In-Center Hemodialysis and Patient Travel Time in Aotearoa New Zealand: A Nationwide Geospatial and Data Linkage Study

被引:1
作者
Birrell, Johanna M. [1 ,2 ]
Webster, Angela C. [1 ,3 ]
Cross, Nicholas B. [1 ,2 ]
Kindon, Andrew [4 ,5 ]
Hobbs, Matthew [4 ,5 ,6 ]
Hedley, James A. [1 ]
Driscoll, Tim [1 ]
De La Mata, Nicole L. [1 ]
机构
[1] Univ Sydney, Sch Publ Hlth, Sydney, NSW, Australia
[2] Te Whatu Ora Waitaha Canterbury, Dept Nephrol, Christchurch, New Zealand
[3] Westmead Hosp, Dept Renal Med, Sydney, NSW, Australia
[4] Univ Canterbury, Te Taiwhenua o Te Hauora, GeoHlth Lab, Te Whare Wananga o Waitaha, Christchurch, Otautahi, New Zealand
[5] Univ Canterbury, Fac Hlth, Te Kaupeka Oranga, Te Whare Waananga o Waitaha, Christchurch, Otautahi, New Zealand
[6] Sheffield Hallam Univ, Coll Hlth Wellbeing & Life Sci, Sheffield, England
基金
英国医学研究理事会;
关键词
dialysis; first nations peoples; geo-spatial mapping; health equity; health services research; travel time; QUALITY-OF-LIFE; DIALYSIS; MORTALITY; SERVICES; OUTCOMES; CARE;
D O I
10.1016/j.ekir.2024.12.028
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Introduction: Prolonged travel time to receive dialysis is associated with decreased quality of life and increased mortality. However, patient travel time is rarely systematically analyzed during health service planning. This study's aims were as follows: (i) examine spatio-temporal trends in travel time for people commencing dialysis in Aotearoa New Zealand (NZ), (ii) assess the relationship between travel time and dialysis modality, and (iii) create interactive nationwide maps to support renal service planning. Methods: AcceSS and Equity in Treatment for kidney disease (ASSET), a health-linked data platform, was used to include all people commencing dialysis in NZ from 2006 to 2019 (N 1/4 6690). Patients' one-way driving times from their residential location to the nearest hemodialysis unit were estimated using geospatial software. Multiple logistic regression modelling explored the association between travel time and dialysis modality, adjusting for demographic, clinical, and service factors. Results: Median one-way driving time was 14 minutes (interquartile interval [IQI]: 8-31) and was significantly higher for patients living in rural (45 minutes [IQI: 28-62]) than in urban areas (11 minutes [IQI:8-18]; P < 0.001). Patients living farther from a unit were independently less likely to receive in-center hemodialysis (0.62 [95% confidence interval, CI: 0.52-0.72] for driving time >= 30 minutes; odds ratio, OR: 0.82 [95% CI:0.68-0.99] for 20-29; reference < 10), as were those in regions with greater hemodialysis unit capacity pressure. Our interactive maps demonstrate marked interregional variation in dialysis modality, patient travel time, and unit capacity. Conclusion: Innovative service design is needed to reduce the burden of travel time, particularly for rural dialysis patients. We present novel geospatial techniques to support dialysis service planning that is targeted to the areas of greatest need.
引用
收藏
页码:921 / 934
页数:14
相关论文
共 51 条
[1]  
[Anonymous], 2022, ArcGIS: Esri's comprehensive geospatial platform
[2]  
[Anonymous], Aotearoa New Zealand haemodialysis infrastructure survey 2023
[3]  
[Anonymous], Dialysis units
[4]  
[Anonymous], Aotearoa New Zealand Health Status Report 2023
[5]  
[Anonymous], Common Code Tables-Domicile code table
[6]  
[Anonymous], AU 2013 suppression
[7]  
[Anonymous], ANZDATA 46th Annual Report 2023
[8]  
[Anonymous], 2022, The ISN joins the discussion on improving quality of life during dialysis at European roundtable
[9]  
[Anonymous], 2021, Living better with CKD-improving the quality of life of CKD patients on dialysis across Europe
[10]  
[Anonymous], NZ District Health Board boundaries-generalized