Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2025 Mar 1.
Published in final edited form as: Gynecol Oncol. 2024 Jan 22;182:141–147. doi: 10.1016/j.ygyno.2024.01.004

Regionalizing Ovarian Cancer Cytoreduction to High-Volume Centers and the Impact on Patient Travel in New York State

Ryan M Kahn a, Xiaoyue Ma b, Sushmita Gordhandas a, Effi Yeoshoua a, Ryan J Ellis c, Xiuling Zhang d, Emeline M Aviki a, Nadeem R Abu-Rustum a, Ginger J Gardner a, Yukio Sonoda a, Oliver Zivanovic a, Kara Long Roche a, Elizabeth Jewell a, Thomas Boerner a, Dennis S Chi a
PMCID: PMC10960664  NIHMSID: NIHMS1962983  PMID: 38262237

Abstract

Objective:

To evaluate the theoretical impact of regionalizing cytoreductive surgery for ovarian cancer (OC) to high-volume facilities on patient travel.

Methods:

We retrospectively identified patients with OC who underwent cytoreduction between 1/1/2004–12/31/2018 from the New York State Cancer Registry and Statewide Planning and Research Cooperative System. Hospitals were stratified by low-volume (<21 cytoreductive surgical procedures for OC annually) and high-volume centers (≥21 procedures annually). A simulation was performed; outcomes of interest were driving distance and time between the centroid of the patient’s residence zip code and the treating facility zip code.

Results:

Overall, 60,493 patients met inclusion criteria. Between 2004–2018, 210 facilities were performing cytoreductive surgery for OC in New York; 159 facilities (75.7%) met low-volume and 51 (24.3%) met high-volume criteria. Overall, 10,514 patients (17.4%) were treated at low-volume and 49,979 (82.6%) at high-volume facilities. In 2004, 78.2% of patients were treated at high-volume facilities, which increased to 84.6% in 2018 (P<.0001). Median travel distance and time for patients treated at high-volume centers was 12.2 miles (IQR, 5.6–25.5) and 23.0 minutes (IQR, 15.2–37.0), and 8.2 miles (IQR, 3.7–15.9) and 16.8 minutes (IQR, 12.4–26.0) for patients treated at low-volume centers. If cytoreductive surgery was centralized to high-volume centers, median distance and time traveled for patients originally treated at low-volume centers would be 11.2 miles (IQR, 3.8–32.3; P<.001) and 20.2 minutes (IQR, 13.6–43.0; P<.001).

Conclusions:

Centralizing cytoreductive surgery for OC to high-volume centers in New York would increase patient travel burden by negligible amounts of distance and time for most patients.

Keywords: ovarian cancer, cytoreduction, high-volume centers, patient travel

Introduction

For women with advanced ovarian cancer, achieving complete gross resection (CGR) of all visible disease at time of primary cytoreductive surgery is associated with the best survival outcomes [1, 2]. As the goal of cytoreductive surgery has evolved, from attaining minimal residual disease to now total macroscopic tumor clearance, the role of complex surgery has become increasingly important [3–7]. The facility where women with a gynecologic malignancy undergo surgery can impact both disease-free survival and overall survival, as prior studies have shown that patients who undergo surgery at high-volume centers have a higher likelihood of CGR following primary debulking surgery for advanced-stage ovarian cancer [8, 9]. Likewise for cervical cancer, surgical volume of centers has been shown to be an independent prognostic factor of disease-free survival, with higher volume of radical hysterectomies associated with improved disease-free survival [10]. An association between surgical volume and outcomes has also been shown for the management of colorectal, esophageal, and pancreatic cancers [11–13]. Findings in support of the volume-outcome relationship have led to proposals to centralize complex surgical procedures to high-volume centers, defined as regionalization through financial incentives or regulatory means to promote the use of high-volume centers for certain types of care [14].

Despite evidence that women with ovarian cancer who seek treatment at high-volume centers experience improved outcomes compared to women treated at low-volume centers, quantifying the burden of travel for patients is not well described. The European Society of Gynaecological Oncology (ESGO) has made significant efforts towards developing a 2-tier accreditation system for surgical centers that treat ovarian cancer [15, 16]. However, to further assess the impact of implementing surgical volume standards and centralizing cytoreductive surgery for ovarian cancer, a better understanding of the travel burden on patients is necessary. This study aims to evaluate the theoretical impact of centralizing cytoreductive surgery to high-volume facilities on travel distance and time for patients with ovarian cancer in New York State.

