Abstract
Background:
Carpometacarpal (CMC) arthroplasty can provide symptomatic relief and improvement in function in patients with CMC osteoarthritis. The study purpose was to identify demographic, 30-day outcome, and reimbursement trends in CMC arthroplasty between 2012 and 2021.
Methods:
This was a retrospective cohort study of adult patients undergoing CMC arthroplasty from January 1, 2012, to December 31, 2021, using the National Surgical Quality Improvement Program database. Patients were stratified based on year of index surgery: 2012-2015, 2016-2018, and 2019-2021. Baseline characteristics were collected and compared using the appropriate statistical test. Multivariable logistic regressions controlling for age and sex were performed to identify independent risk factors for 30-day morbidity, readmissions, and reoperations. Economic analyses assessed changes in reimbursement rates over the span of 10 years.
Results:
A total of 9046 patients were included in the analysis with mean age of 62.7 ± 9.2 and women comprising 74.9% of the total population. Between 2012 and 2021, the annual volume increased from 433 to 1043. The average body mass index (BMI) and proportion of patients with congestive heart failure (CHF) increased in 2019-2021. Increasing age, BMI, smoking, and length of stay ≥ 1 day were independent risk factors for 30-day readmissions. The Medicare reimbursement fee decreased by an average of 1.15% annually, for a total of 9.90% across 10 years.
Conclusions:
The volume of CMC arthroplasty has risen from 2012 to 2021. However, conditions such as obesity and CHF have become more prevalent. Despite the growing patient complexity, Medicare reimbursement fees have markedly decreased.
Keywords: CMC, arthritis, diagnosis, arthroplasty, arthritis, diagnosis, osteoarthritis, arthritis, diagnosis, outcomes, research and health outcomes, reimbursements, epidemiology, research & health outcomes
Introduction
Carpometacarpal (CMC) osteoarthritis of the thumb is the second most common degenerative condition of the hand, affecting 7% of men and 15% of women, and 17% to 33% of postmenopausal women.1 -3 Given the important role of the thumb in overall hand function with 3 planes of motion, the CMC joint is susceptible to injury and overuse, contributing to osteoarthritis. 3 While some patients are asymptomatic despite radiographic evidence of osteoarthritis, many patients experience pain and weakness with common daily activities, negatively impacting quality of life. 4 Treatment options include nonoperative management with activity modification, bracing, analgesics, and injections, as well as surgical treatment. 3
Carpometacarpal arthroplasty is a common procedure that can provide symptomatic relief and improvement in function in patients with CMC osteoarthritis. Werner et al 5 used a national database and found that the number of patients who underwent CMC interposition arthroplasty increased by 46.2% between 2005 and 2011 and that overall incidence increased in all regions of the United States. As the incidence of CMC arthroplasty continues to rise yearly in the setting of an aging population, it is valuable to understand the characteristics of the population that is being treated. While it has been well-documented that the patient population undergoing elective spine and joint replacement procedures have had increasing comorbidities including diabetes and obesity, there is a sparsity of literature regarding the patient population trends in CMC arthroplasty.6,7 The primary purpose of this study was therefore to identify demographic and outcome trends in CMC arthroplasty over the past decade using the National Surgical Quality Improvement Program (NSQIP) database. In addition, with the increasing frequency of CMC arthroplasty, it is important to examine how hand surgeons are reimbursed and the broader impact on their practices. We therefore also analyzed reimbursement trends for CMC arthroplasty.
Materials and Methods
Study Design and Population
This was a retrospective cohort study of prospectively collected data using the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database from years 2012 to 2021. The ACS-NSQIP data set is a validated registry that features data including patient demographics, comorbidities perioperative factors, and 30-day postoperative outcomes from over 700 participating hospitals across the United States.8 -10 This study was exempt from Institutional Review Board review as the ACS-NSQIP is a publicly available, de-identified national registry.
Adult patients diagnosed with osteoarthritis of the first CMC joint were identified in the ACS-NSQIP data set using the International Classification of Diseases (ICD) codes M18.5 and M18.9. We then filtered for adults undergoing CMC arthroplasty from January 1, 2012, to December 31, 2021, using Current Procedural Terminology (CPT) code 25447. Patients were stratified into 3 cohorts based on year of index surgery: 2012-2015, 2016-2018, and 2019-2021. Patients undergoing emergent surgery or missing any demographic, perioperative, or outcomes data were excluded from the study.
