Variation in the Cost of Hip Arthroscopy for Labral Pathological Conditions

Abstract

Background:

Despite growing interest in delivering high-value orthopaedic care, the costs associated with hip arthroscopy remain poorly understood. By employing time-driven activity-based costing (TDABC), we aimed to characterize the cost composition of hip arthroscopy for labral pathological conditions and to identify factors that drive variation in cost.

Methods:

Using TDABC, we measured the costs of 890 outpatient hip arthroscopy procedures for labral pathological conditions across 5 surgeons at 4 surgery centers from 2015 to 2022. All patients were ≥18 years old and were treated by surgeons who each performed ≥20 surgeries during the study period. Costs were normalized to protect the confidentiality of internal hospital cost data. Descriptive analyses and multivariable linear regression were performed to identify factors underlying cost variation.

Results:

The study sample consisted of 515 women (57.9%) and 375 men (42.1%), with a mean age (and standard deviation) of 37.1 ± 12.7 years. Most of the procedures were performed in patients who were White (90.6%) or not Hispanic (93.4%). The normalized total cost of hip arthroscopy per procedure ranged from 43.4 to 203.7 (mean, 100 ± 24.2). Of the 3 phases of the care cycle, the intraoperative phase was identified as the largest generator of cost (>90%). On average, supply costs accounted for 48.8% of total costs, whereas labor costs accounted for 51.2%. A 2.5-fold variation between the 10th and 90th percentiles for total cost was attributed to supplies, which was greater than the 1.8-fold variation attributed to labor. Variation in total costs was most effectively explained by the labral management method (partial R² = 0.332), operating surgeon (partial R² = 0.326), osteoplasty type (partial R² = 0.087), and surgery center (partial R² = 0.086). Male gender (p < 0.001) and younger age (p = 0.032) were also associated with significantly increased costs. Finally, data trends revealed a shift toward labral preservation techniques over debridement during the study period (with the rate of such techniques increasing from 77.8% to 93.2%; P_trend = 0.0039) and a strong correlation between later operative year and increased supply costs, labor costs, and operative time (p < 0.001 for each).

Conclusions:

By applying TDABC to outpatient hip arthroscopy, we identified wide patient-to-patient cost variation that was most effectively explained by the method of labral management, the operating surgeon, the osteoplasty type, and the surgery center. Given current procedural coding trends, declining reimbursements, and rising health-care costs, these insights may enable stakeholders to design bundled payment structures that better align reimbursements with costs.

Level of Evidence:

Economic and Decision Analysis Level IV. See Instructions for Authors for a complete description of levels of evidence.

Health-care costs in the United States are rising at unsustainable rates that cannot be explained by inflation, population growth, or improvements in the quality of care¹. Value-based health care is 1 strategy that aims to fundamentally restructure health-care delivery, measurement, and reimbursement in order to increase value, defined by Porter et al. as health outcomes relative to costs^2-5. Given the growing financial burden of musculoskeletal care in the U.S., value-based initiatives have received increasing attention in the field of orthopaedic surgery^6-10.

Increasing value necessitates the accurate measurement of health-care costs in order to complete the value equation and to identify opportunities to optimize the care pathway^11-13. Time-driven activity-based costing (TDABC) is 1 accounting methodology that measures costs by integrating resource expenditure (i.e., quantity and time) with the associated per-unit cost required to deliver care on a procedure-specific basis^14-16. By leveraging this “bottom-up” approach, TDABC accounts for heterogeneity between care cycles and has been shown to outperform traditional hospital accounting systems by delivering lower costs, improved accuracy, and actionable insights^17-20. TDABC has previously been employed by health organizations to characterize episode-of-care costs^21-25 and to improve value^{11,12,23,26-29}.

Despite the rapidly expanding indications for, and utilization of, hip arthroscopy over the past 2 decades, its costs have not yet been investigated with use of TDABC^30-32. Previous studies have assessed the gross cost and relative cost-effectiveness of hip arthroscopy; however, available analyses have been limited by their derivation of costs from insurance reimbursements, hospital charges, or national averages—all of which have been criticized for limited accuracy and a lack of granularity^33-39. Thus, further investigation is needed to elucidate the factors underlying variation in the true cost of hip arthroscopy.

