Multifaceted Intervention to Increase the Use of Home Dialysis

A Cluster Randomized Controlled Trial

Abstract

Background and objectives 

Home dialysis therapies (peritoneal and home hemodialysis) are less expensive and provide similar outcomes to in-center hemodialysis, but they are underutilized in most health systems. Given this, we designed a multifaceted intervention to increase the use of home dialysis. In this study, our objective was to evaluate the effect of this intervention on home dialysis use in CKD clinics across Canada.

Design, setting, participants, & measurements 

We conducted a cluster randomized controlled trial in 55 CKD clinic clusters in nine provinces in Canada between October 2014 and November 2015. Participants included all adult patients who initiated dialysis in the year following the intervention. We evaluated the implementation of a four-component intervention, which included phone surveys from a knowledge translation broker, a 1-year center-specific audit/feedback on home dialysis use, delivery of an educational package (including tools aimed at both providers and patients), and an academic detailing visit. The primary outcome was the proportion of patients using home dialysis at 180 days after dialysis initiation.

Results 

A total of 55 clinics were randomized (27 in the intervention and 28 in the control), with 5312 patients initiating dialysis in the 1-year follow-up period. In the primary analysis, there was no difference in the use of home dialysis at 180 days in the intervention and control clusters (absolute risk difference, 4%; 95% confidence interval, −2% to 10%). Using a difference-in-difference comparison, the use of home dialysis at 180 days was similar before and after implementation of the intervention (difference of 0% in intervention clinics; 95% confidence interval, −2% to 3%; difference of 0.8% in control clinics; 95% confidence interval, −1% to 3%; P=0.84).

Conclusions 

A multifaceted intervention did not increase the use of home dialysis in adults initiating dialysis.

Clinical Trial registry name and registration number: 

A Cluster Randomized Trial to Assess the Impact of Patient and Provider Education on Use of Home Dialysis, NCT02202018

Visual Abstract

Introduction

Home-based therapies (peritoneal dialysis and home hemodialysis) are underutilized (¹), despite comparative data showing similar quality of life, morbidity, and mortality when compared with in-center hemodialysis and lower cost in most countries (^2–7). In part, this is because decisions around dialysis modality selection are a complicated interplay between physician knowledge and practice, patient and family values, patient autonomy and ability to self-manage, clinical benefits/limitations, resource allocation, incentives, and geographical variation (^8–14). This is often further complicated by late referral to the nephrology team and urgent dialysis initiation for AKI such that choosing the right dialysis modality for the right patient at the right time cannot be accomplished.

The use of home dialysis in Canada remains lower than expected due to a combination of patient, caregiver, provider, and health system barriers (¹⁵). Previous Canadian studies have highlighted several potential patient and caregiver barriers to the use of home therapies, including knowledge, skills, personal circumstances, and social supports (¹³,¹⁴,¹⁶,¹⁷). Provider barriers have been reported to include lack of training in peritoneal dialysis, lack (or perceived lack) of skills and knowledge, bias against peritoneal dialysis as an effective dialysis modality, and possibly inadequate physician reimbursement for home dialysis (¹⁸). Lack of patient awareness and knowledge of home therapies have been consistent barriers noted in prior studies. These barriers persist despite the existence of national guidelines for home-based dialysis therapies (¹⁹) that note the importance of patient education and evidence suggesting that home-based therapies are chosen by most suitable patients when they are provided appropriate education and support (²⁰).

Although studies have shown that patient education can overcome knowledge-related barriers, increasing the use of home dialysis is complex and multifaceted. We recently conducted a cluster randomized trial of multidisciplinary CKD clinics across Canada to determine the effect of standardized education—aimed at patients and providers—on the timing of dialysis initiation (²¹). Because patients and providers must also consider modality choice when they are thinking about the timing of dialysis initiation, we simultaneously delivered a standardized modality education program directed at patients in combination with a provider-directed intervention to address barriers to the use of home dialysis. The goal was to increase the use of home dialysis in patients on incident dialysis in Canada. Here, we describe the effects of our multifaceted modality education intervention on home dialysis use in patients followed by nephrologists in multidisciplinary clinics across Canada.

