Association of Primary Versus Rotating Nephrologist Model of Care in Hemodialysis Programs with Patient Outcomes

Significance Statement

Nephrologist staffing models for patients receiving hemodialysis vary widely. Patients may be cared for continuously by a single primary nephrologist or by a group of nephrologists on a rotating basis. It remains unclear whether these differing care models influence clinical outcomes. In this population-based cohort study of more than 14,000 incident patients on maintenance hemodialysis from Ontario, Canada, we found no difference in mortality, kidney transplantation, home dialysis initiation, hospitalizations, or emergency department visits when care was provided by a single primary nephrologist or a rotating group of nephrologists. These results suggest that primary nephrologist models do not necessarily improve objective clinical outcomes, providing reassurance to patients, providers, and administrators that both models are acceptable options.

Introduction

Variation in how hemodialysis care is provided by nephrologists may affect clinical outcomes.¹ Some hemodialysis programs use a primary nephrologist model where a single nephrologist provides longitudinal care. Other programs use a rotating nephrologist model where a group of ≥2 nephrologists share care for patients. The primary nephrologist model may promote continuity of care,² whereas the rotating nephrologist model may allow for fresh perspectives on complicated patient issues. Given that it remains unclear whether one approach is superior, we compared clinical outcomes between in-center hemodialysis programs that used a primary nephrologist versus rotating nephrologist model of care.

Methods

We conducted a retrospective observational cohort study in Ontario, Canada, using linked administrative datasets at ICES (Supplemental Table 1) in adult patients initiating in-center maintenance hemodialysis from January 1, 2011, to December 31, 2018. The study exposure was the hemodialysis program's dominant model of care: Either a primary nephrologist model or rotating nephrologist model ascertained with a web-based survey (SurveyMonkey) (Supplemental Table 2). The primary outcome was all-cause mortality. Secondary outcomes were kidney transplantation, home dialysis initiation, hospitalizations, and emergency department (ER) visits.

All analyses occurred at the level of the patient. We used multivariable Fine-Gray subdistribution hazard models to evaluate the relationship between model of care and all-cause mortality, kidney transplantation, and home dialysis initiation. We analyzed hospitalizations using Poisson regression and ER visits with a negative binomial model. We controlled for clustering at the level of the in-center hemodialysis program using generalized estimating equations with robust sandwich variance estimators. We selected patient-level and hemodialysis program characteristics as covariates a priori. We adjusted for nine patient characteristics (model 1) and added six in-center hemodialysis program characteristics in model 2. We evaluated the association between nephrologist model of care and all-cause mortality in several prespecified subgroups and sensitivity analyses. See Supplemental Methods for more details.

Results

The study flow diagram is shown in Supplemental Figure 1, and the median follow-up time was 1.8 years (interquartile range, 0.6–3.4). Patient characteristics were generally well-balanced between groups with some differences in race and dialysis program variables (Supplemental Table 3).

Death occurred in 39.8% (2825 of 7090) of patients in the primary nephrologist model and 41.4% (2881 of 6962) in the rotating nephrologist model (Table 1). The primary care nephrologist model was not associated with lower mortality (model 2 subdistribution hazard ratio [sHR], 1.03; 95% confidence interval [CI], 0.92 to 1.16) (Supplemental Figure 2).

Table 1.

Association of nephrologist model of care with patient outcomes

Outcome	Model of Care	Total No. of Patients	Events	Rate (Per 1000 Person Years)	Unadjusted	Adjusted (Model 1)a	Adjusted (Model 2)b
					sHR (95% CI)	sHR (95% CI)	sHR (95% CI)
Primary Outcome
All-cause mortality	Rotating nephrologist	6962	2881 (41.4%)	182.0	1.00 (referent)	1.00 (referent)	1.00 (referent)
	Primary nephrologist	7090	2825 (39.8%)	177.0	0.97 (0.81 to 1.14)	1.03 (0.91 to 1.16)	1.03 (0.92 to 1.16)
Secondary outcomes
Transfer to home dialysis	Rotating nephrologist	6962	691 (9.9%)	43.6	1.00 (referent)	1.00 (referent)	1.00 (referent)
	Primary nephrologist	7090	624 (8.8%)	39.1	0.88 (0.68 to 1.13)	0.86 (0.69 to 1.06)	0.79 (0.60 to 1.03)
Kidney transplantation	Rotating nephrologist	6962	469 (6.7%)	29.6	1.00 (referent)	1.00 (referent)	1.00 (referent)
	Primary nephrologist	7090	632 (8.9%)	39.6	1.36 (1.01 to 1.84)	1.30 (0.91 to 1.86)	1.19 (0.84 to 1.68)
					IRR (95% CI)	IRR (95% CI)	IRR (95% CI)
All-cause hospitalization	Rotating nephrologist	6962	16,436	1038.1	1.00 (referent)	1.00 (referent)	1.00 (referent)
	Primary nephrologist	7090	17,303	1084.1	1.07 (0.72 to 1.60)	1.09 (0.81 to 1.46)	1.16 (0.86 to 1.58)
All-cause ER visits	Rotating nephrologist	6962	38,253	2416.1	1.00 (referent)	1.00 (referent)	1.00 (referent)
	Primary nephrologist	7090	34,955	2190.0	0.81 (0.47 to 1.41)	0.98 (0.72 to 1.34)	1.03 (0.75 to 1.41)

sHR, subdistribution hazard ratio; CI, confidence interval; IRR, incidence rate ratio; ER, emergency department.

