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Original Investigation |

Delay of Surgery for Melanoma Among Medicare Beneficiaries FREE

Jason P. Lott, MD, MHS, MSHP1,2,3; Deepak Narayan, MD4; Pamela R. Soulos, MPH2,5; Jenerius Aminawung, MD, MPH2,5; Cary P. Gross, MD, MPH1,2,5
[+] Author Affiliations
1Robert Wood Johnson Foundation Clinical Scholars Program, Yale University School of Medicine, New Haven, Connecticut
2Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut
3Section of Dermatology, Veterans Affairs Connecticut Healthcare System, New Haven
4Department of Surgery, Yale University School of Medicine, New Haven, Connecticut
5Cancer Outcomes, Public Policy, and Effectiveness Research (COPPER) Center, Yale University School of Medicine, New Haven, Connecticut
JAMA Dermatol. 2015;151(7):731-741. doi:10.1001/jamadermatol.2015.119.
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Published online

Importance  Timely delivery of surgery for cancer affects health care quality and outcomes. However, population-based studies characterizing the delay of surgery for melanoma in the United States have not been performed.

Objective  To assess the delay of surgery for melanoma by tumor-, patient-, and physician-level characteristics.

Design, Setting, and Participants  We performed a retrospective cohort study of Medicare beneficiaries diagnosed as having melanoma from January 1, 2000, through December 31, 2009, using the Surveillance, Epidemiology, and End Results–Medicare database. We included all patients undergoing surgical excision of melanoma diagnosed by means of results of skin biopsy.

Exposures  Anatomic location and stage of the tumor, patient sociodemographic characteristics, prior melanoma, Elixhauser comorbidities, and the specialties of the physicians who performed the biopsy and surgery.

Main Outcomes and Measures  Surgical delay, measured as the time from the biopsy to surgical excision. We estimated risk-adjusted odds ratios (ORs) and marginal probabilities of delay with 95% CIs for each covariate using mixed-effects logistic regression.

Results  Our cohort consisted of 32 501 cases of melanoma. Most of the patients were white (95.4%), male (63.1%), married (47.9%), and 75 years or older (60.8%) and did not have a prior melanoma (93.7%). Melanomas were most frequently located on the head and neck (40.5%) and staged as in situ disease (48.2%). More than three-quarters of cases (25 269 [77.7%]) underwent excision within 1.5 months of biopsy. Among those treated after 1.5 months (7232 [22.3%]), 2620 (8.1% of all cases) experienced a delay of longer than 3 months. The incidence of a risk-adjusted surgical delay longer than 1.5 months was significantly increased among patients 85 years or older compared with those younger than 65 years (odds ratio [OR], 1.28 [95% CI, 1.05-1.55]; P = .02), those with a prior melanoma (OR, 1.20 [95% CI, 1.08-1.34]; P = .001), and those with an increased comorbidity burden (OR, 1.18 [95% CI, 1.09-1.27]; P < .001). Melanomas that underwent biopsy and excision by dermatologists had the lowest likelihood of delay (probability, 16% [95% CI, 14%-18%]). The highest likelihood of delay (probability, 31% [95% CI, 24%-37%]) occurred when the biopsy was performed by a nondermatologist and excised by a primary care physician. Similar findings were observed for a delay longer than 3 months.

Conclusions and Relevance  Approximately 1 in 5 Medicare beneficiaries experience a delay of surgery for melanoma that is longer than 1.5 months. Those patients undergoing biopsy and surgery by dermatologists have the lowest risk for delay, highlighting potential opportunities for improved access to and coordination of dermatologic care.

Figures in this Article

Melanoma is a leading cause of new cancer diagnoses in the United States, accounting for most skin cancer–related deaths.1 Although surgical excision is the primary therapy for melanoma, few studies have examined delay in undergoing this procedure.26 Surgical delay may result in increased morbidity and mortality for other malignant neoplasms,79 including cancers of the lung,710 rectum,7,11 breast,7,9,1214 and bladder,8,9,15,16 but little association has been shown between delay of surgery for melanoma and survival.2,3,6,17

However, surgical delay may cause anxiety, stress, and psychological harm, and studies have shown that older patients are more likely to have longer wait times for surgery for melanoma.3,6 In addition, surgical delay may reflect limited access to health care and/or inefficient delivery of health care. To our knowledge, no population-based studies have analyzed delay of surgery for melanoma in the United States. No guidelines exist regarding timely surgery for melanoma, although informal recommendations suggest as customary care that melanomas undergo excision within 4 to 6 weeks of diagnostic biopsy.2,4 Moreover, the impact of physician specialty in the performance of skin biopsy and surgical excision and the time elapsing between these interventions have not been examined, and access to relatively newer surgical therapies—such as Mohs micrographic surgery for treatment of melanoma1820—has not been evaluated. These knowledge gaps have resulted in important unanswered questions about which type of physician may deliver optimal care for this disease.

Accordingly, we sought to describe surgical delay among Medicare beneficiaries with melanoma. Specifically, we sought to determine (1) which tumor- and patient-level factors were associated with surgical delay and (2) whether the specialty of the physicians who deliver dermatologic care influenced the delay.

Data Source and Study Cohort

We used the Surveillance, Epidemiology, and End Results (SEER)–Medicare database21 to conduct a retrospective cohort study of Medicare beneficiaries diagnosed as having primary cutaneous melanoma from January 1, 2000, through December 31, 2009. This database links patient-level Medicare administrative claims to patient-level information concerning incident cancer diagnoses reported to the SEER tumor registries.22,23 The SEER-Medicare database is nationally representative, and included geographic regions cover approximately 28% of the US population.24,25 This database is a leading resource for nationwide studies on the quality of cancer treatment and cancer outcomes in the United States.23,26 Fidelity of this information is bolstered by legal penalties for inaccurate and/or falsified claims.27

Because individuals can be diagnosed as having more than 1 melanoma, melanoma cases constituted the unit of analysis for our study. Cases were included if the patients were alive at the time of diagnosis, if the month of diagnosis was known, and if patients were continuously enrolled in fee-for-service Medicare parts A and B from 2 years before to 1 year after the diagnosis. Patients with more than 1 melanoma were considered eligible. However, if 2 or more melanomas occurred within 1 year of each other, these cases were excluded, given that our algorithm for determining surgical delay (described below) would be unable to attribute multiple biopsies and surgical procedures to particular melanoma cases during this interval. Finally, patients in the Greater Georgia SEER registry with melanoma diagnoses before 2004 were excluded because of incomplete claims data.