Independent Variables
Baseline characteristics including age, sex, race (white vs non-white), ethnicity (Hispanic vs Non-Hispanic), height, weight, surgeon specialty, comorbidities, and American Society of Anesthesiologists (ASA) class were collected. Procedural factors including operative time and length of stay were collected. The Modified 5-Item Frailty Index is a validated comorbidity-based risk stratification tool and was calculated for each patient based on presence of 5 comorbidities: congestive heart failure (CHF), diabetes, chronic obstructive pulmonary disease, dependent functional status, and hypertension requiring medication. 11
Outcomes and Economic Analysis
The ACS-NSQIP data set provides postoperative outcomes data for a 30-day period following surgery. The primary outcomes in this study include unplanned readmissions, reoperations, and morbidity. Morbidity was defined as the incidence of at least 1 complication reported in the ACS-NSQIP within the 30-day period. Complications reported in ACS-NSQIP and included in this study include superficial surgical site infection (SSI), deep SSI, organ space SSI, wound dehiscence, pneumonia, unplanned intubation, pulmonary embolism, failure to wean from ventilator for >48 hours, urinary tract infection, myocardial infarction, bleeding requiring transfusion, deep vein thrombosis, and sepsis. Secondary outcomes included procedural factors, such as operative time and length of stay).
Economic analysis was performed using The Centers for Medicare & Medicaid Services Physician Fee Schedule Look-Up Tool to collect physician reimbursement data from 2012 to 2021. Pricing information from all modifiers and all Medicare Administrative Contractors were included and any geographic variability of facility pricing was averaged to determine annual reimbursement rates for thumb CMC arthroplasty. Reimbursement rates were adjusted for inflation using the Bureau of Labor Statistics Consumer Price Index of Urban Research Series and expressed in 2021 constant US dollars. The mean annual percent change and total change over the span of 10 years in reimbursement for thumb CMC arthroplasty were calculated.
Statistical Analysis
Statistical analyses were performed using IBM SPSS Statistics Version 26.0 (IBM, Armonk, NY, USA). Categorical variables were reported as frequencies and proportions. Continuous variables were reported as mean ± standard deviation. Levene’s test for homogeneity of variance was used and analysis of variance (ANOVA) or Kruskal-Wallis tests were used as appropriate. Categorical variables were compared using Pearson Chi-square, Mann-Whitney U, and Fisher’s exact tests as appropriate. Multivariable logistic regressions controlling for age and sex were performed to identify independent risk factors for 30-day morbidity, readmissions, and reoperations using alternating backward stepwise elimination and forward entry of removed variables (entry: 0.05, removal: 0.10). Statistical significance was set at P < .05.
Results
Patient Demographics, Baseline Characteristics, and Perioperative Factors for CMC Arthroplasty Between 2012 and 2021
A total of 9046 patients were included in the analysis with mean age of 62.7 ± 9.2 and women comprising 74.9% of the total population (Table 1). There were 2473 patients in the 2012-2015 cohort, 3351 patients in the 2016-2018 cohort, and 3222 patients in the 2019-2021 cohort. Between 2012 and 2021, the annual volume of CMC arthroplasties as reported by the ACS-NSQIP database increased from 433 to 1043 (Figure 1). On average, patients who underwent CMC arthroplasty between 2019 and 2021 were older compared with those who underwent CMC arthroplasty between 2012 and 2015 (63.1 ± 9.1 vs 62.3 ± 9.2, P = .002). There were more men undergoing CMC arthroplasty between 2019 and 2021 compared with 2012-2015 (26.6% vs 23.7%, P = .032). There were more non-white patients undergoing CMC arthroplasty between 2019 and 2021 compared with 2012-2015 (20.7% vs 19.3%, P < .001). The average BMI of patients undergoing CMC arthroplasty between 2019 and 2021 was greater than that of patients between 2012 and 2015 (30.2 ± 7.2 vs 29.5 ± 6.7, P = .001), with a greater proportion of patients with obesity in the 2019-2021 cohort compared with the 2012-2015 cohort (44.1% vs 39.9%, P = .006) (Figure 2). The proportion of patients with diabetes was lower in the 2019-2021 cohort compared with the 2012-2015 cohort (4.7% vs 10.2%, P = .002), while the proportion of patients with CHF was higher in the 2019-2021 cohort compared with the 2012-2015 cohort (0.7% vs 0.0%, P < .001). The proportion of patients with Modified Frailty-5 Item Index (mFI-5) scores ≥ 2 was greater in the 2019-2021 cohort compared with the 2012-2015 cohort (13.2% vs 10.8%, P = .021). In addition, there were more patients with ASA Class > 2 in the 2019-2021 cohort compared with the 2012-2015 cohort (36.4% vs 32.0%, P < .001). Of those who received inpatient treatment, there were fewer patients with length of stay³ 1 day in the 2019-2021 cohort compared with the 2012-2015 cohort (2.7% vs 5.3%, P < .001). The number of patients undergoing outpatient surgery decreased from 97.9% in the 2012-2015 cohort, to 97.3% in the 2016-2018 cohort, to 96.6% in the 2019-2021 cohort. Inpatient surgical volume increased accordingly, with the number of patients rising from 2.1%, to 2.7%, to 3.4%.
Table 1.
