Abstract
Purpose
Although national efforts to minimize gender biases exist, gender differences in surgery persist. This study aims to investigate gender differences in preoperative resource utilization of patients undergoing wrist arthroscopy for non-traumatic wrist pain.
Methods
Patients who underwent a wrist arthroscopy for non-traumatic pain between 2009–2015 were selected from the Truven MarketScan databases. Demographic and preoperative resource utilization data stratified by gender were recorded. Multivariable regression models were performed to examine the relationship between gender and preoperative resource utilization and to investigate the cost of these services.
Results
A total of 8,972 patients, 2,805 men (42%) and 4,987 women (58%), met our inclusion criteria. Women were less likely to utilize imaging modalities preoperatively (OR: 0.08, CI: 0.07–1.00, p-value: 0.02). However, women utilized more occupational therapy (OR: 1.2, CI: 1.1–1.3, p-value: 0.002), non-narcotic analgesia (OR: 1.2, CI: 1.1–1.3, p-value: 0.001), and narcotic analgesia (OR: 1.6, CI: 1.5–1.8, p-value: <0.001). Preoperative costs during the 12 months prior to surgery were similar between genders ($1,308 vs. $1,367, respectively, p-value: 0.07). However, women accrued more costs from occupational therapy ($130 vs. $93, p-value: 0.003), non-narcotic medications ($65 vs. $46, p-value: <0.001), and narcotic medications ($568 vs. $197, p-value: <0.001).
Conclusion
Significant gender differences exist in the preoperative care for patients undergoing wrist arthroscopy. Men utilize more imaging implying more intense preoperative investigation for wrist pain, whereas women use more conservative measures such as occupational therapy, narcotic, and non-narcotic analgesia, highlighting possible implicit provider biases in preoperative management and potential gender differences in disease presentation.
Keywords: gender disparities, resource utilization, wrist arthroscopy, wrist pain
Introduction
In 2016, approximately 25,250 wrist arthroscopies were performed at ambulatory surgical centers in the United States, of which 42% were performed on women.1 Wrist arthroscopies have a variety of diagnostic and therapeutic applications including identifying or confirming carpal pathology, characterizing and repairing cartilaginous or ligamentous injuries, aiding fracture reduction, and evaluating etiologies of wrist pain.2–4 With advances in techniques, indications for wrist arthroscopy continue to grow. Before undergoing wrist arthroscopy, patients usually have an extensive preoperative work-up. This preoperative care may include noninvasive imaging, such as x-rays and magnetic resonance imaging (MRI), repeated visits with healthcare professionals, occupational therapy (OT), and corticosteroid injections. However, the preoperative healthcare utilization of patients with non-traumatic wrist pain varies, and how gender influences this preoperative work-up is unclear.
Growing evidence suggests that gender inequalities persist for both medical5,6 and surgical interventions, including cardiac revascularization7, hip and knee arthroplasty8, and renal transplantation.9,10 In a study by Hawker et al., women had a higher prevalence of hip and knee arthritis with more functional disability but were less likely to undergo total joint arthroplasty compared to men.8 The authors propose that provider biases account for disparities in surgical intervention. Furthermore, preoperative healthcare resource utilization analysis based on gender for patients undergoing total joint arthroplasty revealed that women were more likely to utilize conservative treatments including corticosteroid injections, imaging, and occupational therapy, underscoring previous findings of biases in healthcare delivery.11 Disparities in healthcare have gained substantial publicity in the media, and national initiatives that aim to minimize them have been developed. The Department of Health and Human Services documented gaps in healthcare quality that exist based on ethnicity, race, and gender, and has devised an action plan to minimize these disparities in healthcare.12 Additionally, the Institute of Medicine’s report, Crossing the Quality Chasm, incorporates the delivery of equitable care regardless of individual patient characteristics, including gender, as one of its main aims for improvement.13
As wrist arthroscopy becomes a mainstay in diagnostic and therapeutic treatment of wrist pain, understanding differences in healthcare delivery based on gender will be critical in offering more equitable and uniform care. Surgical disparities continue to be a national problem, and the gender differences in preoperative resource utilization of patients undergoing wrist arthroscopy remain unclear. Based upon the aforementioned findings in the field of joint arthroplasty, we hypothesize that we would find similar results in wrist arthroscopy patients, with women undergoing more preoperative care before surgery. Given national efforts to minimize surgical disparities, we sought to evaluate population-level gender differences in preoperative healthcare administration and resource utilization for patients undergoing wrist arthroscopy.