The Yale University Human Research Protection Program determined that this study did not constitute research on human subjects; therefore, institutional review board approval and informed consent were waived. Patient data were deidentified.

Primary Outcome and Covariates of Interest

The primary outcome was delay of surgery for melanoma, defined as the interval from the biopsy to surgical resection. Starting from the first day of the month of melanoma diagnosis (as reported by the SEER-Medicare database), we looked forward in time (to 12 months) to identify the earliest administrative claim for a non-Mohs or a Mohs surgical excision using the Health Care Financing Administration Common Procedural Coding System and codes from the International Classification of Diseases, Ninth Revision (ICD-9) (eTable in the Supplement). We attributed this claim date as the date of surgery. We looked backward from the date of surgery to identify the most proximal occurrence of a claim associated with a skin biopsy, with a maximum look-back period of 15 months (eTable in the Supplement). We attributed this claim date as the date of biopsy. Surgical delay was calculated as the difference in days from the date of skin biopsy to the date of surgical excision.

Patient-level covariates included age, sex, race (categorized as white vs nonwhite given the relatively uncommon occurrence of melanoma across all nonwhite populations), marital status (categorized as married, unmarried, and unknown), prior melanoma, and a census tract estimate of annual income. We assessed the history of influenza vaccination in the 2 years before melanoma diagnosis as a proxy measure for patient-level access to primary care,2831 which may, in turn, affect care coordination32 and delay of surgery for melanoma.

Elixhauser comorbidities (excluding the cancer diagnosis)33 were identified by searching claims from 24 through 3 months before the diagnosis for relevant ICD-9 codes that occurred on at least 1 inpatient claim or on 2 or more outpatient claims occurring more than 30 days apart and were summed (categorized as 0, 1-2, or ≥3 conditions).

Tumor-level covariates included the year of diagnosis, SEER historical stage, and anatomic location (categorized as head/neck, trunk, extremities, and other/unknown). We also classified melanoma according the sixth edition of the American Joint Committee on Cancer staging system.34 However, because of a lack of necessary information within the SEER-Medicare database,34 thin melanomas diagnosed before 2004 could not be classified as stage I vs stage II disease; therefore, we categorized these melanomas as stage I/II disease. Accordingly, we provided descriptive statistics regarding melanoma case distribution across American Joint Committee on Cancer stage but used the SEER historical stage for our risk-adjusted analyses.

We designed our model to account for the impact of physician specialty in 3 ways. First, we included a covariate denoting the specialty of the physician performing the biopsy (categorized as a dermatologist or a nondermatologist). Second, we included a covariate denoting the specialty of the physician performing the excision (categorized as a general/plastic surgeon, a dermatologist, a Mohs surgeon, a primary care physician, and other/unknown). Information within Medicare claims identifying the physician specialty was used to construct these categories. For Mohs surgery in particular, we classified any physician who had associated billing claims for Mohs micrographic surgery as a Mohs surgeon. Mohs surgeons were categorized separately from dermatologists, given their additional surgical training, and separately from general/plastic surgeons, given their dermatologic expertise. Because surgical delay may depend on coordination of care between physicians performing biopsies and performing surgical procedures, we included an interaction term for pairs of physicians of different specialties performing biopsies and surgical procedures. This term enabled the evaluation of risk of surgical delay by various combinations of physicians, such as the combination of a dermatologist performing the biopsy and surgical excision vs the combination of a primary care physician performing the biopsy and a dermatologist performing the excision.

Given that geographic location is associated with patterns of health care utilization that may influence surgical care of melanoma,35 we assigned the hospital referral region and SEER registry for each patient’s zip code of residence. We used the US Health Resources and Services Administration 2013 Area Health Resources File36 to calculate the mean county-level dermatologist density (per 100 000 people) and primary care physician density for the years 2000 through 2008, given the potential effect of local physician supply on the delivery of health care (eg, areas with a limited primary care workforce may face challenges in coordinating surgical therapy for melanoma, whereas areas with smaller numbers of dermatologists may have limited capacity for providing surgical care). We also categorized each county according to its 2003 rural-urban continuum status (metropolitan vs nonmetropolitan), recognizing that residents of inner city and rural areas have relatively limited access to health care services.37

Statistical Analysis

We calculated the distribution of surgical delay in weeks. In addition, we examined the distribution of melanoma cases in our sample across tumor-, patient-, and physician-level covariates and across the following 3 temporal strata of delay: 1.5 months or less, longer than 1.5 months, and longer than 3 months. We used the χ2 test to compare the proportion of melanoma cases experiencing (1) delays of 1.5 months or less vs longer than 1.5 months and (2) delays of 1.5 months or less vs longer than 3 months. The 1.5-month threshold of surgical delay was chosen according to informal recommendations that melanomas should be excised within this time interval.2,4 We selected a priori the 3-month threshold to represent extreme delay.

We used regression-based multivariate modeling to evaluate potential factors associated with delays longer than 1.5 and longer than 3 months. We used mixed-effects logistic regression to adjust for multilevel clustering of melanoma cases within the hospital referral region, in turn clustered within the SEER registry, to assess the impact of tumor-, patient-, physician-, and geographic-level covariates. This analytic approach uses random intercepts to account for case clustering and produces accurate SEs.38 We chose logistic regression as our primary analytic model because our data lack any censoring, and all cases were observed for an identical length of follow-up. These characteristics permit unbiased estimates of factors affecting delay to be calculated with this technique.

