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1.
Int J Cancer ; 147(3): 887-896, 2020 08 01.
Artigo em Inglês | MEDLINE | ID: mdl-31837006

RESUMO

Cervical cancer is widely preventable through screening, but little is known about the duration of protection offered by a negative screen in North America. A case-control study was conducted with records from population-based registries in New Mexico. Cases were women diagnosed with cervical cancer in 2006-2016, obtained from the Tumor Registry. Five controls per case from the New Mexico HPV Pap Registry were matched to cases by sex, age and place of residence. Dates and results of all cervical screening and diagnostic tests since 2006 were identified from the pap registry. We estimated the odds ratio of nonlocalized (Stage II+) and localized (Stage I) cervical cancer associated with attending screening in the 3 years prior to case-diagnosis compared to women not screened in 5 years. Of 876 cases, 527 were aged 25-64 years with ≥3 years of potential screening data. Only 38% of cases and 61% of controls attended screening in a 3-year period. Women screened in the 3 years prior to diagnosis had 83% lower risk of nonlocalized cancer (odds ratio [OR] = 0.17, 95% CI: 0.12-0.24) and 48% lower odds of localized cancer (OR = 0.52, 95% CI: 0.38-0.72), compared to women not screened in the 5 years prior to diagnosis. Women remained at low risk of nonlocalized cancer for 3.5-5 years after a negative screen compared to women with no negative screens in the 5 years prior to diagnosis. Routine cervical screening is effective at preventing localized and nonlocalized cervical cancers; 3 yearly screening prevents 83% of nonlocalized cancers, with no additional benefit of more frequent screening. Increasing screening coverage remains essential to further reduce cervical cancer incidence.


Assuntos
Detecção Precoce de Câncer/estatística & dados numéricos , Neoplasias do Colo do Útero/epidemiologia , Esfregaço Vaginal/estatística & dados numéricos , Adulto , Estudos de Casos e Controles , Feminino , Humanos , Incidência , Pessoa de Meia-Idade , New Mexico/epidemiologia , Teste de Papanicolaou , Sistema de Registros , Neoplasias do Colo do Útero/prevenção & controle , Adulto Jovem
2.
Gynecol Oncol ; 159(2): 344-353, 2020 11.
Artigo em Inglês | MEDLINE | ID: mdl-32977987

RESUMO

OBJECTIVE: Despite widespread cervical screening, an estimated 13,800 women will be diagnosed with cervical cancer in the United States in 2020. To inform improvements, the screening histories of women diagnosed with cervical cancer in New Mexico were assessed. METHODS: Data were collected on all cervical screening, diagnostic tests and treatment procedures for all women diagnosed with cervical cancer aged 25-64 yrs. in New Mexico from 2006 to 2016. Women were categorized by their screening attendance in the 5-40 months (screening interval) and 1-4 months (peri-diagnostic interval) prior to cancer diagnosis. RESULTS: Of the 504 women diagnosed between May 2009-December 2016, 64% were not screened or had only inadequate screening tests in the 5-40 months prior to diagnosis, and 90 of 182 screened women (49%) had only negative screens in this period. Only 32% (N = 162) of cervical cancers were screen-detected. Women with adenocarcinomas were more likely to have had a recent negative screen (41/57 = 722%) than women with squamous cancers (50/112 = 45%). Both older women (aged 45-64 years) and women with more advanced cancers were less likely to have been screened, and if screened, were more likely to have a false-negative outcome. Only 9% of cancers were diagnosed in women who did not attend biopsy or treatment after positive tests requiring clinical management. Screening currently prevents 35% of cancers, whereas full screening coverage could prevent 61% of cervical cancers. CONCLUSION: Improved screening coverage has the largest potential for reducing cervical cancer incidence, though there is also a role for improved recall procedures and screening sensitivity.