Methods
Data Source
The Truven MarketScan Research Databases, including the Commercial Claims and Encounters Database and the Medicare Supplemental and Coordination of Benefits Database, from 2009 to 2015 was used to conduct this study. The Truven MarketScan Databases consists of insurance claims from employee-sponsored healthcare and Medicare Advantage or supplemental insurance. These databases, containing over 28 billion patient records, capture inpatient and outpatient encounters, patient-level costs, and details on prescription drug utilization.14 Encrypted patient identification numbers allow for longitudinal tracking of patient encounters, resource utilization, pharmaceutical drug information, and other health plan data. Because of the de-identified nature of the data, the study received an exempt status from the institutional review board.
Study Sample
The study cohort was comprised of all patients, ages 18 and older, who underwent wrist arthroscopy and had a diagnosis of wrist pain during the study period. Patients were identified using Current Procedural Terminology (CPT) codes and International Classification of Disease, Ninth Revision, Clinical Modification diagnosis and procedure codes (ICD-9CM) (Table 1). To allow time to examine preoperative utilization data, all patients enrolled in the database less than 12 months prior to undergoing wrist arthroscopy were excluded from the study. We also excluded patients who underwent wrist arthroscopy for infectious purposes, had a history of acute hand, wrist, finger, or upper extremity trauma, inflammatory arthritis, Kienbock disease, or chronic pain.
Table 1.
Diagnosis and Procedure Codes
| Coding System | Codes |
|---|---|
| ICD-9* Diagnosis Codes for Wrist Pain | 715.04, 715.12–715.14, 715.22–715.24, 715.32–715.34, 715.92–715.94, 716.42–716.44, 716.62–716.64, 716.82–716.84, 716.92–716.94, 718.02–718.04, 718.32–718.34, 718.42–718.44, 718.52–718.54, 718.82–718.84, 718.92–718.94, 719.02–719.04, 719.42–719.44, 719.52–719.54, 719.62–719.64, 719.82–719.84, 719.92–719.94, 842.X, 905.2, 905.6, 905.7, 905.8, 906.3, 906.4 |
| CPT† Codes for Wrist Arthroscopy | 29844, 29845, 29846, 29847 |
|
| |
| CPT† Codes for Imaging | X-ray: 73090, 73100, 73110, 73120, 73130, 73140 CT: 73200, 73201, 73202, 73206 MRI: 73218, 73219, 73220, 73221, 73222, 73223, 73225 |
|
| |
| CPT† Codes for Occupational Therapy | 07035, 29125, 96372, 97001, 97003, 97004, 97010, 97012, 97014, 97018, 97022, 97032, 97033, 97110, 97112, 97124, 97140, 97530, 97810, 97813, A4570, L3807, L3908 |
International Classification of Disease, Ninth Revision, Clinical Modification
Current Procedural Terminal
Dependent Variables
Patient-specific preoperative resource utilization was obtained for the study sample for the 12 months prior to undergoing wrist arthroscopy. Data collected included the number of clinic visits, number of emergency department visits, frequency of occupational therapy use, amount of corticosteroid use, and level of imaging use (x-rays, computed tomography, magnetic resonance imaging). We also collected data on pharmacologic analgesia usage and separated it into narcotic and non-narcotic categories. The cost associated with the preoperative care was also calculated.
Explanatory Variables
Variables of interest included patient-specific characteristics. Sociodemographic data were collected and consisted of age, gender, household income, insurance type, and the patient’s geographic region. The Elixhauser Comorbidity Index was calculated for each patient using ICD-9CM codes to categorize comorbidities.15 Comorbidity scores were calculated as a proxy of health condition.16 Additionally, presence of obesity and smoking status were recorded for each patient.
Statistical Analysis
We examined the association between gender and preoperative resource utilization prior to undergoing wrist arthroscopy. Patient characteristics, resource utilization, and cost between men and women were examined using Chi-square tests for categorical values and Mann-Whitney U test for continuous variables. We performed multivariable linear regression model to examine how gender influenced the receipt of each type of healthcare resource, including clinic visits, occupational therapy use, corticosteroid injection use, imaging use, and the use of non-narcotic and narcotic analgesia. We then performed multivariable linear regression with log transformation to compare the cost of healthcare services prior to wrist arthroscopy between men and women, controlling for demographic and clinical characteristics of each patient. In each model, we used patient characteristics, including age, comorbidity score, median household income, type of insurance, smoking status, obesity, and geographic region as the covariates. These covariates were chosen due to their propensity to influence the association between gender and resource utilization and cost.