Materials and Methods

Overview

As noted, this study was conducted alongside a cluster randomized trial examining the effect of standardized education—aimed at patients and providers—on the timing of dialysis initiation (²¹). In this parallel study, we used the same clusters, but the inclusion criteria for this study were broader as patients were included regardless of GFR or whether they were followed by a nephrologist before dialysis. Although the main purpose of the intervention was to reduce early starts, the audit/feedback available to the intervention sites also included use of home dialysis, and all provider- and patient-facing tools spoke not just about when to start dialysis but also about the types of dialysis (with a preference toward use of home dialysis where appropriate).

Fifty-five multidisciplinary chronic disease clinics (clusters) across Canada were randomized to receive either an active knowledge translation intervention or no intervention to increase the use of home dialysis at 180 days after dialysis initiation. The active knowledge translation intervention included audit and feedback as well as patient- and provider-directed educational tools delivered at a comprehensive in-person medical detailing visit (²¹,²²).

Clusters (CKD clinics) were randomized to receive the intervention at different points in time, and patients on incident dialysis in these clusters were followed to assess the primary outcome using data routinely collected by the Canadian Organ Replacement Registry.

Study Population and Data Sources

At the time of this study, there were 73 multidisciplinary CKD clinics across Canada providing care to nearly all patients with severe CKD, and they are responsible for the elective initiation of dialysis (²³). Each clinic is associated with one or more dialysis facilities, which formed the clusters used for randomization. Of the clinics in the network, 55 clusters were randomized (Figure 1). Fourteen clinics in Quebec were excluded from randomization as they do not submit data to the Canadian Organ Replacement Registry. Because measurement of outcomes occurred at the level of the dialysis facility, for clinics that send their new dialysis starts to the same dialysis facility, we combined these clinics into clusters. This was done for eight clinics (four clusters) to create unique measurement clusters and ensure that all patients within a dialysis unit were managed in a similar fashion within their clinics. The remaining 55 clusters (59 clinics) were all geographically separated (not located in the same office building) and staffed by nephrologists who do not see outpatients in another CKD clinic.

Figure 1.: Study flow of clinic clusters and patients.

The effectiveness of the intervention was assessed in all patients older than 18 years who initiated dialysis between September 1, 2013 and September 1, 2016.

The duration of the follow-up period after intervention was 12 months. We hypothesized that clusters randomized to the active intervention would start a greater proportion of their patients on home dialysis by 180 days after dialysis initiation as compared with clusters randomized to no intervention (control group).

Data Source

To assess effectiveness, we used data collected by the Canadian Organ Replacement Registry, which is a national registry that captures the incidence, prevalence, treatment changes, and outcomes of over 99% of patients on maintenance dialysis in Canada (outside Quebec). The Canadian Organ Replacement Registry is a validated registry that includes the following information on all patients with kidney failure: demographics, comorbidities, vascular access, dialysis modality, transplantation, and mortality (²⁴,²⁵). Data are collected by dialysis facilities and are centrally housed at the Canadian Institute for Health Information. Data are collected by completion of a registration form by the dialysis provider on each patient at dialysis initiation and yearly thereafter. A change of status form is completed to document patient death, transplantation, or a switch in dialysis modality.

Cluster Randomization

In this stratified cluster randomized study, the unit of observation was the patient (i.e., outcomes were measured at the level of an individual patient), and the unit of randomization was the cluster. As described in a related paper (²¹), we performed constrained randomization using software for random number generation with allocation concealment, stratifying on province/region and size of the cluster (<200, 200–600, or >600 patients). A simulation of the randomization was completed to ensure balance on prespecified cluster-level variables. Approximately 1000 iterations were performed, and a randomization scheme that resulted in good balance on all measured cluster factors was selected. Randomization assignments were concealed until the planned implementation of the intervention for a given region. Sample size was constrained by the number of clinic clusters available for randomization across Canada, and study power was on the basis of the timing of dialysis initiation outcome as noted in a related paper (²¹).

Outcomes

The primary outcome was use of home dialysis (peritoneal dialysis or home hemodialysis) at 180 days after dialysis initiation among the study population (i.e., all patients older than 18 years initiating dialysis). We used 180 days because that provided enough time for a patient to be informed about home dialysis and make a switch to home dialysis if that was their preference. The secondary outcome was the use of home dialysis at 180 days after dialysis initiation among all patients initiating dialysis who were followed by a nephrologist prior to dialysis initiation for at least 90 days. Other outcomes we assessed were any use of home dialysis within 180 days and the use of home dialysis at dialysis initiation, both in the overall cohort of patients over 18 years of age initiating dialysis.

