Abstract
Background
Kidney care has increasingly understood environmental impacts, and patient transportation to care is recognized as one of its largest greenhouse gas (GHG) emissions sources.
Objective
Our health region aims to reduce the environmental impact of kidney services while providing equitable care, hence assessment of transportation distances and associated emissions was undertaken.
Design
A retrospective observational study was performed to determine round trip and yearly transportation distances from residence to corresponding kidney care setting.
Setting
All registered kidney care services throughout British Columbia.
Patients
All adult patients in a provincial registry who were receiving scheduled pre-dialysis, conservative management, and home and facility-based dialysis therapies, in 2023.
Measurements
Yearly GHG emissions by modality were calculated by multiplying distance travelled by locally sourced emissions factors by vehicle type, then by frequency of care, as defined by local best practices.
Methods
Transportation distances and emissions data were reported in median with interquartile range, for a base scenario of travel via gas car, and for four alternate hypothetical emissions lowering scenarios.
Results
The cohort included 15,772 adult patients, with distance travelled to care in 2023 exceeding 17 million kilometres, and corresponding annual GHG emissions of 3873 tonnes of carbon dioxide equivalents. Significant variability existed in transportation distance and emissions both within and between care modalities. Home dialysis patients had the longest median round trip distances (and corresponding emissions) for home hemodialysis and peritoneal dialysis of 52.4 and 27.3 kilometres (11.5 and 6.0 kilograms carbon dioxide equivalents, respectively); whereas facility hemodialysis patients had the greatest annual median distances of 2265.2 kilometres and annual emissions of 498.1 kilograms. Combining all transportation to care emissions reductions scenarios resulted in a 62% reduction in GHG emissions.
Limitations
Staff transportation was not considered, including that for supported home dialysis modalities, and public transit by light transport vehicle was assumed to follow the most direct road distance from residence to dialysis treatment facility.
Conclusions
Patient transportation to kidney therapies in British Columbia has climate change impact considerations, and appropriate use of virtual care, home dialysis therapies, and various low emissions transportation options offer significant improvement opportunities.
Keywords: environmentally sustainable kidney care, green nephrology, planetary health, climate change, chronic kidney disease
Introduction
Human activities have degraded Earth’s atmosphere, lands, and waters such that seven of nine planetary boundaries (modeled quantitative assessments of safe limits of the processes that together maintain stability and resiliency of Earth’s natural systems) have been exceeded (climate change, biosphere integrity, land-system and freshwater changes, biogeochemical flows, and introduction of novel entities e.g. plastics and pharmaceuticals to Earth’s biosphere). 1 As we approach or unknowingly cross critical ‘tipping points’, we risk deleterious, cascading effects on Earth’s interconnected ecological systems (i.e. mountain glaciers, coral reefs, ocean currents and ice sheets) on which life depends.2,3
Urgent calls for climate-resilient, low-carbon, equitable, and sustainable health systems have been issued,4,5 noting that healthcare is responsible for 5.2% of global greenhouse gas (GHG) emissions. 4 In 2019, the Canadian healthcare system emitted 33 megatonnes of carbon dioxide equivalents (CO2e, which refers to the collective heat trapping capacity of both CO2 and non-CO2 atmospheric gases (e.g. methane and nitrous oxide), referent to that of CO2), comprising 4.6% of our national GHG emissions. 6 Further, these emissions resulted in a median estimate of 23,000 disability adjusted life years per annum. 6
The fossil fuel component of air pollution is the second leading cause of death from non-communicable disease, 7 responsible for one in five deaths worldwide, 8 including 15,000 premature deaths per year in Canada. 9 Particulate matter air pollution that arises from, among other sources, the combustion of fossil fuels, is associated with chronic kidney disease (CKD). In one analysis, in 2017 there were over 3.2 million incident and over 120 million prevalent global CKD cases attributable to poor air quality (including as many as 106,000 prevalent CKD cases in Canada). 10
The National Health Service (NHS) of England informs that 10% of their health system GHG emissions arise from patient (5%) and staff (5%) travel to health care facilities, 11 whereas in 2010 a single kidney service in the United Kingdom quantified 15 % of their program’s GHG emissions originating from patient travel to and from their region’s kidney care facilities. 12 In one satellite hemodialysis facility in Australia, a country whose vast geography more closely resembles Canada’s, 19.6% of yearly facility greenhouse gas emissions were attributed to patient travel to hemodialysis. 13 In a recent life cycle assessment of kidney therapies in British Columbia, Saleem et al report that emissions from combined patient and staff travel comprised the highest category of emissions for both hemodialysis and deceased donor transplant care, and the second highest category of emissions for peritoneal dialysis care. 14
Longer travel to hemodialysis care has additional significant and broad implications. Firstly, people who rely on kidney replacement therapies in Canada have significant treatment associated out of pocket costs (OOPC), though cost of travel is notably absent from existing patient reimbursement. 15 These costs could be easily determined from travel distances to kidney services, which have not been previously described in British Columbia (BC), or to our knowledge, elsewhere in Canada. Further, in an international cohort derived from the Dialysis Outcome and Practice Patterns Study (DOPPS), longer travel time to hemodialysis (determined by distance travelled as well as time, comparing longer than 60 minutes to less than 15) was associated with a 20% higher mortality risk, lower quality of life scores, and a greater number of skipped and shortened treatments, 16 thereby highlighting a need for care teams to explore ways to reduce travel to therapy.
