Difference In Travel Distance Research Articles

Who is your prenatal care provider? An algorithm to identify the predominant prenatal care provider with claims data.

Using claims data to identify a predominant prenatal care (PNC) provider is not always straightforward, but it is essential for assessing access, cost, and outcomes. Previous algorithms applied plurality (providing the most visits) and majority (providing majority of visits) to identify the predominant provider in primary care setting, but they lacked visit sequence information. This study proposes an algorithm that includes both PNC frequency and sequence information to identify the predominant provider and estimates the percentage of identified predominant providers. Additionally, differences in travel distances to the predominant and nearest provider are compared. The dataset used for this study consisted of 108,441 live births and 2,155,076 associated South Carolina Medicaid claims from 2015-2018. Analysis focused on patients who were continuously enrolled throughout their pregnancy and had any PNC visit, resulting in 32,609 pregnancies. PNC visits were identified with diagnosis and procedure codes and specialty within the estimated gestational age. To classify PNC providers, seven subgroups were created based on PNC frequency and sequence information. The algorithm was developed by considering both the frequency and sequence information. Percentage of identified predominant providers was reported. Chi-square tests were conducted to assess whether the probability of being identified as a predominant provider for a specific subgroup differed from that of the reference group (who provided majority of all PNC). Paired t-tests were used to examine differences in travel distance. Pregnancies in the sample had an average of 7.86 PNC visits. Fewer than 30% of the sample had an exclusive provider. By applying PNC frequency information, a predominant provider can be identified for 81% of pregnancies. After adding sequential information, a predominant provider can be identified for 92% of pregnancies. Distance was significantly longer for pregnant individuals traveling to the identified predominant provider (an average of 5 miles) than to the nearest provider. Inclusion of PNC sequential information in the algorithm has increased the proportion of identifiable predominant providers by 11%. Applying this algorithm reveals a longer distance for pregnant individuals travelling to their predominant provider than to the nearest provider.

Understanding user equilibrium states of road networks: Evidence from two Chinese mega-cities using taxi trajectory mining

User equilibrium (UE) has long been regarded as the cornerstone of transport planning studies. Despite its fundamental importance, our understanding of the actual UE state of road networks has remained surprisingly incomplete. Using big datasets of taxi trajectories, this study investigates the UE states of road networks in two Chinese mega-cities, i.e., Wuhan and Shenzhen. Effective indicators, namely relative gaps, are introduced to quantify how actual traffic states deviate from theoretical UE states. Advanced machine learning techniques, including XGBoost and SHAP values, are employed to analyze nonlinear relationships between network disequilibrium states and seven influencing factors extracted from trajectory data. The results in these two study areas reveal consistent and significant gaps between actual traffic states and the theoretical UE states at various times of the day during both weekdays and weekends. The XGBoost analysis shows that differences in travel distances, travel speeds, and signalized intersection numbers among alternative routes are the primary causes of road network disequilibrium. The results of this study could present several important methodological and policy implications for using the UE models in transport applications.

UNDERSTANDING USER EQUILIBRIUM STATES OF ROAD NETWORKS USING BIG TRAJECTORY DATA

Abstract. User equilibrium (UE) has long been regarded as the cornerstone of transport planning studies. Despite its fundamental importance, our understanding of the actual UE state of road networks has remained surprisingly incomplete. Using big datasets of taxi trajectories, this study investigates the UE states of road networks in Wuhan. Effective indicators, namely relative gaps, are introduced to quantify how actual traffic states deviate from theoretical UE states. Advanced machine learning techniques, including XGBoost and SHAP values, are employed to analyze nonlinear relationships between network disequilibrium states and seven influencing factors extracted from trajectory data. The results reveal significant gaps between actual traffic states and the theoretical UE states at various times of the day during both weekdays and weekends. The XGBoost analysis shows that differences in travel distances, travel speeds, and signalized intersection numbers among alternative routes are the primary causes of road network disequilibrium. The results of this study could have several important methodological and policy implications for using the UE models in transport applications.

Disparities in access to opioid treatment programs and buprenorphine providers by race and ethnicity in the contiguous U.S.