Methods

Patient data source

In this retrospective cohort study, patients with ovarian cancer who underwent surgical cytoreduction between January 1, 2004, and December 31, 2018, were identified from the New York State Cancer Registry (NYSCR) and the Statewide Planning and Research Cooperative System (SPARCS). The NYSCR is a database that tracks patient, tumor, and treatment data for all cases of cancer in New York State. The SPARCS is an all-payer database that compiles patient, clinician, hospital, and in treatment data for all inpatient stays and hospital discharges in New York State. Similar methodology has been used in colorectal cancer studies [17–19]. Patients with ovarian, fallopian tube, or primary peritoneal cancer were identified from NYSCR and SPARCS using procedure codes from the International Classification of Diseases, Nineth Revision (ICD-9; codes 183.0, 183.2) and the ICD, Tenth Revision (ICD-10; codes C56.1, C56.2, 56.9, C78.6). Patients who underwent cytoreductive surgery for ovarian cancer were identified using ICD-9 and ICD-10 procedure codes (listed in Supplemental Table S1) for the associated diagnosis.

Available data included patient age, zip code of residence, treatment data, and diagnoses, as well as treating facility identifiers and zip code of the treating facility. In our study, we used cutoffs from a 2010 National Cancer Database (NCDB) study by Bristow et al. In their study of more than 45,000 patients with ovarian cancer, overall survival was significantly correlated with hospital case volume, with a high-volume cutoff of ≥21 cytoreductive surgical procedures for ovarian cancer per year [9]. Hospital volume was stratified by low volume (<21 cytoreductive surgical procedures for ovarian cancer per year averaged from 2004 to 2018) and high volume (≥21 cytoreductive surgical procedures for ovarian cancer per year averaged from 2004 to 2018), as this threshold has been demonstrated to show a difference in patient outcomes [9]. Patients who were diagnosed with ovarian, fallopian tube, or primary peritoneal cancer and underwent cytoreductive surgery in a New York State hospital between January 1, 2004, and December 31, 2018, were included. Patients were excluded if the zip code of residence, zip code of treating facility, or distance between the residence and treating facility could not be identified.

Geomapping software

Distance between patient residence and treatment facility was calculated as the driving distance between the centroid of the residence zip code and the treatment facility zip code. Geographic distance and travel time were measured using CDXTech ZipStream™ [20], which is a publicly accessible software used to geocode, reverse-geocode, and calculate driving distance and time. Route optimization technology from CDXTech ZipStream™ Geographic Access Analysis was used to calculate the minimal distance and time between zip codes.

Statistical analysis

Statistical tests and analyses were performed using SAS version 9.4 (SAS Institute, USA) and Stata software version 17.0 (StataCorp, College Station, TX). Distances traveled and travel times were expressed as medians with interquartile ranges (IQRs). The Wilcoxon rank sum test was performed to compare median distance traveled, median travel time, and age between patients treated in high-volume centers and low-volume centers and between different years. The Wilcoxon signed rank test was performed to compare the improvement and difference in travel time if participants were centralized to high-volume centers. The Cochran-Armitage test for trend was performed to test if there was a clear trend in the increased proportion of patients treated in high-volume hospitals between 2004 and 2018. Use of SPARCS data was approved by a Data Protection Review Board. Institutional Review Board approval was obtained.

Results

Patient and facility characteristics

A total of 74,226 patients were initially identified; 13,733 patients were excluded due to missing zip code of residence, missing treating facility information, or inability to calculate the distance between residence and treatment facility. A total of 60,493 patients met inclusion criteria for investigation (Figure 1). The median age overall was 62 years (IQR, 53–71 years). The median age of patients traveling to low-volume centers was 64 years (IQR, 54–74 years), and 61 years (IQR, 52–71 years) for patients traveling to high-volume centers (P<.001). Among all 60,493 patients, 56,723 (93.8%) had a residence zip code within New York State and 3770 (6.2%) had a residence zip code outside of New York State.

Figure 1.

Figure 1.

Open in a new tab

Flow diagram of the patient selection process

Between 2004 and 2018, 210 facilities were performing cytoreductive surgery for ovarian cancer in New York State; 159 (75.7%) met criteria for a low-volume center and 51 (24.3%) met criteria for a high-volume center. Between 2004 and 2018, 17.4% (10,514 of 60,493) of patients underwent cytoreductive surgery for ovarian cancer at low-volume centers and 82.6% (49,979 of 60,493) of patients underwent cytoreductive surgery for ovarian cancer at high-volume centers. In 2004, 78.2% (3153 of 4032) of patients underwent cytoreductive surgery for ovarian cancer at high-volume centers, and in 2018, 84.6% (3180 of 3759) of patients underwent surgery at high-volume centers (P<.0001) (Table 1).

Table 1.

