Comparing GIS-based measures in access to mammography and their validity in predicting neighborhood risk of late-stage breast cancer

Geospatial Modeling Methods in Epidemiological Kidney Research: An Overview and Practical Example

Geospatial modeling methods in population-level kidney research have not been used to full potential because few studies have completed associative spatial analyses between risk factors and exposures and kidney conditions and outcomes. Spatial modeling has several advantages over traditional modeling, including improved estimation of statistical variation and more accurate and unbiased estimation of coefficient effect direction or magnitudes by accounting for spatial data structure. Because most population-level kidney research data are geographically referenced, there is a need for better understanding of geospatial modeling for evaluating associations of individual geolocation with processes of care and clinical outcomes. In this review, we describe common spatial models, provide details to execute these analyses, and perform a case-study to display how results differ when integrating geographic structure. In our case-study, we used U.S. nationwide 2019 chronic kidney disease (CKD) data from Centers for Disease Control and Prevention's Kidney Disease Surveillance System and 2006 to 2010 U.S. Environmental Protection Agency environmental quality index (EQI) data and fit a nonspatial count model along with global spatial models (spatially lagged model [SLM]/pseudo-spatial error model [PSEM]) and a local spatial model (geographically weighted quasi-Poisson regression [GWQPR]). We found the SLM, PSEM, and GWQPR improved model fit in comparison to the nonspatial regression, and the PSEM model decreased the positive relationship between EQI and CKD prevalence. The GWQPR also revealed spatial heterogeneity in the EQI-CKD relationship. To summarize, spatial modeling has promise as a clinical and public health translational tool, and our case-study example is an exhibition of how these analyses may be performed to improve the accuracy and utility of findings.

GIS Mapping and Breast Cancer Health Care Access Gaps for African American Women

Black women face an unequal opportunity to survive breast cancer compared with White women. One would expect that US metropolitan areas with high percentages of Black people should report similar racial disparities in breast health. Yet, this is not the case. To provide insights about breast cancer disparities in cities with above-average and below-average racial disparities, we use GIS analysis. We depict racial composition and income categories on the same map with mammography facility locations to distinguish unique patterns of mammography access, a critical resource for breast cancer care. Looking more closely at low health disparities cities, a general and consistent pattern arises. Both White and Black people are concentrated in middle-income neighborhoods. Further, MQSA-certified facilities are not clustered in affluent areas but tend to be centrally located in the middle of the city or highly dispersed across the city, regardless of income. Our findings are consistent with the hypothesis that metropolitan areas that have a preponderance of racially segregated low-income Black households-a characteristic of neighborhoods that have experienced a history of racism and disinvestment-are more likely to experience disparities in access to primary breast care than middle-income Black, middle-income White, or high-income White neighborhoods.

Value of Geographical Information Systems in Analyzing Geographic Accessibility to Inform Radiotherapy Planning: A Systematic Review

PURPOSE

Vulnerable populations face geographical barriers in accessing radiotherapy (RT) facilities, resulting in heterogeneity of care received and cancer burden faced. We aimed to explore the current use of Geographical Information Systems (GIS) in access to RT and use these findings to create sustainable solutions against barriers for access in low- and middle-income countries.

MATERIALS AND METHODS

A systematic review using the PRISMA search strategy was done for studies using GIS to explore outcomes among patients with cancer. Included studies were reviewed and classified into three umbrella categories of how GIS has been used in studying access to RT.

RESULTS

Forty articles were included in the final review. Thirty-eight articles were set in high-income countries and two in upper-middle-income countries. Included studies were published from 2000 to 2020, and were comprised of patients with all-cancers combined, breast, colon, skin, lung, prostate, ovarian, and rectal carcinoma patients. Studies were categorized under three groups on the basis of how they used GIS in their analyses: to describe geographic access to RT, to associate geographic access to RT with outcomes, and for RT planning. Most studies fell under multiple categories.

CONCLUSION

Although this field is relative nascent, there is a wide array of functions possible through GIS for RT planning, including identifying high-risk populations, improving access in high-need areas, and providing valuable information for future resource allocation. GIS should be incorporated in future studies, especially set in low- and middle-income countries, which evaluate access to RT.

Spatial evaluation of animal health care accessibility and veterinary shortage in France

The decrease in the supply of veterinary healthcare in France adversely affects health of food-producing animals. In a One Health perspective, the health of people, animals and their shared environment are interconnected, and adequate supply of veterinary healthcare is required to ensure public health. Prevention of outbreaks and zoonotic diseases that may impact public health mobilizes a set of public policies, including strengthening veterinary workforce. These policies should be informed by quantification of animal health care accessibility, yet this has not been well characterized. The objective was to quantify the accessibility to veterinary healthcare for cattle, swine, and poultry sectors in France. A Two-Step Floating Catchment Area (2SFCA) approach was used to measure the level of accessibility to veterinary clinics. In the cattle sector, the 2SFCA score indicated relatively high accessibility in the north and south of France, but insufficient accessibility elsewhere. In the swine sector, there was high accessibility in the north east and in north of France, medium accessibility in the south west, and insufficient accessibility elsewhere. Finally, in the poultry sector, all regions had insufficient accessibility. Sensitivity analysis examining the effects of a change in spatial accessibility according to various travel time showed that the optimal threshold to compute 2SFCA score in cattle, swine and poultry sectors were respectively, 45, 60 and 60 min. According to a definition of “underserved area” derived from an official decree and the optimal thresholds to compute 2SFCA, the cattle, swine and poultry sector have on average 75.3, 89.9 and 98.3% underserved area, respectively. We provided evidence that the supply of animal health care was not sufficient and we proposed recommendations on how to assess animal health care accessibility, enabling modelling and visualization of the effects of potential public policies aimed at reducing veterinary shortages.