BC Renal, an organization that coordinates the care of people with kidney disease in the province of British Columbia, 17 is seeking opportunities to align care with environmental sustainability. Accurate quantification of GHG emissions of kidney services serve as a useful baseline for subsequent decarbonization efforts as BC Renal aims to reduce care related emissions by 40% by 2030. 18
Herein, we add to the body of knowledge of travel related burden to kidney care, through assessing its associated climate change impact.
Methods
Study Population and Data Collection
Patient Records and Outcome Management Information System (PROMIS) is a province-wide clinical information system to which registration is mandatory for access and funding to care in kidney care clinics (KCC) and dialysis facilities in BC, Canada. 17 This retrospective population-level study cohort consisted of adult patients receiving outpatient, scheduled, non-urgent kidney care who were actively registered in PROMIS as of February 28, 2023, including those with CKD G3, G4, and G5 (with G5 including both people receiving maintenance dialysis (G5D) and those not treated with maintenance dialysis (G5ND), with dialysis therapies including home dialysis (peritoneal (PD) and hemodialysis (HHD)), and facility hemodialysis (community HD and in-centre HD (ICHD)).
The primary data of interest was the one-way shortest road distance traveled for each anonymized patient in the study cohort. The one-way traveled distance was computed between the centric latitude/longitude coordinates of the patient’s residential postal codes and the latitude/longitude coordinates of their corresponding kidney care clinic or dialysis facility using the Open Source Routing Machine (ORSM) package in R with interface to the locally installed ORSM application programming interface.
Approval for this study was granted by the behavioural research ethics board of the University of British Columbia, and from BC Renal, approval H22-02433.
Emissions Calculations
Emissions factors for each vehicle type were obtained from BC best practices methodology 19 guidance and are summarized in Supplemental Table 1. Frequency of travel for care is depicted in Supplemental Table 2 and is modeled on provincial best practices for Kidney Care Clinic (KCC) and home dialysis care, and includes per annum one clinic visit for KCC registrants with CKD G3a, two for G3b, four for G4, six for G5ND; and six home dialysis care visits for both PD and HHD. Both community and ICHD include 156 hemodialysis treatments annually, and calculations were performed assuming complete attendance.
As accurate data is not kept for transportation method or vehicle type for travel to kidney care appointments, several assumptions were made by varying the proportion of patients traveled by different transportation methods, vehicle types and the frequency of appointments. We considered one base scenario and four alternate scenarios as sensitivity analyses (refer to Supplemental Table 3). The base scenario was defined as all patients travelling by gasoline car according to the provincial best practices frequency of care. Alternate Scenario 1 was defined as 75% of patients travelling by gasoline car and 25% of patients travelling by electric vehicle (EV) (based on 2023 provincial government reports 20 that nearly 23% of new vehicle sales in BC were electric cars). Alternate Scenario 2 was that 50% of patients travelled by gasoline car and 50% of patients travelled by light duty truck (no occupancy data was available hence assumed 75% occupancy rate in a 16 seat vehicle (the most common light transport truck in use in British Columbia has 16 seats 21 )). Alternate Scenario 3 was a 50% use of virtual versus in person visits for KCC, PD and HHD patients (no change in the dialysis frequencies for people receiving ICHD and community HD), and all travelled by gasoline car. Alternate Scenario 4 was a combination of the aforementioned scenarios, specifically that 50% of patients travelled by light duty truck, 37.5% of patients travelled by gasoline car, 12.5% of patients travelled by EV, and KCC, PD, and HHD patients conducted 50% of care appointments virtually.