BackgroundThe burden of drug overdose mortality varies by race and ethnicity, with American Indian/Alaska Native (AI/AN), Black, and White people experiencing the largest burden. We analyzed census block group data to evaluate differences in travel distance to opioid treatment programs (OTP) and buprenorphine providers by race and ethnicity. MethodsThe Substance Abuse and Mental Health Services Administration provided the addresses of OTPs and buprenorphine providers. The study classified block groups as majority (≥50 %) AI/AN, Black, Asian, White, no single racial majority, or Hispanic. We classified deprivation and rurality using the Area Deprivation Index and Rural-Urban Commuting Area codes. The study applied generalized linear mixed models. ResultsAmong all block groups, the median road distance to the nearest OTPs and buprenorphine providers was 8 and 2 miles, respectively. AI/AN-majority block groups had the longest median distances to OTPs (88 miles versus 4–10 miles) and buprenorphine providers (17 miles versus 1–3 miles) compared to other racial or ethnic majority block groups. For OTPs and buprenorphine providers, travel distances were slightly greater in more deprived block groups compared to less deprived block groups. The median distance to the nearest OTPs and buprenorphine providers were larger in micropolitan and small town/rural block groups compared to metropolitan areas. ConclusionsDisparities exist in travel distance to OTPs and buprenorphine providers. People in block groups with AI/AN-majority, nonmetropolitan, or more deprived designation experience travel disparities accessing treatment. Future research should develop targeted interventions to reduce access to care disparities for individuals with opioid use disorder.

How to schedule the Volleyball Nations League

The Volleyball Nations League is the elite annual international competition within volleyball, with the sixteen best nations per gender contesting the trophy in a tournament that spans over 6 weeks. The first five weeks contain a single round robin tournament, where matches are played in different venues across the globe. As a consequence, each team follows an intensive travel plan, where it happens quite often that there is a large discrepancy between travel burdens of opposing teams. This is considered a disadvantage for the team that travelled more. We analyse this problem, and find that it is closely related to the well-known Social Golfer Problem: we name the resulting problem the Traveling Social Golfer Problem (TSGP). We propose a decomposition approach for the TSGP, leading to the so-called Venue Assignment Problem and the Nation Assignment Problem. We prove that a solution to the Venue Assignment problem determines the amount of unfairness, and we also prove that any solution of the Venue Assignment problem can be extended to a solution to the Nation Assignment problem satisfying the so-called home-venue property. Using integer programming methods, we find, for real-life instances, the fairest schedules with respect to the difference in travel distance.

Spatial and Temporal Trends in Travel for COVID-19 Vaccinations

Understanding spatial and temporal trends in travel for COVID-19 vaccinations by key demographic characteristics (i.e., gender, race, age) is important for ensuring equitable access to and increasing distribution efficiency of vaccines and other health services. The aim of this study is to examine trends in travel distance for COVID-19 vaccinations over the course of the vaccination rollout in North Carolina. Data were collected using electronic medical records of individuals who had first- or single-dose COVID-19 vaccination appointments through UNC Health between December 15, 2020, and August 31, 2021 (N = 204,718). Travel distances to appointments were calculated using the Euclidean distance from individuals' home ZIP code centroids to clinic addresses. Descriptive statistics and multivariable regression models with individuals' home ZIP codes incorporated as fixed effects were used to examine differences in travel distances by gender, race, and age. Males and White individuals traveled significantly farther for vaccination appointments throughout the vaccination rollout. On average, females traveled 14. 4 miles, 3.5% shorter distances than males; Black individuals traveled 13.6 miles, 10.0% shorter distances than White individuals; and people aged 65 and older traveled 14.5 miles, 2.6% longer distances than younger people living in the same ZIP code. Controlling for socioeconomic status and spatial proximity to vaccination clinics at the ZIP code level, males and White individuals traveled longer distances for vaccination appointments, demonstrating more ability to travel for vaccinations. Results indicate a need to consider differential ability to travel to vaccinations by key demographic characteristics in COVID-19 vaccination programs and future mass health service delivery efforts.