Patient Demographics, Baseline Characteristics, and Perioperative Factors for CMC Arthroplasty Between 2012 and 2021. a
| 2012-2015 (n = 2473) | 2016-2018 (n = 3351) | 2019-2021 (n = 3222) | P-value | |
|---|---|---|---|---|
| Age (years) | 62.3 ± 9.2 | 62.7 ± 9.1 | 63.1 ± 9.1 | .002 |
| Sex | .032 | |||
| Men | 585 (23.7) | 824 (24.6) | 856 (26.6) | |
| Women | 1888 (76.3) | 2527 (75.4) | 2366 (73.4) | |
| Race | <.001 | |||
| White | 1995 (80.7) | 2745 (81.9) | 7169 (79.3) | |
| Non-white | 478 (19.3) | 606 (18.1) | 1877 (20.7) | |
| Hispanic ethnicity | <.001 | |||
| Hispanic | 18 (0.7) | 91 (2.7) | 96 (3.0) | |
| Non-Hispanic | 2455 (99.3) | 3260 (97.3) | 3126 (97.0) | |
| BMI (kg/m2) | 29.5 ± 6.7 | 29.9 ± 6.9 | 30.2 ± 7.2 | .001 |
| Specialty | .091 | |||
| Orthopedic surgery | 2101 (85.0) | 2914 (87.0) | 2778 (86.2) | |
| Plastic surgery | 372 (15.0) | 437 (13.0) | 444 (13.8) | |
| Obesity | 987 (39.9) | 1421 (42.4) | 1422 (44.1) | .006 |
| Diabetes | 252 (10.2) | 413 (12.3) | 427 (13.3) | .002 |
| Smoking status | 343 (13.9) | 431 (12.9) | 402 (12.5) | .288 |
| Functional status | .28 | |||
| Independent | 2461 (99.5) | 3336 (99.6) | 3214 (99.8) | |
| Partially dependent | 12 (0.5) | 15 (0.4) | 8 (0.2) | |
| Totally dependent | 0 (0) | 0 (0) | 0 (0) | |
| COPD | 117 (4.7) | 155 (4.6) | 174 (5.4) | .302 |
| CHF | 1 (0.0) | 8 (0.2) | 23 (0.7) | <.001 |
| HTN requiring medication | 1148 (46.4) | 1552 (46.3) | 1476 (45.8) | .879 |
| Disseminated cancer | 2 (0.1) | 2 (0.1) | 1 (0.0) | .723 |
| Steroid use | 88 (3.6) | 98 (2.9) | 127 (3.9) | .075 |
| Bleeding disorder | 47 (1.9) | 50 (1.5) | 48 (1.5) | .385 |
| mFI-5 | .021 | |||
| <2 | 2207 (89.2) | 2943 (87.8) | 2797 (86.8) | |
| ≥2 | 266 (10.8) | 408 (12.2) | 425 (13.2) | |
| ASA class | <.001 | |||
| I | 155 (6.3) | 195 (5.8) | 132 (4.1) | |
| II | 1552 (62.8) | 1937 (57.8) | 1865 (57.9) | |
| III | 742 (30.0) | 1178 (35.2) | 1194 (37.1) | |
| IV | 24 (1.0) | 41 (1.2) | 31 (1.0) | |
| Operative time (minutes) | 75.0 ± 39.0 | 75.6 ± 37.0 | 75.4 ± 36.2 | .846 |
| Length of stay ≥ 1 day | 132 (5.3) | 128 (3.8) | 86 (2.7) | <.001 |
| Outpatient/inpatient | .012 | |||
| Outpatient | 2422 (97.9) | 3262 (97.3) | 3144 (96.6) | |
| Inpatient | 51 (2.1) | 89 (2.7) | 108 (3.4) |
Note. ASA = American Society of Anesthesiologists, BMI = body mass index, CHF = congestive heart failure, CMC = carpometacarpal, COPD = chronic obstructive pulmonary disorder, HTN = hypertension, mFI-5 = Modified 5-Item Frailty Index.
Data are presented as mean ± standard deviation or n (% of year group).
Figure 1.
Yearly case volume of CMC arthroplasty from 2012 to 2021 as identified in the NSQIP database.
Note. CMC = carpometacarpal, NSQIP = National Surgical Quality Improvement Program.
Figure 2.
Yearly mean BMI of patients undergoing CMC arthroplasty from 2012 to 2021 as identified in the NSQIP database.
Note. CMC = carpometacarpal, NSQIP = National Surgical Quality Improvement Program.
30-Day Morbidity, Readmissions, and Reoperations Following CMC Arthroplasty Between 2012 and 2021
The overall rate of morbidity (any complication) was greater in the 2019-2021 cohort compared with the 2012-2015 cohort (2.0% vs 0.9%, P < .001) (Table 2). Likewise, the rate of superficial incisional infection was greater in the 2019-2021 cohort compared with the 2012-2015 cohort (1.2% vs 0.5%, P < .001). There were no other significant differences for individual complications, overall readmissions, or reoperations between the cohorts.
Table 2.