Under each scenario, for each patient, the annual return trip GHG emissions were calculated by first doubling the one-way travelled road distance, then multiplying the return trip distance by the emission factor of the corresponding vehicle type and frequency of care of the corresponding treatment modality.
Statistical Analysis
Patient characteristics were summarized for the overall study cohort and by treatment modalities. Median with interquartile range or frequency with percentage were reported according to the underlying distribution of the variables.
Due to right skewed data distribution, descriptive statistics for multiple study parameters were reported in median with interquartile range, with data presented both for the overall study cohort, and by treatment modality. Included parameters were round-trip distance travelled per patient and corresponding GHG emissions per round trip per patient; and yearly round-trip distance per patient and corresponding yearly per patient GHG emissions. Total yearly system GHG emissions were a summation of all patients’ yearly emissions according to treatment modality and emissions scenario. The total yearly system GHG emissions for each alternative scenario were compared to the base scenario, representing emissions reduced.
All analyses were performed using SAS software, Version 9.4 of the SAS System for Windows (SAS Institute Inc., Cary, NC, USA) and R Studio Version 2025.05.1+513 (Posit Software, PBC, Boston, MA, USA).
Results
The study cohort included a total 15,772 adult patients with CKD G3a-G5 (G5ND and G5D) (Figure 1). The median age for the overall study cohort was 74 [IQR: 65-81], with median age ranging from 58 in the HHD group to 85 in the KCC G5ND group (Table 1). Overall, 44% of the study cohort were female, and 50% were Caucasian. Common causes of kidney disease include diabetes, hypertension, and glomerulonephritis, affecting 29%, 28%, and 15% of the cohort, respectively.
Figure 1.
Cohort derivation
Table 1.
Cohort Demographics, Patients Traveling to Outpatient, Scheduled, Non-urgent Kidney Care Clinic and Dialysis Services in British Columbia
| | Non-dialysis CKD | Dialysis CKD | BC total | |||||
|---|---|---|---|---|---|---|---|---|
| KCC non-conservative pathway | KCCconservative pathway | KCC overall | PD | Home HD | Community HD | In-center HD | ||
| No. of Patients | 11961 | 274 | 12235 | 869 | 132 | 1047 | 1489 | 15772 |
| Age; years: median [Q1-Q3] | 75 [67-82] | 85 [79-90] | 75 [67-82] | 69 [59-76] | 58 [46-69] | 71 [60-78] | 70 [60-79] | 74 [65-81] |
| Male sex: n (%) | 6575 (54.97) | 142 (51.82) | 6717 (54.9) | 542 (62.37) | 85 (64.39) | 644 (61.51) | 884 (59.37) | 8872 (56.25) |
| Race/Ethnicity, n (%) | ||||||||
| Caucasian | 5878 (49.14) | 111 (40.51) | 5989 (48.95) | 462 (53.16) | 90 (68.18) | 545 (52.05) | 732 (49.16) | 7818 (49.57) |
| Asian Oriental | 779 (6.51) | 31 (11.31) | 810 (6.62) | 174 (20.02) | 13 (9.85) | 148 (14.14) | 238 (15.98) | 1383 (8.77) |
| Asian South/East | 1386 (11.59) | 28 (10.22) | 1414 (11.56) | 160 (18.41) | 17 (12.88) | 231 (22.06) | 321 (21.56) | 2143 (13.59) |
| Other | 3509 (29.34) | 92 (33.58) | 3601 (29.43) | 73 (8.4) | 12 (9.09) | 122 (11.65) | 198 (13.3) | 4006 (25.4) |
| Unspecified | 409 (3.42) | 12 (4.38) | 421 (3.44) | 0 (0) | 0 (0) | 1 (0.1) | 0 (0) | 422 (2.68) |
| Etiology of renal disease, n (%) | ||||||||
| Congenital | 129 (1.08) | 1 (0.36) | 130 (1.06) | 15 (1.73) | 4 (3.03) | 18 (1.72) | 35 (2.35) | 202 (1.28) |
| Diabetes | 3274 (27.37) | 76 (27.74) | 3350 (27.38) | 285 (32.8) | 32 (24.24) | 367 (35.05) | 542 (36.4) | 4576 (29.01) |
