The Impact of Surgeon Variability on Patient-Reported Outcomes in Total Hip Arthroplasty

Inflammatory bowel disease patients undergoing total hip arthroplasty have higher odds of implant-related complications

PURPOSE

This study evaluates whether IBD patients are at increased risk of implant-related complications after THA.

MATERIALS AND METHODS

A retrospective study from 01 January 2010 to 31 October 31 2020 using an administrative claims database was performed. IBD patients undergoing THA (n = 11,025), without corticosteroid treatment, were propensity score matched to controls in a 1:5 ratio (n = 55,121) based on age, sex, and the Charlson Comorbidity Index (CCI). Outcomes evaluated included periprosthetic fracture, aseptic loosening, prosthetic joint infection, and THA revision within 2 years of index procedure. Chi-square analyses were used to compare the matched cohorts. The association of IBD and implant-related complications was evaluated using logistical regression to calculate odds ratios (ORs), 95% confidence intervals (95% CIs), and p-values. A p-value < 0.001 was used as the significance threshold.

RESULTS

Patients with IBD had a greater incidence and odds of total implant complications (7.03% vs. 3.98%; OR 1.76; p < 0.001) compared with matched controls. IBD patients had significantly higher incidence and odds of developing periprosthetic fracture (0.50% vs. 0.20%; OR 2.46; p < 0.001), THA revisions (2.21% vs. 1.17%; OR 1.91; p < 0.001), aseptic loosening (1.45% vs. 0.84%; OR 1.75; p < 0.001), and prosthetic joint infection (2.87% vs. 1.77%; OR 1.64; p < 0.001).

CONCLUSIONS

Patients with IBD who underwent primary THA had a significantly higher risk of implant-related complications compared to matched controls. Providers should use this study to appropriately assess post-complication risk factors for their patients with IBD.

How to Raise the Bar in the Capture of Patient-Reported Outcome Measures in Total Joint Arthroplasty: Results from Active and Passive Follow-up Measures

BACKGROUND

With the upcoming U.S. Centers for Medicare & Medicaid Services 2027 policy for mandatory reporting of patient-reported outcome measures (PROMs) for total hip or knee arthroplasty (THA or TKA), it is important to evaluate the resources required to achieve adequate PROM collection and reporting at a clinically relevant rate of follow-up. This study aimed to (1) determine follow-up rates for 1-year PROMs when the follow-up was conducted with active methods (attempted contact by staff) and passive (automated) methods, and (2) evaluate factors associated with higher odds of requiring active follow-up or being lost to follow-up following THA or TKA.

METHODS

A prospective cohort of patients undergoing primary elective THA (n = 7,436) or TKA (n = 10,119) between January 2016 and December 2020 at a single institution were included. The primary outcome was the response rate achieved with active and passive follow-up methods at our institution. Patient characteristics, health-care utilization parameters, PROM values, and patient satisfaction were compared between follow-up methods.

RESULTS

Passive and active measures were successful for 38% (2,859) and 40% (3,004) of the THA cohort, respectively, while 21% (1,573) were lost to follow-up. Similarly, passive and active measures were successful for 40% (4,001) and 41% (4,161) of the TKA cohort, respectively, while 20% (2,037) were lost to follow-up. Younger age, male sex, Black or another non-White race, fewer years of education, smoking, Medicare or Medicaid insurance, and specific baseline PROM phenotypes (i.e., with scores in the lower half for pain, function, and/or mental health) were associated with loss to follow-up. Older age, male sex, Black race, and a residence with a higher Area Deprivation Index were associated with requiring active follow-up.

CONCLUSIONS

One of 5 patients were lost to follow-up despite active and passive measures following THA or TKA. These patients were more likely to be younger, be male, be of Black or another non-White race, have fewer years of education, be a smoker, have Medicaid insurance, and have specific baseline PROM phenotypes. Innovative strategies aimed at targeting individuals with these baseline characteristics may help raise the bar and increase follow-up while mitigating costs after total joint arthroplasty.

