Search

Introduction: Rural‐urban health inequities, exacerbated by deprivation and ethnicity, have been clearly described in the international literature. To date, the same inequities have not been as clearly demonstrated in Aotearoa New Zealand despite the lower socioeconomic status and higher proportion of Māori living in rural towns. This is ascribed by many health practitioners, academics and other informed stakeholders to be the result of the definitions of 'rural' used to produce statistics. Aims: To outline a protocol to produce a 'fit‐for‐health purpose' rural‐urban classification for analysing national health data. The classification will be designed to determine the magnitude of health inequities that have been obscured by use of inappropriate rural‐urban taxonomies. Methods: This protocol paper outlines our proposed mixed‐methods approach to developing a novel Geographic Classification for Health. In phase 1, an agreed set of community attributes will be used to modify the new Statistics New Zealand Urban Accessibility Classification into a more appropriate classification of rurality for health contexts. The Geographic Classification for Health will then be further developed in an iterative process with stakeholders including rural health researchers and members of the National Rural Health Advisory Group, who have a comprehensive 'on the ground' understanding of Aotearoa New Zealand's rural communities and their attendant health services. This protocol also proposes validating the Geographic Classification for Health using general practice enrolment data. In phase 2, the resulting Geographic Classification for Health will be applied to routinely collected data from the Ministry of Health. This will enable current levels of rural‐urban inequity in health service access and outcomes to be accurately assessed and give an indication of the extent to which older classifications were masking inequities. [ABSTRACT FROM AUTHOR]

Objective In 2008, Oamaru Hospital became the second rural hospital in New Zealand to install a computed tomography ( CT) scanner. This article assesses the impact of this on local CT scanning rates. Design Observational: review of radiology department data. Setting Rural hospital imaging services. Participants CT scanning patients residing in Otago region during the study period. Interventions There is no intervention in this observational study. Main outcome measures CT scanning rates and waiting times before and after the introduction of the rural scanner. Results Prior to the scanner being commissioned, there was a significant urban versus rural disparity in CT utilisation. Residents in the neighbouring urban centre were 1.4 times more likely to access CT (33.2 (95% confidence interval ( CI) 32.2-34.2) versus 23.0 (95% CI 21.0-25.1) scans per 1000 residents per annum). Twenty months after the scanner was commissioned, the rate for the rural community had almost doubled to 45.6 (95% CI 43.0-48.2) and was 1.2 times greater than for the urban community. This difference was not sustained, and rural and urban communities had similar CT scanning rates in 2011 and 2012. Mean waiting time for residents in the rural community fell from 21.1 (95% CI 17.1-25.2) days prior to the scanner to 6.7 (95% CI 5.6-7.8) days after the scanner was commissioned. Conclusions On-site CT increased the rural scanning rate, corrected the rural-urban disparity and reduced waiting times without apparent over servicing. [ABSTRACT FROM AUTHOR]

The article discusses the mismatch between the rural population and the population that receives rural health care services in New Zealand. Topics include the factors that affect health access, the definition of rural or urban which is unsuitable for health purposes and the proposed working definitions to identify the proportion that accesses rural health services.