| Glomerulonephritis | 1488 (12.44) | 17 (6.2) | 1505 (12.3) | 257 (29.57) | 48 (36.36) | 238 (22.73) | 300 (20.15) | 2348 (14.89) |
| Hypertension | 3708 (31) | 91 (33.21) | 3799 (31.05) | 163 (18.76) | 13 (9.85) | 178 (17) | 272 (18.27) | 4425 (28.06) |
| Polycystic kidney disease | 355 (2.97) | 5 (1.82) | 360 (2.94) | 32 (3.68) | 14 (10.61) | 42 (4.01) | 37 (2.48) | 485 (3.08) |
| Other | 3007 (25.14) | 84 (30.66) | 3091 (25.26) | 117 (13.46) | 21 (15.91) | 204 (19.48) | 303 (20.35) | 3736 (23.69) |
| CKD G-staging, n (%) | ||||||||
| G3a | 1380 (11.54) | 0(0) | 1380 (11.28) | | | | | |
| G3b | 4181 (34.96) | 0(0) | 4181 (34.17) | | | | | |
| G4 | 5644 (47.19) | 0(0) | 5644 (46.13) | | | | | |
| G5 | 756 (6.32) | 274 (100) | 1030 (8.42) | | | | | |
Table 2 depicts the per patient round trip and annual travel distances and corresponding GHG emissions (in kilograms (kg) CO2e), by treatment modality, under the base scenario. Home dialysis patients traveled furthest to care, with median round trip distances for HHD and PD being 52.40 km [IQR: 19.40, 214.97] and 27.30 km [IQR: 13.59, 68.54], respectively. However, when the frequency of travel to care was considered, yearly travel distance, and hence emissions, were greatest for facility hemodialysis, totalling median values of 2264.18 km [IQR: 1179.98, 4325.57] and 498.12 kg CO2e [IQR: 259.60, 951.62] for ICHD, and 1976.52 km [IQR: 948.79, 3950.54] and 434.83 kg [IQR: 208.73, 869.12] CO2e for community HD. This variability across all care settings is depicted in Figure 2, arranged from smallest to largest dispersion according to treatment modality. The modality with the greatest single round trip variability was HHD, while ICHD had the greatest annual travel distance.
Table 2.
Per Patient Round Trip and Annual Travel Distances and GHG Emissions for Kidney Care in BC
| Treatment modality | Round trip per patient travel and emissions | Annual trip per patient travel and emissions | ||
|---|---|---|---|---|
| Distance (km), median [Q1-Q3] | Emissions (kg CO2e), median [Q1-Q3]* | Distance (km), median [Q1-Q3] | Emissions (kg CO2e), median [Q1-Q3] | |
| KCC non-conservative pathway | 25.85 [11.82-73.50] | 5.69 [2.60-16.17] | 72.04 [29.86-228.97] | 15.85 [6.57-50.37] |
| KCC conservative pathway | 25.39 [12.93-73.34] | 5.59 [2.84-16.13] | 152.33 [77.57-440.02] | 33.51 [17.06-96.8] |
| KCC overall | 25.84 [11.84-73.50] | 5.68 [2.60-16.17] | 73.50 [30.40-231.18] | 16.17 [6.69-50.86] |
| PD | 27.33 [13.59-68.54] | 6.01 [2.99-15.08] | 164 [81.56-411.26] | 36.08 [17.94-90.48] |
| Home HD | 52.40 [19.40-214.97] | 11.53 [4.27-47.29] | 314.42 [116.38-1289.81] | 69.17 [25.6-283.76] |
| Community HD | 12.67 [6.08-25.32] | 2.79 [1.34-5.57] | 1976.52 [948.79-3950.54] | 434.83 [208.73-869.12] |
| In-centre HD | 14.51 [7.56-27.73] | 3.19 [1.66-6.10] | 2264.18 [1179.98-4325.57] | 498.12 [259.60-951.62] |
| Overall | 23.20 [10.73-62.89] | 5.10 [2.36-13.84] | 114.77 [38.92-643.3] | 25.25 [8.56-141.53] |
*emissions factor 0.22 kg CO2e per kilometer traveled.
Figure 2.
Variability in Travel-related GHG Emissions by Kidney Therapy, British Columbia under the base scenario of 100% gas car transportation. Boxplots with overlaid patient-level points compare travel distance and associated CO2e emitted across modalities: (A) emissions per round trip per patient (kg CO2e), (B) annual CO2e emissions per patient (kg), (C) patient composition (by modality), and (D) proportional treatment modality contribution to total annual travel distance (percent).