Influence of geographic access and socioeconomic characteristics on breast cancer outcomes: A systematic review

Socio-economic and geographical inequalities in breast cancer mortality have been widely described in European countries and the United States. To investigate the combined effects of geographic access and socio-economic characteristics on breast cancer outcomes, a systematic review was conducted exploring the relationships between: (i) geographic access to healthcare facilities (oncology services, mammography screening), defined as travel time and/or travel distance; (ii) breast cancer-related outcomes (mammography screening, stage of cancer at diagnosis, type of treatment and rate of mortality); (iii) socioeconomic status (SES) at individuals and residential context levels. In total, n = 25 studies (29 relationships tested) were included in our systematic review. The four main results are: The statistical significance of the relationship between geographic access and breast cancer-related outcomes is heterogeneous: 15 were identified as significant and 14 as non-significant. Women with better geographic access to healthcare facilities had a statistically significant fewer mastectomy (n = 4/6) than women with poorer geographic access. The relationship with the stage of the cancer is more balanced (n = 8/17) and the relationship with cancer screening rate is not observed (n = 1/4). The type of measures of geographic access (distance, time or geographical capacity) does not seem to have any influence on the results. For example, studies which compared two different measures (travel distance and travel time) of geographic access obtained similar results. The relationship between SES characteristics and breast cancer-related outcomes is significant for several variables: at individual level, age and health insurance status; at contextual level, poverty rate and deprivation index. Of the 25 papers included in the review, the large majority (n = 24) tested the independent effect of geographic access. Only one study explored the combined effect of geographic access to breast cancer facilities and SES characteristics by developing stratified models.

Trends in spatial access to colonoscopy in South Carolina, 2000-2014

BACKGROUND

Colonoscopy use has increased since Medicare began covering screening for average-risk persons. Our objective was to describe changes in spatial access to colonoscopy in South Carolina (SC) between 2000 and 2014.

METHODS

Using data from the SC Ambulatory Surgery Database, we created annual ZIP Code Tabulation Area (ZCTA) spatial accessibility scores. We assessed changes in accessibility, colonoscopy supply, and potential demand, overall and by metropolitan designation. Spatial clustering was also explored.

RESULTS

Spatial accessibility decreased across both small rural and metropolitan ZCTAs but was significantly higher in metropolitan areas during the first part of the study period . The proportion of persons with no access to colonoscopy within 30 min increased over time but was consistently higher in small rural areas. Clusters of low accessibility grew over time.

CONCLUSIONS

The supply of colonoscopy facilities decreased relative to the potential demand, and clusters of low access increased, indicating a contraction of services.

Spatial accessibility to colonoscopy and its role in predicting late-stage colorectal cancer

OBJECTIVE

To better determine the relationship between spatial access to colonoscopy and colorectal cancer (CRC) outcomes, our objective was to examine the agreement of the classic, enhanced, and variable two-step floating catchment area (2SFCA) methods in evaluating spatial access to colonoscopy and to compare the predictive validity of each method related to late-stage CRC. 2SFCA methods simultaneously consider supply/demand of services and impedance (ie, travel time).

DATA SOURCES

Colonoscopy provider locations were obtained from the South Carolina Ambulatory Surgery Database. ZIP code tabulation area (ZCTA) level population estimates and area-level poverty level were obtained from the American Community Survey. Rurality was determined by the United States Department of Agriculture's Rural-Urban Commuting Area codes. Individual-level CRC data were obtained from the South Carolina Central Cancer Registry.

STUDY DESIGN

Using the classic, enhanced, and variable 2SFCA methods, we calculated ZCTA-level spatial access to colonoscopy. We assessed agreement between the three methods by calculating Spearman's rank coefficients and weighted Kappas (Κ). Global and Local Moran's I were used to assess spatial clustering of accessibility scores across 2SFCA methods. We performed multilevel logistic regression analyses to examine the association between spatial accessibility to colonoscopy, area- and individual-level factors, and late-stage CRC.

PRINCIPAL FINDINGS

We found strong agreement (Weighted Κ = 0.82; 95% CI = 0.79-0.86) and identified similar clustering patterns with the classic and enhanced 2SFCA methods. There was negligible agreement among the classic/enhanced 2SFCA and the variable 2SFCA. Across all 2SFCA methods, regression models showed that spatial access to colonoscopy, rurality, and poverty level were not associated with greater odds of late-stage CRC, though Black race was associated with late-stage CRC across all models.

CONCLUSIONS

None of the 2SFCA methods showed an association with late-stage CRC. Future studies should explore which elements (spatial or nonspatial) of access to care have the greatest impact on CRC outcomes.

Association of Participation in Health Check-ups with Risk Factors for Cardiovascular Diseases

BACKGROUND

We compared the risk factors for cardiovascular diseases (CVDs) among Koreans who did and did not participate in national periodic health check-ups, after adjustment for demographic factors, socioeconomic status, and lifestyle factors.

METHODS

This cross-sectional study used data from the Korea National Health and Nutrition Examination Survey (KNHANES) from 2007 to 2018. Study subjects were classified as participants or non-participants in health check-ups, based on attendance at national periodic health check-ups during the previous two years.

RESULTS

Comparison of participants and non-participants in health check-ups indicated statistically significant differences in age, gender, region, education level, monthly income, employment status, obesity, smoking, alcohol consumption, exercise, and marital status. After adjustment for demographic, socioeconomic factors, and health-related behaviors, woman non-participants were more likely to have metabolic syndrome, pre-hypertension, hypertension, prediabetes, and diabetes, and man non-participants were more likely to have pre-diabetes and diabetes.

CONCLUSION

Subjects who participated in periodic health check-ups had fewer CVD-related risk factors than non-participants. Thus, health care providers should encourage non-participants to attend periodic health check-ups so that appropriate interventions can be implemented and decrease the risk for CVDs in these individuals.

Do mobile units contribute to spatial accessibility to mammography for uninsured women?

Limited spatial accessibility to mammography, and socioeconomic barriers (e.g., being uninsured), may contribute to rural disparities in breast cancer screening. Although mobile mammography may contribute to population-level access, few studies have investigated this relationship. We measured mammography access for uninsured women using the variable two-step floating catchment area (V2SFCA) method, which estimates access at the local level using estimated potential supply and demand. Specifically, we measured supply with mammography machine certifications in 2014 from FDA and brick-and-mortar and mobile facility data from the community-based Breast Screening and Patient Navigation (BSPAN) program. We measured potential demand using Census tract-level estimates of female residents aged 45-74 from 5-year 2012-2016 American Community Survey data. Using the sign test, we compared mammography access estimates based on 3 facility groupings: FDA-certified, program brick-and-mortar only, and brick-and-mortar plus mobile. Using all mammography facilities, accessibility was high in urban Dallas-Ft. Worth, low for the ring of adjacent counties, and high for rural counties outlying this ring. Brick-and-mortar-based estimates were lower for the outlying ring, and mobile-unit contribution to access was observed more in urban tracts. Weak mobile-unit contribution across the study area may indicate suboptimal dispatch of mobile units to locations. Geospatial methods could identify the optimal locations for mobile units, given existing brick-and-mortar facilities, to increase access for underserved areas.

