Evidence-Based Thresholds for the Volume and Cost Relationship in Total Hip Arthroplasty: Outcomes and Economies of Scale

The incremental risk of fragility fractures in aging men

INTRODUCTION

While the United States Preventative Services Task Force recommends osteoporosis screening for women 65 years and older, there is no definitive recommendation for routine osteoporosis screening in men. The purpose of this study was to determine the age at which the odds of fragility fractures (FFx) increase in men to help guide future policy discussions evaluating an optimal screening strategy in this population.

METHODS

Men older than 49 years were identified in the PearlDiver Patient Records Database. Patients were excluded if they had a prior fragility fracture, if they were at high risk for osteoporosis due to comorbidities, or if they carried a diagnosis of and/or were on treatment for osteoporosis. The prevalence of FFx was trended for each age group. A stratum-specific likelihood ratio (SSLR) analysis was conducted to identify data-driven strata that maximize the incremental FFx risk by age for men. Logistic regression analyses controlling for potential confounders were conducted to test these identified strata.

RESULTS

The incidence of FFx started to increase after the age of 64 years for men. Further, the identified data-driven age strata associated with a significant and incremental difference in fragility fractures were the following: 50-64, 65-69, 70-72, 73-75, 76-78, 79-80, and 81+. When compared to the youngest age stratum (50-64 years), multivariable regression showed the risk of fragility fracture incrementally increased starting in those aged 70-72 (RR, 1.31; 95% CI. 1.21-1.46; p < 0.001) with the highest risk in those aged 81+ (RR, 5.35; 95% CI, 5.10-5.62; p < 0.001).

CONCLUSION

In men without a pre-existing history of osteoporosis, the risk of fragility fractures starts to increase after the age of 70. Further work building upon these data may help to identify a specific age at which routine bone health screening in males can help to minimize fractures and their associated morbidity and mortality.

High-volume Arthroplasty Centers Are Associated With Lower Hospital Costs When Performing Primary THA and TKA: A Database Study of 288,909 Medicare Claims for Procedures Performed in 2019

BACKGROUND

With bundled payments and alternative reimbursement models expanding in scope and scale, reimbursements to hospitals are declining in value. As a result, cost reduction at the hospital level is paramount for the sustainability of profitable inpatient arthroplasty practices. Although multiple prior studies have investigated cost variation in arthroplasty surgery, it is unknown whether contemporary inpatient arthroplasty practices benefit from economies of scale after accounting for hospital characteristics and patient selection factors. Quantifying the independent effects of volume-based cost variation may be important for guiding future value-based health reform.

QUESTIONS/PURPOSES

We performed this study to (1) determine whether the cost incurred by hospitals for performing primary inpatient THA and TKA is independently associated with hospital volume and (2) establish whether length of stay and discharge to home are associated with hospital volume.

METHODS

The primary data source for this study was the Medicare Provider Analysis and Review Limited Data Set, which includes claims data for 100% of inpatient Medicare hospitalizations. We included patients undergoing primary elective inpatient THA and TKA in 2019. Exclusion criteria included non-Inpatient Prospective Payment System hospitalizations, nonelective admissions, bilateral procedures, and patients with cancer of the pelvis or lower extremities. A total of 500,658 arthroplasties were performed across 2762 hospitals for 492,262 Medicare beneficiaries during the study period; 59% (288,909 of 492,262) of procedures were analyzed after the exclusion criteria were applied. Most exclusions (37% [182,733 of 492,262]) were because of non-Inpatient Prospective Payment System hospitalizations. Among the study group, 87% (251,996 of 288,909) of procedures were in patients who were 65 to 84 years old, 88% (255,415 of 288,909) were performed in patients who were White, and 63% (180,688 of 288,909) were in patients who were women. Elixhauser comorbidities and van Walraven indices were calculated as measures of patient health status. Hospital costs were estimated by multiplying cost-to-charge ratios obtained from the 2019 Impact File by total hospital charges. This methodology enabled us to use the large Medicare Provider Analysis and Review database, which helped decrease the influence of random cost variation through the law of large numbers. Hospital volumes were calculated by stratifying claims by national provider identification number and counting the number of claims per national provider identification number. The data were then grouped into bins of increasing hospital volume to more easily compare larger-volume and smaller-volume centers. The relationship between hospital costs and volume was analyzed using univariable and multivariable generalized linear models. Results are reported as exponential coefficients, which can be interpreted as relative differences in cost. The impact of surgical volume on length of stay and discharge to home was assessed using binary logistic regression, considering the nested structure of the data, and results are reported as odds ratios (OR).

