A probabilistic sampling method (PSM) for estimating geographic distance to health services when only the region of residence is known

Anonymisation of geographical distance matrices via Lipschitz embedding

Background

Anonymisation of spatially referenced data has received increasing attention in recent years. Whereas the research focus has been on the anonymisation of point locations, the disclosure risk arising from the publishing of inter-point distances and corresponding anonymisation methods have not been studied systematically.

Methods

We propose a new anonymisation method for the release of geographical distances between records of a microdata file—for example patients in a medical database. We discuss a data release scheme in which microdata without coordinates and an additional distance matrix between the corresponding rows of the microdata set are released. In contrast to most other approaches this method preserves small distances better than larger distances. The distances are modified by a variant of Lipschitz embedding.

Results

The effects of the embedding parameters on the risk of data disclosure are evaluated by linkage experiments using simulated data. The results indicate small disclosure risks for appropriate embedding parameters.

Conclusion

The proposed method is useful if published distance information might be misused for the re-identification of records. The method can be used for publishing scientific-use-files and as an additional tool for record-linkage studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12942-015-0031-7) contains supplementary material, which is available to authorized users.

Where do patients with cancer in Iowa receive radiation therapy?

PURPOSE

Multiple studies have shown survival benefits in patients with cancer treated with radiation therapy, but access to treatment facilities has been found to limit its use. This study was undertaken to examine access issues in Iowa and determine a methodology for conducting a similar national analysis.

PATIENTS AND METHODS

All Iowa residents who received radiation therapy regardless of where they were diagnosed or treated were identified through the Iowa Cancer Registry (ICR). Radiation oncologists were identified through the Iowa Physician Information System (IPIS). Radiation facilities were identified through IPIS and classified using the Commission on Cancer accreditation standard.

RESULTS

Between 2004 and 2010, 113,885 invasive cancers in 106,603 patients, 28.5% of whom received radiation treatment, were entered in ICR. Mean and median travel times were 25.8 and 20.1 minutes, respectively, to the nearest facility but 42.4 and 29.1 minutes, respectively, to the patient's chosen treatment facility. Multivariable analysis predicting travel time showed significant relationships for disease site, age, residence location, and facility category. Residents of small and isolated rural towns traveled nearly 3× longer than urban residents to receive radiation therapy, as did patients using certain categories of facilities.

CONCLUSION

Half of Iowa patients could reach their nearest facility in 20 minutes, but instead, they traveled 30 minutes on average to receive treatment. The findings identified certain groups of patients with cancer who chose more distant facilities. However, other groups of patients with cancer, namely those residing in rural areas, had less choice, and some had to travel considerably farther to radiation facilities than urban patients.

Geographic information systems and chronic kidney disease: racial disparities, rural residence and forecasting

The dynamics of health and health care provision in the United States vary substantially across regions, and there is substantial regional heterogeneity in population density, age distribution, disease prevalence, race and ethnicity, poverty and the ability to access care. Geocoding and geographic information systems (GIS) are important tools to link patient or population location to information regarding these characteristics. In this review, we provide an overview of basic GIS concepts and provide examples to illustrate how GIS techniques have been applied to the study of kidney disease, and in particular to understanding the interplay between race, poverty, rural residence and the planning of renal services for this population. The interplay of socioeconomic status and renal disease outcomes remains an important area for investigation and recent publications have explored this relationship utilizing GIS techniques to incorporate measures of socioeconomic status and racial composition of neighborhoods. In addition, there are many potential challenges in providing care to rural patients with chronic kidney disease including long travel times and sparse renal services such as transplant and dialysis centers. Geospatially fluent analytic approaches can also inform system level analyses of health care systems and these approaches can be applied to identify an optimal distribution of dialysis facilities. GIS analysis could help untangle the complex interplay between geography, socioeconomic status, and racial disparities in chronic kidney disease, and could inform policy decisions and resource allocation as the population ages and the prevalence of renal disease increases.