Assuntos
Adenocarcinoma/epidemiologia , Carcinoma de Células Escamosas/epidemiologia , Programas de Rastreamento/estatística & dados numéricos , Neoplasias do Colo do Útero/epidemiologia , Adenocarcinoma/diagnóstico , Adulto , Carcinoma de Células Escamosas/diagnóstico , Detecção Precoce de Câncer/normas , Reações Falso-Negativas , Feminino , Humanos , Programas de Rastreamento/métodos , Pessoa de Meia-Idade , New Mexico/epidemiologia , Sistema de Registros , Neoplasias do Colo do Útero/diagnóstico
3.
Cancer ; 125(15): 2544-2560, 2019 08 01.
Artigo em Inglês | MEDLINE | ID: mdl-31145834

RESUMO

Maps are well recognized as an effective means of presenting and communicating health data, such as cancer incidence and mortality rates. These data can be linked to geographic features like counties or census tracts and their associated attributes for mapping and analysis. Such visualization and analysis provide insights regarding the geographic distribution of cancer and can be important for advancing effective cancer prevention and control programs. Applying a spatial approach allows users to identify location-based patterns and trends related to risk factors, health outcomes, and population health. Geographic information science (GIScience) is the discipline that applies Geographic Information Systems (GIS) and other spatial concepts and methods in research. This review explores the current state and evolution of GIScience in cancer research by addressing fundamental topics and issues regarding spatial data and analysis that need to be considered. GIScience, along with its health-specific application in the spatial epidemiology of cancer, incorporates multiple geographic perspectives pertaining to the individual, the health care infrastructure, and the environment. Challenges addressing these perspectives and the synergies among them can be explored through GIScience methods and associated technologies as integral parts of epidemiologic research, analysis efforts, and solutions. The authors suggest GIScience is a powerful tool for cancer research, bringing additional context to cancer data analysis and potentially informing decision-making and policy, ultimately aimed at reducing the burden of cancer.


Assuntos
Monitoramento Epidemiológico , Sistemas de Informação Geográfica/normas , Neoplasias/epidemiologia , Humanos
6.
Int J Health Geogr ; 14: 26, 2015 Sep 15.
Artigo em Inglês | MEDLINE | ID: mdl-26370237

RESUMO

BACKGROUND: The utility of patient attributes associated with the spatiotemporal analysis of medical records lies not just in their values but also the strength of association between them. Estimating the extent to which a hierarchy of conditional probability exists between patient attribute associations such as patient identifying fields, patient and date of diagnosis, and patient and address at diagnosis is fundamental to estimating the strength of association between patient and geocode, and patient and enumeration area. We propose a hierarchy for the attribute associations within medical records that enable spatiotemporal relationships. We also present a set of metrics that store attribute association error probability (AAEP), to estimate error probability for all attribute associations upon which certainty in a patient geocode depends. METHODS: A series of experiments were undertaken to understand how error estimation could be operationalized within health data and what levels of AAEP in real data reveal themselves using these methods. Specifically, the goals of this evaluation were to (1) assess if the concept of our error assessment techniques could be implemented by a population-based cancer registry; (2) apply the techniques to real data from a large health data agency and characterize the observed levels of AAEP; and (3) demonstrate how detected AAEP might impact spatiotemporal health research. RESULTS: We present an evaluation of AAEP metrics generated for cancer cases in a North Carolina county. We show examples of how we estimated AAEP for selected attribute associations and circumstances. We demonstrate the distribution of AAEP in our case sample across attribute associations, and demonstrate ways in which disease registry specific operations influence the prevalence of AAEP estimates for specific attribute associations. CONCLUSIONS: The effort to detect and store estimates of AAEP is worthwhile because of the increase in confidence fostered by the attribute association level approach to the assessment of uncertainty in patient geocodes, relative to existing geocoding related uncertainty metrics.