Number of patients in our study population treated at low-volume centers and high-volume centers, stratified by year of surgery

Year treated No. of patients (%)
Total Low-volume center High-volume center
2004 4032 879 (21.8) 3153 (78.2)
2005 4081 806 (19.8) 3275 (80.2)
2006 4184 818 (19.6) 3366 (80.4)
2007 4079 742 (18.2) 3337 (81.8)
2008 4085 773 (18.9) 3312 (81.1)
2009 4093 673 (16.4) 3420 (83.6)
2010 4298 704 (16.4) 3594 (83.6)
2011 4161 678 (16.3) 3483 (83.7)
2012 4271 724 (17.0) 3547 (83.0)
2013 4279 674 (15.8) 3605 (84.2)
2014 3834 646 (16.8) 3188 (83.2)
2015 3881 603 (15.5) 3278 (84.5)
2016 3807 610 (16.0) 3197 (84.0)
2017 3649 605 (16.6) 3044 (83.4)
2018 3759 579 (15.4) 3180 (84.6)
Total 60,493 10,514 (17.4) 49,979 (82.6)
Open in a new tab

Overall travel distance and time

Overall, the median travel distance was 11.1 miles (IQR, 5.2–23.2 miles). The median travel distance was 11.4 miles (IQR, 5.2–23.2 miles) in 2004 and 11.4 miles (IQR, 5.2–24.0 miles) in 2018 (P=.81). The median travel time was 21.8 minutes (IQR, 14.6–34.9 minutes). The median travel time was 21.7 minutes (IQR, 14.6–34.9 minutes) in 2004 and 21.9 minutes (IQR, 14.6–35.9 minutes) in 2018 (P=.36). A total of 11.1% (6697 of 60,493) of patients traveled ≥50 miles, and 3.9% (2372 of 60,493) traveled ≥100 miles; 10.0% (6049 of 60,493) of patients traveled ≥60 minutes, and 2.3% (1409 of 60,493) traveled ≥120 minutes.

Travel distance and time by high-volume and low-volume centers

The median travel distance was 12.2 miles (IQR, 5.6–25.2 miles) to high-volume centers and 8.2 miles (IQR, 3.7–15.9 miles) to low-volume centers (P<.001). The median travel time was 23.0 minutes (IQR, 15.2–37.0 minutes) to high-volume centers and 16.8 minutes (IQR, 12.4–26.0 minutes) to low-volume centers (P<.0001). The median travel distance to high-volume centers was 12.5 miles (IQR, 5.7–26.6 miles) in 2004 and 12.4 miles (IQR, 5.6–25.6 miles) in 2018 (P=.89). The median travel time to high-volume centers was 23.1 minutes (IQR, 15.3–38.0 minutes) in 2004 and 23.2 minutes (IQR, 15.1–38.3 minutes) in 2018 (P=.81). The median travel distance to low-volume centers was 8.5 miles (IQR, 3.7–17.9 miles) in 2004 and 7.7 miles (IQR, 3.7–14.9 miles) in 2018 (P=.11). The median travel time to low-volume centers was 17.0 minutes (IQR, 12.4–26.6 minutes) in 2004 and 16.4 minutes (IQR, 12.3–24.3 minutes) in 2018 (P=.24) (Figure 2A, 2B).

Figure 2.

Figure 2.

Open in a new tab

(A) Bar graph of median travel distance (miles) by year stratified by patients who underwent ovarian cancer cytoreductive surgery at high-volume centers, low-volume centers, and for patients who underwent surgery at low-volume centers if centralized to the nearest high-volume center. (B) Bar graph of median travel time (minutes) by year stratified by patients who underwent ovarian cancer cytoreductive surgery at high-volume centers, low-volume centers, and for patients who underwent surgery at low-volume centers if centralized to the nearest high-volume center

A total of 12.5% (6227 of 49,979) of patients traveled ≥50 miles to high-volume centers, and 4.5% (470 of 10,514) traveled ≥50 miles to low-volume centers (P<.01). A total of 4.4% (2193 of 49,979) of patients traveled ≥100 miles to high-volume centers, and 1.7% (179 of 10,514) traveled ≥100 miles to low-volume centers (P<.01). A total of 11.2% (5574 of 49,979) of patients traveled ≥60 minutes to high-volume centers, and 4.5% (475 of 10,514) traveled ≥60 minutes to low-volume centers (P<.01); 2.6% (1288 of 49,979) of patients traveled ≥120 minutes to high-volume centers, and 1.2% (121 of 10,514) traveled ≥120 minutes to low-volume centers (P<.01).

Travel distance and time if care was centralized to high-volume centers

If all cytoreductive surgical procedures for ovarian cancer in New York State were centralized to the 51 high-volume centers between 2004 and 2018 (Figure 3A, 3B), the median travel distance to the nearest high-volume center for patients previously traveling to low-volume centers would have been 11.2 miles (IQR, 3.8–32.3 miles), with a median travel time of 20.2 minutes (IQR, 13.6–43.0 minutes) (Table 2).

Figure 3.