Mobility and Associated CO2 Emissions During and After COVID-19: A Case Study in Indonesia

Changes in transportation trends can occur during and after COVID-19, such as travel distance, trip, and choice of transportation mode. The positive benefits from these changes in transportation trends should be maintained, to reduce disaster risk of environmental hazards from the CO2 emissions. Research on changes in mobility, trips, and CO2 emissions during and after COVID-19 in Indonesia is still very limited; whereas, changes in these transportation variables can be an inspiration for determining sustainable transportation policies in the future. This study aims to compare amid COVID-19 and post-COVID-19 transportation variables—travel distances, trips, and associated CO2 emissions. This research was conducted by giving questionnaires to 400 participants in Aceh Besar District. The questionnaire contains questions regarding the distance traveled, trips, fuel spent, and socio-economic characteristics. The CO2 emissions were calculated using IPCC (2006). The travel distance, trips, and transportation-related CO2 emissions during and after COVID-19 were compared respectively based on statistics. The results showed that there were significant differences in travel distances, trips, and transportation-related CO2 emissions between COVID-19 and the post-COVID-19 situation in the District of Aceh Besar. This article also presents several recommendations based on the data analysis results linked to literature studies about the sustainability of transportation as a result of COVID-19 situation; those are: providing quality public transportation, considering teleworking, providing solutions for workers who do not have access to online work, and paying attention to increasing use of private cars and car sharing post COVID-19.

Regional Trends for the 2021 COVID-19 Independent Plastic Surgery Match Cycle.

Introduction: The coronavirus disease (COVID) created an abrupt change to virtual experiences and interviews for both the integrated and independent plastic surgery match cycle of 2021. Studies have shown that during the 2021 match cycle, integrated applicants were more likely to match at their home institution and region of medical school. These geographic and location trends for the 2021 match cycle have not been explored yet for the independent plastic surgery match.Methods: Information for independent plastic surgery applicants that successfully matched was gathered using publicly available data for the 2019 and 2020 pre-COVID and 2021 COVID match cycles. Zip codes for applicant medical school, applicant residency program, and plastic surgery program were gathered to compare regional and distance outcomes between the pre-COVID and COVID match cycles.Results: Data was collected on 182 applicants from 42 programs. There was no significant difference in the breakdown of gender percentages between the COVID match cycle (63.2% males) and the pre-COVID match cycles (72% males) (p=0.23). The COVID match cycle had 38.6% of applicants match at a plastics program within the same region as their residency, while the pre-COVID match cycles had 47.2% of applicants match the same region (p=0.28). These results continued to be nonsignificant when stratified by the regions of the west, south, midwest, and northeast (p=1.00). With regional matches with respect to medical school, the COVID match cycle had 33.3% of applicants match at a plastics program within the same region as their medical school, while the pre-COVID match cycles had 43.6% (p=0.20). These results continued to be nonsignificant when stratified by the four regions (p=1.00). When comparing the median distances between the COVID match cycle and the pre-COVID match cycle, no region of the United States showed a significant difference in travel distance to a plastics program with respect to medical school or residency (p=1.00).Conclusion: Transitions to virtual interviews and cancellation of away rotations during the COVID match cycle for the independent plastic surgery match did not significantly affect an applicant’s ability to match outside of their region of previous medical school or residency. This may represent diminished program preference for applicants within the same region as their plastic residency.

Disparities in Access to Radiation Therapy by Race and Ethnicity in the United States With Focus on American Indian/Alaska Native People

Striking disparities in access to radiation therapy (RT) exist, especially among racial and ethnic-minority patients. We analyzed census block group data to evaluate differences in travel distance to RT as a function of race and ethnicity, socioeconomic status, and rurality. The Directory of Radiotherapy Centers provided the addresses of facilities containing linear accelerators for RT. We classified block groups as majority (≥ 50%) American Indian/Alaska Native (AI/AN), black, white, Asian, no single racial majority, or Hispanic regardless of race. We used the Area Deprivation Index to classify deprivation and Rural-Urban Commuting Area codes to classify rurality. Generalized linear mixed models tested associations between these factors and distance to nearest RT facility. Median distance to nearest RT facility was 72 miles in AI/AN-majority block groups, but 4 to 7 miles in block groups with non-AI/AN majorities. Multivariable models estimated that travel distances in AI/AN-majority block groups were 39 to 41 miles longer than in areas with non-AI/AN majorities. Travel distance was 1.3 miles longer in the more deprived areas versus less deprived areas and 16 to 32 miles longer in micropolitan, small town, and rural areas versus metropolitan areas. Cancer patients in block groups with AI/AN-majority populations, nonmetropolitan location, and low socioeconomic status experience substantial travel disparities in access to RT. Future research with more granular community- and individual-level data should explore the many other known barriers to access to cancer care and their relationship to the barriers posed by distance to RT care.