Estimating health service utilization potential using the supply-concentric demand-accumulation spatial availability index: a pulmonary rehabilitation case study

The potential for a population at a given location to utilize a health service can be estimated using a newly developed measure called the supply-concentric demand accumulation (SCDA) spatial availability index. Spatial availability is the amount of demand at the given location that can be satisfied by the supply of services at a facility, after discounting the intervening demand among other populations that are located nearer to a facility location than the given population location. This differs from spatial accessibility measures which treat absolute distance or travel time as the factor that impedes utilization. The SCDA is illustrated using pulmonary rehabilitation (PR), which is a treatment for people with chronic obstructive pulmonary disease (COPD). The spatial availability of PR was estimated for each Census block group in Georgia using the 1105 residents who utilized one of 45 PR facilities located in or around Georgia. Data was provided by the Centers for Medicare & Medicaid Services. The geographic patterns of the SCDA spatial availability index and the two-step floating catchment area (2SFCA) spatial accessibility index were compared with the observed PR utilization rate using bivariate local indicators of spatial association. The SCDA index was more associated with PR utilization (Morans I = 0.607, P < 0.001) than was the 2SFCA (Morans I = 0.321, P < 0.001). These results suggest that the measures of spatial availability may be a better way to estimate the health care utilization potential than measures of spatial accessibility.

Effect of geographic accessibility to primary care on treatment status of hypertension

Although primary care access is known to be an important factor when seeking care, its effect on individual health risk has not been evaluated by an appropriate spatial measure. This study examined whether geographic accessibility to primary care assessed by a sophisticated form of spatial measure is associated with a risk of hypertension and its treatment status among Japanese people in rural areas, where primary care is not yet established as specialization. We used an enhanced two-step floating catchment area method to calculate the neighborhood residential unit-level primary and secondary care accessibility for 52,029 subjects who participated in the 2015 annual health checkup held at 15 cities in Shimane Prefecture. Their hypertension level and treatment status were examined cross-sectionally with their neighborhood primary care and secondary care accessibility (computed with two separate distance-decay weight: slow and quick) by multivariable logistic regression controlling for demographics and neighborhood income level. The findings showed that greater geographic accessibility to primary care was associated with a decreased risk of hypertension in both slow and quick distance-decay weight, odds ratio (OR) = 0.989 (95% Confidence Interval (CI) = 0.984, 0.994), OR = 0.989 (95%CI = 0.984, 0.993), respectively. On the other hand, better secondary care accessibility was associated with an increased risk of hypertension and untreated hypertension; however, the effect of secondary care was mitigated by the effect of primary care accessibility in both slow and quick distance-decay model, hypertension: OR = 0.974 (95% CI = 0.957, 0.991), OR = 0.981 (95%CI = 0.970, 0.991), untreated hypertension: OR = 0.970 (95%CI = 0.944, 0.996), OR = 0.975 (95%CI = 0.959, 0.991), respectively. In addition, the results revealed that young and fit people were at a higher risk of untreated hypertension, which is a unique finding in the context of the Japanese healthcare system. Our findings indicate the importance of primary care even in Japan, where it is not yet established, and also emphasize the need for a culturally specific perspective in health equity.

Using floating catchment area (FCA) metrics to predict health care utilization patterns

BACKGROUND

Floating Catchment Area (FCA) metrics provide a comprehensive measure of potential spatial accessibility to health care services and are often used to identify geographic disparities in health care access. An unexplored aspect of FCA metrics is whether they can be useful in predicting where people actually seek care. This research addresses this question by examining the utility of FCA metrics for predicting patient utilization patterns, the flows of patients from their residences to facilities.

METHODS

Using more than one million inpatient hospital visits in Michigan, we calculated expected utilization patterns from Zip Codes to hospitals using four FCA metrics and two traditional metrics (simple distance and a Huff model) and compared them to observed utilization patterns. Because all of the accessibility metrics rely on the specification of a distance decay function and its associated parameters, we conducted a sensitivity analysis to evaluate their effects on prediction accuracy.

RESULTS

We found that the Three Step FCA (3SFCA) and Modified Two Step FCA (M2SFCA) were the most effective metrics for predicting utilization patterns, correctly predicting the destination hospital for nearly 74% of hospital visits in Michigan. These two metrics were also the least sensitive to changes to the distance decay functions and parameter settings.

CONCLUSIONS

Overall, this research demonstrates that FCA metrics can provide reasonable predictions of patient utilization patterns and FCA utilization models could be considered as a substitute when utilization pattern data are unavailable.

Using spatially adaptive floating catchments to measure the geographic availability of a health care service: Pulmonary rehabilitation in the southeastern United States

A spatially adaptive floating catchment is a circular area that expands outward from a provider location until the estimated demand for services in the nearest population locations exceeds the observed number of health care services performed at the provider location. This new way of creating floating catchments was developed to address the change of spatial support problem (COSP) by upscaling the availability of the service observed at a provider location to the county-level so that its geographic association with utilization could be measured using the same spatial support. Medicare Fee-for-Service claims data were used to identify beneficiaries aged ≥ 65 years who received outpatient pulmonary rehabilitation (PR) in the Southeastern United States in 2014 (n = 8798), the number of PR treatments these beneficiaries received (n = 132,508), and the PR providers they chose (n = 426). The positive correlation between PR availability and utilization was relatively low, but statistically significant (r = 0.619, p < 0.001) indicating that most people use the nearest available PR services, but some travel long distances. SAFCs can be created using data from health care systems that collect claim-level utilization data that identifies the locations of providers chosen by beneficiaries of a specific health care procedure.

The role of service factors on variations in place of death: an observational study

Background

Previous studies have revealed that there is significant geographical variation in place of death in (PoD) England, with sociodemographic and clinical characteristics explaining ≤ 25% of this variation. Service factors, mostly modifiable, may account for some of the unexplained variation, but their role had never been evaluated systematically.

Methods

A national population-based observational study in England, using National Death Registration Database (2014) linked to area-level service data from public domains, categorised by commissioning, type and capacity, location and workforce of the services, and the service use. The relationship between the service variables and PoD was evaluated using beta regression at the area level and using generalised linear mixed models at the patient level. The relative contribution of service factors at the area level was assessed using the per cent of variance explained, measured by R2. The total impact of service factors was evaluated by the area under the receiver operating characteristic curve (AUC). The independent effect of service variables was measured at the individual level by odds ratios (ORs).

