Travel time and distance to health care only partially account for the ethnic inequalities in cervical cancer stage at diagnosis and mortality in New Zealand

Brewer, Naomi; Pearce, Neil; Day, Peter; Borman, Barry

doi:10.1111/j.1753-6405.2012.00843.x

Cited by 15 publications

(14 citation statements)

References 27 publications

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“…Since our study is the first to describe distance and time to all services across the continuum of cervical cancer preventive care, we do not have comparative measures. The most similar cervical cancer research study to our work examined travel distance and travel time to the nearest general practitioner and the nearest cancer center . Our data are in agreement with Brewer and colleagues who reported a median distance to the nearest cancer center facility, which would be equipped to perform diagnostic and excisional precancer treatment services for cervical cancer prevention, as 21 km compared to less than 1 km for a general practice facility that would predominantly provide cervical cancer screening services.…”

Section: Discussionsupporting

confidence: 90%

Health Service Accessibility and Risk in Cervical Cancer Prevention: Comparing Rural Versus Nonrural Residence in New Mexico

McDonald

Goldberg

Scarinci

et al. 2016

The Journal of Rural Health

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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).

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Section: Discussionsupporting

confidence: 90%

Health Service Accessibility and Risk in Cervical Cancer Prevention: Comparing Rural Versus Nonrural Residence in New Mexico

McDonald

Goldberg

Scarinci

et al. 2016

The Journal of Rural Health

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“…There were differences in the patient origins and healthcare destinations used to determine the patient journeys. The majority used the patients’ address (full address/postcode/zip code) as the origin for the journey, but others used the centroids of larger geographical areas19 34 62 90 or the referring hospital72 or the city of residence 116. It was recognised that for the longitudinal studies, there was a potential for patients to move addresses, but no studies used differing residential locations where people moved house to calculate the distances and travel times.…”

Section: Resultsmentioning

confidence: 99%

“…This has the potential to underestimate the impact of distance/travel times on health outcomes—where patients are potentially making multiple trips to a range of hospitals over the course of the year for a range of health issues. In an attempt to be more representative of the travel burden, Brewer et al 19 used the follow-up radiation centre address as the destination for patients rather than the place they had the surgery, as they argued patients would have to make this journey more frequently. Studies such as Jones et al 38 considered the impact of a range of potential healthcare settings (eg, distance to the nearest cancer centre, general practitioner (GP) and hospital of first referral).…”

Section: Discussionmentioning

confidence: 99%

Are differences in travel time or distance to healthcare for adults in global north countries associated with an impact on health outcomes? A systematic review

et al. 2016

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ObjectivesTo investigate whether there is an association between differences in travel time/travel distance to healthcare services and patients' health outcomes and assimilate the methodologies used to measure this.DesignSystematic Review. We searched MEDLINE, Embase, Web of Science, Transport database, HMIC and EBM Reviews for studies up to 7 September 2016. Studies were excluded that included children (including maternity), emergency medical travel or countries classed as being in the global south.SettingsA wide range of settings within primary and secondary care (these were not restricted in the search).Results108 studies met the inclusion criteria. The results were mixed. 77% of the included studies identified evidence of a distance decay association, whereby patients living further away from healthcare facilities they needed to attend had worse health outcomes (eg, survival rates, length of stay in hospital and non-attendance at follow-up) than those who lived closer. 6 of the studies identified the reverse (a distance bias effect) whereby patients living at a greater distance had better health outcomes. The remaining 19 studies found no relationship. There was a large variation in the data available to the studies on the patients' geographical locations and the healthcare facilities attended, and the methods used to calculate travel times and distances were not consistent across studies.ConclusionsThe review observed that a relationship between travelling further and having worse health outcomes cannot be ruled out and should be considered within the healthcare services location debate.

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“…These agencies do not generally publicly release FTE GP data at scales smaller than that of the state which are of limited if any use at all in a geographic analysis [21], although very occasionally data at fine scales are released on specific request for some research [9,22] and reports [23]. Contrast this, for example, with the CIHI database in Canada and the resulting research [16,17], research with US-AMA data [10,11,51,52] in the United states or GP data in New Zealand [53,54]. …”

Section: Discussionmentioning

confidence: 99%

General practitioner (family physician) workforce in Australia: comparing geographic data from surveys, a mailing list and medicare

Mazumdar

Konings

Butler

et al. 2013

BMC Health Serv Res

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BackgroundGood quality spatial data on Family Physicians or General Practitioners (GPs) are key to accurately measuring geographic access to primary health care. The validity of computed associations between health outcomes and measures of GP access such as GP density is contingent on geographical data quality. This is especially true in rural and remote areas, where GPs are often small in number and geographically dispersed. However, there has been limited effort in assessing the quality of nationally comprehensive, geographically explicit, GP datasets in Australia or elsewhere.Our objective is to assess the extent of association or agreement between different spatially explicit nationwide GP workforce datasets in Australia. This is important since disagreement would imply differential relationships with primary healthcare relevant outcomes with different datasets. We also seek to enumerate these associations across categories of rurality or remoteness.MethodWe compute correlations of GP headcounts and workload contributions between four different datasets at two different geographical scales, across varying levels of rurality and remoteness.ResultsThe datasets are in general agreement with each other at two different scales. Small numbers of absolute headcounts, with relatively larger fractions of locum GPs in rural areas cause unstable statistical estimates and divergences between datasets.ConclusionIn the Australian context, many of the available geographic GP workforce datasets may be used for evaluating valid associations with health outcomes. However, caution must be exercised in interpreting associations between GP headcounts or workloads and outcomes in rural and remote areas. The methods used in these analyses may be replicated in other locales with multiple GP or physician datasets.

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Travel time and distance to health care only partially account for the ethnic inequalities in cervical cancer stage at diagnosis and mortality in New Zealand

Cited by 15 publications

References 27 publications

Health Service Accessibility and Risk in Cervical Cancer Prevention: Comparing Rural Versus Nonrural Residence in New Mexico

Health Service Accessibility and Risk in Cervical Cancer Prevention: Comparing Rural Versus Nonrural Residence in New Mexico

Are differences in travel time or distance to healthcare for adults in global north countries associated with an impact on health outcomes? A systematic review

General practitioner (family physician) workforce in Australia: comparing geographic data from surveys, a mailing list and medicare

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