with 95% control limits to identify outliers based on 1 or 3 years of data, both overall and by specific indication for revision. The expected number was calculated on the basis of patient mix with use of logistic regression models. The statistical reliability of ranking hospitals (rankability) on these outcomes indicates the percentage of total variation that is explained by "true" hospital differences rather than chance. Rankability was evaluated using fixed and random effects models, for overall revisions and specific indications for revision, including 1 versus 3 years of data. RESULTS: The present study included 86,468 THAs and 73,077 TKAs from 97 and 98 hospitals, respectively. Thirteen hospitals performing THAs were identified as negative outliers (median O/E ratio, 1.9; interquartile range [IQR], 1.5-2.5), with 5 hospitals as outliers in multiple years. Eight negative outliers were identified for periprosthetic joint infection; 4, for dislocation; and 2, for prosthesis loosening. Seven hospitals performing TKAs were identified as negative outliers (median O/E ratio, 2.3; IQR, 2.2-2.8), with 2 hospitals as outliers in multiple years. Two negative outlier hospitals were identified for periprosthetic joint infection and 1 was identified for technical failures. The rankability for overall revisions was 62% (moderate) for THA and 46% (low) for TKA. CONCLUSIONS: There was large between-hospital variation in 1-year revision rates after primary THA and TKA. For most outlier hospitals, a specific indication for revision could be identified as contributing to worse performance, particularly for THA; these findings are starting points for quality-improvement initiatives.@en

Background:Given the low early revision rate after total hip arthroplasty (THA) and total knee arthroplasty (TKA), hospital performance is typically compared using 3 years of data. The purpose of this study was to assess how much earlier worsening hospital performance in 1-year revision rates after THA and TKA can be detected.Methods:All 86,468 THA and 73,077 TKA procedures performed from 2014 to 2016 and recorded in the Dutch Arthroplasty Register were included. Negative outlier hospitals were identified by significantly higher O/E (observed divided by expected) 1-year revision rates in a funnel plot. Monthly Shewhart p-charts (with 2 and 3-sigma control limits) and cumulative sum (CUSUM) charts (with 3.5 and 5 control limits) were constructed to detect a doubling of revisions (odds ratio of 2), generating a signal when the control limit was reached. The median number of months until generation of a first signal for negative outliers and the number of false signals for non-negative outliers were calculated. Sensitivity, specificity, and accuracy were calculated for all charts and control limit settings using outlier status in the funnel plot as the gold standard.Results:The funnel plot showed that 13 of 97 hospitals had significantly higher O/E 1-year revision rates and were negative outliers for THA and 7 of 98 hospitals had significantly higher O/E 1-year revision rates and were negative outliers for TKA. The Shewhart p-chart with the 3-sigma control limit generated 68 signals (34 false-positive) for THA and 85 signals (63 false-positive) for TKA. The sensitivity for THA and TKA was 92% and 100%, respectively; the specificity was 69% and 51%, respectively; and the accuracy was 72% and 54%, respectively. The CUSUM chart with a 5 control limit generated 18 signals (1 false-positive) for THA and 7 (1 false-positive) for TKA. The sensitivity was 85% and 71% for THA and TKA, respectively; the specificity was 99% for both; and the accuracy was 97% for both. The Shewhart p-chart with a 3-sigma control limit generated the first signal for negative outliers after a median of 10 months (interquartile range [IQR] = 2 to 18) for THA and 13 months (IQR = 5 to 18) for TKA. The CUSUM chart with a 5 control limit generated the first signal after a median of 18 months (IQR = 7 to 22) for THA and 21 months (IQR = 9 to 25) for TKA.Conclusions:Monthly monitoring using CUSUM charts with a 5 control limit enables earlier detection of worsening 1-year revision rates with accuracy so that initiatives to improve care can start earlier. @en

Background and purpose — The Netherlands Registry of Orthopedic Implants (LROI) uses audit and feedback (A&F) as the strategy to improve performance outcomes after total hip and knee arthroplasty (THA/TKA). Effectiveness of A&F depends on awareness of below-average performance to initiate improvement activities. We explored the awareness of Dutch orthopedic surgeons regarding their performance on outcomes after THA/TKA and factors associated with this awareness. Methods — An anonymous questionnaire was sent to all 445 eligible Dutch orthopedic surgeons performing THA/TKA. To assess awareness on own surgeon-group performance, they were asked whether their 1-year THA/TKA revision rates over the past 2 years were below average (negative outlier), average (non-outlier), above average (positive outlier) in the funnel plot on the LROI dashboard, or did not know. Associations were determined with (1) dashboard login at least once a year (yes/no); (2) correct funnel-plot interpretation (yes/no) and; (3) recall of their 1-year THA/TKA revision rate (yes/no). Results — 44% of respondents started the questionnaire, 158 THA and 156 TKA surgeons. 55% of THA surgeons and 55% of TKA surgeons were aware of their performance. Surgeons aware of their performance more often logged in on the LROI dashboard, more often interpreted funnel plots correctly, and more often recalled their revision rate. 38% of THA and 26% of TKA surgeons scored “good” on all 3 outcomes. Interpretation — Only half of the orthopedic surgeons were aware of their performance status regarding outcomes after THA/TKA. This suggests that to increase awareness, orthopedic surgeons need to be actively motivated to look at the dashboard more frequently and educated on interpretation of funnel plots for audit and feedback to be effective.@en