RESULTS

Hospital cost and mean length of stay decreased, while rates of discharge to home increased with increasing hospital volume. After controlling for potential confounding variables such as patient demographics, health status, and geographic location, we found that inpatient arthroplasty costs at hospitals with 10 or fewer, 11 to 100, and 101 to 200 procedures annually were 1.32 (95% confidence interval [CI] 1.30 to 1.34; p < 0.001), 1.17 (95% CI 1.17 to 1.17; p < 0.001), and 1.10 (95% CI 1.10 to 1.10; p < 0.001) times greater than those of hospitals with 201 or more inpatient procedures annually. In addition, patients treated at smaller-volume hospitals had increased odds of experiencing a length of stay longer than 2 days (OR 1.25 to 3.44 [95% CI 1.10 to 4.03]; p < 0.001) and decreased odds of being discharged to home (OR 0.34 to 0.78 [95% CI 0.29 to 0.86]; p < 0.001).

CONCLUSION

Higher-volume hospitals incur lower costs, shorter lengths of stay, and higher rates of discharge to home than lower-volume hospitals when performing inpatient THA and TKA. These findings suggest that small and medium-sized regional hospitals are disproportionately impacted by declining reimbursement and may necessitate special treatment to remain viable as bundled payment models continue to erode hospital payments. Further research is also warranted to identify the key drivers of this volume-based cost variation, which may facilitate quality improvement initiatives at the hospital and policy levels.

The BTK Safety Score: A Novel Scoring System for Risk Stratifying Patients Undergoing Simultaneous Bilateral Total Knee Arthroplasty

Selection of appropriate candidates for simultaneous bilateral total knee arthroplasty (si-BTKA) is crucial for minimizing postoperative complications. The aim of this study was to develop a scoring system for identifying patients who may be appropriate for si-BTKA. Patients who underwent si-BTKA were identified in the National Surgical Quality Improvement Program database. Patients who experienced a major 30-day complication were identified as high-risk patients for si-BTKA who potentially would have benefitted from staged bilateral total knee arthroplasty. Major complications included deep wound infection, pneumonia, renal insufficiency or failure, cerebrovascular accident, cardiac arrest, myocardial infarction, pulmonary embolism, sepsis, or death. The predictive model was trained using randomly split 70% of the dataset and validated on the remaining 30%. The scoring system was compared against the American Society of Anesthesiologists (ASA) score, the Charlson Comorbidity Index (CCI), and legacy risk-stratification measures, using area under the curve (AUC) statistic. Total 4,630 patients undergoing si-BTKA were included in our cohort. In our model, patients are assigned points based on the following risk factors: +1 for age ≥ 75, +2 for age ≥ 82, +1 for body mass index (BMI) ≥ 34, +2 for BMI ≥ 42, +1 for hypertension requiring medication, +1 for pulmonary disease (chronic obstructive pulmonary disease or dyspnea), and +3 for end-stage renal disease. The scoring system exhibited an AUC of 0.816, which was significantly higher than the AUC of ASA (0.545; p < 0.001) and CCI (0.599; p < 0.001). The BTK Safety Score developed and validated in our study can be used by surgeons and perioperative teams to risk stratify patients undergoing si-BTKA. Future work is needed to assess this scoring system's ability to predict long-term functional outcomes.

Evaluation of the volume-value relationship in hip fracture care using evidence-based thresholds

BACKGROUND

Studies have shown high-volume surgeons and hospitals deliver higher value care. The aims of this study were to establish meaningful thresholds defining high-volume surgeons and hospitals performing hip fracture surgery and to examine the relative market share of hip fracture cases using these surgeon and hospital strata.