Results
A total of 8,972 patients underwent wrist arthroscopy for non-traumatic wrist pain between 2009 and 2015 and had at least 12 months of continuous preoperative enrollment. Our cohort included 3,805 men (42%) and 4,987 women (58%). Table 2 outlines their demographic, social, and clinical characteristics by gender. Women had significantly higher preoperative risk, as measured by the Elixhauser comorbidity score (p<0.001). However, in our cohort, more men were obese compared to women (p<0.01). There were no differences in regional variation, household income, insurance type, or smoking status between men and women.
Table 2.
Patient Demographic and Clinical Data by Gender
| Patient characteristics | Men (%) | Women (%) | P values |
|---|---|---|---|
| Total | 3,805 (42%) | 4,987 (58%) | |
| Age | <0.001 | ||
| 18–34 | 1,082 (28%) | 1,296 (26%) | |
| 35–44 | 838 (22%) | 1,164 (23%) | |
| 45–54 | 940 (25%) | 1,424 (29%) | |
| 55–64 | 765 (20%) | 971 (20%) | |
| 65 and older | 180 (5%) | 132 (3%) | |
| Median household income in the area of residence* | 0.116 | ||
| <40,000 | 70 (2%) | 75 (2%) | |
| ≥40,000 and <50,000 | 936 (25%) | 1,324 (27%) | |
| ≥50,000 and <60,000 | 1,473 (39%) | 1,837 (37%) | |
| ≥60,000 and <70,000 | 553 (15%) | 702 (14%) | |
| ≥70,000 | 216 (6%) | 268 (5%) | |
| Missing | 557 (15%) | 781 (16%) | |
| Comorbidity score | <0.001 | ||
| 0 | 2,507 (66%) | 2,740 (55%) | |
| 1–3 | 208 (6%) | 454 (9%) | |
| 4–8 | 664 (18%) | 1,091 (22%) | |
| >8 | 426 (11%) | 702 (14%) | |
| Region | 0.217 | ||
| Northeast | 846 (22%) | 1,120 (23%) | |
| North central | 837 (22%) | 1,066 (21%) | |
| South | 1,249 (33%) | 1,678 (34%) | |
| West | 802 (21%) | 999 (20%) | |
| Missing | 71 (2%) | 124 (3%) | |
| Insurance Type | 0.206 | ||
| PPO | 2,341 (62%) | 3,009 (60%) | |
| Comprehensive | 107 (3%) | 121 (2%) | |
| HMO | 366 (10%) | 460 (9%) | |
| POS | 280 (7%) | 416 (8%) | |
| Other | 414 (11%) | 543 (11%) | |
| Missing | 297 (8%) | 438 (9%) | |
| Smoking | 0.892 | ||
| Yes | 3,660 (96%) | 4,793 (96%) | |
| No | 145 (4%) | 194 (4%) | |
| Obesity | <0.001 | ||
| Yes | 3,641 (96%) | 4,657 (93%) | |
| No | 164 (4%) | 330 (7%) | |
| Mean Time to Surgery (Days) | 222 | 237 | 0.51 |
Median household income not represented in integers
Preoperative resource utilization separated by gender is presented in Table 3 and Table 4. Women had more clinic visits than men (p<0.001). There were too few emergency department visits in each cohort to include in our analysis (2 visits for men (0.1%) and 2 visits for women (0%)). Men underwent more imaging in general (88% vs. 86%), with the difference stemming from greater use of X-rays (76% vs. 71%, p=<0.001) and CT scans (2.3% vs. 1.6%, p=0.025). However, there was no difference in MRI usage between the groups. Women underwent more occupational therapy evaluations and used more narcotic and non-narcotic pain medication than men (p<0.001).
Table 3.