Therefore, the purposes of this study were to employ TDABC to characterize the cost composition of outpatient hip arthroscopy for labral pathological conditions and to identify factors that drive variation in cost. We hypothesized that there exists a wide variation in cost that is moderately (i.e., 30% to 50%) explained by surgeon and procedure-specific features^36,40,41.

Materials and Methods

Sample and Study Design

Following institutional review board approval (Mass General Brigham IRB #2022P002843), all hip arthroscopy procedures performed within a single, large urban health-care system between June 2015 and November 2022 were identified with use of CareMeasurement (Avant-garde Health). This software enabled the collection of patient-level electronic health record (EHR) data, such as staff-entered time stamps, supplies utilized, and associated supply-purchasing costs. Procedures were included if the patient was ≥18 years old, hip arthroscopy was clinically indicated to address labral pathological conditions, and the procedure was performed by a surgeon who completed ≥20 total hip arthroscopy procedures during the study period. This arbitrary cutoff of 20 surgeries was selected to ensure both statistical robustness (i.e., by avoiding overfitting in the multivariable model) and clinical relevance (i.e., by including surgeons with enough volume to be proficient while maximizing study generalizability)⁴². This cutoff ultimately resulted in the exclusion of 2 surgeons who performed 5 and 6 procedures, respectively, over the study period. Additionally, procedures with total costs in the upper (≥95th) and lower (≤5th) percentiles were manually reviewed for anomalies in order to exclude those that demonstrated unreconcilable documenting errors or discrepancies. Notably, these inclusion and exclusion criteria resulted in the inclusion of some hip arthroscopy cases that included concomitant intra-articular procedures (e.g., microfracture), as excluding such cases would artificially deflate cost variation.

Time-Driven Activity-Based Costing

TDABC was performed in accordance with guidelines established by Kaplan, Anderson, and other experts^{14,16,27,43-45}. Briefly, applying TDABC on a patient-specific basis requires outlining process maps to encompass the relevant steps of the care pathway, determining and quantifying the resources required during each step, multiplying the resources expended by their associated per-unit cost, and summing these products to quantify the total cost for a given episode of care. Additional details regarding our application of TDABC are provided in Appendix 1 and Appendix Tables 1, 2, and 3^{21-24,27,29,40,46}.

Data Collection and Outcomes

Data regarding patient characteristics were manually extracted from the EHR and included age, body mass index (BMI), gender, race, ethnicity, American Society of Anesthesiologists (ASA) classification, previous hip surgeries, and insurance status. Granular procedure-specific features were manually obtained from operative notes and included the surgeon, surgery center, members of the provider team, and arthroscopic interventions performed. Of note, “labral augmentation” refers to labral repair with augmentation via a capsular autograft^47,48. Procedure-specific time stamps and supply costs were extracted with use of CareMeasurement and were subsequently verified during chart review.

Statistical Analysis

All costs were calculated in U.S. dollars and, per institutional policy, subsequently multiplied by an undisclosed constant to normalize the study mean for the total cost to 100 in order to protect the confidentiality of internal hospital cost data; this normalization preserved relative values and had no impact on the subsequent statistical analysis. Descriptive statistics are presented as means and standard deviations (SDs) for continuous variables and as frequencies and percentages for categorical variables. Given the large sample size, the Kolmogorov-Smirnov test and quantile-quantile plots were utilized to assess normality⁴⁹. Such testing revealed that the cost data approximated a normal distribution; thus, parametric tests were employed for untransformed costs. Associations between costs and continuous variables were explored with use of the Pearson correlation coefficient (r), whereas costs were compared between categorical variables with use of the unpaired t test or 1-way analysis of variance, as appropriate. Multivariable linear regression was performed to identify factors independently associated with total costs, controlling for patient characteristics, procedure-specific factors, surgeon, and surgery center. Model variables were selected on the basis of previous literature, clinical relevance, unadjusted analyses, and information criteria (i.e., the Akaike information criterion and Bayesian information criterion)⁵⁰. Analyses were performed with use of R (R Foundation for Statistical Computing; version 4.2.1). Significance was set at p < 0.05.