Table 3 summarizes the yearly per patient emissions and yearly system emissions by treatment modalities under the base and four alternate scenarios (and percent reduction in emissions for each scenario). When compared to the base scenario, scenarios 1 through 4 had 25%, 45%, 13%, and 62% lower emissions, respectively (Figure 3).
Table 3.
Sensitivity Analysis: Annual per Patient and Provincial Median Transport Emissions
| Scenarios | Treatment modality | Yearly per patient emissions (kg CO2e), median (Q1-Q3) | Yearly system emissions (tonnes CO2e) | Reduction in yearly system emissions from base scenario (tonnes CO2e, %) |
|---|---|---|---|---|
| Base scenario* | KCC overall (N=12235) | 16.17 (6.69-50.86) | 844.74 | |
| PD (N=869) | 36.08 (17.94-90.48) | 122.43 | ||
| HHD (N=132) | 69.17 (25.6-283.76) | 42.16 | ||
| Community HD (N=1047) | 434.83 (208.73-869.12) | 1159.45 | ||
| In-centre HD (N=1489) | 498.12 (259.6-951.62) | 1703.73 | ||
| Overall (N=15772) | 25.25 (8.56-141.53) | 3872.51 | ||
| Alternate scenario1* | KCC overall | 12.13 (5.02-8.15) | 633.55 | 211.19 (25%) |
| PD | 27.06 (13.46-67.86) | 91.82 | 30.61 (25%) | |
| HHD | 51.88 (19.20-212.82) | 31.62 | 10.54 (25%) | |
| Community HD | 326.13 (156.55-651.84) | 869.59 | 289.86 (25%) | |
| In-centre HD | 373.59 (194.70-713.72) | 1277.80 | 425.93 (25%) | |
| Overall | 18.94 (6.42-106.15) | 2904.38 | 968.13 (25%) | |
| Alternate scenario 2* | KCC overall | 8.82 (3.65-27.74) | 460.77 | 383.97 (45%) |
| PD | 19.68 (9.79-49.35) | 66.78 | 55.65 (45%) | |
| HHD | 37.73 (13.97-154.78) | 23.00 | 19.16 (45%) | |
| Community HD | 237.18 (113.86-474.07) | 632.43 | 527.02 (45%) | |
| In-centre HD | 271.7 (141.6-519.07) | 929.31 | 774.42 (45%) | |
| Overall | 13.77 (4.67-77.2) | 2112.28 | 1760.23 (45%) | |
| Alternate scenario 3 | KCC overall | 8.42 (3.74-26.84) | 439.14 | 405.6 (48%) |
| PD | 18.04 (8.97-45.24) | 61.21 | 61.22 (50%) | |
| HHD | 34.59 (12.8-141.88) | 21.08 | 21.08 (50%) | |
| Community HD | 434.83 (208.73-869.12) | 1159.45 | 0 (0%) | |
| In-centre HD | 498.12 (259.6-951.62) | 1703.73 | 0 (0%) | |
| Overall | 13.09(4.73-89.10) | 3384.62 | 487.89 (13%) | |
| Alternate scenario 4* | KCC overall | 3.62 (1.61-11.53) | 188.63 | 656.11 (78%) |
| PD | 7.75 (3.85-19.43) | 26.29 | 96.14 (79%) | |
| HHD | 14.86 (5.5-60.94) | 9.06 | 33.1 (79%) | |
| Community HD | 186.78 (89.66-373.33) | 498.04 | 661.41 (57%) | |
| In-centre HD | 213.97 (111.51-408.77) | 731.83 | 971.9 (57%) | |
| Overall | 5.62 (2.03-38.27) | 1453.85 | 2418.66 (62%) |
*Base scenario = 100% gas vehicles, all private vehicle transportation, all in person visits; emission conversion factor 0.22 kg CO2e per km.
**EV = electric vehicle; a weighted CO2 emission conversion factor of: 0.75*0.22 + 0.25*0 = 0.165 is used.
***Emissions factor for light truck = 0.29 kg CO2e per km; weighed CO2 emission factor of 0.50*0.22 + 0.50*0.29*(1/12) = 0.12 is used 19 (based on assumed 75% capacity with occupancy of 16).
****Combined = 50% light truck + 37.5% gas car + 12.5% EV; weighed CO2 emission factor of 0.5*0.29*(1/12)+ 0.375*0.22 + 0.125*0 = 0.0945 is used.