LEVEL OF EVIDENCE

Prognostic Level II . See Instructions for Authors for a complete description of levels of evidence.

Surgeon Performance as a Predictor for Patient-Reported Outcomes After Arthroscopic Partial Meniscectomy

Background

Surgeon performance has been investigated as a factor affecting patient outcomes after orthopaedic procedures to improve transparency between patients and providers.

Purpose/Hypothesis

The purpose of this study was to identify whether surgeon performance influenced patient-reported outcomes (PROMs) 1 year after arthroscopic partial meniscectomy (APM). It was hypothesized that there would be no significant difference in PROMs between patients who underwent APM from various surgeons.

Study Design

Case-control study; Level of evidence, 3.

Methods

A prospective cohort of 794 patients who underwent APM between 2018 and 2019 were included in the analysis. A total of 34 surgeons from a large multicenter health care center were included. Three multivariable models were built to determine whether the surgeon-among demographic and meniscal pathology factors-was a significant variable for predicting the Knee injury and Osteoarthritis Outcome Score (KOOS)-Pain subscale, the Patient Acceptable Symptom State (PASS), and a 10-point improvement in the KOOS-Pain at 1 year after APM. Likelihood ratio (LR) tests were used to determine the significance of the surgeon variable in the models.

Results

The 794 patients were identified from the multicenter hospital system. The baseline KOOS-Pain score was a significant predictor of outcome in the 1-year KOOS-Pain model (odds ratio [OR], 2.1 [95% CI, 1.77-2.48]; P < .001), the KOOS-Pain 10-point improvement model (OR, 0.57 [95% CI, 0.44-0.73), and the 1-year PASS model (OR, 1.42 [95% CI, 1.15-1.76]; P = .002) among articular cartilage pathology (bipolar medial cartilage) and patient-factor variables, including body mass index, Veterans RAND 12-Item Health Survey-Mental Component Score, and Area Deprivation Index. The individual surgeon significantly impacted outcomes in the 1-year KOOS-Pain mixed model in the LR test (P = .004).

Conclusion

Patient factors and characteristics are better predictors for patient outcomes 1 year after APM than surgeon characteristics, specifically baseline KOOS-Pain, although an individual surgeon influenced the 1-Year KOOS-Pain mixed model in the LR test. This finding has key clinical implications; surgeons who wish to improve patient outcomes after APM should focus on improving patient selection rather than improving the surgical technique. Future research is needed to determine whether surgeon variability has an impact on longer-term patient outcomes.

Lower 90-day inpatient readmission and 1-year reoperation in patients undergoing robotic versus manual total hip arthroplasty through an anterior approach

BACKGROUND

The value of robotic-assisted total hip arthroplasty (rTHA) has yet to be determined compared to conventional manual THA (mTHA).

OBJECTIVE

Evaluate 90-day inpatient readmission rates, rates of reoperation, and clinically significant improvement of patient-reported outcome measures (PROMs) at 1-year in a cohort of patients who underwent mTHA or rTHA through a direct anterior (DA) approach.

METHODS

A single-surgeon, prospective institutional cohort of 362 patients who underwent primary THA for osteoarthritis via the DA approach between February 2019 and November 2020 were included. Patient demographics, surgical time, discharge disposition, length of stay, acetabular cup size, 90-day inpatient readmission, 1-year reoperation, and 1-year PROMs were collected for 148 manual and 214 robotic THAs, respectively.

RESULTS

Patients undergoing rTHA had lower 90-day readmission (3.74% vs 9.46%, p= 0.04) and lower 1-year reoperation (0.93% vs 4.73% mTHA, p= 0.04). rTHA acetabular cup sizes were smaller (rTHA median 52, interquartile range [IQR] 50; 54, mTHA median 54, IQR 52; 58, p< 0.001). Surgical time was longer for rTHA (114 minutes vs 101 minutes, p< 0.001). At 1-year post-operatively, there was no difference in any of the PROMs evaluated.