Figure 3.

Open in a new tab

(A) A map of all 210 centers performing ovarian cancer cytoreductive surgery in New York State from 2004 to 2018. (B) A map of all 51 high-volume centers in New York State performing ovarian cancer cytoreductive surgery from 2004 to 2018 (courtesy of easymapmaker.com)

Table 2.

Median travel distance (miles) and median travel time (minutes) for the study population by year for all patients, as well as stratified by patients who underwent ovarian cancer cytoreductive surgery at high-volume centers, low-volume centers, and for patients who underwent surgery at low-volume centers if centralized to the nearest high-volume center

OVERALL HIGH-VOLUME CENTERS LOW-VOLUME CENTERS CENTRALIZATION FROM LOW- TO HIGH-VOLUME CENTERS
Median Distance Traveled Median Time Traveled Median Distance Traveled Median Time Traveled Median Distance Traveled Median Time Traveled Median Distance Traveled Median Time Traveled
2004 11.4 (5.2–23.2) 21.7 (14.6–34.9) 12.5 (5.7–26.6) 23.1 (15.3–38.0) 8.5 (3.7–17.9) 17.0 (12.4–26.6) 10.8 (3.9–34.0) 20.6 (13.2–44.4)
2005 11.0 (5.0–23.6) 21.3 (14.3–34.4) 11.8 (5.3–25.5) 22.4 (14.9–36.5) 8.7 (4.0–17.4) 17.3 (12.4–28.1) 10.6 (3.9–34.3) 19.9 (14.0–44.2)
2006 10.7 (5.0–23.5) 21.1 (14.4–35.1) 11.3 (5.2–24.9) 22.2 (14.9–37.0) 8.9 (4.3–17.7) 17.6 (12.7–27.7) 11.9 (3.8–37.2) 20.8 (14.0–45.3)
2007 10.8 (5.2–22.2) 21.9 (14.5–34.6) 12.3 (5.6–24.8) 23.1 (15.3–35.8) 7.7 (3.6–15.8) 16.4 (12.2–25.4) 10.5 (4.5–29.3) 19.9 (13.2–45.3)
2008 11.3 (5.3–23.2) 21.9 (14.6–34.6) 12.5 (5.8–25.1) 23.1 (15.1–36.7) 8.2 (3.7–16.4) 16.9 (12.7–26.3) 12.2 (4.4–33.7) 20.9 (14.4–44.8)
2009 10.8 (5.1–21.9) 21.1 (14.4–32.4) 11.6 (5.4–23.5) 22.3 (15.0–33.9) 7.7 (3.6–15.7) 16.6 (11.5–26.2) 11.0 (3.6–28.2) 20.7 (13.0–41.3)
2010 11.3 (5.3–23.6) 21.4 (14.4–35.2) 12.3 (5.4–25.4) 22.4 (14.8–37.2) 8.5 (4.1–16.0) 16.9 (12.7–26.2) 13.3 (4.0–34.4) 21.9 (14.3–44.0)
2011 11.3 (5.3–23.6) 22.3 (14.6–35.0) 12.6 (5.7–27.1) 23.7 (15.2–38.1) 7.5 (3.4–14.5) 16.2 (12.2–25.1) 10.2 (3.5–28.9) 19.8 (13.0–40.2)
2012 11.1 (5.3–23.4) 21.7 (14.6–35.0) 12.3 (5.6–24.9) 23.1 (15.3–38.3) 8.2 (3.5–15.8) 16.9 (12.1–25.3) 13.5 (3.4–34.2) 21.4 (13.5–43.6)
2013 11.4 (5.5–24.4) 22.2 (14.7–35.7) 12.4 (6.0–27.1) 23.3 (15.5–37.7) 7.8 (3.3–17.1) 16.9 (12.4–27.2) 13.3 (4.1–38.5) 23.0 (13.6–50.7)
2014 11.1 (5.2–23.2) 21.9 (14.6–34.9) 12.4 (5.9–24.9) 23.2 (15.6–37.0) 7.4 (3.3–15.5) 16.0 (11.6–24.8) 9.1 (3.5–30.7) 19.7 (13.0–42.0)
2015 11.1 (5.0–23.1) 22.0 (14.6–35.2) 12.1 (5.3–25.8) 23.1 (15.2–36.7) 8.5 (3.5–15.3) 17.0 (12.6–25.2) 12.8 (3.7–28.6) 21.5 (14.4–40.0)
2016 11.0 (5.1–22.2) 21.4 (14.4–33.9) 11.9 (5.5–23.8) 22.9 (15.0–36.4) 7.7 (3.5–14.1) 16.4 (11.7–24.0) 10.3 (3.7–25.2) 19.8 (13.5–37.4)
2017 11.9 (5.3–23.1) 22.4 (14.9–35.6) 12.7 (5.7–25.5) 23.5 (15.6–37.7) 8.9 (3.8–17.0) 17.1 (12.8–26.9) 12.5 (3.5–34.5) 20.1 (13.5–44.5)
2018 11.4 (5.2–24.0) 21.9 (14.6–35.9) 12.4 (5.6–25.6) 23.2 (15.1–38.3) 7.7 (3.7–14.9) 16.4 (12.3–24.3) 9.3 (3.8–25.3) 18.8 (13.9–40.8)
TOTAL 11.1 (5.2–23.2) 21.8 (14.6–34.9) 12.2 (5.6–25.2) 23.0 (15.2–37.0) 8.2 (3.7–15.9) 16.8 (12.4–26.0) 11.2 (3.8–32.3) 20.2 (13.6–43.0)
Open in a new tab