Assuntos
Viés , Confiabilidade dos Dados , Mapeamento Geográfico , Prontuários Médicos , Registro Médico Coordenado , Prontuários Médicos/estatística & dados numéricos , North Carolina , Probabilidade , Sistema de Registros , Análise de Regressão
7.
Int J Health Geogr ; 12: 50, 2013 Nov 08.
Artigo em Inglês | MEDLINE | ID: mdl-24207169

RESUMO

BACKGROUND: Geocoding, the process of converting textual information describing a location into one or more digital geographic representations, is a routine task performed at large organizations and government agencies across the globe. In a health context, this task is often a fundamental first step performed prior to all operations that take place in a spatially-based health study. As such, the quality of the geocoding system used within these agencies is of paramount concern to the agency (the producer) and researchers or policy-makers who wish to use these data (consumers). However, geocoding systems are continually evolving with new products coming on the market continuously. Agencies must develop and use criteria across a number axes when faced with decisions about building, buying, or maintaining any particular geocoding systems. To date, published criteria have focused on one or more aspects of geocode quality without taking a holistic view of a geocoding system's role within a large organization. The primary purpose of this study is to develop and test an evaluation framework to assist a large organization in determining which geocoding systems will meet its operational needs. METHODS: A geocoding platform evaluation framework is derived through an examination of prior literature on geocoding accuracy. The framework developed extends commonly used geocoding metrics to take into account the specific concerns of large organizations for which geocoding is a fundamental operational capability tightly-knit into its core mission of processing health data records. A case study is performed to evaluate the strengths and weaknesses of five geocoding platforms currently available in the Australian geospatial marketplace. RESULTS: The evaluation framework developed in this research is proven successful in differentiating between key capabilities of geocoding systems that are important in the context of a large organization with significant investments in geocoding resources. Results from the proposed methodology highlight important differences across all axes of geocoding system comparisons including spatial data output accuracy, reference data coverage, system flexibility, the potential for tight integration, and the need for specialized staff and/or development time and funding. Such results can empower decisions-makers within large organizations as they make decisions and investments in geocoding systems.


Assuntos
Bases de Dados Factuais/normas , Sistemas de Informação Geográfica/normas , Mapeamento Geográfico , Humanos , Austrália Ocidental/epidemiologia
8.
Geogr Anal ; 2022 Jul 09.
Artigo em Inglês | MEDLINE | ID: mdl-35941845

RESUMO

Sufficient and reliable health care access is necessary for people to be able to maintain good health. Hence, investigating the uncertainty embedded in the temporal changes of inputs would be beneficial for understanding their impact on spatial accessibility. However, previous studies are limited to implementing only the uncertainty of mobility, while health care resource availability is a significant concern during the coronavirus disease (COVID-19) pandemic. Our study examined the stochastic distribution of spatial accessibility under the uncertainties underlying the availability of intensive care unit (ICU) beds and ease of mobility in the Greater Houston area of Texas. Based on the randomized supply and mobility from their historical changes, we employed Monte Carlo simulation to measure ICU bed accessibility with an enhanced two-step floating catchment area (E2SFCA) method. We then conducted hierarchical clustering to classify regions of adequate (sufficient and reliable) accessibility and inadequate (insufficient and unreliable) accessibility. Lastly, we investigated the relationship between the accessibility measures and the case fatality ratio of COVID-19. As result, locations of sufficient access also had reliable accessibility; downtown and outer counties, respectively, had adequate and inadequate accessibility. We also raised the possibility that inadequate health care accessibility may cause higher COVID-19 fatality ratios.

9.
J Community Health ; 36(6): 933-42, 2011 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-21461957

RESUMO

Recent studies have produced inconsistent results in their examination of the potential association between proximity to healthcare or mammography facilities and breast cancer stage at diagnosis. Using a multistate dataset, we re-examine this issue by investigating whether travel time to a patient's diagnosing facility or nearest mammography facility impacts breast cancer stage at diagnosis. We studied 161,619 women 40 years and older diagnosed with invasive breast cancer from ten state population based cancer registries in the United States. For each woman, we calculated travel time to their diagnosing facility and nearest mammography facility. Logistic multilevel models of late versus early stage were fitted, and odds ratios were calculated for travel times, controlling for age, race/ethnicity, census tract poverty, rural/urban residence, health insurance, and state random effects. Seventy-six percent of women in the study lived less than 20 min from their diagnosing facility, and 93 percent lived less than 20 min from the nearest mammography facility. Late stage at diagnosis was not associated with increasing travel time to diagnosing facility or nearest mammography facility. Diagnosis age under 50, Hispanic and Non-Hispanic Black race/ethnicity, high census tract poverty, and no health insurance were all significantly associated with late stage at diagnosis. Travel time to diagnosing facility or nearest mammography facility was not a determinant of late stage of breast cancer at diagnosis, and better geographic proximity did not assure more favorable stage distributions. Other factors beyond geographic proximity that can affect access should be evaluated more closely, including facility capacity, insurance acceptance, public transportation, and travel costs.