METHODS

We performed a retrospective cohort study in a database of 103,935 patients undergoing hip fracture repair. We generated stratum-specific likelihood ratio (SSLR) models of a receiver operating characteristic (ROC) curve using length of stay (LOS) and cost value metrics. Volume thresholds predictive of decreased LOS and costs for surgeons and hospitals were identified.

RESULTS

Analysis of annual surgeon hip fracture volume produced two volume categories for LOS and cost: 0-30 (low) and 31+ (high). Analysis of LOS by annual hospital hip fracture volume produced strata at: 0-59 (low), 60-146 (medium), and 147 or more (high). Analysis of cost by annual hospital volume produced strata at: 0-125 (low) and 126+ (high). LOS and cost both decreased significantly (p < 0.05) in progressively higher volume categories. Low-volume surgeons performed the majority of hip fracture cases, although they were performed at medium- or high-volume centres.

CONCLUSIONS

This study demonstrates a direct relationship between volume and value, translating to improvement in hip fracture care delivery for both surgeons and hospitals. Higher volume hospitals while lower volume surgeons perform the majority of hip fracture cases, suggesting optimisation opportunities. However, systems-based practices at the hospital level likely drive value to a greater extent than individual surgeons.

Defining the Volume-Outcome Relationship in Reverse Shoulder Arthroplasty: A Nationwide Analysis

BACKGROUND

As the utilization of reverse total shoulder arthroplasty (RSA) grows, it is increasingly important to examine the relationship between hospital volume and RSA outcomes. We hypothesized that hospitals that perform a higher volume of RSAs would have improved outcomes. We also performed stratum-specific likelihood ratio (SSLR) analysis with the aim of delineating concrete definitions of hospital volume for RSA.

METHODS

The Nationwide Readmissions Database was queried for patients who had undergone elective RSA from 2011 to 2015. Annual hospital volume and 90-day outcome data were collected, including readmission, revision, complications, hospital length of stay (LOS), supramedian cost, and discharge disposition. SSLR analysis was performed to determine hospital volume cutoffs associated with increased risks for adverse events. Cutoffs generated through SSLR analysis were confirmed via binomial logistic regression.

RESULTS

The proportion of patients receiving care at high-volume centers increased from 2011 to 2015. SSLR analysis produced hospital volume cutoffs for each outcome, with higher-volume centers showing improved outcomes. The volume cutoffs associated with the best rates of 90-day outcomes ranged from 54 to 70 RSAs/year, whereas cost and resource utilization cutoffs were higher, with the best outcomes in hospitals performing >100 RSAs/year. SSLR analysis of 90-day readmission produced 3 hospital volume categories (1 to 16, 17 to 69, and ≥70 RSAs/year), each significantly different from each other. These were similar to the strata for 90-day revision (1 to 16, 17 to 53, and ≥54 RSAs/year) and 90-day complications (1 to 9, 10 to 68, and ≥69 RSAs/year). SSLR analysis produced 6 hospital volume categories for cost of care over the median value (1 to 5, 6 to 25, 26 to 47, 48 to 71, 72 to 105, and ≥106 RSAs/year), 5 categories for an extended LOS (1 to 10, 11 to 25, 26 to 59, 60 to 105, and ≥106 RSAs/year), and 4 categories for non-home discharge (1 to 31, 32 to 71, 72 to 105, and ≥106 RSAs/year).

CONCLUSIONS

We have defined hospital surgical volumes that maximize outcomes after RSA, likely related to surgical experience, ancillary staff familiarity, and protocolized pathways. This information may be used in future policy decisions to consolidate complex procedures, such as RSA, at high-volume destinations, or to encourage lower-volume institutions to strategize an approach to function as a higher-volume center.

LEVEL OF EVIDENCE

Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Monitoring hip posture in total hip arthroplasty using an inertial measurement unit-based hip smart trial system: An in vitro validation experiment using a fixed pelvis model

Intraoperative measurement of hip posture is the basis for assessing hip range of motion (ROM) and predicting postoperative functional limits allowable for activities of daily living. Although computer navigation for total hip arthroplasty (THA) has improved the accuracy of intraoperative ROM evaluation, it has not gained widespread popularity due to its complex and time-consuming protocol. We therefore developed an inertial measurement unit-based hip smart trial system (IMUHST) for intraoperative monitoring of hip posture. An in vitro validation experiment was conducted using bone models with a three-dimensional measurement model as the reference standard. The absolute mean error, Bland - Altman analysis and intra-class correlation coefficient demonstrated that the validity and reliability of this system meets the requirement for clinical application. Given that monitoring posture is the basis for evaluating the direction(s) of potential impingement, subluxation and dislocation, the IMUHST is a promising development direction of computer assisted surgery in THA.