Thirty-Day Outcomes Following CMC Arthroplasty Between 2012 and 2021. a
| 2012-2015 (n = 2473) | 2016-2018 (n = 3351) | 2019-2021 (n = 3222) | P-value | |
|---|---|---|---|---|
| Readmission | 19 (0.8) | 27 (0.8) | 14 (0.4) | .135 |
| Reoperation | 7 (0.3) | 17 (0.5) | 12 (0.4) | .389 |
| Morbidity (any complication) | 22 (0.9) | 26 (0.8) | 63 (2.0) | <.001 |
| Superficial infection | 12 (0.5) | 10 (0.3) | 38 (1.2) | <.001 |
| Deep infection | 1 (0.0) | 3 (0.1) | 0 (0.0) | .224 |
| Organ space infection | 0 (0.0) | 1 (0.0) | 2 (0.1) | .44 |
| Wound dehiscence | 1 (0.0) | 2 (0.1) | 5 (0.2) | .275 |
| Pneumonia | 2 (0.1) | 0 (0.0) | 1 (0.0) | .245 |
| Reintubation | 1 (0.0) | 1 (0.0) | 1 (0.0) | .973 |
| Pulmonary embolism | 1 (0.0) | 1 (0.0) | 0 (0.0) | .555 |
| Failure to wean | 1 (0.0) | 0 (0.0) | 0 (0.0) | .265 |
| Urinary tract infection | 6 (0.2) | 7 (0.2) | 16 (0.5) | .086 |
| Myocardial infarction | 1 (0.0) | 1 (0.0) | 0 (0.0) | .555 |
| Bleeding requiring transfusion | 0 (0.0) | 0 (0.0) | 1 (0.0) | .405 |
| Deep vein thrombosis | 0 (0.0) | 1 (0.0) | 0 (0.0) | .427 |
| Sepsis | 0 (0.0) | 3 (0.1) | 2 (0.1) | .349 |
Note. CMC = carpometacarpal.
Data are presented as n (% of year group).
Multivariable Analysis: Predictors for 30-Day Outcomes Following CMC Arthroplasty
On multivariable analysis, operative years 2019-2021 (reference 2012-2015) (odds ratio [OR]: 2.11 [95% CI, 1.30-3.45], P = .003) and diabetes (OR: 2.15 [95% CI, 1.37-3.38], P < .001) were identified as independent predictors for morbidity (Table 3). Increasing age (OR: 1.04 [95% CI, 1.01-1.08], P = .008), BMI (OR: 1.05 [95% CI, 1.02-1.09], P = .003), mFI-5 score ≥ 2 (OR: 2.53 [95% CI, 1.43-4.49], P = .001), smoking (OR: 2.27 [95% CI, 1.15-4.44], P = .017), and length of stay ≥ 1 day (OR: 2.69 [95% CI, 1.20-6.04], P = .017) were identified as independent risk factors for 30-day readmissions. Increasing BMI (OR: 1.05 [95% CI, 1.01-1.09], P = .014) and length of stay ≥ 1 day (OR: 4.09 [95% CI, 1.56-10.69], P = .004) were identified as independent risk factors for 30-day reoperation.
Table 3.
Multivariable Analysis: Predictors for 30-Day Outcomes Following CMC Arthroplasty.
| Odds ratio | 95% CI | P-value | |
|---|---|---|---|
| Morbidity | |||
| Age | 1.02 | 0.99-1.04 | .173 |
| Sex (women) | 1.15 | 0.74-1.78 | .545 |
| Operative years | |||
| 2012-2015 | Ref | Ref | Ref |
| 2016-2018 | 0.84 | 0.48-1.49 | .557 |
| 2019-2021 | 2.11 | 1.30-3.45 | .003 |
| Obesity | 1.42 | 0.96-2.09 | .081 |
| Diabetes | 2.15 | 1.37-3.38 | <.001 |
| Readmissions | |||
| Age | 1.04 | 1.01-1.08 | .008 |
| Sex (women) | 0.83 | 0.48-1.46 | .527 |
| Operative years | |||
| 2012-2015 | Ref | Ref | Ref |
| 2016-2018 | 1.02 | 0.57-1.85 | .94 |
| 2019-2021 | 0.54 | 0.27-1.09 | .085 |
| BMI | 1.05 | 1.02-1.09 | .003 |
| mFI-5 ≥ 2 | 2.53 | 1.43-4.49 | .001 |
| Smoker | 2.27 | 1.16-4.44 | .017 |
| LOS ≥ 1 day | 2.69 | 1.20-6.04 | .017 |
| Reoperation | |||
| Age | 1.01 | 0.97-1.04 | .72 |
| Sex (women) | 0.65 | 0.32-1.31 | .227 |
| Operative years | |||
| 2012-2015 | Ref | Ref | Ref |
| 2016-2018 | 1.79 | 0.74-4.35 | .195 |
| 2019-2021 | 1.33 | 0.52-3.41 | .549 |
| BMI | 1.05 | 1.01-1.09 | .014 |
| LOS ≥ 1 day | 4.09 | 1.56-10.69 | .004 |
Note. BMI = body mass index, CMC = carpometacarpal, LOS = length of stay, mFI-5 = Modified 5-Item Frailty Index.