Assuntos
Neoplasias da Mama/patologia , Acessibilidade aos Serviços de Saúde/estatística & dados numéricos , Seguro Saúde/estatística & dados numéricos , Mamografia/estatística & dados numéricos , Idoso , Neoplasias da Mama/diagnóstico , Neoplasias da Mama/epidemiologia , Diagnóstico Tardio/estatística & dados numéricos , Feminino , Acessibilidade aos Serviços de Saúde/economia , Disparidades nos Níveis de Saúde , Humanos , Cobertura do Seguro/economia , Cobertura do Seguro/estatística & dados numéricos , Seguro Saúde/economia , Modelos Logísticos , Mamografia/economia , Pessoa de Meia-Idade , Estadiamento de Neoplasias , Pobreza , Sistema de Registros , Fatores de Tempo , Viagem/economia , Viagem/estatística & dados numéricos , Estados Unidos/epidemiologia
10.
Geohealth ; 5(12): e2021GH000430, 2021 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-34859166

RESUMO

While the spatial resolution of exposure surfaces has greatly improved, our ability to locate people in space remains a limiting factor in accurate exposure assessment. In this case-control study, two approaches to geocoding participant locations were used to study the impact of geocoding uncertainty on the estimation of ambient pesticide exposure and breast cancer risk among women living in California's Central Valley. Residential and occupational histories were collected and geocoded using a traditional point-based method along with a novel area-based method. The standard approach to geocoding uses centroid points to represent all geocoded locations, and is unable to adapt exposure areas based on geocode quality, except through the exclusion of low-certainty locations. In contrast, area-based geocoding retains the complete area to which an address matched (the same area from which the centroid is returned), and therefore maintains the appropriate level of precision when it comes to assessing exposure by geography. Incorporating the total potential exposure area for each geocoded location resulted in different exposure classifications and resulting odds ratio estimates than estimates derived from the centroids of those same areas (using a traditional point-based geocoder). The direction and magnitude of these differences varied by pesticide, but in all cases odds ratios differed by at least 6% and up to 35%. These findings demonstrate the importance of geocoding in exposure estimation and suggest it is important to consider geocode certainty and quality throughout exposure assessment, rather than simply using the best available point geocodes.

11.
Prehosp Disaster Med ; 36(2): 135-140, 2021 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-33517947

RESUMO

INTRODUCTION: Hurricane Harvey (2017) forced the closure of hemodialysis centers across Harris County, Texas (USA) disrupting the provision of dialysis services. This study aims to estimate the percentage of hemodialysis clinics flooded after Harvey, to identify the proportion of such clinics located in high-risk flood zones, and to assess the sensitivity of the Federal Emergency Management Agency (FEMA) Flood Insurance Rate Maps (FIRMs) for estimation of flood risk. METHODS: Data on 124 hemodialysis clinics in Harris County were extracted from Medicare.gov and geocoded using ArcGIS Online. The FIRMs were overlaid to identify the flood zone designation of each hemodialysis clinic. RESULTS: Twenty-one percent (26 of 124) of hemodialysis clinics in Harris County flooded after Harvey. Of the flooded clinics, 57.7% were in a high-risk flood zone, 30.8% were within 1km of a high-risk flood zone, and 11.5% were not in or near a high-risk flood zone. The FIRMs had a sensitivity of 58%, misidentifying 42% (11 of 26) of the clinics flooded. CONCLUSION: Hurricanes are associated with severe disruptions of medical services, including hemodialysis. With one-quarter of Harris County in the 100-year floodplain, projected increases in the frequency and severity of disasters, and inadequate updates of flood zone designation maps, the implementation of new regulations that address the development of hemodialysis facilities in high-risk flood areas should be considered.