^aModel 1 is adjusted for age, sex, rural residence, race, primary cause of ESKD, health care utilization in the previous year (ER visits, general practitioner visits, and cardiology visits), and Charlson Comorbidity Index.

^bModel 2 is adjusted for covariates from model 1 and program characteristics, including academic hospital, hemodialysis patients per program, full-time dietician equivalents, presence of nurse practitioner or physician assistant at the main/hub dialysis center, number of satellite dialysis centers per program, and number of satellite patients per program.

Kidney transplantation occurred in 8.9% (632 of 7090) of patients in the primary nephrologist model versus 6.7% (469 of 6962) in the rotating nephrologist model; however, there was no association with model of care (model 2 sHR, 1.19; 95% CI, 0.84 to 1.68; Table 1 and Supplemental Figure 2). Transfer to home dialysis occurred in 8.8% (624 of 7090) of patients in the primary nephrologist model and 9.9% (691 of 6962) in the rotating model, with no association after multivariable adjustment (model 2 sHR, 0.79; 95% CI, 0.60 to 1.03; Table 1 and Supplemental Figure 2). We also did not find an association between model of care and hospitalizations or ER visits (Table 1).

There was no evidence of heterogeneity for all-cause mortality in subgroups, with the exception of hemodialysis programs with >500 patients and Charlson ≥4, where higher mortality was observed in the primary care nephrologist model (Supplemental Figure 3). The robustness of our findings was confirmed in multiple sensitivity analyses (Supplemental Table 4).

Discussion

In this study of more than 14,000 patients, care by a single primary nephrologist did not improve clinical outcomes relative to a rotating group of nephrologists. The lack of association was largely consistent across subgroups and sensitivity analyses. There was a potential interaction between nephrologist model of care and mortality in primary nephrologist programs with more than 500 patients or Charlson ≥4, suggesting potential harm possibly related to fatigue, high patient caseloads, and greater comorbidity.³ The lack of association of the primary nephrologist model with any improvement in outcomes underscores that the nephrologist is only a single member of a multidisciplinary team.^4,5 Although both home dialysis and transplantation therapies require patient education and support that might be enhanced by a closer nephrologist-patient relationship, other factors may act as greater treatment barriers (e.g., family supports, cultural background, and systemic health care processes).⁴ The rate of hospitalizations and ER visits also did not differ, suggesting no model led to earlier detection and management of acute medical problems.

This is the first study to address the model of nephrologist care delivery in a large, incident hemodialysis population with complete ascertainment of clinical outcomes and limited loss to follow-up. We conducted a rigorous survey of programs, confirmed responses, and adjusted for multiple program characteristics.

This study does have limitations. We did not capture the actions of nephrologists during patient interactions, and it is possible that the primary nephrologist model may improve quality of care and patient-reported outcome measures (e.g., symptom burden, mental health, and the patient experience); these data were not available but warrant further study. In addition, it is possible that patients receiving care at programs with a primary nephrologist model were sicker and more complex. Other unknown hemodialysis program factors could have also contributed to confounding (e.g., anemia/iron protocols).

In conclusion, we found that among incident in-center maintenance hemodialysis recipients, a primary nephrologist model of care was not associated with improved clinical outcomes as compared with a rotating nephrologist model. Although our results do not indicate an optimal model of care, this study supports both models being acceptable and may have implications on hemodialysis program nephrologist staffing.