Results

Participants

Of the 1,036 procedures screened for the study, 890 met the inclusion criteria (Fig. 1). Procedures were performed by 5 surgeons operating at 4 outpatient surgery centers within a single institution. The study sample consisted of 515 women (57.9%) and 375 men (42.1%), with a mean age (and SD) of 37.1 ± 12.7 years and a mean BMI of 26.6 ± 4.7 kg/m². Most of the procedures were performed in patients who were White (90.6%) or not Hispanic (93.4%). The most common method of labral management was labral repair (59.7%), and the most commonly performed type of osteoplasty was femoral osteoplasty with acetabular rim trimming (45.7%; Table I).

Fig. 1.

Flowchart detailing the selection process for the study sample.

TABLE I.

Characteristics of the Study Population (N = 890)^*

Variable	Mean ± SD or No. (%)
Year of surgery
2015	9 (1.0%)
2016	61 (6.9%)
2017	86 (9.7%)
2018	142 (16.0%)
2019	93 (10.4%)
2020	142 (16.0%)
2021	180 (20.2%)
2022	177 (19.9%)
Age (yr)	37.1 ± 12.7
BMI (kg/m2)	26.6 ± 4.7
Gender
Female	515 (57.9%)
Male	375 (42.1%)
Race
Asian	23 (2.6%)
Black or African American	22 (2.5%)
White	806 (90.6%)
Other	21 (2.4%)
Unavailable	18 (2.0%)
Ethnicity
Hispanic or Latino	34 (3.8%)
Not Hispanic or Latino	831 (93.4%)
Unavailable	25 (2.8%)
ASA class
1	380 (42.7%)
2	476 (53.5%)
3	34 (3.8%)
Previous ipsilateral surgery	30 (3.4%)
Previous contralateral surgery	85 (9.6%)
No. of suture anchors	3.1 ± 1.1
Osteoplasty type
Acetabuloplasty	162 (18.2%)
Femoroplasty	224 (25.2%)
Combined	407 (45.7%)
None	97 (10.9%)
Labral procedure
Debridement	76 (8.5%)
Repair	531 (59.7%)
Augmentation†	266 (29.9%)
Reconstruction	17 (1.9%)
Capsular management
Interportal capsulotomy with repair	259 (29.1%)
Interportal capsulotomy without repair	120 (13.5%)
T-capsulotomy with repair	206 (23.1%)
T-capsulotomy without repair	8 (0.9%)
Puncture capsulotomy	297 (33.4%)
Surgeon
Surgeon 1	297 (33.4%)
Surgeon 2	275 (30.9%)
Surgeon 3	231 (26.0%)
Surgeon 4	52 (5.8%)
Surgeon 5	35 (3.9%)
Surgery center
Surgery center A	366 (41.1%)
Surgery center B	254 (28.5%)
Surgery center C	177 (19.9%)
Surgery center D	93 (10.4%)
Insurance
Government	93 (10.4%)
Private	763 (85.7%)
Workers’ Compensation or MVA claims	34 (3.8%)

^*MVA = motor vehicle accident.

^†Labral augmentation refers to labral repair with augmentation via capsular autograft^47,48.

Cost Composition and Descriptive Demographics

The normalized total cost of hip arthroscopy per procedure ranged from 43.4 to 203.7 (mean, 100 ± 24.2; Fig. 2). On average, supply costs accounted for 48.8% of total costs, and labor costs accounted for the remaining 51.2% (fixed, 8.5%; variable, 42.7%; Fig. 3). The majority (91.5%) of total costs were incurred during the intraoperative phase, with the remaining costs incurred during the preoperative (5.5%) and postoperative phases (3.0%; Table II). Relevant time metrics by phase are summarized in Table III. Between procedures in the 10th and 90th percentiles for total costs, there was a 1.8-fold variation in total costs, a 2.5-fold variation in supply costs, and a 1.8-fold variation in labor costs. Further analysis of procedures in the 10th and 90th percentiles for supply costs identified a 5.0-fold variation in the costs of implants (i.e., suture anchors and allografts), a 1.3-fold variation in the costs of individual anchors from different manufacturers, and a 3.1-fold variation in the costs of other supplies (e.g., disposables). Total cost was strongly correlated with operative time (r = 0.81; 95% confidence interval [CI], 0.78 to 0.83; p < 0.001), labor costs (r = 0.80; 95% CI, 0.78 to 0.83; p < 0.001), and supply costs (r = 0.89; 95% CI, 0.88 to 0.90; p < 0.001). Normality testing revealed that cost data followed a normal distribution (D = 0.0253; p = 0.62; see Appendix Fig. 1).