Assuntos
Tempestades Ciclônicas , Desastres , Idoso , Inundações , Humanos , Medicare , Diálise Renal , Estados Unidos
12.
Sci Rep ; 10(1): 21753, 2020 12 10.
Artigo em Inglês | MEDLINE | ID: mdl-33303896

RESUMO

Identifying emergent patterns of coronavirus disease 2019 (COVID-19) at the local level presents a geographic challenge. The need is not only to integrate multiple data streams from different sources, scales, and cadences, but to also identify meaningful spatial patterns in these data, especially in vulnerable settings where even small numbers and low rates are important to pinpoint for early intervention. This paper identifies a gap in current analytical approaches and presents a near-real time assessment of emergent disease that can be used to guide a local intervention strategy: Geographic Monitoring for Early Disease Detection (GeoMEDD). Through integration of a spatial database and two types of clustering algorithms, GeoMEDD uses incoming test data to provide multiple spatial and temporal perspectives on an ever changing disease landscape by connecting cases using different spatial and temporal thresholds. GeoMEDD has proven effective in revealing these different types of clusters, as well as the influencers and accelerators that give insight as to why a cluster exists where it does, and why it evolves, leading to the saving of lives through more timely and geographically targeted intervention.


Assuntos
Algoritmos , COVID-19/epidemiologia , Bases de Dados Factuais , Monitoramento Epidemiológico , Sistemas de Informação Geográfica , Pandemias , SARS-CoV-2 , Humanos
13.
Int J Health Geogr ; 7: 60, 2008 Nov 26.
Artigo em Inglês | MEDLINE | ID: mdl-19032791

RESUMO

BACKGROUND: The process of geocoding produces output coordinates of varying degrees of quality. Previous studies have revealed that simply excluding records with low-quality geocodes from analysis can introduce significant bias, but depending on the number and severity of the inaccuracies, their inclusion may also lead to bias. Little quantitative research has been presented on the cost and/or effectiveness of correcting geocodes through manual interactive processes, so the most cost effective methods for improving geocoded data are unclear. The present work investigates the time and effort required to correct geocodes contained in five health-related datasets that represent examples of data commonly used in Health GIS. RESULTS: Geocode correction was attempted on five health-related datasets containing a total of 22,317 records. The complete processing of these data took 11.4 weeks (427 hours), averaging 69 seconds of processing time per record. Overall, the geocodes associated with 12,280 (55%) of records were successfully improved, taking 95 seconds of processing time per corrected record on average across all five datasets. Geocode correction improved the overall match rate (the number of successful matches out of the total attempted) from 79.3 to 95%. The spatial shift between the location of original successfully matched geocodes and their corrected improved counterparts averaged 9.9 km per corrected record. After geocode correction the number of city and USPS ZIP code accuracy geocodes were reduced from 10,959 and 1,031 to 6,284 and 200, respectively, while the number of building centroid accuracy geocodes increased from 0 to 2,261. CONCLUSION: The results indicate that manual geocode correction using a web-based interactive approach is a feasible and cost effective method for improving the quality of geocoded data. The level of effort required varies depending on the type of data geocoded. These results can be used to choose between data improvement options (e.g., manual intervention, pseudocoding/geo-imputation, field GPS readings).


Assuntos
Interpretação Estatística de Dados , Bases de Dados Factuais/normas , Sistemas de Informação Geográfica/normas , Bases de Dados Factuais/estatística & dados numéricos , Sistemas de Informação Geográfica/estatística & dados numéricos , Humanos , Fatores de Risco
14.
Geospat Health ; 12(1): 526, 2017 05 11.
Artigo em Inglês | MEDLINE | ID: mdl-28555477