Preoperative Resource Utilization by Gender
| Men (%) | Women (%) | P values | |
|---|---|---|---|
| Clinic visits | <0.001 | ||
| None | 382 (10%) | 584 (12%) | |
| 1–2 | 640 (17%) | 806 (16%) | |
| 3–5 | 2,304 (61%) | 2,846 (57%) | |
| >5 | 479 (13%) | 751 (15%) | |
| Imaging Use | 0.015 | ||
| No | 471 (12%) | 707 (14%) | |
| Yes | 3,334 (88%) | 4,280 (86%) | |
| X-ray | <0.001 | ||
| No | 916 (24%) | 1,439 (29%) | |
| Yes | 2,889 (76%) | 3,548 (71%) | |
| CT | 0.025 | ||
| No | 3,719 (98%) | 4,908 (98%) | |
| Yes | 86 (2%) | 79 (2%) | |
| MRI | 0.229 | ||
| No | 1,292 (34%) | 1,756 (35%) | |
| Yes | 2,513 (66%) | 3,231 (65%) | |
| OT | <0.001 | ||
| No | 2,676 (70%) | 3,300 (66%) | |
| Yes | 1,129 (30%) | 1,687 (34%) | |
| Corticosteroid Use | 0.632 | ||
| No | 2,775 (73%) | 3,613 (72%) | |
| Yes | 1,030 (27%) | 1,374 (28%) | |
| Narcotic Use | <0.001 | ||
| No | 2,136 (56%) | 2,185 (44%) | |
| Yes | 1,669 (44%) | 2,802 (56%) | |
| Non-narcotic Use | <0.001 | ||
| No | 2,010 (53%) | 2,426 (49%) | |
| Yes | 1,795 (47%) | 2,561 (51%) |
CT: computed tomography; MRI: magnetic resonance imaging; OT: occupational therapy
Table 4.
Mean Preoperative Resource Utilization by Gender
| Mean values | Men | Women | P values |
|---|---|---|---|
| Clinic visit | 2.62 | 2.65 | 0.616 |
| Imaging | 1.80 | 1.70 | <0.001 |
| X-ray | 1.08 | 1.01 | <0.001 |
| CT | 0.023 | 0.016 | 0.021 |
| MRI | 0.70 | 0.68 | 0.322 |
| OT visit | 0.95 | 1.14 | <0.001 |
| Corticosteroid Injection | 0.327 | 0.333 | 0.604 |
CT: computed tomography; MRI: magnetic resonance imaging; OT: occupational therapy
Using multivariable analysis, gender was predictive for preoperative resource utilization for imaging, x-ray use, OT use, narcotic and non-narcotic medication use. Women had significantly lower odds of using diagnostic imaging in general (OR: 0.8, CI: 0.7–1.0, p-value: 0.02) and particularly x-rays (OR: 0.8, CI: 0.7–0.8, p-value: <0.001) (Table 5). However, gender was not predictive of CT or MRI usage. Women used significantly more conservative measures such as occupational therapy services (OR: 1.2, CI: 1.1–1.3, p-value: 0.002). They were also more likely to receive both narcotic and non-narcotic pain medications (OR: 1.6, CI: 1.5–1.8, p-value: <0.001; OR: 1.2, CI: 1.1–1.3, p-value: 0.001, respectively).
Table 5.
Multivariable Logistic Regression of Gender and Resource Utilization*
| Odds ratio of receiving each type of service (95% CI) | P values | |
|---|---|---|
| Clinic visits | ||
| Men | ||
| Women | 0.8 (0.7–1.0) | 0.01 |
| Imaging | ||
| Men | ||
| Women | 0.8 ( 0.7–1.0 ) | 0.02 |
| X-ray | ||
| Men | ||
| Women | 0.8 ( 0.7–0.8 ) | <0.001 |
| CT | ||
| Men | ||
| Women | 0.8 (0.7–1.1) | 0.21 |
| MRI | ||
| Men | ||
| Women | 0.9 ( 0.8–1.0 ) | 0.16 |
| OT visit | ||
| Men | ||
| Women | 1.2 ( 1.1–1.3 ) | 0.002 |
| Corticosteroid injections | ||
| Men | ||
| Women | 1.0 ( 0.9–1.1 ) | 0.74 |
| Non-narcotic analgesia | ||
| Men | ||
| Women | 1.2 ( 1.1–1.3 ) | 0.001 |
| Narcotic analgesia | ||
| Men | ||
| Women | 1.6 (1.5–1.8) | <0.001 |
CT: computed tomography; MRI: magnetic resonance imaging; OT: occupational therapy
covariates used in the model include age, comorbidity score, median household income, type of insurance, smoking status, obesity, and geographic region
Using univariate analysis, the mean cost of 12 months of preoperative care for a patient undergoing wrist arthroscopy was $1,341. After dividing cost based on gender, the average total cost of care during the 12 months prior to undergoing wrist arthroscopy was not significantly different (mean cost for men: $1,308 vs. mean cost for women: $1,276, p-value 0.07) (Table 6). Table 7 shows the results of multivariable analysis of cost based on gender, controlling for patient age, median household income, type of insurance, comorbidity score, region, smoking, and obesity. The mean cost of imaging for a man was $672 compared to $543 for a woman (p-value: 0.024). More specifically, gender imparted a significant cost difference for x-rays (mean cost for men: $74 vs. mean cost for women: $45, p-value: <0.001). On the other hand, the average cost for occupational therapy visits for women was $130 compared to $93 for men (p-value 0.003). Additionally, the cost of non-narcotic and narcotic analgesia was significantly higher for women ($65 for non-narcotic analgesia for women, $568 for narcotic analgesia for women, p-value <0.001 for both).
