Research Publications

@article{Birrell2024,

title = {Geographic variation in kidney failure and transplantation in Aotearoa New Zealand: A population‐based data linkage study},

author = {Johanna M. Birrell and Angela C. Webster and Nicholas B. Cross and Tim Driscoll and Heather Dunckley and Ben Beaglehole and Ian Dittmer and Curtis Walker and Merryn Jones and John Irvine and Melanie L. Wyld and Kate R. Wyburn and Nicole L. De La Mata},

doi = {10.1111/nep.14409},

issn = {1440-1797},

year  = {2024},

date = {2024-12-00},

urldate = {2024-12-00},

journal = {Nephrology},

volume = {29},

number = {12},

pages = {941--954},

publisher = {Wiley},

abstract = {<jats:title>Abstract</jats:title><jats:sec><jats:title>Aim</jats:title><jats:p>This study aimed to describe the epidemiology of kidney replacement therapy (KRT) in Aotearoa New Zealand and assess the impact of residential location on access to kidney transplantation.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>AcceSS and Equity in Transplantation (ASSET), a health‐linked data platform, was used to identify people commencing KRT in New Zealand from 2006 to 2019 and analyse regional epidemiology. Health services were classified as ‘transplanting’, ‘intermediate’ or ‘remote’ depending on their degree of separation from a transplant centre. Multiple logistic regression modelling was used to assess the predictors of deceased donor waitlisting or living donor transplantation within 6 months after starting KRT. Web‐based mapping software was used to develop interactive geospatial maps.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>The cohort was 7704 people newly starting KRT. Living in an intermediate [odds ratio (OR): 0.73 (95% confidence interval (CI): 0.61–0.88)] or remote [OR: 0.38 (95% CI: 0.27–0.54)) region and Māori (OR: 0.35 (95% CI: 0.28–0.44)], Pacific [OR: 0.32 (95% CI: 0.24–0.42)) and Asian (OR: 0.66 (95% CI: 0.50–0.87)] ethnicity were associated with a decreased likelihood of timely waitlisting or transplantation. Regional maps can be explored <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="https://storymaps.arcgis.com/stories/35b8bb67d5544076b0526793ceb2eb5b">here</jats:ext-link>.</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>There is marked geospatial and ethnic variation in the epidemiology of kidney failure and access to kidney transplantation across New Zealand. Geospatial mapping of kidney failure epidemiology and transplantation outcomes can provide opportunities to direct resources towards populations at greatest need.</jats:p><jats:p><jats:boxed-text content-type="graphic" position="anchor"><jats:graphic xmlns:xlink="http://www.w3.org/1999/xlink" mimetype="image/png" position="anchor" specific-use="enlarged-web-image" xlink:href="graphic/nep14409-gra-0001-m.png"><jats:alt-text>image</jats:alt-text></jats:graphic></jats:boxed-text></jats:p></jats:sec>},

keywords = {Geographic Variation},

pubstate = {published},

tppubtype = {article}

}

@article{Cutting2022,

title = {AcceSS and Equity in Transplantation (ASSET) New Zealand: Protocol for population-wide data linkage platform to investigate equity in access to kidney failure health services in New Zealand},

author = {Rachel B. Cutting and Angela C. Webster and Nicholas B. Cross and Heather Dunckley and Ben Beaglehole and Ian Dittmer and John Irvine and Curtis Walker and Merryn Jones and Melanie Wyld and Patrick J. Kelly and Kate Wyburn and Nicole L. De La Mata},

editor = {Justyna Gołębiewska},

doi = {10.1371/journal.pone.0273371},

issn = {1932-6203},

year  = {2022},

date = {2022-08-25},

urldate = {2022-08-25},

journal = {PLoS ONE},

volume = {17},

number = {8},

publisher = {Public Library of Science (PLoS)},

abstract = {<jats:sec id="sec001">

<jats:title>Background</jats:title>

<jats:p>Kidney transplantation is considered the ideal treatment for most people with kidney failure, conferring both survival and quality of life advantages, and is more cost effective than dialysis. Yet, current health systems may serve some people better than others, creating inequities in access to kidney failure treatments and health outcomes. AcceSS and Equity in Transplantation (ASSET) investigators aim to create a linked data platform to facilitate research enquiry into equity of health service delivery for people with kidney failure in New Zealand.</jats:p>

</jats:sec>

<jats:sec id="sec002">

<jats:title>Methods</jats:title>

<jats:p>The New Zealand Ministry of Health will use patients’ National Health Index (NHI) numbers to deterministically link individual records held in existing registry and administrative health databases in New Zealand to create the data platform. The initial data linkage will include a study population of incident patients captured in the Australia and New Zealand Dialysis and Transplant Registry (ANZDATA), New Zealand Blood Service Database and the Australia and New Zealand Living Kidney Donor Registry (ANZLKD) from 2006 to 2019 and their linked health data. Health data sources will include National Non-Admitted Patient Collection Data, National Minimum Dataset, Cancer Registry, Programme for the Integration of Mental Health Data (PRIMHD), Pharmaceutical Claims Database and Mortality Collection Database. Initial exemplar studies include 1) kidney waitlist dynamics and pathway to transplantation; 2) impact of mental illness on accessing kidney waitlist and transplantation; 3) health service use of living donors following donation.</jats:p>

</jats:sec>

<jats:sec id="sec003">

<jats:title>Conclusion</jats:title>

<jats:p>The AcceSS and Equity in Transplantation (ASSET) linked data platform will provide opportunity for population-based health services research to examine equity in health care delivery and health outcomes in New Zealand. It also offers potential to inform future service planning by identifying where improvements can be made in the current health system to promote equity in access to health services for those in New Zealand.</jats:p>

</jats:sec>},

keywords = {Equity},

pubstate = {published},

tppubtype = {article}

}