CONCLUSION

Robotic THA demonstrated lower 90-day readmissions and 1-year reoperation rates than manual THA via the DA approach. PROMs were not significantly different between the two groups at one year.

Intersurgeon Variability of Minimal Clinically Important Difference for Worsening Achievement Rates After Total Joint Arthroplasty

BACKGROUND

Using the Patient-Reported Outcome Measurement Information System, we sought to evaluate surgeon performance variability via minimal clinically important difference for worsening (MCID-W) achievement rates in primary and revision total knee and hip arthroplasty.

METHODS

This retrospective study analyzed 3,496 primary total hip arthroplasty (THA), 4,622 primary total knee arthroplasty (TKA), 592 revision THA, and 569 revision TKA patients. Patient factors collected included demographics, comorbidities, and Patient-Reported Outcome Measurement Information System physical function short form 10a scores. Surgeon factors collected included caseload, years of experience, and fellowship training. The MCID-W rate was calculated as the percent of patients in each surgeon's cohort who achieved MCID-W. Distribution was presented via a histogram with associated average, standard deviation, range, and interquartile range (IQR). Linear regressions were performed to evaluate the potential correlation between surgeon- and patient-level factors with MCID-W rate.

RESULTS

The average MCID-W rates of the surgeons represented in the primary THA and TKA cohorts were 12.7 ± 9.2% (range, 0 to 35.3%; IQR, 6.7 to 15.5%) and 18.0 ± 8.2% (range, 0 to 36%; IQR, 14.3 to 22.0%). The average MCID-W rates among the revision THA and TKA surgeons were 36.0 ± 22.2% (range, 9.1 to 90%; IQR, 25.0 to 41.4%) and 21.2 ± 7.7% (range, 8.1 to 37.0%; IQR, 16.6 to 25.4%). Strong correlations were not found between patient- or surgeon-level factors and MCID-W rate of the surgeon.

CONCLUSION

We demonstrated variance in MCID-W achievement rates across surgeons in both primary and revision joint arthroplasty, independent of patient- or surgeon-level factors.

How Much Perioperative Pain and Dysfunction Underlie the HOOS JR and KOOS JR?

BACKGROUND

The Hip Disability and Osteoarthritis Outcome Score Joint Replacement (HOOS JR) and Knee Injury and Osteoarthritis Outcome Score Joint Replacement (KOOS JR) scores represent pain and dysfunction as a single number ranging from 0 (extreme pain and dysfunction) to 100 (no pain or functional limitations). However, scores between 0 and 100 lack a simple interpretation because they reflect varying combinations of pain levels and dysfunction. Given that most adverse events and improvement occur within the first 90 days after surgery, a deeper understanding of the level of pain and dysfunction may reveal missed opportunities for patient care.

QUESTIONS/PURPOSES

(1) What does a given preoperative or postoperative HOOS JR and KOOS JR score indicate about pain and ability to perform daily activities? (2) How much of a change in score (that is, delta) is needed to indicate significant improvement in pain control and daily functioning?

METHODS

The Michigan Arthroplasty Registry Collaborative Quality Initiative contains more than 95% of THAs and TKAs performed in Michigan. Between January 2017 and March 2019, 84,175 people in the registry underwent primary THA or TKA and were potentially eligible for this retrospective, comparative study of the first 90 postoperative days. Eighty-four percent (70,608 of 84,175) were excluded because their surgeons did not attain a target survey collection proportion of 70% and another 6% (5042) were missing covariate information or surveys, leaving 10% (8525) for analysis. The mean age and percentage of women were 65 ± 11 years and 55% (2060 of 3716), respectively, for patients undergoing THA and 67 ± 9 years and 61% (2936 of 4809), respectively, for those undergoing TKA. There were no clinically meaningful differences between patients who were analyzed and those who were excluded except for lower representation of non-White patients in the analyzed group. For interpretation, patient responses to Question 7 (pain) and Question 6 (function) from the Patient-Reported Outcomes Measurement Information System global items (PROMIS-10) were dichotomized into "much pain" (rating of pain 4 to 10 of 10) versus "less pain" (rating of ≤ 3) and "good function" (able to perform most activities) versus "poor function" (not able to perform most activities) and combined into four pain-function categories. We examined the mean preoperative and postoperative HOOS JR and KOOS JR scores for each pain-function category, adjusted for patient characteristics. We calculated the size of the delta associated with an increase to a more favorable category postoperatively (versus staying in the same or worse category) via multivariable logistic regression that controlled for patient characteristics.