Table 6.
Cost of Resource Utilization by Gender
| Mean values | Men ($) | Women ($) | P values |
|---|---|---|---|
| Total (12 months preoperative) | 1308 | 1367 | 0.072 |
| Clinic | 269 | 264 | 0.172 |
| Imaging | 672 | 646 | 0.085 |
| X-ray | 73 | 69 | <0.001 |
| CT | 11 | 8 | 0.021 |
| MRI | 587 | 569 | 0.406 |
| OT visit | 93 | 107 | <0.001 |
| Corticosteroid Injection | 31 | 31 | 0.804 |
| Non-narcotic Analgesia | 46 | 56 | <0.001 |
| Narcotic Analgesia | 197 | 263 | <0.001 |
CT: computed tomography; MRI: magnetic resonance imaging; OT: occupational therapy
Table 7.
Multivariable Linear Regression of Gender and Cost*
| Type of Service | Mean Cost for Men ($) | Mean Cost for Women ($) | P values |
|---|---|---|---|
| Total (12 months preoperative) | 1,308 | 1,276 | 0.61 |
| Clinic | 269 | 221 | 0.014 |
| Imaging | 672 | 543 | 0.024 |
| X-ray | 74 | 45 | <0.001 |
| CT | 11 | 11 | 0.195 |
| MRI | 587 | 500 | 0.219 |
| OT | 93 | 130 | 0.003 |
| Corticosteroid Injection | 31 | 32 | 0.711 |
| Non-narcotic Analgesia | 46 | 65 | <0.001 |
| Narcotic Analgesia | 197 | 568 | <0.001 |
CT: computed tomography; MRI: magnetic resonance imaging; OT: occupational therapy
covariates used in the model include age, comorbidity score, median household income, type of insurance, smoking status, obesity, and geographic region
Discussion
Despite national efforts to minimize healthcare disparities, we found significant gender differences in resource utilization prior to undergoing wrist arthroscopy. Men underwent significantly more preoperative imaging, particularly x-rays, whereas women underwent more preoperative conservative treatment including occupational therapy, and used more narcotic and non-narcotic pain medications. However, regardless of these differences in treatment patterns, there was no difference in the total cost of preoperative care for wrist arthroscopy between men and women. Given current national initiatives to minimize gender biases, uncovering drivers for gender disparities in resource utilization merits additional investigation. Some possible reasons behind these gender disparities are implicit gender biases in treatment, and differences in the presentation of non-traumatic wrist pain between men and women.
Gender disparities in surgery have been demonstrated for a variety of surgical subspecialties. Studies investigating use of joint arthroplasty have confirmed significant gender differences in utilization patterns8. Though women have a higher prevalence of osteoarthritis, they are less likely to undergo joint arthroplasty than men8,17. Furthermore, orthopaedic surgeons are more likely to offer total joint arthroplasty to men than women, emphasizing the implicit gender biases present in surgical treatment18. However, these disparities are not limited to orthopaedic surgery. Women undergo fewer percutaneous cardiac interventions and coronary artery bypass graft surgeries despite having similar rates of coronary heart disease as men19–21. A study by Khan et al. found that women with coronary heart disease were referred for cardiac intervention later in their disease course, which adversely impacted outcomes and increased their risk of operative death22. Implicit gender biases of physicians may play a role in influencing treatment recommendations including referral for more invasive measures such as cardiac intervention23. Findings from our study corroborate these gender disparities. We found that the preoperative work-up prior to undergoing wrist arthroscopy differed significantly between men and women. Multivariable analysis found that women utilized fewer diagnostic modalities such as imaging (p=0.02) and x-rays (p<0.001) but received significantly more conservative treatment measures including narcotic (p<0.001), and non-narcotic pain medications (p<0.001). Unlike radiologic test, these conservative measures may not help providers in discerning the etiologies of non-traumatic wrist pain. Though the exact circumstances surrounding these gender differences in preoperative care are impossible to ascertain using the MarketScan databases, recent literature has hypothesized that the drivers of gender differences in surgical care include unequal access to care, patient preferences, inherent provider biases, and differences in disease presentation9,24. Factors influencing gender differences in resource utilization prior to undergoing wrist arthroscopy should be further studied to determine reasons behind these disparities.