Fig. 2.

Scatterplot depicting variation in the normalized cost of outpatient hip arthroscopy for labral pathological conditions. Each point represents an individual procedure, with the procedure number denoted by its position on the x axis.

Fig. 3.

Cost composition of outpatient hip arthroscopy stratified by labor and supply costs (Fig. 3-A) and phases of the care cycle (Fig. 3-B).

TABLE II.

Normalized Cost Estimates for the Hip Arthroscopy Care Cycle

Variable	Mean ± SD
Total cost	100.0 ± 24.2
Total supply cost	48.8 ± 16.1
Implant and/or allograft costs	15.8 ± 9.2
Other (e.g., disposables) costs	33.0 ± 12.9
Total labor cost	51.2 ± 12.3
Fixed labor cost	8.5 ± 0.2
Variable labor cost	42.7 ± 12.2
Preoperative cost	5.5 ± 0.1
Intraoperative cost	91.5 ± 24.2
Postoperative cost	3.0 ± 0.2

TABLE III.

Derived Time Estimates by Phase of the Hip Arthroscopy Care Cycle^*

Metric	Duration (min)
Preoperative phase (“check-in” to “wheeled into OR”)	111.1 ± 52.3
Delayed start (“scheduled start” to “wheeled into OR”)	18.0 ± 36.0
Intraoperative phase (“wheeled into OR” to “wheeled out of OR”)	171.7 ± 54.7
Delayed exit (“wound closure” to “anesthesia stop”)	26.9 ± 9.6
Postoperative phase (“wheeled out of OR” to “discharge”)	157.8 ± 95.7

^*OR = operating room. Values are given as the mean ± SD.

Unadjusted Cost Analyses

A positive correlation (r = 0.41; p < 0.001) between total cost and operative year was demonstrated throughout the study period. Patient characteristics that were significantly associated with higher costs were younger age (r = −0.24; p < 0.001), Black race (e.g., mean normalized costs of 111.0 [Black patients] versus 99.2 [White patients]; p = 0.023), and male gender (106.1 [male] versus 95.6 [female]; p < 0.001). However, total cost was not found to be significantly associated with BMI, ethnicity, ASA class, previous ipsilateral or contralateral hip surgery, or insurance coverage (p > 0.05 for all). Regarding operative features, the more labor-intensive labral management methods (i.e., repair, augmentation, or reconstruction), osteoplasty types (e.g., combined femoroacetabular decompression), and capsular management techniques (e.g., interportal capsulotomy with repair) were associated with significantly higher total costs (p < 0.001; Table IV).

TABLE IV.

Unadjusted Analyses Exploring Associations Between Study Characteristics and Normalized Total Costs^*

Variable	Pearson Correlation Coefficient (95% CI)	P Value
Year of surgery	0.41 (0.35, 0.46)	<0.001
Age	−0.24 (−0.30, −0.17)	<0.001
BMI	0.03 (−0.03, 0.09)	0.37

Variable	Mean Normalized Cost (95% CI)	P Value
Gender		<0.001
Female	95.6 (93.6, 97.6)
Male	106.1 (103.6, 108.6)
Race		0.023
Asian	102.6 (95.1, 110.1)
Black or African American	111.0 (100.0, 122.0)
White	99.2 (97.6, 100.8)
Other	105.6 (92.0, 119.2)
Unavailable	112.1 (94.3, 129.9)
Ethnicity		0.15
Hispanic or Latino	104.3 (95.0, 113.6)
Not Hispanic or Latino	99.6 (98.0, 101.2)
Unavailable	107.7 (96.1, 119.3)
ASA class		0.38
1	100.6 (98.4, 102.8)
2	99.2 (96.9, 101.5)
3	104.5 (93.3, 115.7)
Previous ipsilateral surgery		0.82
Yes	99.0 (85.7, 112.3)
No	100.0 (98.4, 101.6)
Previous contralateral surgery		0.12
Yes	103.9 (98.2, 109.6)
No	99.6 (97.9, 101.3)
Osteoplasty type		<0.001
Acetabuloplasty	89.4 (86.5, 92.3)
Femoroplasty	95.1 (92.7, 97.5)
Combined	114.1 (112.1, 116.1)
None	70.1 (66.5, 73.7)
Labral procedure		<0.001
Debridement	64.2 (60.0, 68.4)
Repair	104.6 (102.7, 106.5)
Augmentation†	97.8 (95.9, 99.7)
Reconstruction	149.8 (134.8, 164.8)
Capsular management		<0.001
Interportal capsulotomy with repair	117.5 (114.8, 120.2)
Interportal capsulotomy without repair	70.0 (65.8, 74.2)
T-capsulotomy with repair	100.4 (96.9, 103.9)
T-capsulotomy without repair	118.2 (93.0, 143.4)
Puncture capsulotomy	96.1 (94.0, 98.2)
Insurance		0.064
Government	94.5 (88.8, 100.2)
Private	100.6 (98.9, 102.3)
Workers’ Compensation/MVA claims	102.2 (91.6, 112.8)