A total of 13.6% (1429 of 10,514) of patients would be ≥50 miles from the nearest high-volume center in New York State; 2.8% (296 of 10,514) of patients would be ≥100 miles from the nearest high-volume center in New York State. A total of 12.8% (1341 of 10,514) of patients would be ≥60 minutes from the nearest high-volume center in New York State; 2.4% (257 of 10,514) of patients would be ≥120 minutes from the nearest high-volume center in New York State.

Discussion

Our population-based study aimed to evaluate the theoretical impact of regionalizing cytoreductive surgery for ovarian cancer to high-volume facilities on patient travel distance and time in a highly urbanized state. Using New York State data from 2004 to 2018 for 60,493 patients, we found 82.6% of patients underwent cytoreductive surgery for ovarian cancer at high-volume centers and 17.4% of patients underwent surgery at low-volume centers. The percentage of patients with ovarian cancer who underwent cytoreductive surgery at high-volume centers significantly increased over time, from 78.2% in 2004 to 84.6% in 2018. Patients were significantly more likely to travel further to high-volume centers for their surgery, with a median distance of 12.2 miles (median travel time, 23.0 minutes), compared to low-volume centers, with a median distance of 8.2 miles (median travel time, 16.8 minutes). If all cytoreductive surgical procedures for ovarian cancer in New York State were centralized to the 51 high-volume centers, the median travel distance of patients who had undergone cytoreductive surgery at low-volume centers would increase to 11.2 miles (median travel time, 20.2 minutes), with 12.8% of patients requiring a travel time ≥1 hour and 2.4% of patients requiring a travel time ≥2 hours.

It is widely established that CGR of disease at time of cytoreduction for ovarian cancer has been strongly correlated with improved survival outcomes [1, 2, 21]. Achieving CGR depends on various factors, including extent of tumor bulk, bowel involvement, and patient selection. Many gynecologic oncologists have implemented changes to surgical practice, including diversifying skillsets and participating in multidisciplinary care team approaches, as the role of complex surgery for advanced-stage ovarian cancer has become increasingly important [6, 21]. A 2006 retrospective study by Aletti et al investigated the association between tendency of the operating surgeon to perform comprehensive surgical procedures (defined as performing comprehensive procedures in more vs less than 50% of surgical procedures) and ovarian cancer outcomes. The authors found surgeons who performed comprehensive procedures in more than 50% of cytoreductive surgical procedures had a greater percentage of achieving CGR, as well as increased median survival among patients, compared to surgeons who performed comprehensive procedures in less than 50% of cytoreductive surgical procedures [22]. Several studies have since demonstrated that where patients with ovarian cancer undergo cytoreductive surgery affects outcomes. Studies from the United Kingdom, Austria, Finland, Denmark, and the United States have all demonstrated an association between increasing surgical volume of cytoreduction for ovarian cancer and a greater probability of obtaining optimal resection (≤1 cm of residual disease) and CGR [8, 23–26].

The benefits of complex cytoreductive surgery at high-volume centers has garnered widespread support for the regionalization of surgical care [27, 28]. However, regionalization does not occur in a vacuum, and ramifications of this approach must be considered [29]. In our study, 13.6% of patients (1429 of 10,514) would be ≥50 miles from the nearest high-volume center in New York State. Centralization of surgical care could have added difficulty for a substantial proportion of this patient population, and it would also likely have greater implications regarding the fragmentation of care. It has been hypothesized that an additional burden of increased travel could lead to negative effects of fragmentation of care and may potentially reduce patient access to care [29]. Our results demonstrate negligible increases in travel distance and time, with a median increase of 3.0 miles and 3.4 minutes, respectively, for patients with ovarian cancer in New York State to access high-volume centers. Given these insignificant increases, potential negative effects of fragmentation of care from travel burden among this population likely would be mitigated but certainly warrant future investigation.