Optimizing the Volume-Value Relationship in Laminectomy: An Evidence-Based Analysis of Outcomes and Economies of Scale

STUDY DESIGN

Retrospective cohort study.

OBJECTIVE

The objective of the present study was to establish evidence-based volume thresholds for surgeons and hospitals predictive of enhanced value in the setting of laminectomy.

SUMMARY OF BACKGROUND DATA

Previous studies have attempted to characterize the relationship between volume and value; however, none to the authors' knowledge has employed an evidence-based approach to identify thresholds yielding enhanced value.

METHODS

In total, 67,758 patients from the New York Statewide Planning and Research Cooperative System database undergoing laminectomy in the period 2009 to 2015 were included. We used stratum-specific likelihood ratio analysis of receiver operating characteristic curves to establish volume thresholds predictive of increased length of stay (LOS) and cost for surgeons and hospitals.

RESULTS

Analysis of LOS by surgeon volume produced strata at: <17 (low), 17 to 40 (medium), 41 to 71 (high), and >71 (very high). Analysis of cost by surgeon volume produced strata at: <17 (low), 17 to 33 (medium), 34 to 86 (high), and >86 (very high). Analysis of LOS by hospital volume produced strata at: <43 (very low), 43 to 96 (low), 97 to 147 (medium), 148 to 172 (high), and >172 (very high). Analysis of cost by hospital volume produced strata at: <43 (very low), 43 to 82 (low), 83 to 115 (medium), 116 to 169 (high), and >169 (very high). LOS and cost decreased significantly (P < 0.05) in progressively higher volume categories for both surgeons and hospitals. For LOS, medium-volume surgeons handle the largest proportion of laminectomies (36%), whereas very high-volume hospitals handle the largest proportion (48%).

CONCLUSION

This study supports a direct volume-value relationship for surgeons and hospitals in the setting of laminectomy. These findings provide target-estimated thresholds for which hospitals and surgeons may receive meaningful return on investment in our increasingly value-based system. Further value-based optimization is possible in the finding that while the highest volume hospitals handle the largest proportion of laminectomies, the highest volume surgeons do not.

LEVEL OF EVIDENCE

3.

Fixed and Variable Relationship Models to Define the Volume-Value Relationship in Spinal Fusion Surgery: A Macroeconomic Analysis Using Evidence-Based Thresholds

Objective

Increased surgical volume has been associated with improved patient outcomes at the surgeon and hospital level. To date, clinically meaningful stratified volume benchmarks have yet to be defined for surgeons or hospitals in the context of spinal fusion surgery. The objective of this study was to establish evidence-based thresholds using outcomes and cost to stratify surgeons and hospitals performing spinal fusion surgery by volume.

Methods

Using 155,788 patients undergoing spinal fusion surgery, we created and applied 4 models using stratum-specific likelihood ratio (SSLR) analysis of a receiver operating characteristic (ROC) curve. This statistical approach was used to generate 4 sets of volume thresholds predictive of increased length of stay (LOS) and increased cost for surgeons and hospitals.

Results

SSLR analysis of the 2 ROC curves by annual surgical volume produced 3 or 4 distinct volume categories. Analysis of LOS by annual surgeon spinal fusion volume produced 4 strata: low, medium, high, and very high. Analysis of LOS by annual hospital spinal fusion volume produced 3 strata: low, medium, and high. No relationship between volume and cost could be clearly defined based on the generation of ROC curves for surgeons or hospitals offering spinal fusion.

Conclusion

This study used evidence-based thresholds to identify a direct, variable relationship model between volume and outcomes of spinal fusion surgery, using LOS as a surrogate, for both surgeons and hospitals. A fixed relationship model was identified between surgeon and hospital volume and cost, as no statistically meaningful relationship could be established.