Results

Among the 431,735 adult deaths, hospitals were the most common PoD (47.3%), followed by care homes (23.1%), homes (22.5%) and hospices (6.1%). One-third (30.3%) of the deaths were due to cancer and two-thirds (69.7%) were due to non-cancer causes. Almost all service categories studied were associated with some of the area-level variation in PoD. Service type and capacity had the strongest link among all service categories, explaining 14.2–73.8% of the variation; service location explained 10.8–34.1% of the variation. The contribution of other service categories to PoD was inconsistent. At the individual level, service variables appeared to be more useful in predicting death in hospice than in hospital or care home, with most AUCs in the fair performance range (0.603–0.691). The independent effect of service variables on PoD was small overall, but consistent. Distance to the nearest care facility was negatively associated with death in that facility. At the Clinical Commissioning Group level, the number of hospices per 10,000 adults was associated with a higher chance of hospice death in non-cancer causes (OR 30.88, 99% confidence interval 3.46 to 275.44), but a lower chance of hospice death in cancer causes. There was evidence for an interaction effect between the service variables and sociodemographic variables on PoD.

Limitations

This study was limited by data availability, particularly those specific to palliative and end-of-life care; therefore, the findings should be interpreted with caution. Data limitations were partly due to the lack of attention and investment in this area.

Conclusion

A link was found between service factors and PoD. Hospice capacity was associated with hospice death in non-cancer cases. Distance to the nearest care facility was negatively correlated with the probability of a patient dying there. Effect size of the service factors was overall small, but the interactive effect between service factors and sociodemographic variables suggests that high-quality end-of-life care needs to be built on service-level configuration tailored to individuals’ circumstances.

Future work

A large data gap was identified and data collection is required nationally on services relevant to palliative and end-of-life care. Future research is needed to verify the identified links between service factors and PoD.

Funding

The National Institute for Health Research Health Services and Delivery Research programme.

Spatial Accessibility to Mammography Services in the Lower Mississippi Delta Region States

PURPOSE

To characterize spatial access to mammography services across 8 Lower Mississippi Delta Region (LMDR) states. These states include the Delta Region, a federally designated, largely rural, and impoverished region with a high proportion of black residents and low mammography utilization rates.

METHODS

Using the enhanced 2-step floating catchment area method, we calculated spatial accessibility scores for mammography services across LMDR census tracts. We compared accessibility scores between the Delta and non-Delta Regions of the LMDR. We also performed hotspot analysis and constructed spatial lag models to detect clusters of low spatial access and to identify sociodemographic factors associated with access, respectively. We obtained mammography facility locations data from the Food and Drug Administration and sociodemographic variables from the American Community Survey and the US Department of Agriculture.

RESULTS

Overall, there were no differences in spatial accessibility scores between the Delta and non-Delta Regions, though there was some state-to-state variation. Clusters of low spatial access were found in parts of the Arkansas, Mississippi, and Tennessee Delta. Spatial lag models found that poverty was associated with greater spatial access to mammography.

CONCLUSIONS

The lack of identified differences in spatial access to mammography in the Delta and non-Delta Regions suggests that psychosocial or financial barriers play a larger role in lower mammography utilization rates. Identifying clusters of low spatial access to mammography services can help inform resource allocation. Further, our study underscores the value of using coverage-based methods rather than travel time or container measures to evaluate spatial access to care.

Developing a Priority Scoring Index for Mobile Mammography Sites: Considerations for Screening Access in Rural and Remote Settings

Geographic location continues to be an important indicator in incidence of, access to treatment for, and mortality from breast cancer. Disparities in access to screening and early detection persist in Appalachian Virginia. We developed an index to identify sites which would most benefit from increased frequency of mobile mammography visits, based on geographically relevant population-level risk factors (late stage of tumor diagnosis) and accessibility risk factors (access to FDA [US Food and Drug Administration] mammography sites, access of women aged 50+ years to primary care physicians at existing mobile sites). These 4 components for the Priority Index were subsequently standardized and multiplied to importance weights. The percentage of mammograms performed in the target geographic region has increased each year, respectively. This article presents methodological considerations for developing a priority algorithm to increase access to breast cancer early screening and detection for vulnerable women.

Use of an E2SFCA Method to Measure and Analyse Spatial Accessibility to Medical Services for Elderly People in Wuhan, China

Current studies on measuring the accessibility of medical services for the elderly (AMSE) have ignored the potential competition among supply and demand and the distance decay laws. Hence, an enhanced two-step floating catchment area (E2SFCA) method (i.e., the road network-based Gaussian 2SFCA method) is proposed to calculate AMSE scores after considering different types of roads, including urban rail transit, freeways, major roads, minor roads and rural roads. Based on the first National Geographic Conditions Monitoring (NGCM) data, this study took Wuhan, China, as a case study and assessed the variation of AMSE using two different threshold times (i.e., Platinum Ten and Golden Hour). Next, global (i.e., sensitivity and hot spot analysis) and local analyses (i.e., three regional area internal comparisons) of AMSE scores were conducted to accurately identify details in the variation of spatial accessibility. It was observed that the E2SFCA method could be easily applied to measure AMSE. The results showed that 48.63% of the elderly population in Wuhan had a higher or the highest level of medical accessibility in "Platinum Ten", while 72.97% had a higher or the highest level in the "Golden Hour", and hot spots of AMSE scores were located in central urban areas and presented an enclosure structure using both threshold travel times, which could provide guidance to governments or planners on issues of spatial planning and identifying elderly medical services shortage areas.

Travel Times for Screening Mammography: Impact of Geographic Expansion by a Large Academic Health System

RATIONALE AND OBJECTIVES

This study aims to assess the impact of off-campus facility expansion by a large academic health system on patient travel times for screening mammography.

MATERIALS AND METHODS

Screening mammograms performed from 2013 to 2015 and associated patient demographics were identified using the NYU Langone Medical Center Enterprise Data Warehouse. During this time, the system's number of mammography facilities increased from 6 to 19, reflecting expansion beyond Manhattan throughout the New York metropolitan region. Geocoding software was used to estimate driving times from patients' homes to imaging facilities.

RESULTS

For 147,566 screening mammograms, the mean estimated patient travel time was 19.9 ± 15.2 minutes. With facility expansion, travel times declined significantly (P < 0.001) from 26.8 ± 18.9 to 18.5 ± 13.3 minutes (non-Manhattan residents: from 31.4 ± 20.3 to 18.7 ± 13.6). This decline occurred consistently across subgroups of patient age, race, ethnicity, payer status, and rurality, leading to decreased variation in travel times between such subgroups. However, travel times to pre-expansion facilities remained stable (initial: 26.8 ± 18.9 minutes, final: 26.7 ± 18.6 minutes). Among women undergoing mammography before and after expansion, travel times were shorter for the postexpansion mammogram in only 6.3%, but this rate varied significantly (all P < 0.05) by certain demographic factors (higher in younger and non-Hispanic patients) and was as high as 18.2%-18.9% of patients residing in regions with the most active expansion.

