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Record W4229335543 · doi:10.2215/cjn.02150222

Is There an Ideal Recipe to Increase Home Dialysis Use?

2022· letter· en· W4229335543 on OpenAlexafffundabout
Jenny I. Shen, Jeffrey Perl

Bibliographic record

VenueClinical Journal of the American Society of Nephrology · 2022
Typeletter
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesCanadian Institutes of Health Research
KeywordsMedicineDialysisHome dialysisIntensive care medicineHome hemodialysisIntervention (counseling)Kidney transplantationKidney diseaseTransplantationHemodialysisFamily medicineInternal medicineNursing

Abstract

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Home dialysis offers similar clinical and patient-reported outcomes as in-center dialysis (1). Because there are few absolute contraindications to either type of therapy, modality choice should primarily be on the basis of patients’ preferences. However, prevalent home dialysis use has remained <15% in the United States despite studies that show that nearly half of patients prefer it when educated about their dialysis modality treatment options (2,3). In recognition of the underutilization of home dialysis and kidney transplantation, the United States aims to have 80% of incident patients with kidney failure treated with either of these therapies by 2025, as part of its Advancing American Kidney Health Initiative (4). With the current limited supply of kidneys available for transplant, widespread increases in the use of home dialysis are needed to reach this ambitious goal. Such an endeavor will undoubtedly require dramatic changes in the way in which home dialysis education, initiation, and practice are performed as well as expanded access to care and education for patients with advanced CKD prior to KRT. In Canada, where multidisciplinary advanced CKD care is universally available, Manns et al. (5) report in this issue of CJASN the outcomes of a large-scale intervention within 55 clinics to increase the use of home dialysis in Canada. From 2014 to 2015, these clinics were cluster randomized and stratified by clinic size and province to a multipronged intervention aimed at improving the utilization of home dialysis. First, a knowledge translation broker, someone trained in delivering information, surveyed the clinics about current practices. Then, one of the study investigators, all of whom are nephrologists, completed a medical detailing visit that reviewed the current guidelines, provided specific information on the clinic’s current performance (audit and feedback), introduced both provider- and patient-directed educational materials, and identified a local champion. Provider-focused tools included a Canadian version of the Method to Assess Treatment Choices for Home Dialysis (MATCH-D) tool to assist the staff in identifying possible home dialysis candidates. Patient-facing educational materials included posters, handouts, videos, and a decision aid. The knowledge translation broker and the visiting nephrologist reinforced the use of these educational materials via follow-up calls and emails to either the clinic and/or the local champions. The primary outcome was the percentage of patients using home dialysis at 180 days after dialysis initiation, starting from the date of the medical detailing visit. The outcome was abstracted from Canada’s national dialysis registry, the Canadian Organ Replacement Register. At study start, characteristics of the patients in the intervention and control arms were balanced, but clinics in the intervention group already had a higher use of home dialysis than their control clinic counterparts (28% versus 23%). Postintervention, there was no difference between the two groups in the proportion of patients on home dialysis at initiation (absolute risk difference, 4%; 95% confidence interval, −2% to 10%) or on day 180 after dialysis initiation (absolute risk difference, 4%; 95% confidence interval, −2% to 9%). Further, in both groups, the proportion of home dialysis use remain unchanged from baseline. Analyses restricting the population to those who had seen a nephrologist prior to dialysis initiation, adjusting for patient differences and imputation to address missing data, and restricted to clinics who reported high engagement with the provided tools 3–6 months after the detailing visit also demonstrated no significant changes between the control and treatment groups in the primary outcome. The investigators should be greatly applauded for moving the field forward from mostly single-center interventions to a scientifically rigorous, multicenter, randomized clinical trial of home modality use that used a systematic evaluation of multiple different interventions and outcomes. They used targeted interventions that have been shown to improve home dialysis use: predialysis education and benchmarking a clinic’s performance against other clinics. Not only did they address knowledge gaps among patients, but they also attempted to educate staff about patient eligibility for home dialysis. Within this context, 14% of those who initiated center-based dialysis switched to home dialysis by 180 days. Why did the study fail to show between-group differences? One possibility is that although it had a “recipe for success” supported by prior evidence, wide-scale implementation may have required a more individualized approach that catered to all tastes and local ingredients. Regarding education, patients and providers learn and understand information differently, and it is possible that the largely written materials were not well suited to those who learn best by other means or languages and who present with unique cultural considerations not addressed by these educational tools (6,7). Although many patients rely on their health care team for education and advice, many also value peer support and education, which were not evaluated (8). When it comes to comparing a clinic’s performance against others, knowing how they perform relative to other clinics is important, but motivation to improve performance may be lacking if there is no culture of accountability, incentives, or penalties, particularly in the face of no specific a priori home dialysis utilization targets. Improved feedback and evaluation from patients and providers may have been needed around engagement, activation, and comprehension. Did this intervention contain all of the ingredients necessary for