Despite the known advantages of regionalizing surgery to high-volume centers, whether patients prefer to travel to regional centers remains controversial. It has been hypothesized that patients choose to undergo care at low-volume centers based on disparities in access to care, such as race, insurance status, and comorbidity burden [30, 31]. A study by Finlayson et al of 100 patients who were awaiting elective surgery explored how patients view the tradeoff between lower operative mortality risk and the benefits of local care [32]. Using a gamble utility assessment technique, their survey showed if the local operative mortality risk was 6% (which was twice the determined regional risk of 3%), 45% of patients would still prefer local surgery. If the local risk was increased to 4-fold higher than the regional risk, 23% of patients would still prefer surgery at a local center, and if the local risk was 6-fold higher than the regional risk, 18% of patients would still favor local surgery. The authors concluded patient perspectives regarding proximity to personal support systems, continuity of care with familiar physicians, and avoidance of practical problems associated with traveling for specialized care also informed patients’ decision-making of where to undergo care [32].

In addition to travel distance, another barrier to implementing policies that support the regionalization of oncologic care has been suboptimal healthcare quality reporting and a lack of public transparency. Access to comparative information on hospitals’ quality of cancer care is limited, and public access to hospital volume for certain types of care is nearly non-existent [33], which has led to a lack of patient-preference metrics to inform healthcare decisions [34, 35]. A 2020 study by Ellis et al sought to determine factors individuals value when making decisions about where to receive care [36]. They found a relative indifference in how patients viewed measures of healthcare quality that are commonly thought to be important, such as complication and death rates. In addition, they found more than 60% of patients decide where to receive care via research through simple online searches and exploring hospital websites. These findings demonstrate patients often consider factors unrelated to hospital rankings and quality measures when deciding where to receive care [36]. As a result, appropriate standards of healthcare quality remain controversial, which may make it difficult for patients to determine whether reported healthcare quality data are truthful, timely, and transparent [34, 37]. We believe our results provide important information to improve transparency regarding patient travel patterns for ovarian cancer treatment at the state level, which can be used to inform future policy and accreditation planning. Another important perceived barrier is whether high-volume centers have the capacity (resources, facility, staffing, etc.) to accommodate an influx of patients. Future proposals and policies for implementation would need to account for this increase in volume.

Although our study has vital implications for policy formation, it is not without limitations. Our study population was limited to patients who underwent cytoreductive surgery in New York State, which likely has different population patterns and hospital structures compared to other states. We did not exclude the 6% of patients whose zip code of residence was outside of New York State, as we felt it was important to analyze the theoretical impact that regionalizing cytoreductive surgery would have on these patients as well. In addition, we did not have data from facilities in neighboring states and were therefore unable to determine whether there were closer high-volume centers for patients near the state border. However, such data would have likely resulted in even shorter travel distances and times than reported. Another limitation is that our data set did not include patients’ exact addresses, and thus we could not determine the true driving distance from residence to treatment facility. The centroid of residence zip code, however, likely served as an accurate surrogate given our large study population (>60,000 patients), which likely mitigated any differences for patients closer to and further from the centroid. A limitation of utilizing CDXTech ZipStream™ for our analysis is that it assumes the patient would be traveling by car; however, it does not take into account the burden of using public transportation or rideshare, which could also bias total travel time and distance. An additional limitation is that our analysis model does not consider that low-volume centers could combine to create new high-volume centers.

This retrospective study provides important insight into how centralizing cytoreductive surgery for ovarian cancer to high-volume centers could impact travel for patients. Our results demonstrate valuable information that can be used to better educate patients and enable them to make more informed decisions regarding the treatment-travel tradeoff. Our findings suggest that if cytoreductive surgical procedures for ovarian cancer were centralized to high-volume centers in New York State, the additional travel burden would increase by negligible amounts of distance and time for most patients. Understanding the impact of travel on optimizing cancer care may be useful for future state planning and policy decision-making.

Supplementary Material

1

Highlights.

  • The impact on patient travel from ovarian cancer surgery regionalization to high-volume centers has not been studied

  • Centralizing ovarian cancer surgery in New York State would increase patient travel by negligible distance and time

  • These findings could have future implications for patient education and health policy on the regionalization of care

Funding

This research was funded in part by the National Institutes of Health/National Cancer Institute Cancer Center Support Grant P30 CA008748.

Footnotes

Conflicts of Interest

Outside the submitted work, D. Chi reports personal fees from Apyx Medical, Verthermia Inc., Biom ‘Up, and AstraZeneca, as well as recent or current stock/options ownership of Apyx Medical, Verthemia, Intuitive Surgical, Inc., TransEnterix, Inc., Doximity, Moderna, and BioNTech SE. N.R. Abu-Rustum reports research funding paid to the institution by GRAIL. E.L. Jewell reports personal fees from Covidien/Medtronic. K. Long Roche reports travel support from Intuitive Surgical. The other authors do not have potential conflicts of interest to declare.