CONCLUSIONS

Health system mammography facility geographic expansion can improve average patient travel burden and reduce travel time variation among sociodemographic populations. Nonetheless, existing patients strongly tend to return to established facilities despite potentially shorter travel time locations, suggesting strong site loyalty. Variation in travel times likely relates to various factors other than facility proximity.

Variation in Patients' Travel Times among Imaging Examination Types at a Large Academic Health System

RATIONALE AND OBJECTIVES

Patients' willingness to travel farther distances for certain imaging services may reflect their perceptions of the degree of differentiation of such services. We compare patients' travel times for a range of imaging examinations performed across a large academic health system.

MATERIALS AND METHODS

We searched the NYU Langone Medical Center Enterprise Data Warehouse to identify 442,990 adult outpatient imaging examinations performed over a recent 3.5-year period. Geocoding software was used to estimate typical driving times from patients' residences to imaging facilities. Variation in travel times was assessed among examination types.

RESULTS

The mean expected travel time was 29.2 ± 20.6 minutes, but this varied significantly (p < 0.001) among examination types. By modality, travel times were shortest for ultrasound (26.8 ± 18.9) and longest for positron emission tomography-computed tomography (31.9 ± 21.5). For magnetic resonance imaging, travel times were shortest for musculoskeletal extremity (26.4 ± 19.2) and spine (28.6 ± 21.0) examinations and longest for prostate (35.9 ± 25.6) and breast (32.4 ± 22.3) examinations. For computed tomography, travel times were shortest for a range of screening examinations [colonography (25.5 ± 20.8), coronary artery calcium scoring (26.1 ± 19.2), and lung cancer screening (26.4 ± 14.9)] and longest for angiography (32.0 ± 22.6). For ultrasound, travel times were shortest for aortic aneurysm screening (22.3 ± 18.4) and longest for breast (30.1 ± 19.2) examinations. Overall, men (29.9 ± 21.6) had longer (p < 0.001) travel times than women (27.8 ± 20.3); this difference persisted for each modality individually (p ≤ 0.006).

CONCLUSIONS

Patients' willingness to travel longer times for certain imaging examination types (particularly breast and prostate imaging) supports the role of specialized services in combating potential commoditization of imaging services. Disparities in travel times by gender warrant further investigation.

Impact of geographic accessibility on utilization of the annual health check-ups by income level in Japan: A multilevel analysis

Although both geographic accessibility and socioeconomic status have been indicated as being important factors for the utilization of health care services, their combined effect has not been evaluated. The aim of this study was to reveal whether an income-dependent difference in the impact of geographic accessibility on the utilization of government-led annual health check-ups exists. Existing data collected and provided by Chiba City Hall were employed and analyzed as a retrospective cohort study. The subjects were 166,966 beneficiaries of National Health Insurance in Chiba City, Japan, aged 40 to 74 years. Of all subjects, 54,748 (32.8%) had an annual health check-up in fiscal year 2012. As an optimal index of geographic accessibility has not been established, five measures were calculated: travel time to the nearest health care facility, density of health care facilities (number facilities within a 30-min walking distance from the district of residence), and three indices based on the two-step floating catchment area method. Three-level logistic regression modeling with random intercepts for household and district of residence was performed. Of the five measures, density of health care facilities was the most compatible according to Akaike's information criterion. Both low density and low income were associated with decreased utilization of the health check-ups. Furthermore, a linear relationship was observed between the density of facilities and utilization of the health check-ups in all income groups and its slope was significantly steeper among subjects with an equivalent income of 0.00 yen than among those with equivalent income of 1.01-2.00 million yen (p = 0.028) or 2.01 million yen or more (p = 0.040). This result indicated that subjects with lower incomes were more susceptible to the effects of geographic accessibility than were those with higher incomes. Thus, better geographic accessibility could increase the health check-up utilization and also decrease the income-related disparity of utilization.

Predictors of non-drug psychiatric/psychotherapeutic treatment in children and adolescents with mental or behavioural disorders

Children and adolescents with mental health problems need effective and safe therapies to support their emotional and social development and to avoid functional impairment and progress of social deficits. Though psychotropic drugs seem to be the preferential treatment, psychotherapy and psychosocial interventions are essential in mental health care. For Germany, current data on the utilization of psychotherapy and psychosocial interventions in children with mental health problems is lacking. To analyse why certain children and adolescents with mental or behavioural disorders do and others do not receive non-drug treatment, we assessed predictors associated with specific non-drug psychiatric/psychotherapeutic treatment including psychosocial interventions, psychotherapy and other non-drug treatments. The study is based on data of two large German health insurance funds, AOK and TK, comprising 30 % of the German child and adolescent population. Predictors of non-drug psychiatric/psychotherapeutic treatment were analysed for 23,795 cases and two controls for every case of the same age and sex in children aged 0-17 years following a new diagnosis of mental or behavioural disorder in 2010. Predictors were divided according to Andersen's behavioural model into predisposing, need and enabling factors. The most prominent and significant predictors positively associated with non-drug psychiatric/psychotherapeutic treatment were the residential region as predisposing factor; specific, both ex- and internalizing, mental and behavioural disorders, psychiatric co-morbidity and psychotropic drug use as need factors; and low area deprivation and high accessibility to outpatient physicians and inpatient institutions with non-drug psychiatric/psychotherapeutic department as enabling factors. In conclusion, the present study suggests that the residential region as proxy for supply of therapist and socioeconomic situation is an influencing factor for the use of psychotherapy. The analysis sheds further light on predisposing, need and enabling factors as predictors of non-drug psychotherapeutic/psychiatric treatment in children and adolescents with mental or behavioural health disorders in Germany. More research is needed to further understand the factors promoting the gap between the need and utilization of mental health care.

Advances in spatial epidemiology and geographic information systems

The field of spatial epidemiology has evolved rapidly in the past 2 decades. This study serves as a brief introduction to spatial epidemiology and the use of geographic information systems in applied research in epidemiology. We highlight technical developments and highlight opportunities to apply spatial analytic methods in epidemiologic research, focusing on methodologies involving geocoding, distance estimation, residential mobility, record linkage and data integration, spatial and spatio-temporal clustering, small area estimation, and Bayesian applications to disease mapping. The articles included in this issue incorporate many of these methods into their study designs and analytical frameworks. It is our hope that these studies will spur further development and utilization of spatial analysis and geographic information systems in epidemiologic research.