Following randomization, the intervention was applied in a staggered rollout between October 2014 and November 2015, with observation for the primary outcome occurring in the intervention clusters (and the control clusters in the same strata) starting on the date of the medical detailing visit.

Intervention

The intervention was aimed to increase use of home dialysis and was delivered at the same time as an intervention aiming to improve appropriate timing of dialysis initiation. Because they were relevant to the same patient population, it made sense to combine them. Moreover, there was enthusiasm across Canadian centers about the timing of dialysis initiation given a recent randomized controlled trial (²⁶) and a new Canadian guideline on the timing of dialysis initiation (²⁷).

As noted in Figure 2 and described in more detail in Supplemental Appendix, the combined intervention consisted of audit and feedback, patient- and provider-directed educational tools, and a comprehensive in-person medical detailing visit (²¹,²²).

Figure 2.: Overview of the combined intervention designed to increase the use of home dialysis (additional details are in Supplemental Appendix ) ( ²¹ , ³³ , ⁴⁰ ).

Statistical Methods

To assess the effectiveness of patient education and provider tools, we used a cluster randomized trial design. The unit of randomization was the CKD clusters. No interim analyses were undertaken.

The time at which the cluster began the intervention was randomly determined. All patients received usual care up until the point of study initiation, with clusters subsequently being randomized to intervention every 3 months in four separate time periods until, by the end of 18 months, all clusters randomized to receive the intervention had received it. Dichotomous outcomes (such as whether the patient used home dialysis at 180 days) were compared using an adjusted two-sample t test. To adjust for individual- and cluster-level covariates as well as correlation within clusters (²⁸), we used generalized estimating equations (GEEs) to obtain the population average effect of the intervention in the presence of clustering. Confidence interval widths were not adjusted for multiple testing. We also conducted a stratified analysis to align with the constrained randomization in our design, but because the results were consistent with the nonstratified models, we present the more parsimonious approach.

We also used a differences-in-differences approach to control for differences in the baseline rate of home dialysis use in the two groups (²⁹). To do this, we constructed GEE models where the changes over time were compared using the interaction between group (intervention and control) and time (postintervention versus preintervention). For categorical outcomes, the log-binomial model was used when possible, and for nonconvergent models, we applied a log Poisson model. For continuous models, we applied a GEE model with a normal distribution and identity link (³⁰).

We conducted several additional analyses. We repeated our models adjusted for patient-level characteristics with missing data being imputed with five imputations using SAS software’s PROC MI and a sensitivity analysis including all dialysis starts (irrespective of 90 days of nephrology follow-up before dialysis initiation). Finally, a post hoc analysis was conducted that included only clusters that were found in the follow-up survey to have been high users of the knowledge translation tools, defined as those who responded to a 6-month follow-up phone-based survey and rated the intervention greater than or equal to three of five on a Likert scale.

Ethical Considerations

Ethics approval was received from the Conjoint Health Research and Ethics Board, University of Calgary. Consistent with best practice (³¹), the research ethics board provided a waiver of consent for both patients and clinical directors for trial participants because the study interventions and data collection processes pose minimal risk; the intervention involved an already published clinical practice guideline, and the data required for this study were already routinely collected. Patients were not contacted, and outcomes were collected through the Canadian Organ Replacement Registry, which as noted above, routinely collects these data for dissemination to kidney programs. Although we did not mandate a change in care at CKD clinics, we encouraged the entire health care team to support the use of home dialysis.

Results

Baseline Characteristics

Patients were well balanced across intervention and control clusters, with no clinically important differences noted across the trial period (Table 1) or before or after the trial period for the difference-in-differences analysis (Supplemental Table 1). There were 2476 and 2836 patients who initiated dialysis across intervention and control clusters during the trial period, respectively (Figure 1).