We estimated risk-adjusted odds ratios (ORs) and 95% CIs for each covariate. We calculated risk-adjusted marginal probabilities of surgical delay stratified by physician combinations, holding all other covariates constant at their sample means. These probabilities represent the actual chance of occurrence (rather than ratios of probabilities) and absolute risk for surgical delay.

Finally, we performed sensitivity analyses using multivariate Cox proportional hazards regression modeling. This approach provides the instantaneous relative risk of undergoing surgery at any given time point and is estimated using the hazard ratio (HR). In this model, HR > 1.00 indicates a quicker time to surgery (less delay), whereas HR < 1.00 indicates a slower time to surgery (more delay).

All analyses were performed using commercially available software (SAS, version 9.2 [SAS Institute Inc] and Stata, version 13.1 [StataCorp]). All statistical tests were 2 tailed with α = .05.

Our final sample included 32 501 cases of melanoma. Patients were more likely to be white (95.4%), male (63.1%), married (47.9%), and 75 years or older (60.8%) and to have no prior melanoma (93.7%) (Table 1). Melanoma cases were more likely to undergo biopsy by dermatologists (88.4%) compared with nondermatologists (11.6%). Likewise, melanomas were more likely to be excised by dermatologists (41.9%) compared with general/plastic surgeons (30.5%), Mohs surgeons (9.1%), or primary care physicians (1.2%) (Table 1). Melanomas were most commonly located on the head and neck (40.5%) and staged as in situ disease (48.2%). In addition, according to the sixth edition of the American Joint Committee on Cancer criteria, 8283 cases (25.5%) were classified as stage I; 4681 cases (14.4%), stage I/II; 1314 cases (4.0%), stage II; 1746 cases (5.4%), stage III; 230 cases (0.7%), stage IV; and 582 cases (1.8%), unknown.

Table Graphic Jump LocationTable 1.  Unadjusted Risk for Delay of Surgery for Melanoma by Patient-, Physician-, and Tumor-Level Characteristics
Unadjusted Risk for Surgical Delay

The distribution of surgical delay ranged from 4 to 450 (median, 27.0; mean, 44.3) days and varied by specialty of the physician performing the biopsy and surgery (Figure 1 and Figure 2). Of the total study population, 25 269 melanoma cases (77.7%) underwent excision within 1.5 months, whereas 7232 (22.3%) underwent excision after 1.5 months. In all, 2620 cases (8.1%) underwent excision after 3 months. Age and comorbidity burden were significantly associated with a delay of longer than 1.5 months (P < .001), as were marital status (P = .001), race (P = .01), prior melanoma (P = .001), anatomic location (P < .001), SEER historical stage (P < .001), and median annual income (P = .004) (Table 1).

Place holder to copy figure label and caption
Figure 1.
Delay of Surgery for Melanoma by Specialty of the Physician Performing the Biopsy

Most diagnostic skin biopsies for melanoma (N = 32 501) were performed by dermatologists (28 744 [88.4%]) compared with nondermatologists (3757 [11.6%]). For biopsies performed by nondermatologists, 940 cases (25.0%) were treated surgically after 1.5 months and 420 (11.2%) after 3 months. For biopsies performed by dermatologists, 6292 cases (21.9%) were treated surgically after 1.5 months; 2200 (7.7%), after 3 months.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.
Delay of Surgery for Melanoma by the Specialty of the Physician Performing the Surgery

Most surgical procedures for melanoma (N = 32 501) were performed by dermatologists (13 634 [41.9%]), followed by general/plastic surgeons (9915 [30.5%]) and Mohs surgeons (2958 [9.1%]). For melanomas excised by dermatologists, 2247 surgical procedures (16.5%) occurred after 1.5 months compared with 2614 (26.4%) for general/plastic surgeons and 710 (24.0%) for Mohs surgeons. Surgical procedures performed after 3 months occurred for 1017 melanomas treated by dermatologists (7.5%) compared with 761 treated by general/plastic surgeons (7.7%) and 206 treated by Mohs surgeons (7.0%). Data for cases of melanoma treated by primary care physicians (384 [1.2%]) and other/unknown specialist physicians (5610 [17.3%]) are not shown.

Graphic Jump Location

Physician specialty was also significantly associated with the risk for surgical delay (P < .001) (Table 1). For example, 21.9% of melanoma cases experienced a delay longer than 1.5 months when the biopsy was performed by a dermatologist compared with 25.0% when the biopsy was performed by a nondermatologist. Likewise, only 16.5% of melanoma cases experienced a delay longer than 1.5 months when the surgery was performed by a dermatologist compared with 24.0% for Mohs surgeons, 26.4% for general/plastic surgeons, and 30.7% for primary care physicians.

Adjusted Risk for Surgical Delay Longer Than 1.5 Months

After accounting for clinical and demographic factors, the adjusted risk for a surgical delay longer than 1.5 months (Table 2) was significantly associated with being 85 years or older (OR, 1.28 [95% CI, 1.05-1.55]; P = .02), prior melanoma (OR, 1.20 [95% CI, 1.08-1.34]; P = .001), and the presence of 1 to 2 Elixhauser comorbidities (OR, 1.10 [95% CI, 1.04-1.17]; P = .002) or 3 or more Elixhauser comorbidities (OR, 1.18 [95% CI, 1.09-1.27]; P < .001). History of influenza vaccination, median annual income, and geographic-level variables were not associated with delay (Table 2).

Table Graphic Jump LocationTable 2.  Risk-Adjusted Surgical Delay by Patient-, Physician-, and Tumor-Level Characteristicsa

The adjusted risk for a surgical delay longer than 1.5 months was significantly reduced when a dermatologist performed the biopsy compared with a nondermatologist (OR, 0.68 [95% CI, 0.57-0.82]; P < .001). The risk for delay was significantly increased when a primary care physician performed the surgery compared with a dermatologist (OR, 1.49 [95% CI, 1.08-2.08]; P = .02), although no significant differences were observed with other surgical specialties (Table 2). Compared with a dermatologist performing the biopsy and surgery, we observed a significantly higher risk for surgical delay (OR, 1.49 [95% CI, 1.19-1.87], P < .001) when a dermatologist performed the biopsy and a general/plastic surgeon subsequently performed the surgery.