Spatial Access to Primary Care Providers in Appalachia: Evaluating Current Methodology

PURPOSE

The goal of this research was to examine spatial access to primary care physicians in Appalachia using both traditional access measures and the 2-step floating catchment area (2SFCA) method. Spatial access to care was compared between urban and rural regions of Appalachia.

METHODS

The study region included Appalachia counties of Pennsylvania, Ohio, Kentucky, and North Carolina. Primary care physicians during 2008 and total census block group populations were geocoded into GIS software. Ratios of county physicians to population, driving time to nearest primary care physician, and various 2SFCA approaches were compared.

RESULTS

Urban areas of the study region had shorter travel times to their closest primary care physician. Provider to population ratios produced results that varied widely from one county to another because of strict geographic boundaries. The 2SFCA method produced varied results depending on the distance decay weight and variable catchment size techniques chose. 2SFCA scores showed greater access to care in urban areas of Pennsylvania, Ohio, and North Carolina.

CONCLUSION

The different parameters of the 2SFCA method-distance decay weights and variable catchment sizes-have a large impact on the resulting spatial access to primary care scores. The findings of this study suggest that using a relative 2SFCA approach, the spatial access ratio method, when detailed patient travel data are unavailable. The 2SFCA method shows promise for measuring access to care in Appalachia, but more research on patient travel preferences is needed to inform implementation.

Evaluating and Comparing Methods for Measuring Spatial Access to Mammography Centers in Appalachia (Re-Revised)

PURPOSE

This study evaluated spatial access to mammography centers in Appalachia using both traditional access measures and the two-step floating catchment area (2SFCA) method.

METHODS

Ratios of county mammography centers to women age 45 and older, driving time to nearest mammography facility, and various 2SFCA approaches were compared throughout Pennsylvania, Ohio, Kentucky, and North Carolina.

RESULTS

Closest travel time measures favored urban areas. The 2SFCA method produced varied results depending on the parameters chosen. Appalachia areas had greater travel times to their closest mammography center. Appalachia areas in OH and NC had worse 2SFCA scores than non-Appalachia areas of the same states.

CONCLUSION

A relative 2SFCA approach, the spatial access ratio (SPAR) method, was recommended because it helped minimize the differences between various 2SFCA approaches.

Is the closest facility the one actually used? An assessment of travel time estimation based on mammography facilities

Background

Characterizing geographic access depends on a broad range of methods available to researchers and the healthcare context to which the method is applied. Globally, travel time is one frequently used measure of geographic access with known limitations associated with data availability. Specifically, due to lack of available utilization data, many travel time studies assume that patients use the closest facility. To examine this assumption, an example using mammography screening data, which is considered a geographically abundant health care service in the United States, is explored. This work makes an important methodological contribution to measuring access—which is a critical component of health care planning and equity almost everywhere.

Method

We analyzed one mammogram from each of 646,553 women participating in the US based Breast Cancer Surveillance Consortium for years 2005–2012. We geocoded each record to street level address data in order to calculate travel time to the closest and to the actually used mammography facility. Travel time between the closest and the actual facility used was explored by woman-level and facility characteristics.

Results

Only 35 % of women in the study population used their closest facility, but nearly three-quarters of women not using their closest facility used a facility within 5 min of the closest facility. Individuals that by-passed the closest facility tended to live in an urban core, within higher income neighborhoods, or in areas where the average travel times to work was longer. Those living in small towns or isolated rural areas had longer closer and actual median drive times.

Conclusion

Since the majority of US women accessed a facility within a few minutes of their closest facility this suggests that distance to the closest facility may serve as an adequate proxy for utilization studies of geographically abundant services like mammography in areas where the transportation networks are well established.

Travel by public transit to mammography facilities in 6 US urban areas

We examined lack of private vehicle access and 30 minutes or longer public transportation travel time to mammography facilities for women 40 years of age or older in the urban areas of Boston, Philadelphia, San Antonio, San Diego, Denver, and Seattle to identify transit marginalized populations - women for whom these travel characteristics may jointly present a barrier to clinic access. This ecological study used sex and race/ethnicity data from the 2010 US Census and household vehicle availability data from the American Community Survey 2008-2012, all at Census tract level. Using the public transportation option on Google Trip Planner we obtained the travel time from the centroid of each census tract to all local mammography facilities to determine the nearest mammography facility in each urban area. Median travel times by public transportation to the nearest facility for women with no household access to a private vehicle were obtained by ranking travel time by population group across all U.S. census tracts in each urban area and across the entire study area. The overall median travel times for each urban area for women without household access to a private vehicle ranged from a low of 15 minutes in Boston and Philadelphia to 27 minutes in San Diego. The numbers and percentages of transit marginalized women were then calculated for all urban areas by population group. While black women were less likely to have private vehicle access, and both Hispanic and black women were more likely to be transit marginalized, this outcome varied by urban area. White women constituted the largest number of transit marginalized. Our results indicate that mammography facilities are favorably located for the large majority of women, although there are still substantial numbers for whom travel may likely present a barrier to mammography facility access.

Small-area spatio-temporal analyses of participation rates in the mammography screening program in the city of Dortmund (NW Germany)

Background

The population-based mammography screening program (MSP) was implemented by the end of 2005 in Germany, and all women between 50 and 69 years are actively invited to a free biennial screening examination. However, despite the expected benefits, the overall participation rates range only between 50 and 55 %. There is also increasing evidence that belonging to a vulnerable population, such as ethnic minorities or low income groups, is associated with a decreased likelihood of participating in screening programs. This study aimed to analyze in more detail the intra-urban variation of MSP uptake at the neighborhood level (i.e. statistical districts) for the city of Dortmund in northwest Germany and to identify demographic and socioeconomic risk factors that contribute to non-response to screening invitations.

Methods

The numbers of participants by statistical district were aggregated over the three periods 2007/2008, 2009/2010, and 2011/2012. Participation rates were calculated as numbers of participants per female resident population averaged over each 2-year period. Bayesian hierarchical spatial models extended with a temporal and spatio-temporal interaction effect were used to analyze the participation rates applying integrated nested Laplace approximations (INLA). The model included explanatory covariates taken from the atlas of social structure of Dortmund.