Table 1. - Baseline characteristics of clusters and patients (as used for primary analysis)

Cluster and Patient Characteristics	Intervention, n=27	Control, n=28
Cluster characteristics, n	2476	2836
Mean no. of patients in the clinic	770 (667)	699 (598)
No. of nephrologists	5 (2–8)	5 (2.5–9)
Cluster size, patients, n (%)
<200	3 (11)	2 (7)
200–600	11 (41)	13 (46)
>600	13 (48)	13 (46)
Model of care, n (%)
Rotating nurse and rotating nephrologist	2 (7)	3 (11)
Same nurse and rotating nephrologist	3 (11)	2 (7)
Rotating nurse and same nephrologist	6 (22)	5 (18)
Same nurse and same nephrologist	15 (56)	17 (61)
Mixed	1 (4)	1 (4)
Region, n (%)
Alberta	2 (7)	2 (7)
British Columbia	6 (11)	6 (21)
Maritime provinces	4 (7)	4 (14)
Prairie provinces (Manitoba/Saskatchewan)	3 (6)	3 (11)
Ontario	12 (22)	13 (46)
Patients initiating dialysis, n	2476	2836
Demographics and laboratory values at dialysis initiation
Age (SD), yr	64 (0.3)	64 (0.3)
Men, n (%)	1580 (64)	1708 (60)
BMI, kg/m2	28.9 (0.2)	28.7 (0.1)
Hemoglobin, g/dl	9.6 (0.03)	9.4 (0.03)
Phosphate, mg/dl	6.1 (0.04)	5.9 (0.04)
Albumin, g/dl	3.2 (0.02)	3.1 (0.01)
Comorbidities, n (%)
Angina	294 (12)	354 (12)
Previous CABG	355 (14)	504 (18)
Cerebrovascular accident	325 (13)	359 (13)
Current smoker	344 (14)	386 (14)
Diabetes mellitus	1385 (56)	1569 (55)
Hypertension	1920 (78)	2180 (77)
Lung disease	287 (12)	389 (14)
Malignant neoplasm	371 (15)	474 (17)
Myocardial infarction	423 (17)	525 (19)
Peripheral vascular disease	367 (15)	468 (17)
Pulmonary edema	576 (23)	727 (26)
Cause of kidney failure, n (%)
Hypertension	222 (9)	316 (11)
Diabetes mellitus	1058 (43)	1120 (39)
GN	277 (11)	318 (11)
Obstruction	38 (2)	38 (1)
Interstitial	181 (7)	241 (9)
Polycystic kidney disease	107 (4)	84 (3)
Other and unknown	593 (24)	719 (25)
Race/ethnicity, n (%)
White	1582 (64)	1900 (67)
East Asian	190 (8)	187 (7)
Indigenous	192 (8)	190 (7)
South Asian	147 (6)	228 (8)
Black	88 (4)	95 (3)
Other	277 (11)	236 (8)
Distance from patient’s residence to center, km, n (%)
<50	1937 (78)	2291 (81)
50–100	377 (15)	345 (12)
>150	162 (7)	200 (7)

BMI, body mass index; CABG, coronary artery bypass graft.

Despite similar patient characteristics (Table 1), there was a baseline difference in use of home dialysis at 180 days among patients in intervention (28%) and control (23%) clusters before the intervention was implemented (P=0.10). There seemed to be a lower use of home dialysis within control clusters between 2010 and 2016 compared with intervention clusters (Supplemental Figure 1).

Primary Outcome: Use of Home Dialysis at 180 Days after Dialysis Initiation

The use of home dialysis at 180 days did not vary in the trial period across intervention and control clusters, with a relative risk of 1.16 (95% confidence interval [95% CI], 0.92 to 1.45) and absolute risk difference of 4% (95% CI, 2% to 9%) (Table 2). Using a difference-in-difference comparison, the use of home dialysis at 180 days was similar before and after implementation of the intervention (difference, 0% in intervention clinics; 95% CI, −2% to 3%; difference, 0.8% in control clinics; 95% CI, −1% to 3%; P=0.84) (Figure 3 and Table 3). After adjusting for clustering, the absolute between-group risk difference was −0.3% (95% CI, −4% to 3%; relative risk adjusted for clustering, 0.99; 95% CI, 0.86 to 1.13).