^*Boldface denotes significance. MVA = motor vehicle accident.

^†Labral augmentation refers to labral repair with augmentation via capsular autograft47,48.

Adjusted Cost Analyses

Consistent with the unadjusted analyses, multivariable linear regression revealed that gender, age, the type of osteoplasty, and the method of labral management explained significant variation in total costs, whereas BMI and ASA class were not significant contributors to cost variation. Interestingly, no significant association was found between costs and operative year from 2015 to 2019 (p > 0.1), whereas procedures occurring between 2020 and 2022 were associated with significantly higher costs (p < 0.05 for all). The linear regression model that incorporated these factors as well as operating surgeon and surgery center explained 75.0% of the observed variation in total costs. Notably, the method of labral management independently explained the most variation in total costs (partial R² = 0.332), followed by the operating surgeon (partial R² = 0.326), osteoplasty type (partial R² = 0.087), and surgery center (partial R² = 0.086; Table V).

TABLE V.

Multivariable Linear Regression of Study Characteristics Underlying Variation in Normalized Total Costs^*

Variable	Mean Difference	95% CI		Partial R2†	P Value
		Lower	Upper
Patient characteristics
Age, per 1-year increase	−0.08	−0.16	−0.01	0.005	0.032
BMI, per 1-unit increase	0.01	−0.18	0.19	<0.001	0.945
Male gender	4.98	3.17	6.80	0.032	<0.001
ASA class‡				<0.001
2	0.04	−1.81	1.89		0.966
3	1.38	−3.33	6.09		0.566
Procedure-specific factors
Year of surgery§				0.036
2016	7.00	−2.03	16.03		0.129
2017	7.38	−1.54	16.31		0.105
2018	7.00	−1.78	15.78		0.118
2019	7.45	−1.46	16.36		0.101
2020	13.83	5.02	22.63		0.002
2021	12.15	3.36	20.94		0.007
2022	11.18	2.38	19.99		0.013
Osteoplasty type#				0.087
Acetabuloplasty	5.19	1.38	9.00		0.008
Femoroplasty	8.22	4.85	11.60		<0.001
Combined	14.60	10.86	18.34		<0.001
Labral procedure**				0.332
Repair	23.68	20.10	27.27		<0.001
Augmentation††	23.26	17.83	28.69		<0.001
Reconstruction	71.34	64.44	78.23		<0.001

^*Boldface denotes significance. This model also controlled for surgeon (partial R² = 0.326) and surgery center (partial R² = 0.086)

^†Multiple R² = 0.750.

^‡Reference: ASA class 1.

^§Reference: 2015.

^#Reference: no osteoplasty.

^**Reference: labral debridement.

^††Labral augmentation refers to labral repair with augmentation via capsular autograft^47,48.