Figure 3.
Annual system reduction in CO2 emissions relative to the baseline scenario across alternative scenarios and modalities in tonnes. Reduction is calculated as the difference between annual emissions under the baseline scenario and those under each alternative scenario
In British Columbia in 2023, the total distance that all kidney patients travelled to receive care for registered kidney services, including KCC and dialysis care, was 17,602,330 km, with corresponding GHG emissions of 3873 tonnes. The shortest return trip to kidney care was well under 1 km (from a contiguous long term care facility), and the longest was 1888.1 km.
Analyses were also performed by BC health regions, results of which will be shared with each, but are not presented here.
Discussion
In this health region assessment of the climate change impact of travel to scheduled non-transplant kidney services, in 2023 alone total GHG emissions were 3873 tonnes CO2e, or a theoretical average of 246 kg CO2e per patient, with total distance travelled 17,602,330 km, which equates to 440 hypothetical circumnavigations of Earth. 22 In other terms, 3873 tonnes of CO2e equates to emissions from the energy consumption of 907 Canadian homes, 23 or the amount emitted by nearly 3000 people flying economy class between New York and Paris. 24 The largest contribution, not surprisingly, originated from ICHD, repeated driving to which comprised 44% of total travel emissions, amounting to 1704 tonnes CO2e. The emissions contribution from travel to other treatment modalities includes 21.8% from KCC (noting that 78% of the study cohort received care in these settings), 30% from community HD, and 4.3% from combined home dialysis modalities (despite HHD then PD having the longest median travel distances). Distance traveled varies by health authority (data not shown), highlighting inequality in treatment accessibility hence travel costs borne by patients receiving kidney services. To our knowledge, this analysis is the first comprehensive description of the climate change impact of transportation to a range of kidney therapies in a major health region.
We performed sensitivity analyses using regional data derived estimates of feasible alternate transportation scenarios. The most impactful single theoretical intervention was 50% of visits occurring by light duty truck (versus exclusively single occupant gas vehicle), such as is provided by public transportation in some urban areas in our health region. 25 Further emissions reductions could be realized if these vehicles were electric - as demonstrated in scenario 1, emissions reductions proportional to EV uptake could be achieved. Societal level transitions are required to impact change from gasoline to electric vehicle EV use, and in the healthcare realm initiatives could include designated parking and charging stations for these vehicles. Multiple combined transportation efficiency inputs, including enhanced EV and public transit ridership to care, and use of virtual care when appropriate, were modeled to result in 63% lower emissions.
In our region, combined patient and staff travel to in-centre hemodialysis and peritoneal dialysis are known to comprise over 80% and 11% of total climate change impact, respectively. 14 Health regions with geographies comparable to our own have also assessed climate change impact of travel to dialysis therapies. By comparison, annual per patient GHG emissions from travel to HD in one urban region of Australia are comparatively larger, 1764 kg CO2e (comprising 36.6% of Australian in-centre HD emissions, 26 though differences in system boundaries between analyses limit comparability). In a regional US setting, patient and staff travel to in-centre HD accounted for 28.3% of emissions, comprising 2177 tonnes CO2e average per facility per year. 27 This publication also highlighted travel as the most variable category contributing to emissions.
Distance traveled to care is an important equity consideration, and variability of distance traveled both within and between care modalities emerged in our analysis. Literature exploring travel to kidney therapies in large health regions to date describe inequitable access in rural versus urban settings,28,29 worse outcome with longer travel time to therapy, 16 and care redesign to enhance patient-centredness and improved care access. 30 Additionally, there is a substantial and growing literature on the use of telehealth to improve environmental performance of care, both in kidney care as well as a widening range of care settings. 31 For post-transplant kidney care, per assessment GHG emissions savings between 0.7 and 372 kg CO2e have been described.32-34 It should be emphasized, however, that data supporting clinical outcomes of virtual care lags behind that demonstrating environmental benefit.
The environmental efficiencies inherent in home dialysis therapies,14,26 in addition to the known cost savings 35 and clinical benefits36-38 they provide, is thus highlighted.
Strengths of this study include its large sample size in a geographically diverse region encompassed by a unified provincial database. Additional strengths include the accessibility of transportation data being collected in other health regions, and the use of sensitivity analyses to evaluate potential improvement scenarios.