Reimbursement Trends for CMC Arthroplasty From Between 2012 and 2021
The unadjusted facility price increased from $824.73 in 2012 to $854.53 in 2021, while the adjusted facility price decreased from $948.44 in 2012 to $854.53 in 2021 (Figure 3). The Medicare reimbursement for CMC arthroplasty decreased by an average of 1.15% annually, for a total of 9.90% over the span of a decade (Table 4).
Figure 3.
Yearly adjusted and adjusted facility price for CMC arthroplasty procedures from 2012 to 2021.
Note. CMC = carpometacarpal.
Table 4.
Reimbursement Trends for CMC Arthroplasty From 2012 to 2021.
| Year | Work RVU | PE RVU | Malpractice RVU | Total RVU | Unadjusted Facility Price | Adjusted Facility Price* | Unadjusted % Change Yearly | Adjusted % Change Yearly | Mean Adjusted % Change Yearly | Adjusted % Change 2012-2021 |
|---|---|---|---|---|---|---|---|---|---|---|
| 2012 | 11.14 | 11.4 | 1.96 | 24.53 | $824.73 | $948.44 | - | - | ||
| 2013 | 11.14 | 11.4 | 1.96 | 24.47 | $832.54 | $949.10 | 0.95% | 0.07% | −1.15% | −9.90% |
| 2014 | 11.14 | 10.5 | 1.87 | 23.48 | $841.12 | $942.05 | 1.03% | −0.74% | ||
| 2015 | 11.14 | 10.6 | 2.02 | 23.71 | $847.74 | $949.47 | 0.79% | 0.79% | ||
| 2016 | 11.14 | 10.5 | 2.03 | 23.71 | $848.92 | $933.81 | 0.14% | −1.65% | ||
| 2017 | 11.14 | 10.6 | 2.02 | 23.77 | $853.07 | $921.32 | 0.49% | −1.34% | ||
| 2018 | 11.14 | 10.7 | 2 | 23.83 | $857.87 | $909.34 | 0.56% | −1.30% | ||
| 2019 | 11.14 | 10.7 | 2 | 23.83 | $858.81 | $893.16 | 0.11% | −1.78% | ||
| 2020 | 11.14 | 10.8 | 1.98 | 23.88 | $861.82 | $870.44 | 0.35% | −2.54% | ||
| 2021 | 11.14 | 11.4 | 1.98 | 24.49 | $854.53 | $854.53 | −0.85% | −1.83% |
Note. CMC = carpometacarpal, RVU = relative value units.
Discussion
This study demonstrates that the volume of CMC arthroplasty has increased dramatically from 2012 to 2021, with increased rates of minority populations undergoing the procedure. However, those undergoing CMC arthroplasty have become progressively more obese with higher rates of CHF and increased frailty and ASA class. Despite the growing complexity of the patient population, Medicare reimbursement fees for CMC arthroplasty have markedly decreased.
The increase in the volume of CMC arthroplasty found in this study is consistent with findings in other studies. Werner et al 5 used the PearlDiver Patient Records Database to evaluate trends and found that the number of patients who underwent CMC interposition arthroplasty increased by 46.2% between 2005 and 2011. They additionally found that overall incidence increased in all regions of the United States. Women were more likely to have the procedure at all time points, which is consistent with the higher reported incidence of CMC osteoarthritis in women, possibly secondary to increased joint laxity and subtle geometry differences.5,12 Interestingly, there was an increase in the ratio of men from 23.7% to 26.6% from 2012 to 2021, which is similar to Werner et al’s finding of an increase in the ratio of men from 18.1% to 23.9% from 2005 to 2011. 5
In this study, there was an increase in the percentage of minorities undergoing CMC arthroplasty. In a study evaluating the risk factors for failed nonsurgical treatment for CMC osteoarthritis, Schloemann et al found that non-white patients comprised 9% of all patients undergoing nonoperative treatment and only 5% of those undergoing surgery. 13 There is a well-recognized history of racial disparity in elective orthopedic surgeries. 14 For example, rates for elective total knee replacement are significantly lower for black men than non-Hispanic white men, and a recent analysis found that the distribution of patients’ race did not vary from 2013 to 2022.15,16 It is important to continue investigating racial disparities in orthopedic surgery, while recognizing that economic, cultural, social, and political factors all play a complex role in patient access to care.