RESULTS

Patients in the least favorable "much pain, poor function" category preoperatively had adjusted mean scores of 40 (95% confidence interval 39 to 41) for both the HOOS JR and KOOS JR. Those with mixed levels of pain and function had mean scores between 46 and 55. Those in the most favorable "less pain, good function" category had means of 60 (95% CI 58 to 62) and 59 (95% CI 58 to 61) for the HOOS JR and KOOS JR, respectively. The adjusted delta to achieve a pain level of ≤ 3 or the ability to perform most activities was 30 (95% CI 26 to 36) on the HOOS JR and 27 (95% CI 22 to 29) on the KOOS JR scales.

CONCLUSION

These adjusted means of the HOOS JR and KOOS JR provide context for understanding the levels of pain and dysfunction for individuals as well for patients reported in other studies. Potential quality improvement efforts could include tracking the proportion of patients with THA or TKA who achieved a sufficient delta to attain pain levels of ≤ 3 or the ability to perform most activities. Future studies are needed to understand pain and function represented by the HOOS JR and KOOS JR at 1 to 2 years, how these may differ by patient subgroups, and whether scores can be improved through quality improvement efforts.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Hospital Teaching Status and Patient-Reported Outcomes Following Primary Total Hip Arthroplasty: An American Joint Replacement Registry Study

INTRODUCTION

Previous studies have shown lower morbidity and mortality rates after total hip arthroplasty (THA) at academic teaching hospitals. This study sought to determine the relationship between hospital teaching status and patient-reported outcome measures following primary THA.

METHODS

Using American Joint Replacement Registry data from 2012 to 2020, 4,447 primary, elective THAs with both preoperative and one year postoperative Hip disability and Osteoarthritis Outcome Score, Joint Replacement (HOOS, JR) scores were analyzed. The main exposure variable was hospital teaching status, with three cohorts, as follows: major teaching hospitals, minor teaching hospitals, and non-teaching hospitals. Mean preoperative and one year postoperative HOOS, JR scores were compared.

RESULTS

Preoperative HOOS, JR scores (nonteaching: 49.69 ± 14.42 versus major teaching: 47.68 ± 15.10 versus minor teaching: 42.46 ± 19.19, P < .001) were significantly higher at non-teaching hospitals than major and minor teaching hospitals, and these differences persisted at one year postoperatively (87.40 ± 15.14 versus 83.87 ± 16.68 versus 80.37 ± 19.27, P < .001). Both preoperative and postoperative differences in HOOS, JR scores were less than the minimum clinically important difference (MCID) at both time points. In multivariate regressions, non-teaching and minor teaching hospitals had similar odds of MCID achievement in HOOS, JR scores compared to major teaching hospitals.

CONCLUSION

Using the HOOS, JR score as a validated outcome measure, undergoing primary THA at an academic teaching hospital did not correlate with higher postoperative HOOS, JR scores or greater chances of MCID achievement in HOOS, JR scores compared to non-teaching hospitals. Further work is required to determine the most important factors that may lead to improvement in patient-reported outcomes following THA.

The learning curve for anatomic and reverse total shoulder arthroplasty: a systematic review

Background

Despite the rising incidence of anatomic total shoulder arthroplasty (ATSA) and reverse total shoulder arthroplasty (RTSA) among surgeons, little is known about the learning curve associated with these procedures. The purpose of this systematic review was to (1) identify the learning curves associated with ATSA and RTSA, (2) evaluate the effect of the learning curves on clinical outcomes, and (3) determine the number of cases needed to achieve proficiency.