Consent Statement

This retrospective study was approved by the Institutional Review Boards at Memorial Sloan Kettering Cancer Center and the New York State Department, and all patients provided written consent.

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

References

  • 1.Chi DS et al. , Improved progression-free and overall survival in advanced ovarian cancer as a result of a change in surgical paradigm, Gynecol. Oncol. 114 (2009) 26–31. [DOI] [PubMed] [Google Scholar]
  • 2.Chang SJ, Hodeib M, Chang J, and Bristow RE, Survival impact of complete cytoreduction to no gross residual disease for advanced-stage ovarian cancer: a meta-analysis. Gynecol Oncol, 2013. 130(3): p. 493–8. [DOI] [PubMed] [Google Scholar]
  • 3.Tseng JH, et al. , Continuous improvement in primary Debulking surgery for advanced ovarian cancer: Do increased complete gross resection rates independently lead to increased progression-free and overall survival? Gynecol Oncol, 2018. 151(1): p. 24–31. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Cummins C, et al. Investigating the Impact of Ultra-Radical Surgery on Survival in Advanced Ovarian Cancer Using Population-Based Data in a Multicentre UK Study. Cancers, 2022. 14, DOI: 10.3390/cancers14184362. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Sundar S, et al. , Quality of life from cytoreductive surgery in advanced ovarian cancer: Investigating the association between disease burden and surgical complexity in the international, prospective, SOCQER-2 cohort study. BJOG: An International Journal of Obstetrics & Gynaecology, 2022. 129(7): p. 1122–1132. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Kahn RM, et al. , Intrathoracic surgery as part of primary cytoreduction for advanced ovarian cancer: Going to the next level - A Memorial Sloan Kettering Cancer Center study. Gynecol Oncol, 2023. 170: p. 46–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Fotopoulou C, Intrathoracic surgery as part of primary cytoreduction for advanced ovarian cancer: The evolution of a “pelvic” surgeon. Gynecol Oncol, 2023. 170: p. A1–a3. [DOI] [PubMed] [Google Scholar]
  • 8.Nasioudis D, et al. , Impact of hospital surgical volume on complete gross resection (CGR) rates following primary debulking surgery for advanced stage epithelial ovarian carcinoma. Gynecol Oncol, 2019. 154(2): p. 401–404. [DOI] [PubMed] [Google Scholar]
  • 9.Bristow RE, Palis BE, Chi DS, and Cliby WA, The National Cancer Database report on advanced-stage epithelial ovarian cancer: Impact of hospital surgical case volume on overall survival and surgical treatment paradigm. Gynecologic Oncology, 2010. 118(3): p. 262–267. [DOI] [PubMed] [Google Scholar]
  • 10.Bizzarri N, et al. , Association of Hospital Surgical Volume With Survival in Early-Stage Cervical Cancer Treated With Radical Hysterectomy. Obstet Gynecol, 2023. 141(1): p. 207–214. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Xu Z, et al. , Is the Distance Worth It? Patients With Rectal Cancer Traveling to High-Volume Centers Experience Improved Outcomes. Dis Colon Rectum, 2017. 60(12): p. 1250–1259. [DOI] [PubMed] [Google Scholar]
  • 12.Speicher PJ, et al. , Traveling to a High-volume Center is Associated With Improved Survival for Patients With Esophageal Cancer. Ann Surg, 2017. 265(4): p. 743–749. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Lidsky ME, et al. , Going the Extra Mile: Improved Survival for Pancreatic Cancer Patients Traveling to High-volume Centers. Ann Surg, 2017. 266(2): p. 333–338. [DOI] [PubMed] [Google Scholar]
  • 14.Epstein AM, Volume and Outcome — It Is Time to Move Ahead. New England Journal of Medicine, 2002. 346(15): p. 1161–1164. [DOI] [PubMed] [Google Scholar]
  • 15.Querleu D, et al. , European society of gynaecologic oncology quality indicators for advanced ovarian cancer surgery. International Journal of Gynecological Cancer, 2016. 26(7): p. 1354–1363. [DOI] [PubMed] [Google Scholar]
  • 16.Fotopoulou C, Concin N, Planchamp F, et al. , Quality indicators for advanced ovarian cancer surgery from the European Society of Gynaecological Oncology (ESGO): 2020 update, Int. J. Gynecol. Cancer 30 (4) (2020. Apr) 436–440 [DOI] [PubMed] [Google Scholar]