Exploratory Cost Analyses

To explore the potential mechanisms through which gender, age, and operative year drove costs, several hypothesis-generating analyses were performed. Male patients demonstrated significantly higher supply costs (mean normalized costs of 50.3 versus 47.6; p = 0.013) and labor costs (mean normalized costs of 55.8 versus 47.9; p < 0.001) and significantly longer operative times than female patients (mean operative times of 192.2 versus 156.8 minutes; p < 0.001). They also underwent combined femoroacetabular osteoplasty at a higher rate (62.1% versus 33.8%; p < 0.001; see Appendix Table 4). Younger patients underwent labral debridement at lower rates and underwent osteoplasty at higher rates than older patients. Consistent with our findings that each of these factors was associated with increased operative time, a negative correlation was identified between age and operative time (r = −0.29; 95% CI, −0.35 to −0.23; see also Appendix Table 5). Additionally, the utilization of labral preservation techniques increased relative to that of debridement during the study period, from a rate of 77.8% to 93.2% (P_trend = 0.0039). Finally, a later operative year was positively correlated with increased labor costs (r = 0.35; 95% CI, 0.29 to 0.40; p < 0.001), supply costs (r = 0.35; 95% CI, 0.30 to 0.41; p < 0.001), and operative time (r = 0.37; 95% CI, 0.31 to 0.43; p < 0.001; Fig. 4).

Fig. 4.

Trends in normalized labor and supply costs and operative time during the study period. Labor cost equation (dashed blue line): Y = 2.4x + 42.8; p = 0.0010. Supply cost equation (dotted black line): Y = 2.8x + 38.9; p = 0.0035. Operative time equation (solid red line): Y = 11.2x + 131.3; p < 0.001.

Discussion

As health-care systems increasingly prioritize containing costs and implementing bundled reimbursement structures, insights into the drivers of health-care expenditure are of growing interest to providers, hospitals, policymakers, and other stakeholders^1,51. On the basis of its documented accuracy and granularity^{10,15,17,40,52}, we utilized TDABC in the present study to explore the composition of and variation in the cost of outpatient hip arthroscopy. We identified the intraoperative phase of the care cycle as the largest generator of cost, accounting for >90% of total costs. After adjusting for potential confounders, the preoperative demographic features that were associated with increased costs included male gender, younger age, and later operative year. Finally, cost variation was most effectively explained by the method of labral management, operating surgeon, type of osteoplasty, and surgery center.

Sex-specific differences in hip morphology have previously been described in the literature, with male sex being associated with a higher prevalence of cam-type impingement and more severe chondral and labral wear^53-58. The results of the present study align with these findings, as the proportion of male patients who underwent femoroplasty with or without acetabuloplasty (84.2%) was greater than the proportion of female patients who did the same (61.2%), which may partially account for the differences in operative times and labor costs between men and women. Moreover, in addition to undergoing femoral osteoplasty at a higher rate, we speculate that the male patients also had larger cam deformities, which further increased the average operative time for this group. Additionally, consistent with previous literature^36,59, we identified a negative correlation between age and costs, which could be explained by our findings that the mean patient age for more complex labral management and osteoplasty procedures was younger than that for less labor-intensive procedures. Regarding the method of labral management, it is unsurprising that repair, augmentation, and reconstruction were associated with significantly higher costs, considering the required increase in operative time and the additive costs of implants and/or grafts. However, amid mounting pressure to reduce health-care costs, it is imperative to emphasize that cost containment is not synonymous with value improvement^3,12. This insight is particularly relevant to hip arthroscopy in view of accumulating evidence showing that, compared with debridement, labral preservation techniques provide superior long-term survivorship and functional outcomes^60-63.

Consistent with recent database studies demonstrating a shift toward labral preservation over debridement^30,64, we observed an increased frequency of labral preservation techniques throughout the period of the present study. This trend likely contributed to the strong positive correlations of operative year with labor costs, supply costs, and operative time. Despite these refinements in the surgical technique, procedural coding (i.e., Current Procedural Terminology [CPT; American Medical Association] codes) for hip preservation remains outdated and lacks specificity for common procedures such as labral augmentation and reconstruction. In the present study, labral repair, when compared with labral debridement, was predictably found to be associated with significantly higher total costs. However, hip arthroscopy with femoroplasty, acetabuloplasty, and labral debridement (CPT 29914 and 29915) equates to the same relative value units as that with femoroplasty, acetabuloplasty, and labral repair (CPT 29914 and 29916)^65,66. This coding schema financially disincentivizes surgeons from employing more labor-intensive methods of labral preservation, effectively disregarding the growing body of outcomes-based research supporting the use of such techniques⁶⁰. This misalignment of incentives between providers, payers, and patients highlights the need to reform CPT coding to both reflect the work being performed and compensate providers appropriately for higher-quality, evidence-based interventions^65,67,68.