The marginal risk-adjusted probabilities of a surgical delay longer than 1.5 months by combinations of physicians performing the biopsy and surgery demonstrate similar patterns of delay. The minimum probability of delay occurred when a dermatologist performed the biopsy and surgery (probability of delay, 16% [95% CI, 14%-18%]; P < .001), whereas the maximum probability of delay occurred when a nondermatologist performed the biopsy and a primary care physician performed the surgery (probability of delay, 31% [95% CI, 24%-37%]; P < .001) or when a dermatologist performed the biopsy and a primary care physician performed the surgery (probability of delay, 31% [95% CI, 22%-40%]; P < .001) (Table 3).

Table Graphic Jump LocationTable 3.  Risk-Adjusted Marginal Probabilities of Surgical Delay by Combination of Physician Specialtya
Adjusted Risk for Surgical Delay Longer Than 3 Months

When we assessed factors associated with a delay longer than 3 months, we found similar, although not identical, results (Table 2). Compared with patients younger than 65 years, the risk for a delay was significantly associated with being aged 75 to 79 years (OR, 1.48 [95% CI, 1.09-2.02]; P = .01), being aged 80 to 84 years (OR, 1.40 [95% CI, 1.03-1.92]; P = .03), being 85 years or older (OR, 1.55 [95% CI, 1.13-2.12]; P = .006), being of female sex (OR, 0.90 [95% CI, 0.82-0.99]; P = .02), having a prior melanoma (OR, 1.56 [95% CI, 1.35-1.82]; P < .001), and having 1 to 2 Elixhauser comorbidities (OR, 1.18 [95% CI, 1.07-1.29]; P = .001) and 3 or more Elixhauser comorbidities (OR, 1.23 [95% CI, 1.10-1.38]; P < .001). Again, no significant associations were observed for a history of influenza vaccination, median annual income, or geographic-level variables.

The risk for a delay longer than 3 months was associated with the specialties of the physicians performing the biopsy and the excision. The likelihood of delay was significantly reduced when a dermatologist performed the biopsy (OR, 0.57 [95% CI, 0.44-0.71]; P < .001) compared with a nondermatologist. Compared with an excision performed by a dermatologist, the risk for a delay was decreased when performed by a general/plastic surgeon (OR, 0.70 [95% CI, 0.53-0.94]; P = .02) and increased when performed by a primary care physician (OR, 1.70 [95% CI, 1.14-2.53]; P = .008). The minimum risk-adjusted marginal probability of a delay longer than 3 months occurred when a dermatologist performed the biopsy and a Mohs surgeon or a general/plastic surgeon performed the surgery (probability of delay, 6% [95% CI, 5%-7%] for both combinations; P < .001). The maximum probability of delay occurred when a dermatologist performed the biopsy and a primary care physician performed the surgery (probability of delay, 22% [95% CI, 14%-30%]; P < .001).

Sensitivity Analyses

Sensitivity analyses using Cox proportional hazards regression modeling (in which HR > 1.00 indicates a quicker time to surgery) yielded similar results to those of our primary logistic regression model. For instance, surgery occurred significantly sooner when a dermatologist performed the biopsy compared with a nondermatologist (HR, 1.27 [95% CI, 1.10-1.47]; P = .001). Similar to the primary analysis, the combination of physicians performing the biopsy and excision affected the time to surgery. Compared with a dermatologist performing both procedures, the time to surgery was slower when a dermatologist performed the biopsy and a general/plastic surgeon performed the surgery (HR, 0.77 [95% CI, 0.66-0.90]; P = .001) and when a dermatologist performed the biopsy and a primary care physician performed the surgery (HR, 0.65 [95% CI, 0.44-0.94]; P = .02).

This study provides the first population-based estimates of delay of surgery for melanoma among Medicare beneficiaries. Among our study population, 22.3% of patients experienced a delay of longer than 1.5 months for surgical treatment of their melanoma, whereas 8.1% of patients waited longer than 3 months. These data suggest that a delay of surgery for melanoma is relatively common. Our results demonstrate variation in the receipt of dermatologic care and build on prior research showing improved melanoma-related outcomes for those patients who are married,39 younger, and healthier and who have earlier stages of disease.40,41

These results reveal the effect of physician specialty on the provision of timely surgical care for melanoma. Survey-based research,42 for example, suggests that the delay in melanoma diagnosis and treatment may be reduced when the initial evaluation and surgical therapy are provided by a dermatologist compared with another physician. In our study, the risk for a surgical delay of longer than 1.5 months was reduced when a dermatologist performed the biopsy and was minimized when both procedures were performed by a dermatologist. Dermatologists performing the initial biopsy for diagnosis may underscore the importance of specialized expertise in diagnosing melanoma and (with appropriate concern) in initiating prompt delivery of surgical care. Likewise, having a dermatologist perform the biopsy and surgery for melanoma may indicate enhanced coordination of care between physicians of the same specialty. Delays associated with nondermatologists may reflect inadequate patient-level risk adjustment, unknown confounders associated with the ability to access dermatologists, or care discontinuities arising from intrinsic barriers to dermatology referral and consultation.

Our study does not address the biological significance of surgical delay, and we cannot draw conclusions regarding functional outcomes and morbidity that may or may not result from the provision of surgery in a prompt or an untimely fashion. The decision-making process for surgery may be especially complex for elderly patients diagnosed as having melanoma of the head and neck, for whom surgery may impose a greater burden. Appropriate patient- and family-centered care may dictate the need for additional time to achieve consensus regarding therapy, and surgical delays in this setting may occur. Nonetheless, we believe that understanding delay is important for these and other patients with Medicare coverage to ensure that appropriate and expedient care is provided when desired.