Those undergoing CMC arthroplasty have become progressively more obese with higher rates of CHF and increased frailty and ASA class. Analyzing the NSQIP database from 2005 to 2015, Shah et al identified age over 65, ASA Class 4, and diabetes, and renal dialysis as potential risk factors for postoperative complications of CMC arthroplasty. 17 These comorbid risk factors are increasingly relevant as this study highlights a continued rise in comorbidities and 30-day complication rates. This trend is also similar to those found in other orthopedic surgery specialties. In a retrospective study using data from the Premier Healthcare Database, Bekeris et al 18 found that patients undergoing hip fracture repair from 2006 to 2016 had an increasing number of preoperative comorbidities, including obesity, with 2.6% and 5.4% of patients being obese in 2006 and 2016, respectively. Several studies have similarly shown increasing rates of comorbidities in patients undergoing elective hand procedures, spine surgery, arthroplasty, and rotator cuff repairs.7,16,19 -21 Further, in a prospective study of data collected from a tertiary referral unit at a teaching hospital in the United Kingdom, Birks et al 22 found that higher rates of preoperative comorbidities were correlated with poor function as determined by the Patient Outcomes of Surgery Hand/Arm (POS) questionnaire and the Euro-Qol 5 dimension 3-level measures. We found that diabetes was a significant predictive factor for perioperative morbidity, while BMI, mFI-5 score ≥ 2, smoking status, and length of stay ≥1 day were predictive of readmission, and BMI and length of stay ≥1 day alone were predictive of reoperation within 30 days. As CMC arthroplasty is generally an outpatient procedure, intraoperative complications leading to suboptimal outcomes likely explain why there was still 0.5% of patients with length of stay³ 1 day in the 2019-2021 cohort. It is important to note that we were unable to control for the impact of the COVID-19 pandemic on the 2019-2021 cohort. It is possible that the pandemic contributed to the rise in comorbidities seen in the cohort. However, whether COVID-19 significantly impacted the 2019-2021 cohort does not negate the fact that comorbidities have steadily increased over time.
Despite the growing complexity of the patient population and increase in volume of CMC arthroplasties performed, there has been a decrease in compensation for performing these procedures. We found that from 2012 to 2021, the Medicare reimbursement fee for CMC arthroplasty decreased by an average of 1.15% annually, and a total of 9.90% over the decade. In a study using the Medicare Physician Fee Schedule (MPFS) database, Malik et al 23 found that the average reimbursement for 20 different hand procedures decreased by 20.9% from 2002 to 2018, and that the reimbursement rate for CMC arthroplasty specifically decreased by 25.1%. This trend is seen across other surgical specialties as well. Sibia et al found that, from 2013 to 2023, MPFS payments decreased by 22.8% for surgery generally, and Kandi et al demonstrated that Medicare reimbursements for the 20 most common craniofacial surgeries decreased 0.8% per year from 2000 to 2021.24,25 The decrease in reimbursement rates follow legislative attempts to address the climbing costs of health care in the United States. 26 Given these findings, it will be important for hand surgeons performing procedures with declining reimbursement rates to minimize other costs. For example, given the increasing costs of surgical facilities, one may consider performing operations in ambulatory surgery centers (ASCs) where reimbursements are equivalent based on CPT codes, but facility fees are much lower when compared with inpatient hospital procedures. Fabricant et al found that performing orthopedic surgery in an ASC led to a 17% to 43% savings compared with when those same procedures were performed at a university-based hospital. 27 This was in large part attributable to shorter procedure lengths, lower supply utilization, and shorter operating room times. 27 Attempts to reduce expenses in the setting of decreased reimbursements may lead to a shift in practice that will directly impact patients. Lower reimbursement rates may discourage hand surgeons from operating on high-comorbidity patients to reduce admission risks and its associated costs. Surgeons may also offer patients faster and cheaper surgical techniques, such as suture suspension arthroplasty, or alternative procedures, like CMC denervation. 28
There are several limitations that should be acknowledged and are common to large database studies. First, the results are based upon a national database collection process, which may not accurately describe the procedures performed or the complications that follow. The data is also limited to contributing institutions, which consists mostly of large academic hospitals. 29 There are many private practices and ASCs that perform CMC arthroplasty but are not recorded in the NSQIP database. Further, while there are several different techniques that can be used for CMC arthroplasty, the database does not allow for distinction between these procedures. CPT code 25447 encompasses popular CMC arthroplasty techniques including interposition, suspensionplasty, suture button, and suture tape. There are other CPT codes for CMC arthroplasty (codes 25445 and 25210, for example); however, these refer to procedures that are less commonly used. Code 25445 is specific to arthroplasties with artificial prosthetic replacements, whereas 25210 codes for the trapeziectomy procedure. Future iterations of this study can investigate outcomes of these other techniques. In addition, as shown in Table 1, CMC arthroplasty is more commonly performed as an outpatient procedure. The smaller volume of inpatient procedures poses a limitation to our analysis of length of stay between each cohort. Yet length of stay remains an important factor to analyze given the increase in both inpatient surgeries and in complications that may necessitate admission. Additional intraoperative factors may also play a role on postoperative outcomes and future studies may aim to include data regarding anesthesia type and time, in addition to overall operative time. Finally, outcomes were limited to 30 days postoperatively, limiting the data analysis to short-term reoperations. It therefore should be noted that the reasons for reoperation early in the postoperative period are different from those requiring revision at later time points. Future research into this subject may use databases with postoperative outcomes past 30 days.