Disparities in Access to Radiation Therapy Facilities Among American Indians/Alaska Natives and Hispanics in Washington State

Racial and ethnic minorities in the state of Washington experience higher cancer mortality relative to whites. We sought to characterize differences in travel distance to radiation therapy (RT) facilities in Washington by race and ethnicity with a special focus on non-Hispanic American Indians and Alaska Natives as a contributor to limited access and cancer disparities. Geocoded mortality data from Washington Department of Health (2011-2018) were used to identify decedents with mortality related to all-causes, all cancers, and cancers likely requiring access to RT. This was determined from optimal RT usage estimates by diagnosis. RT facility locations were ascertained from the Directory of Radiation Therapy Centers and confirmed. Distance from decedents' address listed on death certificates to nearest RT facility was calculated. Generalized mixed models were used for statistical analysis. We identified 418,754 deaths; 109,134 were cancer-related, 60,973 likely required RT. Among decedents with cancers likely requiring RT, non-Hispanic American Indians and Alaska Natives decedents would have had to travel 1.16 times (95% confidence interval [CI], 1.09-1.24) farther from their residences to reach the nearest treatment facility compared with non-Hispanic whites. This association existed in metro counties but was more pronounced in nonmetro counties (1.39 times farther; 95% CI, 1.22-1.58). In addition, Hispanics would have had to travel 1.11 times farther (95% CI, 1.06-1.16) to reach the nearest facility compared with non-Hispanic whites, primarily due to differences in urban counties. Decedents in nonmetro counties lived on average 35 miles (SD=29) from RT centers and non-Hispanic American Indians and Alaska Natives in nonmetro counties 53 miles (SD=38). Compared with non-Hispanic white decedents, those who were non-Hispanic black, non-Hispanic Asian, and non-Hispanic Native Hawaiian decedents lived closer to RT facilities. We observed significant disparities in access to RT facilities in Washington, specifically for non-Hispanic American Indians and Alaska Natives and rural decedents. The findings call for initiatives to improve access to critical cancer treatment services for these underserved populations with known disparities in cancer deaths.

Disparities in Access to Radiation Oncology Facilities Among American Indian/Alaska Natives and Hispanics in Metro and Non-Metro Washington State

Racial and ethnic minorities in Washington State (WA) experience higher cancer mortality relative to whites. We sought to characterize differences in travel distance as a marker for access to radiation therapy (RT) facilities in WA and one possible contributing factor to cancer disparities.Geocoded mortality data from the WA Department of Health (2011-2018) were used to identify decedents with mortality related to all causes, all cancers, and cancers likely requiring access to RT (defined as estimated RT usage rate > 50% by anatomical subsite corresponding to ICD-9 or 10 code). Race was defined per US Office of Management and Budget 1997 standard and ethnicity as Hispanic or non-Hispanic. RT facility locations were identified from the Directory of Radiotherapy Centers and validated by internet search or phone calls. Road network distance from decedent's residence to nearest RT facility was calculated on a geographic information platform. Generalized mixed models were used for statistical analysis.We identified 109,134 cancer-related deaths of which 60,973 likely required RT. Among decedents with cancers likely requiring RT, non-Hispanic (NH) American Indian/Alaskan Native (AI/AN) decedents would have had to travel 1.16 times (95% CI 1.09-1.24) farther to reach the nearest treatment facility compared to NH whites. This association existed in metro counties but was more pronounced in non-metro and rural counties, where NH AI/ANs would have had to travel 1.39 times farther compared to NH whites (95% CI 1.22 - 1.58). This translated to an average of 83 miles (SD = 22) for NH AI/AN in rural areas to travel to RT centers whereas NH Whites in rural areas would have had to travel on average 59 miles (SD = 28). Hispanics would have had to travel 1.11 times farther to reach the nearest facility compared to NH whites (95% CI 1.06 - 1.16), primarily due to differences in urban areas. NH African American, NH Asian, and NH Native Hawaiian decedents lived closer to RT facilities compared to the NH white decedents. Based on our findings, we estimated that expanding the federal "safe harbor" restrictions on health systems providing transportation from 50 to 75 miles could open up needed services for 96% of rural NH AI/ANs.NH AI/ANs and rural decedents experience stark disparities in access to RT facilities in WA state. The findings call for creative initiatives to improve access to critical cancer treatment services to combat racial, ethnic and rural disparities in cancer deaths. In depth analysis of local barriers to access for minority communities is necessary to devising practical solutions such as advocating for policy change for "safe harbor" restrictions.