Supplementary Material

jasn-34-1155-s001.pdf ^{(668.1KB, pdf)}

Disclosures

A.X. Garg reports Research Funding: Astellas and Baxter; Advisory or Leadership Role: Currently on the Editorial Boards of American Journal of Kidney Diseases and Kidney International; and Other Interests or Relationships: Served as the Medical Lead Role to Improve Access to Kidney Transplantation and Living Kidney Donation for the Ontario Renal Network (government funded agency located within Ontario Health). This position ended October 2022. S.A. Silver has received consulting fees from AstraZeneca, speaking fees from Baxter Canada and honorarium from Novo Nordisk and Otsuka. S.A. Silver reports Advisory or Leadership Role: Canadian Society of Nephrology Board Member. M.M. Sood reports Consultancy: Astrazeneca; and Advisory or Leadership Role: Bayer, GlaxoSmithKline, and Otsuka. M.M. Sood has received speaker fees from AstraZeneca. A. Thomas reports Honoraria: Astra-Zeneca Pharmaceuticals Canada, GSK Canada, and Otsuka Canada; and Speakers Bureau: GSK Canada and Otsuka Canada. A. Thomas has received speaker fees from AstraZeneca and Otsuka. R. Wald reports Consultancy: Lilly and Otsuka; Research Funding: Baxter; Honoraria: Baxter; Advisory or Leadership Role: Editorial Boards of CJASN, Kidney Medicine, and Kidney360; and Other Interests or Relationships: Contributor for UpToDate. R. Wald has received unrestricted grant support and speaking fees from Baxter. Data Access/Access to Data Analysis Protocol: The analysis was conducted by members of the ICES Kidney Dialysis & Transplantation (KDT) team at the ICES Western facility (London, ON). Y. Kang was responsible for the data analysis. The protocol can be obtained by emailing S.A. Silver at samuel.silver@queensu.ca. All remaining authors have nothing to disclose.

Funding

This study was conducted under the auspices of the ICES Kidney Dialysis Transplantation Program at ICES Western who are supported by a grant from the Canadian Institutes of Health Research (CIHR). ICES is funded by an annual grant from the Ontario Ministry of Health (MOH) and Ministry of Long-Term Care (MLTC). Core funding for ICES Western is provided by the Academic Medical Organization of Southwestern Ontario (AMOSO), the Schulich School of Medicine and Dentistry (SSMD), Western University, and the Lawson Health Research Institute (LHRI). Parts of this material are based on data and information compiled and provided by Ministry of Health (MOH), CIHI, and Ontario Health (OH). However, the analyses, conclusions, opinions, and statements expressed herein are solely those of the authors and do not reflect those of the funding or data sources; no endorsement is intended or should be inferred. We thank IQVIA Solutions Canada Inc. for use of their Drug Information File. The funders had no role in in study design; data collection, analysis, or reporting; or the decision to submit for publication.

Author Contributions

Conceptualization: Amit X. Garg, Nivethika Jeyakumar, Samuel A. Silver, Alison Thomas, Ron Wald, Kevin Yau.

Data curation: Megan Freeman, Nivethika Jeyakumar, Samuel A. Silver, Alison Thomas, Yuguang Kang.

Formal analysis: Yuguang Kang, Samuel A. Silver, Kevin Yau.

Funding acquisition: Samuel A. Silver.

Investigation: Ziv Harel, Samuel A. Silver, Ron Wald, Kevin Yau.

Methodology: Stephanie N. Dixon, Amit X. Garg, Ziv Harel, Nivethika Jeyakumar, Samuel A. Silver, Manish M. Sood, Ron Wald, Kevin Yau.

Project administration: Nivethika Jeyakumar, Samuel A. Silver.

Resources: Samuel A. Silver, Ron Wald.

Supervision: Samuel A. Silver, Ron Wald.

Visualization: Yuguang Kang.

Writing – original draft: Samuel A. Silver, Kevin Yau.

Writing – review & editing: Stephanie N. Dixon, Megan Freeman, Amit X. Garg, Ziv Harel, Nivethika Jeyakumar, Yuguang Kang, Samuel A. Silver, Manish M. Sood, Alison Thomas, Ron Wald, Kevin Yau.

Supplemental Material

This article contains the following supplemental material online at http://links.lww.com/JSN/E416.

Supplemental Methods.

Supplemental Table 1. Diagnostic codes used for cohort build, baseline characteristics and outcomes.

Supplemental Table 2. Survey questions completed by dialysis program directors/leadership.

Supplemental Table 3. Baseline characteristics of incident patients on maintenance in-center hemodialysis in the primary nephrologist and rotating nephrologist model of care.

Supplemental Table 4. Sensitivity analyses for all-cause mortality.

Supplemental Figure 1. Study cohort build. Independent health facilities refer to privately owned dialysis enterprises while a permanent exit refers to withdrawal, recovery from dialysis, transfer out of region, or lost to follow-up.

Supplemental Figure 2. Cumulative incidence function curves for (A) all-cause mortality, (B) kidney transplantation, and (C) home dialysis initiation.

Supplemental Figure 3. Prespecified subgroup analyses for all-cause mortality with adjustment from model 2. Model 2 includes patient characteristics: age, sex, rural residence, race, primary cause of ESKD, health care utilization in the previous year (emergency department visits, general practitioner visits, and cardiology visits), Charlson Comorbidity Index, and program characteristics: academic hospital, hemodialysis patients per program, full-time dietician equivalents, presence of nurse practitioner or physician assistant at the main/hub dialysis center, number of satellite dialysis centers per program, and number of satellite patients per program.