Conclusion
Carpometacarpal arthroplasty is a common procedure that can provide symptomatic relief and improvement in function in patients with CMC osteoarthritis. As the incidence of CMC arthroplasty continues to rise yearly in the setting of an aging population, it is valuable to understand the trends and characteristics of the population that is being treated. The volume of CMC arthroplasty procedures has risen significantly from 2012 to 2021 with greater representation of minorities. However, conditions such as obesity, CHF, and fragility have become more prevalent. Despite the growing complexity of the patient population, Medicare reimbursement fees for CMC arthroplasty have markedly decreased. This discrepancy highlights the need for a reassessment of reimbursement policies to better align with the evolving health care landscape.
Footnotes
Author’s Note: All work was performed at New York University School of Medicine, New York, NY.
Ethical Approval: Institutional review board approval was not required for this study.
Statement of Human and Animal Rights: All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2008.
Statement of Informed Consent: Informed consent is not applicable for this study.
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.
ORCID iDs: Michelle A. Richardson 
https://orcid.org/0000-0002-6029-0949
Sophia Jacobi
https://orcid.org/0009-0002-7033-5183
Samara Moll
https://orcid.org/0009-0007-9553-5399
References
- 1. Haara MM, Heliövaara M, Kröger H, et al. Osteoarthritis in the carpometacarpal joint of the thumb: Prevalence and associations with disability and mortality. J Bone Joint Surg Am. 2004;86(7):1452-1457. doi: 10.2106/00004623-200407000-00013 [DOI] [PubMed] [Google Scholar]
- 2. Armstrong AL, Hunter JB, Davis TR. The prevalence of degenerative arthritis of the base of the thumb in post-menopausal women. J Hand Surg Br. 1994;19(3):340-341. doi: 10.1016/0266-7681(94)90085-X [DOI] [PubMed] [Google Scholar]
- 3. Gillis J, Calder K, Williams J. Review of thumb carpometacarpal arthritis classification, treatment and outcomes. Can J Plast Surg. 2011;19(4):134-138. doi: 10.1177/229255031101900409 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Bakri K, Moran SL. Thumb carpometacarpal arthritis. Plast Reconstr Surg. 2015;135(2):508-520. doi: 10.1097/PRS.0000000000000916 [DOI] [PubMed] [Google Scholar]
- 5. Werner BC, Bridgforth AB, Gwathmey FW, Dacus AR. Trends in thumb carpometacarpal interposition arthroplasty in the United States, 2005-2011. Am J Orthop (Belle Mead NJ). 2015;44(8):363-368. [PubMed] [Google Scholar]
- 6. Crowninshield RD, Rosenberg AG, Sporer SM. Changing demographics of patients with total joint replacement. Clin Orthop Relat Res. 2006;443:266-272. doi: 10.1097/01.blo.0000188066.01833.4f [DOI] [PubMed] [Google Scholar]
- 7. Wilson LA, Fiasconaro M, Liu J, et al. Trends in comorbidities and complications among patients undergoing inpatient spine surgery. Spine (Phila Pa 1976). 2020;45(18):1299-1308. doi: 10.1097/BRS.0000000000003280 [DOI] [PubMed] [Google Scholar]
- 8. Bohl DD, Singh K, Grauer JN. Nationwide databases in orthopaedic surgery research. J Am Acad Orthop Surg. 2016;24(10):673-682. doi: 10.5435/JAAOS-D-15-00217 [DOI] [PubMed] [Google Scholar]
- 9. Shiloach M, Frencher SK, Jr, Steeger JE, et al. Toward Robust Information: Data Quality and Inter-Rater Reliability in the American College of Surgeons National Surgical Quality Improvement Program. J Am Coll Surg. 2010;210(1):6-16. doi: 10.1016/j.jamcollsurg.2009.09.031 [DOI] [PubMed] [Google Scholar]
- 10. Molina CS, Thakore RV, Blumer A, Obremskey WT, Sethi MK. Use of the national surgical quality improvement program in orthopaedic surgery. Clin Orthop Relat Res. 2015;473(5):1574-1581. doi: 10.1007/s11999-014-3597-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Velanovich V, Antoine H, Swartz A, Peters D, Rubinfeld I. Accumulating deficits model of frailty and postoperative mortality and morbidity: Its application to a national database. J Surg Res. 2013;183(1):104-110. doi: 10.1016/j.jss.2013.01.021 [DOI] [PubMed] [Google Scholar]
- 12. Van Heest AE, Kallemeier P. Thumb carpal metacarpal arthritis. J Am Acad Orthop Surg. 2008;16(3):140-151. doi: 10.5435/00124635-200803000-00005 [DOI] [PubMed] [Google Scholar]