Access to Chimeric Antigen Receptor TCell Therapy for Diffuse Large BCell Lymphoma.

IntroductionGeographic access to novel oncology therapies, and the extent to which it may vary by potential sites of care, regions, and population characteristics, is poorly understood. We examined how expanding access to chimeric antigen receptor (CAR) T cell therapy administration sites impacts patient travel distances and time.MethodsWe used geographic information system techniques to calculate shortest travel distance and time between patients with relapsed/refractory diffuse large B cell lymphoma (DLBCL) and the nearest CAR T cell therapy administration site in three scenarios: academic hospitals; academic and community multispecialty hospitals; and academic and community multispecialty hospitals plus nonacademic specialty oncology network centers. Main outcome measures were differences in travel distance and time among the scenarios and the relationship between travel time and socioeconomic status, race, rural–urban areas, and non-Hodgkin lymphoma clusters. Non-Hodgkin lymphoma incidence, socioeconomic status, and administration centers were derived from governmental/publicly available data sources.ResultsOf 3922 patients eligible for CAR T cell therapy, more than 37% had to travel more than 1 h to the nearest academic hospital. Average travel time and distance were significantly reduced by 23% and 30% (P < 0.001), respectively, when access was expanded to include community hospitals plus a broader range of oncology specialty treatment centers. Compared to academic hospitals alone, increasing access to include community hospitals decreased time and distance by 7% and 8% (P < 0.01), respectively. In addition, there would be a lower proportion of sites operating as the only care provider within 25 miles if access was expanded outside of academic hospitals only. Longer travel time was associated with lower socioeconomic status.ConclusionMany patients with DLBCL have long travel times to an academic hospital that administers CAR T cell therapy. Expanding access to care through site-of-care planning will help address regional, rural–urban, and sociodemographic equity in the geographic allocation of CAR T cell therapy.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12325-021-01838-z.

Bedload transport in rivers, size matters but so does shape

Bedload transport modelling in rivers takes into account the size and density of pebbles to estimate particle mobility, but does not formally consider particle shape. To address this issue and to compare the relative roles of the density and shape of particles, we performed original sediment transport experiments in an annular flume using molded artificial pebbles equipped with a radio frequency identification tracking system. The particles were designed with four distinct shapes and four different densities while having the same volume, and their speeds and distances traveled under constant hydraulic conditions were analyzed. The results show that particle shape has more influence than particle density on the resting time between particle displacement and the mean traveling distance. For all densities investigated, the particle shape systematically induced differences in travel distance that were strongly correlated (R2 = 0.94) with the Sneed and Folks shape index. Such shape influences, although often mentioned, are here quantified for the first time, demonstrating why and how they can be included in bedload transport models.

Strategic placement of urban agriculture: A spatial optimization approach

AbstractStrategic placement of urban agriculture such as community gardens can expand alternate food supply, support physical activity, and promote social interactions. While social and health benefits are critical priorities when planning new urban agriculture locations, no widely accepted site selection methods have been established. We developed a spatial optimization model to identify new urban agriculture locations in the City of Indianapolis, Marion County, Indiana. Considering block groups with vacant parcels as potential locations, the study uses p‐median optimization to identify the 25 best locations that would minimize travel from any block group in the city to potential garden locations. We weighted each block group based on food access and prevalence of obesity, where food access was characterized on three dimensions: economic, geographical, and informational. The model was simulated for three policy scenarios with equal, stakeholder‐driven, and obesity‐driven weights, and the results were compared with randomly selected locations. We found that optimally selected locations were 52% more efficient than randomly chosen locations in terms of the average distance traveled by residents based on the p‐median solution. However, there was no significant difference in travel distance among the three policy scenarios. The spatial optimization model can help policymakers and practitioners strategically locate urban agriculture sites.