Table 2. - The use of home dialysis at 180 days (primary analysis) and at initiation in the year following the intervention

Outcome	Intervention, n=2476	Control, n=2836	Relative Risk (95% Confidence Interval)	Absolute Risk Difference (95% Confidence Interval)	P Value
Primary outcome
Home dialysis at 180 d postdialysis initiation	705 (29%)	686 (24%)	1.16 (0.92 to 1.45)	4% (−2% to 9%)	0.21
Secondary outcome
Home dialysis at 180 d postdialysis initiation among those with at least 90 d of nephrology care	614/1851 (33%)	588/2011 (29%)	1.13 (0.90 to 1.43)	4% (−3% to 11%)	0.29
Other outcomes
Home dialysis at dialysis initiation	467 (19%)	377 (13%)	1.31 (0.88 to 1.93)	4% (−2% to 10%)	0.17
Any home dialysis within 180 d	784 (32%)	806 (28%)	1.11 (0.89 to 1.39)	3% (−3% to 9%)	0.37

This is only adjusted for cluster correlation in the baseline analysis and not for individual factors.

Figure 3.: Proportion of patients using home dialysis at 180 days for the year before and year after study initiation, by intervention and control clinic clusters. Solid line, intervention cluster; dashed line, control clusters.

Table 3. - Results of differences-in-differences analyses with generalized estimating equations models comparing the 1-year preintervention with the 1-year postintervention

Outcome	Intervention Group			Control Group			Effect of Intervention
	Preintervention, n=2468, no. (%)	Postintervention, n=2476, no. (%)	Difference, % (95% CI)	Preintervention, n=2798, no. (%)	Postintervention, n=2836, no. (%)	Difference, % (95% CI)	Crude Absolute Risk Difference between Groups, % (95% CI)	Absolute Risk Difference between Groups Accounting for Clustering, % (95% CI)	Relative Risk between Groups Accounting for Clustering, Relative Risk (95% CI)	P Value
Primary outcome
Home dialysis at 180 d postdialysis initiation	702 (28)	705 (28)	0 (–2 to 3)	653 (23)	686 (24)	0.8 (–1 to 3)	−0.8 (–4 to 3)	−0.3 (–4 to 3)	0.99 (0.86 to 1.13)	0.84
Secondary outcome
Home dialysis at 180 d postdialysis initiation among those with at least 90 d of nephrology care	610/1860 (33)	614/1851 (33)	0.4 (–3 to 3)	560/1981 (28)	588/2011 (29)	1 (–2 to 4)	−1 (–5 to 4)	−0.2 (–5 to 4)	0.98 (0.85 to 1.14)	0.84
Other outcomes
Home dialysis at dialysis initiation	526 (21)	467 (19)	−2 (–5 to 0.2)	363 (13)	377 (13)	0.3 (–1 to 0.2)	−3 (–6 to 0.1)	−2 (–5 to 0.5)	0.86 (0.72 to 1.03)	0.10
Any home dialysis within 180 d	795 (32)	784 (32)	−1 (–3 to 2)	751 (27)	806 (28)	2 (–1 to 4)	−2 (–6 to 1)	−1 (–5 to 2)	0.95 (0.84 to 1.06)	0.35

95% CI, 95% confidence interval.

Secondary Outcome: Use of Home Dialysis at 180 Days after Dialysis Initiation among Those Who Were Followed by a Nephrologist prior to Dialysis Initiation

Using a difference-in-difference comparison, the use of home dialysis at 180 days was similar before and after implementation of the intervention (difference, 0.4% in intervention clinics; 95% CI, −3% to 3%; difference, 1% in control clinics; 95% CI, –2% to 4%; P=0.84) (Figure 3 and Table 3). After adjusting for clustering, the absolute between-group risk difference was −0.2% (95% CI, −5% to 4%; relative risk adjusted for clustering, 0.98; 95% CI, 0.85 to 1.14).

Other Outcomes

Considering the secondary outcomes of use of home dialysis at initiation and any use of home dialysis within 180 days, there was no difference noted across intervention and control clusters (Tables 2 and 3). Using a log Poisson model to adjust for patient differences and imputing for missing data, there was no difference in use of home dialysis at 180 days.

In a survey completed by 20 of 27 intervention clusters between 3 and 6 months after the in-person visit, 45% of the intervention clusters reported a high ongoing use of the knowledge translation tools. Comparing the 12 of 27 intervention clusters that reported a high subjective use of the knowledge translation tools with control clusters, we did not find any statistically significant changes in the primary outcome (Supplemental Table 2).

Discussion

We noted no difference in the use of home dialysis at 180 days after dialysis initiation in intervention and control clusters. This is despite the use of a multifaceted knowledge translation intervention, including audit and feedback, patient and provider tools and education, and an academic detailing visit, each of which has been shown in other studies to increase uptake (^32–34).