The present study also identified a steady rise in labor and supply costs from 2015 to 2022. This finding is concerning given that the average inflation-adjusted Medicare reimbursement for hip arthroscopy declined by 21.1% from 2011 to 2022⁶⁸. Although the demographic for hip arthroscopy generally consists of patients too young to receive Medicare, declining Medicare reimbursement is relevant because commercial insurance and Medicaid reimbursements are often derived from Medicare rates⁶⁸. This pattern of costs outpacing reimbursement has contributed to disparities in access across all subspecialties of orthopaedic surgery⁶⁹. Relatedly, the reimbursement gap between public and private insurance has led Medicaid beneficiaries to experience longer wait times for scheduled appointments, to travel greater distances for musculoskeletal care, and to even be refused care altogether^69,70. These converging trends of rising costs and declining reimbursements may ultimately result in de facto rationing of joint preservation services, further driving the consolidation of the orthopaedic workforce in order to accommodate the ongoing devaluation of surgical care^68,70.

Finally, variation in costs was explained by both the operating surgeon and surgery center. Such variation between surgeons may have arisen from differences in annual case volume, surgical technique, implant allocation practices, and/or patient selection criteria, as the learning curve for hip arthroscopy has been shown to be particularly demanding⁷¹. Potential strategies to leverage this insight include redirecting patients to high-volume, fellowship-trained surgeons and equipping physicians with actionable, individualized performance data^72,73. Regarding the variation in supply costs due to the use of suture anchors, prior literature has suggested that cost savings may be achieved either by establishing joint administrator-physician committees to negotiate lower prices from vendors or by aligning allocation practices with clinical outcomes^40,74,75. Furthermore, we identified significant cost variation between surgery centers in the present study, possibly owing to differences in facility culture, caseload mix, staffing incentive structures, personnel turnover, supply-chain management, and/or anesthesia protocols^76-78. Although investigating the etiology of these differences was beyond the scope of the present study, their existence suggests that exciting opportunities remain to optimize the hip arthroscopy care pathway and to enhance value.

Limitations

The conclusions of this study should be interpreted in the context of certain limitations. First, given our focus on elucidating the drivers of cost variation, this study did not integrate costs with patient outcomes, which is a crucial step in improving value and an important consideration for future investigations^3-5,11,12,27. Second, to prioritize the most universally collected preoperative and intraoperative characteristics, we did not account for some radiographic parameters, intraoperative findings, and concomitant intra-articular procedures (e.g., for os acetabuli, for chondral defects, and microfracture) that may have influenced operative time and supply costs. Third, on the basis of previous literature, the durations of routine components of the hip arthroscopy care pathway were assumed to be constant across procedures, which may have underestimated cost variation (see Appendix 1 and Appendix Tables 1, 2, and 3)^18,40,45. However, all durations that were related to more variable processes (e.g., operative time) were collected directly from EHR time stamps, which stand as the most accurate data source available for these measures^16,45,79. Moreover, costs that were derived from estimated durations constituted only 8.5% of total costs, with the remaining 91.5% generated with use of EHR-derived, procedure-specific supply costs and time stamps. This approach was informed by the original description of the TDABC methodology by Kaplan et al.^12,14. Fourth, although the present study analyzed procedures from multiple surgeons across 4 surgery centers, the limited racial, ethnic, and geographic diversity of the study sample may reduce the external validity of our findings^80-83. Fifth, patient selection and surgical technique may have differed between the included surgeons. Although analyzing several surgeons increased the external validity of the study, this diversity inherently introduced heterogeneity that may have affected the internal validity, and rigorously investigating the etiology of such heterogeneity was beyond the scope of this study. Lastly, per institutional policy, costs were presented as normalized values, which precludes future studies from utilizing these estimates for cost-effectiveness analyses. Importantly, normalization preserved relative values and had no impact on our investigation of cost drivers or variability.

Conclusions

By applying TDABC to outpatient hip arthroscopy, we identified wide patient-to-patient cost variation that was most effectively explained by the method of labral management, operating surgeon, osteoplasty type, and surgery center. Given the current trends in procedural coding, the decline in reimbursements, and the rise in health-care costs, these insights may enable stakeholders to design bundled payment structures that better align reimbursements with costs.

Appendix

Supporting material provided by the authors is posted with the online version of this article as a data supplement at jbjs.org (http://links.lww.com/JBJS/I33).