the successful growth of home dialysis? Previously reported are six important steps needed to establish an individual on home dialysis. These are (1) identify potential home dialysis candidates, (2) assess home dialysis eligibility, (3) offer home dialysis to the eligible, (4) patients choose home dialysis, (5) create a successful access (i.e., peritoneal dialysis [PD] catheter or vascular access), and (6) initiate home therapy. All steps are important to consider in identifying where programs may be struggling to grow home dialysis. Two other large-scale interventions that successfully grew home dialysis in Ontario, Canada and California, the United States are worth discussing. Importantly and in contrast to this study, both tackled additional barriers. The first intervention is also a Canadian initiative, although it was restricted to the province of Ontario. From 2012 to 2019, the Ontario Renal Network Home Dialysis Initiative implemented 13 different interventions (9). Not only did they address predialysis education and auditing clinics, but they also provided financial support, such as funded home dialysis coordinators and reimbursement of patient costs for home hemodialysis, as well as financial incentives and penalties. They also addressed barriers to successful PD catheter access. To broaden home dialysis eligibility, they promoted assisted PD, funded PD in long-term care homes, promoted urgent PD start, promoted transitional care units where new start patients on in-center hemodialysis received systematic education about home modalities, and piloted an assisted home hemodialysis pilot program. These efforts resulted in an increase in home dialysis use from 22% to 27% from 2012 to 2017 that plateaued at 26% from 2017 to 2019. Notably, the rate of home dialysis use was already 28% in the intervention arm in the study by Manns et al. (5), which may have limited the trial’s ability to show a meaningful growth in home dialysis. An integrated health care delivery system in Northern California in the United States implemented a second successful large-scale intervention (10). They educated not only nephrologists and patients but also providers in primary care, emergency medicine, and surgery. Like the Ontario Renal Network Home Dialysis Initiative, they improved access to urgent start PD and to PD catheter placement in general. The leadership was also engaged and supportive of the initiative, in addition to having a PD champion at each medical center. As an integrated health care system, they also had a financial stake in improving PD uptake. Moreover, they were able to provide predialysis care to the vast majority of their patients. With this multilevel intervention, incident PD initiation jumped from 15% to 34% from 2008 to 2018. Neither the Ontario nor the Northern California intervention was on a national scale, but perhaps this is the reason they succeeded; the smaller size allowed them to better tailor their intervention to the individual clinics. Both also involved integrated health care systems that allowed them to tackle the challenge from multiple fronts and at several different points in the path from the time the patient chooses a modality to when the patient initiates dialysis. Importantly, stakeholders included the payers for dialysis. It also took many years for both initiatives to show their full effect, whereas this study only had 1 year of follow-up. What can we learn from these studies? Increasing home dialysis use past the current 13% of prevalent patients on dialysis in the United States will require evidence-based recipes, the right ingredients, and modification of strategies to suit local tastes. Success will also hinge upon skillful implementation of even well-designed interventions. Long-term, multilevel, locally tailored strategies are only as successful as the strong provider engagement that accompanies them. This will require customization in the form of developing culturally appropriate, multilingual, multimedia educational materials that consider the needs of under-represented communities. It will also involve universal access to predialysis care while fostering dedicated education and home dialysis implementation pathways for those patients who unexpectedly start dialysis and choose to go home. The success of modality education interventions should also be measured by patient satisfaction in the education and decision support received. Moreover, this education will be most successful if accompanied by strong mechanisms of support to patients and their care partners as they make not only a life-changing transition to dialysis but take a further leap to independent dialysis at home. Disclosures J. Perl reports consultancy agreements with AstraZeneca, Baxter Health Care Canada, Bayer, DaVita Healthcare Partners, Fresenius Medical Care, LiberDi, and Otsuka; reports research funding from the Agency for Healthcare Research and Quality during the conduct of the study; reports research funding from Arbor Research Collaborative for Health; reports honoraria from AstraZeneca, Baxter Healthcare USA/Canada, DaVita Healthcare Partners, DCI, Fresenius Medical Care, and US Renal Care; reports speakers bureau for Baxter Healthcare and Fresenius Medical Care; reports salary support from Arbor Research Collaborative for Health; reports other interests or relationships with AHRQ; and is on the advisory board for Liberdi. J.I. Shen reports serving as an associate editor of Kidney Medicine; serving as a scientific advisor or member of the North American Council of the International Society of Peritoneal Dialysis, the Peritoneal Dialysis Outcomes and Practice Patterns Study steering committee, and the Peritoneal Dialysis International editorial board; serving as a member of the American Society of Nephrology and the National Kidney Foundation; and receiving research funding from the Canadian Institutes of Health Research, the Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, and the National Institute of Diabetes and Digestive and Kidney Diseases during the conduct of the study. Funding None.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0040.003
Open science0.0010.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0130.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.056
GPT teacher head0.362
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2022
Admission routes3
Has abstractyes

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