There are several possible reasons why our study did not detect any differences between the study groups. These include baseline differences in the clusters randomized to intervention and control (specifically differences in the baseline use of home dialysis across intervention and control clusters), more variability in the use of home dialysis across clinics than we expected, because our intervention was not effective, and issues with study power. Although there were over 5300 patients in the intervention and control clusters, the effective sample size is 55 clusters, meaning that small imbalances in clusters might have large effects and that our study was likely underpowered to show significant differences.

We noted baseline differences in the use of home dialysis, with higher use of home dialysis in the intervention clusters. Use of home dialysis at initiation in the intervention clusters before the study intervention was 28%, which is higher than in most health systems and higher than the Canadian average in 2015 (22%) (³⁵). Thus, it is possible that these clusters had reached a ceiling in the use of home dialysis and that further increases were not possible with an intervention of the type we tested. It may be that future cluster randomized controlled trials should focus on randomizing clusters with low performance on the outcome of interest for the study to avoid a possible ceiling effect.

It is possible that our intervention was simply not effective—of particular relevance given that the primary focus of the intervention and cluster randomized controlled trial was on improving appropriateness of the timing of dialysis initiation (also a negative study) (²¹). It was also relevant to study the intervention’s effect on the use of home dialysis because the tools all emphasized the use of home dialysis, and decision making on dialysis modality is being made at the same time as consideration around timing of initiation. Despite basing our intervention on an understanding of the barriers to use of home dialysis (patient and physician knowledge), the tools and strategies we used may not have overcome the barriers to use of home dialysis. This may be because the tools were not effective or because the tools and recommendations were not used consistently within clinics. We did measure clinic engagement after the intervention was administered (including whether the educational tools were disseminated to patients and whether clinic processes changed), but even in clusters that appeared engaged, we did not identify a difference in the use of home dialysis at 180 days. In addition, numerous policy interventions to promote home dialysis uptake were in effect in several provinces during the study period. These efforts, led by provincial kidney programs, included funding for and hiring of home dialysis educators and nurse navigators, financial incentives and penalties for kidney care programs, educational tools for patients and staff, decision aids, and others. Collectively, these background interventions may have driven home dialysis uptake at control clusters, attenuating any potential effectiveness of our intervention.

Our results should be considered in the context of past research. A past systematic review looking at the effectiveness of nonfinancial interventions to increase use of peritoneal dialysis suggested that the following were effective: predialysis education, reporting the proportion of patients receiving peritoneal dialysis at different dialysis centers, nephrologist-directed peritoneal dialysis catheter placement (in programs where delays in peritoneal dialysis catheter placement exist), home-assisted peritoneal dialysis, and peritoneal dialysis–first initiatives (³⁶). Our strategy included two of these strategies, although as noted above, it is unclear whether the tools disseminated to intervention clinics were used consistently. Although restricting choice of dialysis modality is controversial, studies suggest that some patients who are not capable of home dialysis can still successfully be managed at home with assisted peritoneal dialysis with equivalent outcomes (³⁷) and at lower cost (³⁸).

Our results have implications for US dialysis centers given recent federal legislation; the Advancing American Kidney Health initiative set a goal that 80% of patients who initiate KRT in 2025 will receive home dialysis or a transplant (³⁹). Our results suggest that increasing the use of home dialysis to meet this goal will be challenging. It is relevant to note, however, that of the 10,578 patients who initiated dialysis with in-center hemodialysis in the pre- and postperiods, 1527 (14%) switched and were receiving home dialysis at 180 days. Given this, interventions that can facilitate patients switching modality after initiation should be explored in future research.

The strengths of this study include its national scope, as we included all provinces except Quebec, and randomization of essentially all Canadians with advanced CKD who were cared for by nephrologists. Limitations included that the level of engagement with the intervention was inconsistent among clinics (with <50% of clinics reporting a high level of engagement with the intervention after 3 months), and we were unable to tailor the intervention to each clinic’s individual needs. In addition, our outcomes were collected from the Canadian Organ Replacement Register and were only on the basis of the proportion of patients who progressed to kidney failure and started dialysis during this time period. It is possible that the effect of the intervention may have been observed in later time periods. Finally, the cluster-level trial design of our study may have limited the power to detect small differences in the efficacy of the intervention.