  • 17.Becerra AZ, et al. , Variation in Delayed Time to Adjuvant Chemotherapy and Disease-Specific Survival in Stage III Colon Cancer Patients. Ann Surg Oncol, 2017. 24(6): p. 1610–1617. [DOI] [PubMed] [Google Scholar]
  • 18.Justiniano CF, et al. , Hospital and surgeon variation in positive circumferential resection margin among rectal cancer patients. Am J Surg, 2019. 218(5): p. 881–886. [DOI] [PubMed] [Google Scholar]
  • 19.Xu Z, et al. , Centralizing Rectal Cancer Surgery: What Is the Impact of Travel on Patients? Dis Colon Rectum, 2020. 63(3): p. 319–325. [DOI] [PubMed] [Google Scholar]
  • 20.CDX Technologies. CDXZipStream Excel zip code add-in. https://www.cdxtech.com/cdxzipstream/. Data downloaded May 2022.
  • 21.Chang SJ, Bristow RE, Chi DS, and Cliby WA, Role of aggressive surgical cytoreduction in advanced ovarian cancer. J Gynecol Oncol, 2015. 26(4): p. 336–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Aletti GD, Gostout BS, Podratz KC, and Cliby WA, Ovarian cancer surgical resectability: Relative impact of disease, patient status, and surgeon. Gynecologic Oncology, 2006. 100(1): p. 33–37. [DOI] [PubMed] [Google Scholar]
  • 23.Kumpulainen S, et al. , The effect of hospital operative volume, residual tumor and first-line chemotherapy on survival of ovarian cancer — A prospective nation-wide study in Finland. Gynecologic Oncology, 2009. 115(2): p. 199–203. [DOI] [PubMed] [Google Scholar]
  • 24.Vernooij F, et al. , Specialized and high-volume care leads to better outcomes of ovarian cancer treatment in the Netherlands. Gynecologic Oncology, 2009. 112(3): p. 455–461. [DOI] [PubMed] [Google Scholar]
  • 25.Olaitan A, Weeks J, Mocroft A, Smith J, Howe K, Murdoch J. The surgical management of women with ovarian cancer in the south west of England. Br J Cancer. 2001. Dec 14;85(12):1824–30. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Fagö-Olsen CL, Høgdall C, Kehlet H, Christensen IJ, Ottesen B. Centralized treatment of advanced stages of ovarian cancer improves survival: a nationwide Danish survey. Acta Obstet Gynecol Scand. 2011. Mar;90(3):273–9. [DOI] [PubMed] [Google Scholar]
  • 27.Agency for Healthcare Research and Quality. Safety in numbers: hospital performance on Leapfrog’s surgical volume standard based on results of the 2019 Leapfrog Hospital Survey. https://psnet.ahrq.gov/issue/safety-numbers-hospital-performance-leapfrogs-surgical-volume-standard-basedresults-2019.
  • 28.Epstein AM. Volume and outcome–it is time to move ahead. N Engl J Med. 2002; 346:1161–4. [DOI] [PubMed] [Google Scholar]
  • 29.Logan CD, et al. , Association of travel distance, surgical volume, and receipt of adjuvant chemotherapy with survival among patients with resectable lung cancer. JTCVS Open, 2023. 13: p. 357–378. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Al-Refaie WB, et al. , Who receives their complex cancer surgery at low-volume hospitals? J Am Coll Surg, 2012. 214(1): p. 81–7. [DOI] [PubMed] [Google Scholar]
  • 31.Liu JH, et al. , Disparities in the Utilization of High-Volume Hospitals for Complex Surgery. JAMA, 2006. 296(16): p. 1973–1980. [DOI] [PubMed] [Google Scholar]
  • 32.Finlayson SR, Birkmeyer JD, Tosteson AN & Nease RF (1999). Patient Preferences for Location of Care. Medical Care, 37 (2), 204–209. [DOI] [PubMed] [Google Scholar]
  • 33.Yang A, et al. , Critical Choices: What Information Do Patients Want When Selecting a Hospital for Cancer Surgery? J Oncol Pract, 2018. 14(8): p. e505–e512. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Pronovost PJ, Wu AW, and Austin JM, Time for Transparent Standards in Quality Reporting by Health Care Organizations. Jama, 2017. 318(8): p. 701–702. [DOI] [PubMed] [Google Scholar]
  • 35.Marang-van de Mheen PJ, et al. , The relative importance of quality of care information when choosing a hospital for surgical treatment: a hospital choice experiment. Med Decis Making, 2011. 31(6): p. 816–27. [DOI] [PubMed] [Google Scholar]
  • 36.Ellis RJ, et al. , National Evaluation of Patient Preferences in Selecting Hospitals and Health Care Providers. Med Care, 2020. 58(10): p. 867–873. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Austin JM, McGlynn EA, and Pronovost PJ, Fostering Transparency in Outcomes, Quality, Safety, and Costs. Jama, 2016. 316(16): p. 1661–1662. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

1
NIHMS1962983-supplement-1.docx (28KB, docx)

RESOURCES