Primary Stroke Centers Should Be Located Using Maximal Coverage Models for Optimal Access

Background and Purpose—

The current self-initiated approach by which hospitals acquire Primary Stroke Center (PSC) certification provides insufficient coverage for large areas of the United States. An alternative, directed, algorithmic approach to determine near optimal locations of PSCs would be justified if it significantly improves coverage.

Methods—

Using geographic location–allocation modeling techniques, we developed a universal web-based calculator for selecting near optimal PSC locations designed to maximize the population coverage in any state. We analyzed the current PSC network population coverage in Iowa and compared it with the coverage that would exist if a maximal coverage model had instead been used to place those centers. We then estimated the expected gains in population coverage if additional PSCs follow the current self-initiated model and compared it against the more efficient coverage expected by use of a maximal coverage model to select additional locations.

Results—

The existing 12 self-initiated PSCs in Iowa cover 37% of the population, assuming a time–distance radius of 30 minutes. The current population coverage would have been 47.5% if those 12 PSCs had been located using a maximal coverage model. With the current self-initiated approach, 54 additional PSCs on average will be needed to improve coverage to 75% of the population. Conversely, only 31 additional PSCs would be needed to achieve the same degree of population coverage if a maximal coverage model is used.

Conclusion—

Given the substantial gain in population access to adequate acute stroke care, it appears justified to direct the location of additional PSCs or recombinant tissue-type plasminogen activator-capable hospitals through a maximal coverage model algorithmic approach.

Rural disparity in domestic violence prevalence and access to resources

OBJECTIVE

Intimate partner violence (IPV) against women is a significant health issue in the United States and worldwide. The majority of studies on IPV have been conducted in urban populations. The objectives of this study are to determine if prevalence, frequency, and severity of IPV differ by rurality and to identify variance in geographic access to IPV resources.

METHODS

A cross-sectional clinic-based survey of 1478 women was conducted to measure the 1-year prevalence of physical, sexual, and psychologic IPV. IPV intervention programs in the state were inventoried and mapped, and the distance to the closest program was estimated for each participant based on an innovative algorithm developed for use when only ZIP code location is available.

RESULTS

Women in small rural and isolated areas reported the highest prevalence of IPV (22.5% and 17.9%, respectively) compared to 15.5% for urban women. Rural women reported significantly higher severity of physical abuse than their urban counterparts. The mean distance to the nearest IPV resource was three times greater for rural women than for urban women, and rural IPV programs served more counties and had fewer on-site shelter services. Over 25% of women in small rural and isolated areas lived >40 miles from the closest program, compared with <1% of women living in urban areas.

CONCLUSIONS

Rural women experience higher rates of IPV and greater frequency and severity of physical abuse yet live much farther away from available resources. More IPV resources and interventions targeting rural women are needed.

A spatial analysis of variations in health access: linking geography, socio-economic status and access perceptions

Background

This paper analyses the relationship between public perceptions of access to general practitioners (GPs) surgeries and hospitals against health status, car ownership and geographic distance. In so doing it explores the different dimensions associated with facility access and accessibility.

Methods

Data on difficulties experienced in accessing health services, respondent health status and car ownership were collected through an attitudes survey. Road distances to the nearest service were calculated for each respondent using a GIS. Difficulty was related to geographic distance, health status and car ownership using logistic generalized linear models. A Geographically Weighted Regression (GWR) was used to explore the spatial non-stationarity in the results.

Results

Respondent long term illness, reported bad health and non-car ownership were found to be significant predictors of difficulty in accessing GPs and hospitals. Geographic distance was not a significant predictor of difficulty in accessing hospitals but was for GPs. GWR identified the spatial (local) variation in these global relationships indicating locations where the predictive strength of the independent variables was higher or lower than the global trend. The impacts of bad health and non-car ownership on the difficulties experienced in accessing health services varied spatially across the study area, whilst the impacts of geographic distance did not.

Conclusions

Difficulty in accessing different health facilities was found to be significantly related to health status and car ownership, whilst the impact of geographic distance depends on the service in question. GWR showed how these relationships were varied across the study area. This study demonstrates that the notion of access is a multi-dimensional concept, whose composition varies with location, according to the facility being considered and the health and socio-economic status of the individual concerned.