Our study has several limitations. The SEER-Medicare database only contains information regarding patients enrolled in traditional fee-for-service Medicare, and our results may not be generalizable to those enrolled in Medicare Advantage (managed care) plans. Our study is retrospective by design, and we were unable to adjust for all confounders. Nevertheless, because of our large sample size, we were able to adjust for numerous patient-, physician-, tumor-, and geographic-level factors that may affect the risk for surgical delay. We also accounted for regional differences in patterns and intensity of the use of health care resources, which further strengthens our results.

We were unable to identify the precise date of melanoma diagnosis because this information was not available. However, this limitation is minor because we constructed our surgical delay outcome to ensure the narrowest window possible from the date of skin biopsy to the date of surgical excision. We could not identify surgical excisions that could have been performed for treatment of other nonmelanoma skin cancers (with surgery for melanoma occurring later), which would bias our results conservatively. We were unable to identify cases of melanoma that were treated by nonsurgical modalities, resulting in inaccurate attribution of surgical resections to melanomas that were treated nonsurgically. We would not expect differential bias toward a shorter or a longer delay in this scenario, which likely represents a small proportion of patients in our cohort. However, some cases of melanoma in situ may be managed with topical therapy (eg, imiquimod for treatment of lentigo maligna melanoma) and close follow-up to monitor for recurrence, which would then be treated surgically. In this situation, the delay between the biopsy and surgery is intentional and expected and does not reflect inadequate access to care. Because a substantial number of our cases have in situ disease (48.2%), our results may be confounded by this therapeutic strategy.

Selection bias may have arisen for select melanomas referred to specialists for surgery based on their stage, anatomic location, or other factors. However, we adjusted for numerous factors that may affect surgical delay, and such adverse selection would have conservatively biased our estimates of delay for specialists. Finally, we could not identify those patients who underwent excisional biopsy of their melanoma and who did not require subsequent surgical therapy.

Our results show that a delay of surgery for melanoma may be relatively common among Medicare beneficiaries. Although no gold standard exists to judge appropriate vs inappropriate surgical delay, minimization of delay is an important patient-centered objective of high-quality dermatologic care, especially given the potential harms of psychological stress associated with untreated malignant neoplasms. Our study highlights opportunities for quality improvement in dermatologic care and suggests that efforts to minimize the delay of surgery for melanoma might focus on increased access to dermatologic expertise and enhanced coordination of care among different specialists.

Accepted for Publication: January 14, 2015.

Corresponding Author: Jason P. Lott, MD, MHS, MSHP, Department of Internal Medicine, Yale University School of Medicine, 333 Cedar St, SHM IE-61, PO Box 208088, New Haven, CT 06520 (jason.lott@yale.edu; jason.lott@gmail.com).

Published Online: April 8, 2015. doi:10.1001/jamadermatol.2015.119.

Author Contributions: Drs Lott and Gross had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Lott, Soulos, Gross.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Lott.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Lott, Soulos, Aminawung.

Administrative, technical, or material support: Narayan, Soulos, Aminawung.

Study supervision: Lott, Gross.

Conflict of Interest Disclosures: Dr Gross has received research grant support from Johnson & Johnson, Merck, and 21st Century Oncology. No other disclosures were reported.

Funding/Support: This study was supported in part by the Robert Wood Johnson Foundation and developmental funding from the P30 Cancer Center Support Grant at the Yale Comprehensive Cancer Center. This study used the linked Surveillance, Epidemiology, and End Results (SEER)–Medicare database. The collection of the California cancer incidence data used in this study was supported by the California Department of Public Health as part of the statewide cancer reporting program mandated by California Health and Safety Code Section 103885; the National Cancer Institute (NCI)’s SEER Program under contract N01-PC-35136 awarded to the Northern California Cancer Center, contract N01-PC-35139 awarded to the University of Southern California, and contract N02-PC-15105 awarded to the Public Health Institute; and the Centers for Disease Control and Prevention’s National Program of Cancer Registries under agreement U55/CCR921930-02 (Public Health Institute).

Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The interpretation and reporting of these data are the sole responsibility of the authors. The authors acknowledge the efforts of the Applied Research Program, NCI; the Office of Research, Development and Information, Centers for Medicare and Medicaid Services (CMS); Information Management Services, Inc (IMS); and the SEER Program tumor registries in the creation of the SEER-Medicare database. The ideas and opinions expressed herein are those of the authors, and endorsement by the State of California, Department of Public Health, the NCI, and the Centers for Disease Control and Prevention or their contractors and subcontractors is not intended nor should be inferred.

Additional Contributions: The Applied Research Program, NCI; the Office of Research, Development and Information, CMS; IMS; and the SEER tumor registries all helped to make possible the creation of the SEER-Medicare database.