Scheduling Multiple Sports Leagues with Travel Distance Fairness: An Application to Argentinean Youth Football

The first division clubs in Argentinean professional football maintain teams in each of six youth leagues, classed by age as major divisions (Under-20, Under-18, Under-17) and minor divisions (Under-16, Under-15, Under-14). Regular season play in these leagues typically follows a single round-robin format; the minor divisions play the same schedule as the majors but with the home-away status of the matches reversed. This setup can give rise to very significant differences in travel distances between the major and minor division teams of a given club, which is a frustrating situation for club officials, coaches, and players alike but almost impossible to avoid with manual season scheduling techniques. Nor are these methods able to take into account any number of other criteria that go into the design of a satisfactory match calendar. This paper reports on models developed using mathematical programming to simultaneously schedule multiple leagues while also meeting a series of other desirable conditions. The central criterion is a better balance in the travel distances of the various teams, pursued through the application of two alternative solution approaches: one based on regional team clusters and the other on explicit analysis of actual distances between the teams’ home venues. The solutions generated by these approaches have been used by the organizers of the Argentinean youth leagues to draw up their season schedules since 2018, which has resulted in a series of benefits for all stakeholders.

GPS를 활용한 여자필드하키 경기상황에 따른 차이 분석

The purpose of this study is to identify the differences in players’ movements depending on the situations that occur during hockey games. In order to achieve the purpose of the study, firstly, 16 Korean women’s hockey players who participated in the FIH Women’s Series Finals were collected. Secondly, the hockey experts’ meeting defined the four conditions of the game and classified the conditions to verify the differences. According to the result of this study, the average number of attacks in hockey games was 120.8 times in offensive situation, 120.2 times in defensive situation, 78.8 times in offensive situation after the count-attacks and 77.8 times in defensive situation after the count-attacks. Second, the difference in travel distance by segment according to the busy conditions was shown to be the most active in both bands 1 and 5, and there was no statistically significant differences with band 6. Thirdly, in acceleration by section, the band 1 to band 3, both the distance and the number of times were higher. Fourthly, in deceleration by segment, both the distance and the number of times were higher in the band 1 to band 3. Thus, it is estimated that coaches would be used as useful information in establishing training strategies and strength settings in the field.

Geographic disparities in residential proximity to colorectal and cervical cancer care providers.

Persistent rural-urban disparities for colorectal and cervical cancers raise concerns regarding access to treatment providers. To the authors knowledge, little is known regarding rural-urban differences in residential proximity to cancer specialists. Using the 2018 Physician Compare data concerning physician practice locations and the 2012 to 2016 American Community Survey, the current study estimated the driving distance from each residential zip code tabulation area (ZCTA) centroid to the nearest cancer provider of the following medical specialties involved in treating patients with colorectal and cervical cancer: medical oncology, radiation oncology, surgical oncology, general surgery, gynecological oncology, and colorectal surgery. Using population-weighted multivariable logistic regression, the authors analyzed the associations between ZCTA-level characteristics and driving distances >60 miles to each type of specialist. ZCTA-level residential rurality was defined using rural-urban commuting area codes. Nearly 1 in 5 rural Americans lives >60 miles from a medical oncologist. Rural-urban differences in travel distances to the nearest cancer care provider(s) increased substantially for cancer surgeons; greater than one-half of rural residents were required to travel 60 miles to reach a gynecological oncologist, compared with 8 miles for their urban counterparts. Individuals residing within ZCTAs with a higher poverty rate, those of American Indian/Alaska Native ethnicity, and/or were located in the South and West regions were more likely than their counterparts to be >60 miles away from any of the aforementioned providers. The substantial travel distances required for rural, low-income residents to reach a cancer specialist should prompt a policy action to increase access to specialized cancer care for millions of rural residents.

Minimum Travel Distance Among Publicly Insured Infants with Severe Congenital Heart Disease: Potential Impact of In-state Restrictions.