Results

Generally, participation rates rose for all districts over the time periods. However, participation was persistently lowest in the inner city of Dortmund. Multivariable regression analysis showed that migrant status and long-term unemployment were associated with significant increases of non-attendance in the MSP.

Conclusion

Low income groups and immigrant populations are clustered in the inner city of Dortmund and the observed spatial pattern of persistently low participation in the city center is likely linked to the underlying socioeconomic gradient. This corresponds with the findings of the ecological regression analysis manifesting socioeconomically deprived neighborhoods as risk factors for low attendance in the MSP. Spatio-temporal surveillance of participation in cancer screening programs may be used to identify spatial inequalities in screening uptake and plan spatially focused interventions.

Predicting Late-stage Breast Cancer Diagnosis and Receipt of Adjuvant Therapy: Applying Current Spatial Access to Care Methods in Appalachia

PURPOSE

The 2-step floating catchment area (2SFCA) method of measuring access to care has never been used to study cancer disparities in Appalachia. First, we evaluated the 2SFCA method in relation to traditional methods. We then examined the impact of access to mammography centers and primary care on late-stage breast cancer diagnosis and receipt of adjuvant hormonal therapy.

METHODS

Cancer registries from Pennsylvania, Ohio, Kentucky, and North Carolina were linked with Medicare data to identify the stage of breast cancer diagnosis for Appalachia women diagnosed between 2006 and 2008. Women eligible for adjuvant therapy had stage I, II, or III diagnosis; mastectomy or breast-conserving surgery; and hormone receptor-positive breast cancers. Geographically weighted regression was used to explore nonstationarity in the demographic and spatial access predictor variables.

RESULTS

Over 21% of 15,299 women diagnosed with breast cancer had late-stage (stages III-IV) diagnosis. Predictors included age at diagnosis [odds ratio (OR)=0.86; P<0.001], insurance status (OR=1.32; P<0.001), county primary care to population ratio (OR=0.95; P<0.001), and primary-care 2SFCA score (OR=0.96; P=0.006). Only 46.9% of eligible women received adjuvant hormonal therapy, and predictors included comorbidity status (OR=1.18; P=0.047), county economic status (OR=1.32; P=0.006), and mammography center 2SFCA scores (OR=1.12; P=0.021).

CONCLUSIONS

Methodologically, the 2SFCA method offered the greatest predictive validity of the access measures examined. Substantively, rates of late-stage breast cancer diagnosis and adjuvant hormonal therapy are substandard in Appalachia.

Geographic disparities in late stage breast cancer incidence: results from eight states in the United States

Background

Late stage of cancer at diagnosis is an important predictor of cancer mortality. In many areas worldwide, cancer registry systems, available data and mapping technologies can provide information about late stage cancer by geographical regions, offering valuable opportunities to identify areas where further investigation and interventions are needed. The current study examined geographical variation in late stage breast cancer incidence across eight states in the United States with the objective to identify areas that might benefit from targeted interventions.

Methods

Data from the Surveillance Epidemiology and End Results Program on late stage breast cancer incidence was used as dependent variable in regression analysis and certain factors known to contribute to high rates of late stage cancer (socioeconomic characteristics, health insurance characteristics, and the availability and utilization of cancer screening) as covariates. Geographic information systems were used to map and highlight areas that have any combination of high late stage breast cancer incidence and significantly associated risk factors.

Results

The differences in mean rates of late stage breast cancer between eight states considered in this analysis are statistically significant. Factors that have statistically negative association with late stage breast cancer incidence across the eight states include: density of mammography facilities, percent population with Bachelor’s degree and English literacy while percent black population has statistically significant positive association with late stage breast cancer incidence.

Conclusions

This study describes geographic disparities in late stage breast cancer incidence and identifies areas that might benefit from targeted interventions. The results suggest that in the eight US states examined, higher rates of late stage breast cancer are more common in areas with predominantly black population, where English literacy, percentage of population with college degree and screening availability are low. The approach described in this work may be utilized both within and outside US, wherever cancer registry systems and technologies offer the same opportunity to identify places where further investigation and interventions for reducing cancer burden are needed.

Geographic Access to Mammography and Its Relationship to Breast Cancer Screening and Stage at Diagnosis: A Systematic Review

INTRODUCTION

A review was conducted to summarize the current evidence and gaps in the literature on geographic access to mammography and its relationship to breast cancer-related outcomes.

METHODS

Ovid, Medline, and PubMed were searched for articles published between January 1, 2000, and April 1, 2013, using Medical Subject Headings and key terms representing geographic accessibility and breast cancer-related outcomes. Owing to a paucity of breast cancer treatment and mortality outcomes meeting the criteria (N = 6), outcomes were restricted to breast cancer screening and stage at diagnosis. Studies included one or more of the following types of geographic accessibility measures: capacity, density, distance, and travel time. Study findings were grouped by outcome and type of geographic measure.

RESULTS

Twenty-one articles met the inclusion criteria. Fourteen articles included stage at diagnosis as an outcome, five included mammography use, and two included both. Geographic measures of mammography accessibility varied widely across studies. Findings also varied, but most articles found either increased geographic access to mammography associated with increased use and decreased late-stage at diagnosis or no association.

CONCLUSION

The gaps and methodologic heterogeneity in the literature to date limit definitive conclusions about an underlying association between geographic mammography access and breast cancer-related outcomes. Future studies should focus on the development and application of more precise and consistent measures of geographic access to mammography.

Neighborhood socioeconomic deprivation, tumor subtypes, and causes of death after non-metastatic invasive breast cancer diagnosis: a multilevel competing-risk analysis

The purpose of this study is to examine the associations of neighborhood socioeconomic deprivation and triple-negative breast cancer (TNBC) subtype with causes of death [breast cancer (BC)-specific and non-BC-specific] among non-metastatic invasive BC patients. We identified 3,312 patients younger than 75 years (mean age 53.5 years; 621 [18.8 %] TNBC) with first primary BC treated at an academic medical center from 1999 to 2010. We constructed a census-tract-level socioeconomic deprivation index using the 2000 U.S. Census data and performed a multilevel competing-risk analysis to estimate the hazard ratios (HR) and 95 % confidence intervals (CI) of BC-specific and non-BC-specific mortality associated with neighborhood socioeconomic deprivation and TNBC subtype. The adjusted models controlled for patient sociodemographics, health behaviors, tumor characteristics, comorbidity, and cancer treatment. With a median 62-month follow-up, 349 (10.5 %) patients died; 233 died from BC. In the multivariate models, neighborhood socioeconomic deprivation was independently associated with non-BC-specific mortality (the most- vs. the least-deprived quartile: HR = 2.98, 95 % CI = 1.33-6.66); in contrast, its association with BC-specific mortality was explained by the aforementioned patient-level covariates, particularly sociodemographic factors (HR = 1.15, 95 % CI = 0.71-1.87). TNBC subtype was independently associated with non-BC-specific mortality (HR = 2.15; 95 % CI = 1.20-3.84), while the association between TNBC and BC-specific mortality approached significance (HR = 1.42; 95 % CI = 0.99-2.03, P = 0.057). Non-metastatic invasive BC patients who lived in more socioeconomically deprived neighborhoods were more likely to die as a result of causes other than BC compared with those living in the least socioeconomically deprived neighborhoods. TNBC was associated with non-BC-specific mortality but not BC-specific mortality.