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Spurgeon  P, Barwell  F, Kerr  D.  Waiting times for cancer patients in England after general practitioners’ referrals: retrospective national survey. BMJ. 2000;320(7238):838-839.
PubMed   |  Link to Article
Olsson  JK, Schultz  EM, Gould  MK.  Timeliness of care in patients with lung cancer: a systematic review. Thorax. 2009;64(9):749-756.
PubMed   |  Link to Article
Korsgaard  M, Pedersen  L, Sørensen  HT, Laurberg  S.  Delay of treatment is associated with advanced stage of rectal cancer but not of colon cancer. Cancer Detect Prev. 2006;30(4):341-346.
PubMed   |  Link to Article
Richards  MA, Westcombe  AM, Love  SB, Littlejohns  P, Ramirez  AJ.  Influence of delay on survival in patients with breast cancer: a systematic review. Lancet. 1999;353(9159):1119-1126.
PubMed   |  Link to Article
Richards  MA, Smith  P, Ramirez  AJ, Fentiman  IS, Rubens  RD.  The influence on survival of delay in the presentation and treatment of symptomatic breast cancer. Br J Cancer. 1999;79(5-6):858-864.
PubMed   |  Link to Article
McLaughlin  JM, Anderson  RT, Ferketich  AK, Seiber  EE, Balkrishnan  R, Paskett  ED.  Effect on survival of longer intervals between confirmed diagnosis and treatment initiation among low-income women with breast cancer. J Clin Oncol. 2012;30(36):4493-4500.
PubMed   |  Link to Article
Fradet  Y, Aprikian  A, Dranitsaris  G, Siemens  R, Tsihlias  J, Fleshner  N; Canadian Surgical Wait Times (SWAT) Initiative.  Does prolonging the time to bladder cancer surgery affect long-term cancer control? a systematic review of the literature. Can J Urol. 2006;13(suppl 3):37-47.
PubMed
Bishop  MC.  The dangers of a long urological waiting list. Br J Urol. 1990;65(5):433-440.
PubMed   |  Link to Article
Epstein  E, Bragg  K, Linden  G.  Biopsy and prognosis of malignant melanoma. JAMA. 1969;208(8):1369-1371.
PubMed   |  Link to Article
Snow  SN, Mohs  FE, Oriba  HA, Dudley  CM, Leverson  G, Hetzer  M.  Cutaneous malignant melanoma treated by Mohs surgery: review of the treatment results of 179 cases from the Mohs Melanoma Registry. Dermatol Surg. 1997;23(11):1055-1060.
PubMed   |  Link to Article
Chin-Lenn  L, Murynka  T, McKinnon  JG, Arlette  JP.  Comparison of outcomes for malignant melanoma of the face treated using Mohs micrographic surgery and wide local excision. Dermatol Surg. 2013;39(11):1637-1645.
PubMed   |  Link to Article
Bricca  GM, Brodland  DG, Ren  D, Zitelli  JA.  Cutaneous head and neck melanoma treated with Mohs micrographic surgery. J Am Acad Dermatol. 2005;52(1):92-100.
PubMed   |  Link to Article
National Cancer Institute. Surveillance, Epidemiology, and End Results Program fact sheet.http://appliedresearch.cancer.gov/seermedicare/overview/seermed_fact_sheet.pdf. Published December 2013. Accessed December 18, 2014.
Potosky  AL, Riley  GF, Lubitz  JD, Mentnech  RM, Kessler  LG.  Potential for cancer related health services research using a linked Medicare–tumor registry database. Med Care. 1993;31(8):732-748.
PubMed   |  Link to Article
Warren  JL, Klabunde  CN, Schrag  D, Bach  PB, Riley  GF.  Overview of the SEER-Medicare data: content, research applications, and generalizability to the United States elderly population. Med Care. 2002;40(8)(suppl):IV-3–IV-18.
PubMed
Ma  X, Wang  R, Long  JB,  et al.  The cost implications of prostate cancer screening in the Medicare population. Cancer. 2014;120(1):96-102.
PubMed   |  Link to Article
National Cancer Institute. Surveillance, Epidemiology, and End Results program.http://seer.cancer.gov/about/factsheets/SEER_brochure.pdf. Published March 2012. Accessed December 18, 2014.
Simone  JV, Hewitt  M. Enhancing Data Systems to Improve the Quality of Cancer Care. Washington, DC: National Academies Press; 2000.
Centers for Medicare and Medicaid Services. Medicare enrollment and claim submission guidelines.https://www.cms.gov/Outreach-and-Education/Medicare-Learning-Network-MLN/MLNProducts/downloads/MedicareClaimSubmissionGuidelines-ICN906764.pdf. Published August 2014. Accessed December 18, 2014.
Stryer  DB, Weinick  RM, Clancy  CM.  Reducing racial and ethnic disparities in health care. Health Serv Res. 2002;37(5):xv-xxvi.
PubMed   |  Link to Article
Logan  JL.  Disparities in influenza immunization among US adults. J Natl Med Assoc. 2009;101(2):161-166.
PubMed
Blewett  LA, Johnson  PJ, Lee  B, Scal  PB.  When a usual source of care and usual provider matter: adult prevention and screening services. J Gen Intern Med. 2008;23(9):1354-1360.
PubMed   |  Link to Article
Hoffman  C, Paradise  J.  Health insurance and access to health care in the United States. Ann N Y Acad Sci. 2008;1136:149-160.
PubMed   |  Link to Article
Starfield  B, Shi  L, Macinko  J.  Contribution of primary care to health systems and health. Milbank Q. 2005;83(3):457-502.
PubMed   |  Link to Article
Elixhauser  A, Steiner  C, Harris  DR, Coffey  RM.  Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8-27.
PubMed   |  Link to Article
National Cancer Institute. SEER training modules.http://training.seer.cancer.gov/melanoma/abstract-code-stage/staging.html. Accessed December 18, 2014.
DeMott  K.  Healthcare practices vary widely from town to town: regional Dartmouth Atlas. Health Syst Lead. 1997;4(1):2-3.
PubMed
Health Resources and Services Administration. Area health resources files. http://ahrf.hrsa.gov/. Accessed December 18, 2014.
Ingram  DD, Franco  SJ.  NCHS urban-rural classification scheme for counties. Vital Health Stat 2. 2012;(154):1-65.
PubMed
Bouwmeester  W, Twisk  JW, Kappen  TH, van Klei  WA, Moons  KG, Vergouwe  Y.  Prediction models for clustered data: comparison of a random intercept and standard regression model. BMC Med Res Methodol. 2013;13:19. doi:10.1186/1471-2288-13-19.
PubMed   |  Link to Article
McLaughlin  JM, Fisher  JL, Paskett  ED.  Marital status and stage at diagnosis of cutaneous melanoma: results from the Surveillance Epidemiology and End Results (SEER) program, 1973-2006. Cancer. 2011;117(9):1984-1993.
PubMed   |  Link to Article
Pollack  LA, Li  J, Berkowitz  Z,  et al.  Melanoma survival in the United States, 1992 to 2005. J Am Acad Dermatol. 2011;65(5)(suppl 1):S78-S86.
PubMed   |  Link to Article
Jemal  A, Saraiya  M, Patel  P,  et al.  Recent trends in cutaneous melanoma incidence and death rates in the United States, 1992-2006. J Am Acad Dermatol.2011;65(5)(suppl 1):S17-25.e1-3. doi:10.1016/j.jaad.2011.04.032.
PubMed   |  Link to Article
Richard  MA, Grob  JJ, Avril  MF,  et al.  Delays in diagnosis and melanoma prognosis, II: the role of doctors. Int J Cancer. 2000;89(3):280-285.
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Figure 1.
Delay of Surgery for Melanoma by Specialty of the Physician Performing the Biopsy