Methods

Four online databases [PubMed (NLM), MEDLINE (OVID), Cochrane Library (Wiley), and Scopus (Elsevier)] were systematically searched and screened according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. The search included results from the inception of each database to May 18, 2022. Data regarding study characteristics, patient demographics, learning curve analyses, patient reported outcome measures, range of motion, complication rates, and reoperation rates were collected. A quality assessment for each article was performed according to the Methodological Index for Nonrandomized Studies criteria.

Results

A total of 13 studies of fair to good quality were included for analysis (one of level II evidence, five of level III, and seven of level IV) with the majority originating from the United States [n = 8, 61.5%]. Overall, there were a total of 3381 cases (1861 RTSA and 1520 ATSA), with a mean patient age of 72.6 years [range: 45-92 years]. From the studies analyzed in this systematic review, for RTSA, the approximate average number of cases surgeons need to perform to move to an acceptable position on the RTSA learning curve is 25 cases. For ATSA, a wider range of 16-86 cases was derived as only two studies reported on ATSA.

Conclusion

Progression along the learning curve for RTSA and ATSA results in decreased operative times, improved patient-reported outcomes, and fewer complications. However, a true learning curve is difficult to quantify given the heterogeneity of reported outcome measures, individual surgeon experience at the time of data collection, and statistical analyses used across studies.

Impaction procedure influences primary stability of acetabular press-fit components

The aim of the study was to investigate whether the primary stability of press-fit acetabular components can be improved by altering the impaction procedure. Three impaction procedures were used to implant acetabular components into human cadaveric acetabula using a powered impaction device. An impaction frequency of 1 Hz until complete component seating served as reference. Overimpaction was simulated by adding ten strokes after complete component seating. High-frequency implantation was performed at 6 Hz. The lever-out moment of the acetabular components was used as measure for primary stability. Permanent bone deformation was assessed by comparison of double micro-CT (µCT) measurements before and after impaction. Acetabular component deformation and impaction forces were recorded, and the extent of bone-implant contact was determined from 3D laser scans. Overimpaction reduced primary acetabular component stability (p = 0.038) but did not significantly increase strain release after implantation (p = 0.117) or plastic deformations (p = 0.193). Higher press-fits were associated with larger polar gaps for the 1 Hz reference impaction (p = 0.002, R² = 0.77), with a similar trend for overimpaction (p = 0.082, R² = 0.31). High-frequency impaction did not significantly increase primary stability (p = 0.170) at lower impaction forces (p = 0.001); it was associated with smaller plastic deformations (p = 0.035, R² = 0.34) and a trend for increased acetabular component relaxation between strokes (p = 0.112). Higher press-fit was not related to larger polar gaps for the 6 Hz impaction (p = 0.346). Overimpaction of press-fit acetabular components should be prevented since additional strokes can be associated with increased bone damage and reduced primary stability as shown in this study. High-frequency impaction at 6 Hz was shown to be beneficial compared with 1 Hz impaction. This benefit has to be confirmed in clinical studies.

The Effect of Surgeon and Hospital Volume on Total Hip Arthroplasty Patient-Reported Outcome Measures: An American Joint Replacement Registry Study

BACKGROUND

Some studies have shown lower morbidity and mortality rates with increased surgeon and hospital volumes after total hip arthroplasty (THA). This study sought to determine the relationship between surgeon and hospital volumes and patient-reported outcome measures after THA using American Joint Replacement Registry data.

METHODS

Using American Joint Replacement Registry data from 2012 to 2020, 4,447 primary, elective THAs with both preoperative and 1-year postoperative Hip Dysfunction and Osteoarthritis Outcome Score for Joint Replacement (HOOS-JR) scores were analyzed. This study was powered to detect the minimum clinically important difference (MCID). The main exposure variables were median annual surgeon and hospital volumes. Tertiles were formed based on the median annual number of THAs conducted: low-volume (1 to 42), medium-volume (42 to 96), and high-volume (≥96) surgeons and low-volume (1 to 201), medium-volume (201 to 392), and high-volume (≥392) hospitals. Mean preoperative and 1-year postoperative HOOS-JR scores were compared.