This study illustrates that increasing the use of home dialysis is challenging. Further research is required to determine the optimal strategy for increasing the use of home dialysis. Although education can increase the proportion of patients who prefer home dialysis, utilization of home dialysis is complex, and more complex interventions that assess and overcome barriers to the use of home dialysis at a patient level are likely required.

Disclosures

A. Alam reports consultancy agreements with AstraZeneca, Janssen, and Otsuka Canada; honoraria from AstraZeneca Inc., Janssen Inc., and Otsuka Pharmaceutical Inc.; speakers bureau for AstraZeneca and Otsuka Canada; and other interests or relationships with Royal College International (Canada). S. Allu reports employment with the Canadians Seeking Solutions and Innovations to Overcome Chronic Kidney Disease (Can-SOLVE CKD) Network. T. Ferguson reports consultancy agreements with Clinpredict LTD, Quanta Dialysis Technologies LTD, Strategic Health Resources, and Tricida Inc. and honoraria from Baxter Corporation. A.X. Garg reports research funding from Astellas and Baxter; serving on the editorial boards of American Journal of Kidney Diseases and Kidney International; serving on the data safety and monitoring board for an anemia trial program funded by GlaxoSmithKline; and serving in the medical lead role to improve access to kidney transplantation and living kidney donation for the Ontario Renal Network (a government-funded agency located within Ontario Health). A.X. Garg has received partnership grant funding from Astellas Canada Inc. for a Canadian Institutes of Health Research–funded grant in the area of living kidney donation. S.J. Kim reports support from Astellas Pharma Canada Inc. and serving in an advisory or leadership role for Canadian Blood Services, the Canadian Organ Replacement Register, the Canadian Society of Transplantation, Health Canada, the Organ Procurement and Transplant Network (OPTN)/United Network for Organ Sharing (UNOS) Data Advisory Committee, and the Scientific Registry of Transplant Recipients Technical Advisory Committee. G.E. Nesrallah reports consultancy agreements with Amgen Inc., AstraZeneca, Baxter Healthcare, and Otsuka and research funding from Baxter Healthcare. M.M. Sood reports consultancy agreements with AstraZeneca; honoraria from AstraZeneca; receiving speaker fees and educational funds from AstraZeneca; serving on the editorial boards of American Journal of Kidney Disease, Canadian Journal of Cardiology, and CJASN; serving as the Deputy Editor of Canadian Journal of Kidney Disease and Health; and serving as a member of the American Society of Nephrology Highlights ESRD Team. S.D. Soroka reports honoraria from AstraZeneca, Bayer, and Otsuka and speakers bureau for AstraZeneca, Bayer, Jannsen, and Otsuka. N. Tangri reports consultancy agreements with Healthlogic, Mesentech Inc., PulseData Inc., Renibus, and Tricida Inc.; ownership interest in Clinpredict Ltd., Healthlogic, Klinrisk, Mesentech Inc., PulseData Inc., Renibus, and Tricida Inc.; research funding from AstraZeneca Inc., Bayer, BI-Lilly, Janssen, Otsuka, and Tricida Inc.; honoraria from AstraZeneca Inc., Bayer, BI-Lilly, Janssen, Otsuka Pharmaceuticals, and Pfizer; advisory or leadership role for Mesentech, Pulsedata Inc., Renibus, and Tricida Inc.; a patent (“A microfluidic device for point of care detection of urine albumin”) pending; other interests or relationships with the National Kidney Foundation; and being the founder of Klinrisk, Clinpredict. All remaining authors have nothing to disclose.

Funding

This study was funded by a Baxter Healthcare Corporation Extramural grant (investigator initiated), the Canadian Institutes of Health Research Network Catalyst Grant - Diabetes, Obesity, Digestive and Kidney, the Kidney Foundation of Canada Network Catalyst Grant - Diabetes, Obesity, Digestive and Kidney, and Research Manitoba. A.X. Garg was supported by the Dr. Adam Linton Chair in Kidney Health Analytics and a Canadian Institutes of Health Research clinical investigator award. B.J. Manns is supported by the Svare Chair in Health Economics and a Canadian Institutes of Health Research foundation award. M.M. Sood is supported by the Jindal Research Chair for the Prevention of Kidney Disease. N. Tangri was supported by the Canadian Institutes of Health Research new investigator award and a Canadian Institutes of Health Research foundation award.