Most diagnostic skin biopsies for melanoma (N = 32 501) were performed by dermatologists (28 744 [88.4%]) compared with nondermatologists (3757 [11.6%]). For biopsies performed by nondermatologists, 940 cases (25.0%) were treated surgically after 1.5 months and 420 (11.2%) after 3 months. For biopsies performed by dermatologists, 6292 cases (21.9%) were treated surgically after 1.5 months; 2200 (7.7%), after 3 months.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.
Delay of Surgery for Melanoma by the Specialty of the Physician Performing the Surgery

Most surgical procedures for melanoma (N = 32 501) were performed by dermatologists (13 634 [41.9%]), followed by general/plastic surgeons (9915 [30.5%]) and Mohs surgeons (2958 [9.1%]). For melanomas excised by dermatologists, 2247 surgical procedures (16.5%) occurred after 1.5 months compared with 2614 (26.4%) for general/plastic surgeons and 710 (24.0%) for Mohs surgeons. Surgical procedures performed after 3 months occurred for 1017 melanomas treated by dermatologists (7.5%) compared with 761 treated by general/plastic surgeons (7.7%) and 206 treated by Mohs surgeons (7.0%). Data for cases of melanoma treated by primary care physicians (384 [1.2%]) and other/unknown specialist physicians (5610 [17.3%]) are not shown.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1.  Unadjusted Risk for Delay of Surgery for Melanoma by Patient-, Physician-, and Tumor-Level Characteristics
Table Graphic Jump LocationTable 2.  Risk-Adjusted Surgical Delay by Patient-, Physician-, and Tumor-Level Characteristicsa
Table Graphic Jump LocationTable 3.  Risk-Adjusted Marginal Probabilities of Surgical Delay by Combination of Physician Specialtya