RESULTS

Preoperative HOOS-JR scores were significantly higher at high-volume hospitals than low-volume and medium-volume hospitals (49.66 ± 15.19 vs. 47.68 ± 15.09 and 48.34 ± 15.22, P < 0.001), although these differences were less than the MCID. At the 1-year follow-up, no difference was noted with no resultant MCID. Preoperative and 1-year HOOS-JR scores did not markedly vary with surgeon volume. In multivariate regression, low-volume and medium-volume surgeons and hospitals had similar odds of MCID achievement in HOOS-JR scores compared with high-volume surgeons and hospitals, respectively.

CONCLUSION

Using the HOOS-JR score as a validated patient-reported outcome measure, higher surgeon or hospital THA volume did not correlate with higher postoperative HOOS-JR scores or greater chances of MCID achievement in HOOS-JR scores compared with medium and lower volume surgeons and hospitals.

The Impact of Surgeon Variability on Patient-Reported Outcome Measures, Length of Stay, Discharge Disposition, and 90-Day Readmission in TKA

BACKGROUND

Studies involving total knee arthroplasty (TKA) have focused on patient-related factors as drivers of outcomes. Although some studies have investigated surgeon and/or surgery-level factors (i.e., approach, volume), the measure of variance in postoperative outcomes across surgeons following TKA has not been determined. The aim of the current study was to evaluate the relationship between the surgeon and 1-year patient-reported outcome measures, the length of stay, the discharge disposition, and 90-day readmission after TKA, as well as the differences in these variables among surgeons.

METHODS

Data were prospectively collected for 5,429 patients who underwent TKA at a large health-care system with 36 surgeons between 2016 and 2018. Likelihood ratio tests were performed to investigate the relationship between surgeon and the 1-year Knee injury and Osteoarthritis Outcome Score (KOOS)-Pain subscale, KOOS-Physical Function Shortform (KOOS-PS), KOOS for Joint Replacement (KOOS-JR), patient acceptable symptom state (PASS), length of stay, discharge disposition, and 90-day readmission. The minimal clinically important difference (MCID) was used to assess meaningful outcomes. Variable importance was determined by the Akaike information criterion (AIC) increase, using ordinal and binary-response mixed-effect models.

RESULTS

There was a significant association between surgeon and KOOS-Pain (p < 0.001), KOOS-PS (p = 0.001), KOOS-JR (p < 0.001), PASS (p = 0.024), length of stay (p < 0.001), discharge disposition (p < 0.001), and 90-day readmission (p < 0.001). When modeling 1-year KOOS-Pain (AIC increase, 15.6), KOOS-PS (AIC increase, 6.8), KOOS-JR (AIC increase, 13.5), PASS (AIC increase, 1.9), length of stay, and discharge disposition, the surgeon variable contributed more to the 1-year outcome than some patient-level factors (e.g., body mass index, Charlson Comorbidity Index). The difference between the highest and lowest median probabilities of attaining the same value for the KOOS-Pain (11.2%), KOOS-PS (9.4%), KOOS-JR (11.8%), PASS (5.9%), length of stay (46.6%), discharge disposition (22.8%), and readmission (13.1%) indicated surgeon-level variability.

CONCLUSIONS

Surgeon-related factors may be stronger contributors to the 1-year patient-reported outcome measures and length of stay than patient characteristics emphasized in the literature. Current findings have suggested variability in patient-reported outcome measures, length of stay, discharge location, and 90-day readmission among surgeons. Surgeon variability should be considered when model-fitting in the setting of TKA.

LEVEL OF EVIDENCE

Prognostic Level II . See Instructions for Authors for a complete description of levels of evidence.