RESUMO

Geocoding is the science and process of assigning geographical coordinates (i.e. latitude, longitude) to a postal address. The quality of the geocode can vary dramatically depending on several variables, including incorrect input address data, missing address components, and spelling mistakes. A dataset with a considerable number of geocoding inaccuracies can potentially result in an imprecise analysis and invalid conclusions. There has been little quantitative analysis of the amount of effort (i.e. time) to perform geocoding correction, and how such correction could improve geocode quality type. This study used a low-cost and easy to implement method to improve geocode quality type of an input database (i.e. addresses to be matched) through the processes of manual geocode intervention, and it assessed the amount of effort to manually correct inaccurate geocodes, reported the resulting match rate improvement between the original and the corrected geocodes, and documented the corresponding spatial shift by geocode quality type resulting from the corrections. Findings demonstrated that manual intervention of geocoding resulted in a 90% improvement of geocode quality type, took 42 hours to process, and the spatial shift ranged from 0.02 to 151,368 m. This study provides evidence to inform research teams considering the application of manual geocoding intervention that it is a low-cost and relatively easy process to execute.


Assuntos
Mapeamento Geográfico , Bases de Dados Factuais , Humanos
15.
J Rural Health ; 33(4): 382-392, 2017 09.
Artigo em Inglês | MEDLINE | ID: mdl-27557124

RESUMO

PURPOSE: Multiple intrapersonal and structural barriers, including geography, may prevent women from engaging in cervical cancer preventive care such as screening, diagnostic colposcopy, and excisional precancer treatment procedures. Geographic accessibility, stratified by rural and nonrural areas, to necessary services across the cervical cancer continuum of preventive care is largely unknown. METHODS: Health care facility data for New Mexico (2010-2012) was provided by the New Mexico Human Papillomavirus Pap Registry (NMHPVPR), the first population-based statewide cervical cancer screening registry in the United States. Travel distance and time between the population-weighted census tract centroid to the nearest facility providing screening, diagnostic, and excisional treatment services were examined using proximity analysis by rural and nonrural census tracts. Mann-Whitney test (P < .05) was used to determine if differences were significant and Cohen's r to measure effect. FINDINGS: Across all cervical cancer preventive health care services and years, women who resided in rural areas had a significantly greater geographic accessibility burden when compared to nonrural areas (4.4 km vs 2.5 km and 4.9 minutes vs 3.0 minutes for screening; 9.9 km vs 4.2 km and 10.4 minutes vs 4.9 minutes for colposcopy; and 14.8 km vs 6.6 km and 14.4 minutes vs 7.4 minutes for precancer treatment services, all P < .001). CONCLUSION: Improvements in cervical cancer prevention should address the potential benefits of providing the full spectrum of screening, diagnostic and precancer treatment services within individual facilities. Accessibility, assessments distinguishing rural and nonrural areas are essential when monitoring and recommending changes to service infrastructures (eg, mobile versus brick and mortar).


Assuntos
Acessibilidade aos Serviços de Saúde/normas , Medição de Risco/métodos , População Rural/estatística & dados numéricos , Neoplasias do Colo do Útero/prevenção & controle , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Detecção Precoce de Câncer/normas , Detecção Precoce de Câncer/estatística & dados numéricos , Feminino , Geografia , Humanos , Programas de Rastreamento/métodos , Programas de Rastreamento/estatística & dados numéricos , Pessoa de Meia-Idade , New Mexico/epidemiologia , Estatísticas não Paramétricas , População Urbana/estatística & dados numéricos , Neoplasias do Colo do Útero/epidemiologia
16.
Health Place ; 21: 110-21, 2013 May.
Artigo em Inglês | MEDLINE | ID: mdl-23454732