References

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PubMed   |  Link to Article
Huff  LS, Chang  CA, Thomas  JF,  et al.  Defining an acceptable period of time from melanoma biopsy to excision. Dermatol Reports. 2012;4(1):e2. doi:10.4081/dr.2012.e2.
PubMed   |  Link to Article
McKenna  DB, Lee  RJ, Prescott  RJ, Doherty  VR.  The time from diagnostic excision biopsy to wide local excision for primary cutaneous malignant melanoma may not affect patient survival. Br J Dermatol. 2002;147(1):48-54.
PubMed   |  Link to Article
Riker  AI, Glass  F, Perez  I, Cruse  CW, Messina  J, Sondak  VK.  Cutaneous melanoma: methods of biopsy and definitive surgical excision. Dermatol Ther. 2005;18(5):387-393.
PubMed   |  Link to Article
Plym  A, Ullenhag  GJ, Breivald  M, Lambe  M, Berglund  A.  Clinical characteristics, management and survival in young adults diagnosed with malignant melanoma: a population-based cohort study. Acta Oncol. 2014;53(5):688-696.
PubMed   |  Link to Article
Carpenter  S, Pockaj  B, Dueck  A,  et al.  Factors influencing time between biopsy and definitive surgery for malignant melanoma: do they impact clinical outcome? Am J Surg. 2008;196(6):834-842.
PubMed   |  Link to Article
Bilimoria  KY, Ko  CY, Tomlinson  JS,  et al.  Wait times for cancer surgery in the United States: trends and predictors of delays. Ann Surg. 2011;253(4):779-785.
PubMed   |  Link to Article
Bardell  T, Belliveau  P, Kong  W, Mackillop  WJ.  Waiting times for cancer surgery in Ontario: 1984-2000. Clin Oncol (R Coll Radiol). 2006;18(5):401-409.
PubMed   |  Link to Article
Spurgeon  P, Barwell  F, Kerr  D.  Waiting times for cancer patients in England after general practitioners’ referrals: retrospective national survey. BMJ. 2000;320(7238):838-839.
PubMed   |  Link to Article
Olsson  JK, Schultz  EM, Gould  MK.  Timeliness of care in patients with lung cancer: a systematic review. Thorax. 2009;64(9):749-756.
PubMed   |  Link to Article
Korsgaard  M, Pedersen  L, Sørensen  HT, Laurberg  S.  Delay of treatment is associated with advanced stage of rectal cancer but not of colon cancer. Cancer Detect Prev. 2006;30(4):341-346.
PubMed   |  Link to Article
Richards  MA, Westcombe  AM, Love  SB, Littlejohns  P, Ramirez  AJ.  Influence of delay on survival in patients with breast cancer: a systematic review. Lancet. 1999;353(9159):1119-1126.
PubMed   |  Link to Article
Richards  MA, Smith  P, Ramirez  AJ, Fentiman  IS, Rubens  RD.  The influence on survival of delay in the presentation and treatment of symptomatic breast cancer. Br J Cancer. 1999;79(5-6):858-864.
PubMed   |  Link to Article
McLaughlin  JM, Anderson  RT, Ferketich  AK, Seiber  EE, Balkrishnan  R, Paskett  ED.  Effect on survival of longer intervals between confirmed diagnosis and treatment initiation among low-income women with breast cancer. J Clin Oncol. 2012;30(36):4493-4500.
PubMed   |  Link to Article
Fradet  Y, Aprikian  A, Dranitsaris  G, Siemens  R, Tsihlias  J, Fleshner  N; Canadian Surgical Wait Times (SWAT) Initiative.  Does prolonging the time to bladder cancer surgery affect long-term cancer control? a systematic review of the literature. Can J Urol. 2006;13(suppl 3):37-47.
PubMed
Bishop  MC.  The dangers of a long urological waiting list. Br J Urol. 1990;65(5):433-440.
PubMed   |  Link to Article
Epstein  E, Bragg  K, Linden  G.  Biopsy and prognosis of malignant melanoma. JAMA. 1969;208(8):1369-1371.
PubMed   |  Link to Article
Snow  SN, Mohs  FE, Oriba  HA, Dudley  CM, Leverson  G, Hetzer  M.  Cutaneous malignant melanoma treated by Mohs surgery: review of the treatment results of 179 cases from the Mohs Melanoma Registry. Dermatol Surg. 1997;23(11):1055-1060.
PubMed   |  Link to Article
Chin-Lenn  L, Murynka  T, McKinnon  JG, Arlette  JP.  Comparison of outcomes for malignant melanoma of the face treated using Mohs micrographic surgery and wide local excision. Dermatol Surg. 2013;39(11):1637-1645.
PubMed   |  Link to Article
Bricca  GM, Brodland  DG, Ren  D, Zitelli  JA.  Cutaneous head and neck melanoma treated with Mohs micrographic surgery. J Am Acad Dermatol. 2005;52(1):92-100.
PubMed   |  Link to Article
National Cancer Institute. Surveillance, Epidemiology, and End Results Program fact sheet.http://appliedresearch.cancer.gov/seermedicare/overview/seermed_fact_sheet.pdf. Published December 2013. Accessed December 18, 2014.
Potosky  AL, Riley  GF, Lubitz  JD, Mentnech  RM, Kessler  LG.  Potential for cancer related health services research using a linked Medicare–tumor registry database. Med Care. 1993;31(8):732-748.
PubMed   |  Link to Article
Warren  JL, Klabunde  CN, Schrag  D, Bach  PB, Riley  GF.  Overview of the SEER-Medicare data: content, research applications, and generalizability to the United States elderly population. Med Care. 2002;40(8)(suppl):IV-3–IV-18.
PubMed
Ma  X, Wang  R, Long  JB,  et al.  The cost implications of prostate cancer screening in the Medicare population. Cancer. 2014;120(1):96-102.
PubMed   |  Link to Article
National Cancer Institute. Surveillance, Epidemiology, and End Results program.http://seer.cancer.gov/about/factsheets/SEER_brochure.pdf. Published March 2012. Accessed December 18, 2014.
Simone  JV, Hewitt  M. Enhancing Data Systems to Improve the Quality of Cancer Care. Washington, DC: National Academies Press; 2000.
Centers for Medicare and Medicaid Services. Medicare enrollment and claim submission guidelines.https://www.cms.gov/Outreach-and-Education/Medicare-Learning-Network-MLN/MLNProducts/downloads/MedicareClaimSubmissionGuidelines-ICN906764.pdf. Published August 2014. Accessed December 18, 2014.
Stryer  DB, Weinick  RM, Clancy  CM.  Reducing racial and ethnic disparities in health care. Health Serv Res. 2002;37(5):xv-xxvi.
PubMed   |  Link to Article
Logan  JL.  Disparities in influenza immunization among US adults. J Natl Med Assoc. 2009;101(2):161-166.
PubMed
Blewett  LA, Johnson  PJ, Lee  B, Scal  PB.  When a usual source of care and usual provider matter: adult prevention and screening services. J Gen Intern Med. 2008;23(9):1354-1360.
PubMed   |  Link to Article
Hoffman  C, Paradise  J.  Health insurance and access to health care in the United States. Ann N Y Acad Sci. 2008;1136:149-160.
PubMed   |  Link to Article
Starfield  B, Shi  L, Macinko  J.  Contribution of primary care to health systems and health. Milbank Q. 2005;83(3):457-502.
PubMed   |  Link to Article
Elixhauser  A, Steiner  C, Harris  DR, Coffey  RM.  Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8-27.
PubMed   |  Link to Article
National Cancer Institute. SEER training modules.http://training.seer.cancer.gov/melanoma/abstract-code-stage/staging.html. Accessed December 18, 2014.
DeMott  K.  Healthcare practices vary widely from town to town: regional Dartmouth Atlas. Health Syst Lead. 1997;4(1):2-3.
PubMed
Health Resources and Services Administration. Area health resources files. http://ahrf.hrsa.gov/. Accessed December 18, 2014.
Ingram  DD, Franco  SJ.  NCHS urban-rural classification scheme for counties. Vital Health Stat 2. 2012;(154):1-65.
PubMed
Bouwmeester  W, Twisk  JW, Kappen  TH, van Klei  WA, Moons  KG, Vergouwe  Y.  Prediction models for clustered data: comparison of a random intercept and standard regression model. BMC Med Res Methodol. 2013;13:19. doi:10.1186/1471-2288-13-19.
PubMed   |  Link to Article
McLaughlin  JM, Fisher  JL, Paskett  ED.  Marital status and stage at diagnosis of cutaneous melanoma: results from the Surveillance Epidemiology and End Results (SEER) program, 1973-2006. Cancer. 2011;117(9):1984-1993.
PubMed   |  Link to Article
Pollack  LA, Li  J, Berkowitz  Z,  et al.  Melanoma survival in the United States, 1992 to 2005. J Am Acad Dermatol. 2011;65(5)(suppl 1):S78-S86.
PubMed   |  Link to Article
Jemal  A, Saraiya  M, Patel  P,  et al.  Recent trends in cutaneous melanoma incidence and death rates in the United States, 1992-2006. J Am Acad Dermatol.2011;65(5)(suppl 1):S17-25.e1-3. doi:10.1016/j.jaad.2011.04.032.
PubMed   |  Link to Article
Richard  MA, Grob  JJ, Avril  MF,  et al.  Delays in diagnosis and melanoma prognosis, II: the role of doctors. Int J Cancer. 2000;89(3):280-285.
PubMed   |  Link to Article

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