Geographic access to breast imaging for US women

PURPOSE

The breast imaging modalities of mammography, ultrasound, and MRI are widely used for screening, diagnosis, treatment, and surveillance of breast cancer. Geographic access to breast imaging services in various modalities is not known at a national level overall or for population subgroups.

METHODS

A retrospective study of 2004-2008 Medicare claims data was conducted to identify ZIP codes in which breast imaging occurred, and data were mapped. Estimated travel times were made for each modality for 215,798 census block groups in the contiguous United States. Using Census 2010 data, travel times were characterized by sociodemographic factors for 92,788,909 women aged ≥30 years, overall, and by subgroups of age, race/ethnicity, rurality, education, and median income.

RESULTS

Overall, 85% of women had travel times of ≤20 minutes to nearest mammography or ultrasound services, and 70% had travel times of ≤20 minutes for MRI with little variation by age. Native American women had median travel times 2-3 times longer for all 3 modalities, compared to women of other racial/ethnic groups. For rural women, median travel times to breast imaging services were 4-8-fold longer than they were for urban women. Black and Asian women had the shortest median travel times to services for all 3 modalities.

CONCLUSIONS

Travel times to mammography and ultrasound breast imaging facilities are short for most women, but for breast MRI, travel times are notably longer. Native American and rural women are disadvantaged in geographic access based on travel times to breast imaging services. This work informs potential interventions to reduce inequities in access and utilization.

Methods to measure potential spatial access to delivery care in low- and middle-income countries: a case study in rural Ghana

BACKGROUND

Access to skilled attendance at childbirth is crucial to reduce maternal and newborn mortality. Several different measures of geographic access are used concurrently in public health research, with the assumption that sophisticated methods are generally better. Most of the evidence for this assumption comes from methodological comparisons in high-income countries. We compare different measures of travel impedance in a case study in Ghana's Brong Ahafo region to determine if straight-line distance can be an adequate proxy for access to delivery care in certain low- and middle-income country (LMIC) settings.

METHODS

We created a geospatial database, mapping population location in both compounds and village centroids, service locations for all health facilities offering delivery care, land-cover and a detailed road network. Six different measures were used to calculate travel impedance to health facilities (straight-line distance, network distance, network travel time and raster travel time, the latter two both mechanized and non-mechanized). The measures were compared using Spearman rank correlation coefficients, absolute differences, and the percentage of the same facilities identified as closest. We used logistic regression with robust standard errors to model the association of the different measures with health facility use for delivery in 9,306 births.

RESULTS

Non-mechanized measures were highly correlated with each other, and identified the same facilities as closest for approximately 80% of villages. Measures calculated from compounds identified the same closest facility as measures from village centroids for over 85% of births. For 90% of births, the aggregation error from using village centroids instead of compound locations was less than 35 minutes and less than 1.12 km. All non-mechanized measures showed an inverse association with facility use of similar magnitude, an approximately 67% reduction in odds of facility delivery per standard deviation increase in each measure (OR = 0.33).

CONCLUSION

Different data models and population locations produced comparable results in our case study, thus demonstrating that straight-line distance can be reasonably used as a proxy for potential spatial access in certain LMIC settings. The cost of obtaining individually geocoded population location and sophisticated measures of travel impedance should be weighed against the gain in accuracy.

Geographic disparities in mammography capacity in the South: a longitudinal assessment of supply and demand

OBJECTIVE

Studies have shown that there is sufficient availability of mammography; however, little is known about geographic variation in capacity. The purpose of this study was to determine the locations and extent of over/undersupply of mammography in 14 southern states from 2002 to 2008.

DATA SOURCES

Mammography facility data were collected from the U.S. Food and Drug Administration (FDA). Population estimates, used to estimate the potential demand for mammography, were obtained from GeoLytics Inc.

STUDY DESIGN

Using the two-step floating catchment area method, we calculated spatial accessibility at the block group level and categorized the resulting index to represent the extent of under/oversupply relative to the potential demand.

PRINCIPAL FINDINGS

Results show decreasing availability of mammography over time. The extent of over/undersupply varied significantly across the South. Reductions in capacity occurred primarily in areas with an oversupply of machines, resulting in a 68 percent decrease in the percent of women living in excess capacity areas from 2002 to 2008. The percent of women living in poor capacity areas rose by 10 percent from 2002 to 2008.

CONCLUSIONS

Our study found decreasing mammography availability and capacity over time, with substantial variation across states. This information can assist providers and policy makers in their business planning and resource allocation decisions.

Cancer cluster investigations: review of the past and proposals for the future

Residential clusters of non-communicable diseases are a source of enduring public concern, and at times, controversy. Many clusters reported to public health agencies by concerned citizens are accompanied by expectations that investigations will uncover a cause of disease. While goals, methods and conclusions of cluster studies are debated in the scientific literature and popular press, investigations of reported residential clusters rarely provide definitive answers about disease etiology. Further, it is inherently difficult to study a cluster for diseases with complex etiology and long latency (e.g., most cancers). Regardless, cluster investigations remain an important function of local, state and federal public health agencies. Challenges limiting the ability of cluster investigations to uncover causes for disease include the need to consider long latency, low statistical power of most analyses, uncertain definitions of cluster boundaries and population of interest, and in- and out-migration. A multi-disciplinary Workshop was held to discuss innovative and/or under-explored approaches to investigate cancer clusters. Several potentially fruitful paths forward are described, including modern methods of reconstructing residential history, improved approaches to analyzing spatial data, improved utilization of electronic data sources, advances using biomarkers of carcinogenesis, novel concepts for grouping cases, investigations of infectious etiology of cancer, and "omics" approaches.