RESUMO

This study evaluated independent and joint effects of census tract (CT) poverty and geographic access to mammography on stage at diagnosis for breast cancer. The study included 161,619 women 40+ years old diagnosed with breast cancer between 2004 -2006 in ten participating US states. Multilevel logistic regression was used to estimate the odds of late-stage breast cancer diagnosis for the entire study population and by state. Poverty was independently associated with late-stage in the overall population (poverty rates >20% OR=1.30, 95% CI=1.26- 1.35) and for 9 of the 10 states. Geographic access was not associated with late-stage diagnosis after adjusting for CT poverty. State-specific analysis provided little evidence that geographic access was associated with breast cancer stage at diagnosis, and after adjusting for poverty, geographic access mattered in only 1 state. Overall, compared to women with private insurance, the adjusted odds ratios for late stage at diagnosis among women with either no insurance, Medicaid, or Medicare were 1.80 (95% CI = 1.65, 1.96), 1.75 (95% CI = 1.68, 1.84), and 1.05 (95% CI 1.01, 1.08), respectively. Although geographic access to mammography was not a significant predictor of late-stage breast cancer diagnosis, women in high poverty areas or uninsured are at greatest risk of being diagnosed with late-stage breast cancer regardless of geographic location and may benefit from targeted interventions.


Assuntos
Neoplasias da Mama/epidemiologia , Diagnóstico Tardio/estatística & dados numéricos , Acessibilidade aos Serviços de Saúde/estatística & dados numéricos , Mamografia/estatística & dados numéricos , Áreas de Pobreza , Adulto , Neoplasias da Mama/diagnóstico , Feminino , Geografia Médica , Humanos , Cobertura do Seguro/estatística & dados numéricos , Seguro Saúde/estatística & dados numéricos , Medicaid/estatística & dados numéricos , Pessoas sem Cobertura de Seguro de Saúde/estatística & dados numéricos , Medicare/estatística & dados numéricos , Pessoa de Meia-Idade , Pobreza/estatística & dados numéricos , Estados Unidos/epidemiologia
17.
Spat Spatiotemporal Epidemiol ; 3(1): 39-54, 2012 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-22469490

RESUMO

Geocoding is often used to produce maps of disease rates from the diagnosis addresses of incident cases to assist with disease surveillance, prevention, and control. In this process, diagnosis addresses are converted into latitude/longitude pairs which are then aggregated to produce rates at varying geographic scales such as Census tracts, neighborhoods, cities, counties, and states. The specific techniques used within geocoding systems have an impact on where the output geocode is located and can therefore have an effect on the derivation of disease rates at different geographic aggregations. This paper investigates how county-level cancer rates are affected by the choice of interpolation method when case data are geocoded to the ZIP code level. Four commonly used areal unit interpolation techniques are applied and the output of each is used to compute crude county-level five-year incidence rates of all cancers in California. We found that the rates observed for 44 out of the 58 counties in California vary based on which interpolation method is used, with rates in some counties increasing by nearly 400% between interpolation methods.


Assuntos
Projetos de Pesquisa Epidemiológica , Mapeamento Geográfico , Neoplasias/epidemiologia , California/epidemiologia , Interpretação Estatística de Dados , Humanos
18.
Breast ; 20(4): 324-8, 2011 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-21440439

RESUMO

PURPOSE: Women with early stage breast cancer who live far from a radiation therapy facility may be more likely to opt for mastectomy over breast conserving surgery (BCS). The geographic dimensions of this relationship deserve further scrutiny. METHODS: For over 100,000 breast cancer patients in 10 states who received either mastectomy or BCS, a newly-developed software tool was used to calculate the shortest travel distance to the location of surgery and to the nearest radiation treatment center. The likelihood of receipt of mastectomy was modeled as a function of these distance measures and other demographic variables using multilevel logistic regression. RESULTS: Women traveling over 75 km for treatment are about 1.4 times more likely to receive a mastectomy than those traveling under 15 km. CONCLUSIONS: Geographic barriers to optimal breast cancer treatment remain a valid concern, though most women traveling long distances to receive mastectomies are doing so after bypassing local options.


Assuntos
Neoplasias da Mama/radioterapia , Neoplasias da Mama/cirurgia , Acessibilidade aos Serviços de Saúde/estatística & dados numéricos , Mastectomia/estatística & dados numéricos , Viagem/estatística & dados numéricos , Saúde da Mulher , Adulto , Idoso , Neoplasias da Mama/patologia , Comportamento de Escolha , Feminino , Humanos , Mastectomia Segmentar/estatística & dados numéricos , Pessoa de Meia-Idade , Estadiamento de Neoplasias , Características de Residência , Estados Unidos
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