Travel distance to surgical centers may be increased when coverage restrictions prevent children with congenital heart disease (CHD) from receiving care at out-of-state congenital heart surgery centers. We estimated the minimum travel distance to congenital heart surgery centers among publicly insured infants with time-sensitive CHD surgical needs, under two different scenarios: if they were and were not restricted to in-state centers. Using 2012 Medicaid Analytic eXtract data from 40 states, we identified 4598 infants with CHD that require surgery in the first year of life. We calculated the minimum travel distance between patients' homes and the nearest cardiac surgery center, assuming patients were and were not restricted to in-state centers. We used linear regression to identify demographic predictors of distance under both scenarios. When patients were not restricted to in-state centers, mean minimum travel distance was 43.7miles, compared to 54.1miles when they were restricted. For 5.9% of patients, the difference in travel distance under the two scenarios exceeded 50miles. In six states, the difference in mean minimum travel distance exceeded 20miles. Under both scenarios, distance was positively predicted by rural status, residence in middle-income zip codes, and white/non-Hispanic or American Indian/Alaskan Native race/ethnicity. For some publicly insured infants with severe CHD, facilitating the receipt of out-of-state care could mitigate access barriers. Existing efforts to regionalize care at fewer centers should be designed to avoid exacerbating access barriers among publicly insured CHD patients.

Effect of regionalization of endometrial cancer care on site of care and patient travel

Complex oncologic surgeries, including those for endometrial cancer, increasingly have been concentrated to greater-volume centers, owing to previous research that has demonstrated associations between greater surgical volume and improved outcomes. There is a potential for concentration of care to have unwanted consequences, including cost burden, delayed treatment, patient dissatisfaction, and possibly worse clinical outcomes, especially for more vulnerable populations. To describe changes in site of care for patients with endometrial cancer in New York State and to determine whether the distance women traveled for hysterectomy has changed over time. We used the New York Statewide Planning and Research Cooperative System to identify women with endometrial cancer who underwent hysterectomy from 2000 to 2014. Demographic and clinical data as well as hospital data were collected. Trends in travel distance (straight-line distance) were analyzed within all hospital referral regions and differences in travel distance over times and across sociodemographic characteristics analyzed. We identified 41,179 subjects. The number of hospitals and surgeons performing hysterectomy decreased across all hospital referral regions over time. The decline in the number of hospitals caring for women with endometrial cancer ranged from -16.7% in Syracuse (12 to 10 hospitals) to -76.5% in Rochester (17 to 4 hospitals). Similarly, the percentage of surgeons within a given hospital referral region operating on women declined from -45.2% in Buffalo (84-46 surgeons) to -77.8% in Albany (72 to 16 surgeons). The median distance to the index hospital for patients increased in all Hospital Referral Regions. For residents in Binghamton, median travel distance increased by 46.9 miles (95% confidence interval, 33.8-60.0) whereas distance increased in Elmira by 19.7 miles (95% confidence interval, 7.3-32.1) and by 12.4 miles (95% confidence interval, 6.4-18.4) in Albany. For residents of Binghamton and Albany, there was a greater than 100% increase in distance traveled over the 15-year time period, with increases of 551.8% (46.9 miles; 95% confidence interval, 33.8-60.0 miles) and 102.5% (12.4 miles; 95% confidence interval, 6.4-18.4 miles), respectively. Travel distance increased for all races and regardless of insurance status but was greatest for white patients and those with private insurance (P<.0001 for both). The number of surgeons and hospitals caring for women with endometrial cancer in New York State has decreased, whereas the distance that patients travel to receive care has increased over time.

Travel distance influences readmissions in colorectal cancer patients—what the primary operative team needs to know

BackgroundMany colorectal cancer patients receive complex surgical care remotely. We hypothesized that their readmission rates would be adversely affected after accounting for differences in travel distance from primary/index hospital and correlate with mortality. Materials and methodsWe identified 48,481 colorectal cancer patients in the Surveillance, Epidemiology and End Results (SEER)-Medicare database. Travel distance was calculated, using Google Maps, and SAS. Multivariate negative binomial regression was used to identify factors associated with readmission rates. Overall survival was analyzed, using Kaplan–Meier and Cox proportional hazard. Results and conclusionsThirty-day readmissions occurred in 14.9% of the cohort, 27.5% of which were to a nonindex hospital. In the colon and rectal cancer cohorts, readmissions were 14.5% and 16.5%, respectively. Rectal cancer patients had an increase in readmission by 13% (incidence rate ratios [IRR] 1.13; 95% confidence interval [CI] 1.05-1.21). Factors associated with readmission were male gender, advanced disease, length of stay (LOS), discharge disposition, hospital volume, Charlson score, and poverty level (P < 0.05). Greater distance traveled increased the likelihood of readmission but did not affect mortality. Travel distance influences readmission rates but not mortality. Discharge readiness to decrease readmissions is essential for colorectal cancer patients discharged from index hospitals.