- 13. Schloemann D, Hammert WC, Liu S, Bernstein DN, Calfee RP. Risk factors for failed nonsurgical treatment resulting in surgery on thumb carpometacarpal arthritis. J Hand Surg Am. 2021;46(6):471-477. doi: 10.1016/j.jhsa.2021.02.009 [DOI] [PubMed] [Google Scholar]
- 14. Schoenfeld AJ, Sturgeon DJ, Dimick JB, et al. Disparities in rates of surgical intervention among racial and ethnic minorities in medicare accountable care organizations. Ann Surg. 2019;269(3):459-464. doi: 10.1097/SLA.0000000000002695 [DOI] [PubMed] [Google Scholar]
- 15. Skinner J, Weinstein JN, Sporer SM, Wennberg JE. Racial, ethnic, and geographic disparities in rates of knee arthroplasty among medicare patients. N Engl J Med. 2003;349(14):1350-1359. doi: 10.1056/nejmsa021569 [DOI] [PubMed] [Google Scholar]
- 16. Ashkenazi I, Lawrence KW, Kaplan M, et al. Demographic and socioeconomic trends of patients undergoing total knee arthroplasty from 2013 to 2022—An analysis from an urban orthopaedic hospital. J Arthroplasty. 2024;39(9):2158-2165. doi: 10.1016/j.arth.2024.04.029 [DOI] [PubMed] [Google Scholar]
- 17. Shah KN, Defroda SF, Wang B, et al. Risk factors for 30-day complications after thumb CMC joint arthroplasty: An American college of surgeons national surgery quality improvement program study. Hand (N Y). 2019;14(3):357-363. doi: 10.1177/1558944717744341 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Bekeris J, Wilson LA, Bekere D, et al. Trends in comorbidities and complications among patients undergoing hip fracture repair. Anesth Analg. 2021;132(2). doi: 10.1213/ANE.0000000000004519 [DOI] [PubMed] [Google Scholar]
- 19. Lipman MD, Carstensen SE, Deal DN. Trends in the treatment of dupuytren disease in the United States between 2007 and 2014. Hand (N Y). 2017;12(1):13-20. doi: 10.1177/1558944716647101 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Halawi MJ, Gronbeck C, Metersky ML, et al. Time trends in patient characteristics and in-hospital adverse events for primary total knee arthroplasty in the United States: 2010-2017. Arthroplast Today. 2021;11:157-162. doi: 10.1016/j.artd.2021.08.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Yanik EL, Chamberlain AM, Keener JD. Trends in rotator cuff repair rates and comorbidity burden among commercially insured patients younger than the age of 65 years, United States 2007-2016. JSES Rev Rep Tech. 2021;1(4):309-316. doi: 10.1016/j.xrrt.2021.06.009 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Birks ME, Sharma K, Steele K, Jones G, Miller JG. Understanding the patient profile and health-related quality of life in patients presenting for hand surgery. J Hand Surg Eur Vol. 2020;45(2):140-146. doi: 10.1177/1753193419880792 [DOI] [PubMed] [Google Scholar]
- 23. Malik AT, Khan SN, Goyal KS. Declining trend in medicare physician reimbursements for hand surgery from 2002 to 2018. J Hand Surg Am. 2020;45(11):1003-1011. doi: 10.1016/j.jhsa.2020.08.010 [DOI] [PubMed] [Google Scholar]
- 24. Kandi LA, Jarvis TL, Shrout M, et al. Trends in medicare reimbursement for the top 20 surgical procedures in craniofacial trauma. J Craniofac Surg. 2023;34(1). doi: 10.1097/SCS.0000000000008840 [DOI] [PubMed] [Google Scholar]
- 25. Sibia US, Millen JC, Klune JR, Bilchik A, Foshag LJ. Analysis of 10-year trends in medicare physician fee schedule payments in surgery. Surgery. 2024;175(4):920-926. doi: 10.1016/j.surg.2023.12.012 [DOI] [PubMed] [Google Scholar]
- 26. Michaud JB, Zhuang T, Shapiro LM, Cohen SA, Kamal RN. Out-of-pocket and total costs for common hand procedures from 2008 to 2016: A nationwide claims database analysis. J Hand Surg Am. 2022;47(11):1057-1067. doi: 10.1016/j.jhsa.2022.06.018 [DOI] [PubMed] [Google Scholar]
- 27. Fabricant PD, Seeley MA, Rozell JC, et al. Cost savings from utilization of an ambulatory surgery center for orthopaedic day surgery. J Am Acad Orthop Surg. 2016;24(12):865-871. doi: 10.5435/JAAOS-D-15-00751 [DOI] [PubMed] [Google Scholar]
- 28. DelSignore JL, Zambito K, Ballatori SE. Suture suspension arthroplasty for thumb carpometacarpal arthritis reconstruction: 12- to 14-year follow-up. Hand (N Y). 2023;18(1):105-112. doi: 10.1177/15589447211003176 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Alluri RK, Leland H, Heckmann N. Surgical research using national databases. Ann Transl Med. 2016;4(20):393. doi: 10.21037/atm.2016.10.49 [DOI] [PMC free article] [PubMed] [Google Scholar]