One possible reason behind these disparities is inherent differences in disease presentation between men and women. Women with chronic wrist pain may present with different subjective symptoms and physical exams compared to men, and gender differences in disease manifestations is a recognized phenomenon. For example, women with acute coronary syndrome have more vague and atypical anginal symptoms than men25,26. These differences may lead to delay in care with worse outcomes27,28. Additionally, pain perceptions and treatment are different between men and women. There is a higher prevalence of musculoskeletal pain, especially wrist pain, in women29,30, and overall, women report more severe musculoskeletal pain31 and have more physical limitations due to this pain than men32. Moreover, women are more likely to use both narcotic and non-narcotic analgesia than men31,33–35. In this study, we found that women with non-traumatic wrist pain used significantly more narcotic (OR: 1.6, CI: 1.5–1.8, p-value: <0.001) and non-narcotic (OR: 1.2, CI: 1.1–1.3, p-value: 0.001) pain medications prior to undergoing wrist arthroscopy. Though the MarketScan databases do not include clinical information, all patients in this cohort ultimately underwent wrist arthroscopy for non-traumatic wrist pain; therefore, all patients met criteria for surgical intervention. Furthermore, given the considerable number of patients presented in this study, we do not expect to have substantial differences in pathology between men and women. However, women in this study used significantly more pain medications than men. Mechanisms for gender differences in pain are still being investigated, but researchers have examined hormonal and psychologic influences with mixed results31. In this study, we have uncovered significant gender differences in the preoperative treatment of non-traumatic wrist pain. Physicians treating non-traumatic wrist pain must be aware of these gender differences in preoperative utilization in order to provide more equitable care.
Healthcare expenditure in the United States is substantial and continues to grow. Given the financial burden of healthcare, reforms aimed at reducing financial waste are currently under negotiation. In this study, there were significant gender differences in preoperative treatment of chronic wrist pain; however, the overall preoperative treatment cost was no different between the genders. After examining individual resource expenditure, the mean cost of conservative measures including occupational therapy, narcotic medications, and non-narcotic medications were significantly higher in women. Even with small differences in total cost of care, providers should continue to explore avenues to decrease expenditure. Through minimizing gender disparities in preoperative resource utilization for chronic wrist pain, providers may be able to eliminate healthcare financial waste.
Our study has several limitations. First, this is a study of insurance claims data, which lack the granularity of disease severity or provider recommendations. Therefore, we cannot comment on whether the preoperative care was patient or provider-driven. Personal preference, employment, and other concerns can factor into patient-driven inclinations towards aggressive or conservative treatment. However, insurance claims databases lack clinical data including patient preferences and employment. Additionally, the same database limitation prevents insight into variations in disease presentation between men and women along with possible differences in patient compliance to conservative treatments. However, given the large number of patients in this study, differences in pathology are likely uniformly distributed between men and women. Second, we did not perform subgroup analyses by geographic area or size of hospital. Institutions may have different practice patterns, and gender disparities may not be nationally uniform. Additionally, we examined data over a 6-year period and are unable to comment on the evolution of gender differences in preoperative resource utilization and if recent efforts to minimize disparities have influenced these gender biases. Lastly, the Truven MarketScan databases contain data from commercial insurance and Medicare supplemental claims; therefore, we are unable to apply these findings to other insurers or the uninsured.
Despite these limitations, this study has important implications for the delivery of uniform and equitable care for patients with non-traumatic wrist pain. With national efforts to eliminate healthcare disparities, understanding and minimizing gender differences in surgical care is paramount. As seen in other surgical disciplines, gender disparities in the treatment of non-traumatic wrist pain exist. Preoperatively, women undergoing wrist arthroscopy for non-traumatic wrist pain use more conservative measures including occupational therapy, narcotic and non-narcotic analgesia. These measures do not help with the diagnosis, but may delay overall treatment. However, men utilize more imaging including x-rays, which is beneficial in the diagnosis of the underlying causes of non-traumatic wrist pain. Implicit provider biases or differences in disease presentation may play a role in these gender disparities. Uncovering the exact drivers of these gender disparities in resource utilization will help provide more uniform and equitable care.
Acknowledgments
Research reported in this publication was supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases of the National Institutes of Health under Award Number 2 K24-AR053120-06. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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