There are also limitations to this study. Firstly, light duty trucks used in the scenario analyses were assumed to travel the most direct route from residence to site of care, however with the assumed 75% occupancy there would be pick-ups and drop-offs along the way that would lengthen travel distance, hence emissions. Secondly, home dialysis calculations were based upon the home modality being self-provided - we did not differentiate between provider supported versus independently performed home dialysis. Fourthly, our study did not assess travel time to dialysis, which may be a more relevant metric in urban areas where slow traffic flows could prolong travel time, which may lead to greater patient dissatisfaction with travel to care. Lastly, the analysis did not evaluate transportation to unscheduled, including urgent or emergent care, nor to inpatient or non-renal outpatient care. These factors could result in significant underestimation of therapies’ transportation-related GHG emissions. Transportation and emissions to people receiving post kidney transplant outpatient care was also excluded, and warrants separate analysis.
Despite these limitations, and recognizing that travel to care amid the vast geography of western Canada may not be broadly generalizable, our findings provide opportunities for improving the patient centredness and environmental performance of kidney care provision. We propose that routine collection of travel distance to different modalities of kidney care be considered as a system-level performance metric, alongside existing quality of care assessments. For pre-dialysis kidney care or home dialysis programs, adoption of virtual care, when appropriate, can save patient travel time, reduce travel risk from inclement road conditions, and reduce out of pocket travel and parking associated costs, for patients and carers. Reduced patient travel to facility-based hemodialysis care might reflect more effective prevention of kidney failure, and/or enhanced transplantation and/or home dialysis uptake. Secondly, providers can communicate the health benefits of widespread societal action toward climate change mitigation (examples herein comprising a few such mitigation options in kidney care), noting higher acute kidney injury occurrence 39 and CKD progression rates 40 as Earth warms, as well as the marked impact of air pollution on kidney health as described above. 10 Planners can ensure that kidney health facilities are optimally situated with respect to patient population density, and all can advocate for low carbon public transit to efficiently serve these sites of care. Further, administrators can ensure that financial and human resources are available to support uptake of transplantation and home therapies, when clinically appropriate and in shared decision-making, with the additional societal benefits described herein. Finally, these data are hopefully of use in advocacy efforts to reimburse out-of-pocket care related travel costs to patients, which may be burdensome to many. 41
Conclusions
We illustrate the environmental impact of transportation to kidney care as a case study of the global challenges faced by health systems as we seek solutions to the climate crisis – seemingly small impacts add up to substantial ones. Many individual and system-level solutions are proposed that can cumulatively reduce this impact, aligning quality patient care with climate change mitigation.
Supplemental Material
Supplemental material for Greenhouse Gas Emissions of Patient Transportation to Kidney Care – A Province-Level Retrospective Cohort Study by Shannon N Wong, Charith Kalu Arachchillage, Lee Er, Tasleem Rajan and Caroline Stigant in Canadian Journal of Kidney Health and Disease.
Author Contributions: Drs. Rajan and Stigant conceived and/or designed the work that led to the submission, all data were extracted from PROMIS and prepared by BC Renal analytics Dr. Kalu Arachchillage and Ms. Er, Dr. Rajan drafted the original manuscript and performed initial analyses, Dr. Kalu Arachchillage and Ms. Er performed final data analyses and created images, and Drs. Wong and Stigant formulated the final manuscript. All authors approved the final version.
Funding: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Dr. Stigant is supported by the Marcia Bell Distinguished Scholar Award, awarded by the University of British Columbia. BC Renal supported funding in this article.
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Data Sharing: Raw data that supports study findings can be accessed upon request from the corresponding author, in accordance with applicable regulations and ethical guidelines. Supplementary material will be made available online
Supplemental Material: Supplemental material for this article is available online.
ORCID iDs
Tasleem Rajan https://orcid.org/0000-0003-4343-2041
Caroline Stigant https://orcid.org/0000-0003-2578-0966
Ethical Considerations
Approval for this study was granted by the behavioural research ethics board of the University of British Columbia, and from BC Renal, approval H22-02433.
Consent for Publication
Dr. Stigant as corresponding author has had full access to the data in the study and has final responsibility for the decision to submit for publication.
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Supplementary Materials
Supplemental material for Greenhouse Gas Emissions of Patient Transportation to Kidney Care – A Province-Level Retrospective Cohort Study by Shannon N Wong, Charith Kalu Arachchillage, Lee Er, Tasleem Rajan and Caroline Stigant in Canadian Journal of Kidney Health and Disease.