Skip to main content

Main menu

  • Home
  • Content
    • Published Ahead of Print
    • Current Issue
    • Podcasts
    • Subject Collections
    • Archives
    • ASN Meeting Abstracts
    • Saved Searches
  • Authors
    • Submit a Manuscript
    • Author Resources
    • Reprint Information
  • Trainees
    • Peer Review Program
    • Prize Competition
  • About CJASN
    • About CJASN
    • Editorial Team
    • CJASN Impact
    • CJASN Recognitions
  • More
    • Alerts
    • Advertising
    • Reprint Information
    • Subscriptions
    • Feedback
  • ASN Kidney News
  • Other
    • JASN
    • Kidney360
    • Kidney News Online
    • American Society of Nephrology

User menu

  • Subscribe
  • My alerts
  • Log in
  • My Cart

Search

  • Advanced search
American Society of Nephrology
  • Other
    • JASN
    • Kidney360
    • Kidney News Online
    • American Society of Nephrology
  • Subscribe
  • My alerts
  • Log in
  • My Cart
Advertisement
American Society of Nephrology

Advanced Search

  • Home
  • Content
    • Published Ahead of Print
    • Current Issue
    • Podcasts
    • Subject Collections
    • Archives
    • ASN Meeting Abstracts
    • Saved Searches
  • Authors
    • Submit a Manuscript
    • Author Resources
    • Reprint Information
  • Trainees
    • Peer Review Program
    • Prize Competition
  • About CJASN
    • About CJASN
    • Editorial Team
    • CJASN Impact
    • CJASN Recognitions
  • More
    • Alerts
    • Advertising
    • Reprint Information
    • Subscriptions
    • Feedback
  • ASN Kidney News
  • Visit ASN on Facebook
  • Follow CJASN on Twitter
  • CJASN RSS
  • Community Forum
Public Policy Series
You have accessRestricted Access

Improving Outcomes in Patients Receiving Dialysis: The Peer Kidney Care Initiative

James B. Wetmore, David T. Gilbertson, Jiannong Liu and Allan J. Collins
CJASN July 2016, 11 (7) 1297-1304; DOI: https://doi.org/10.2215/CJN.12981215
James B. Wetmore
*Chronic Disease Research Group, Minneapolis Medical Research Foundation, Minneapolis, Minnesota;
†Division of Nephrology, Hennepin County Medical Center, Minneapolis, Minnesota; and
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
David T. Gilbertson
*Chronic Disease Research Group, Minneapolis Medical Research Foundation, Minneapolis, Minnesota;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jiannong Liu
*Chronic Disease Research Group, Minneapolis Medical Research Foundation, Minneapolis, Minnesota;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Allan J. Collins
*Chronic Disease Research Group, Minneapolis Medical Research Foundation, Minneapolis, Minnesota;
‡Department of Medicine, University of Minnesota, Minneapolis, Minnesota
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data Supps
  • Info & Metrics
  • View PDF
Loading

Abstract

The past decade has witnessed a marked reduction in mortality rates among patients receiving maintenance dialysis. However, the reasons for this welcome development are uncertain, and greater understanding is needed to translate advances in care into additional survival gains. To fill important knowledge gaps and to enable dialysis provider organizations to learn from one another, with the aim of advancing patient care, the Peer Kidney Care Initiative (Peer) was created in 2014 by the chief medical officers of 14 United States dialysis provider organizations and the Chronic Disease Research Group. Areas of particular clinical importance were targeted to help shape the public health agenda in CKD and ESRD. Peer focuses on the effect of geographic variation on outcomes, the implications of seasonality for morbidity and mortality, the clinical significance of understudied disorders affecting dialysis patients, and the debate about how best to monitor and evaluate progress in care. In the realm of geovariation, Peer has provided key observations on regional variation in the rates of ESRD incidence, hospitalization, and pre-ESRD care. Regarding seasonality, Peer has reported on variation in both infection-related and non–infection-related hospitalizations, suggesting that ambient environmental conditions may affect a range of health outcomes in dialysis patients. Specific medical conditions that Peer highlights include Clostridium difficile infection, which has become strikingly more common in patients in the year after dialysis initiation, and chronic obstructive pulmonary disease, the treatments for which have the potential to contribute to sudden cardiac death. Finally, Peer challenges the nephrology community to consider alternatives to standardized mortality ratios in assessing progress in care, positing that close scrutiny of trends over time may be the most effective way to drive improvements in patient care.

  • dialysis
  • end-stage renal disease
  • outcomes
  • death
  • sudden
  • cardiac
  • hospitalization
  • humans
  • incidence
  • morbidity
  • patient care
  • renal dialysis
  • renal insufficiency
  • chronic

Introduction

The Surgeon General’s first Healthy People (HP) report in 1979 (1) was a landmark event formalizing the concept that improvement of the health of the United States population should be a societal priority. The HP endeavor establishes key decennial public health goals for the nation (2) and has been joined by similar efforts in other developed countries (3). In more affluent countries, public health efforts are focused on major noncommunicable diseases (NCDs), such as cardiovascular disease (CVD) and diabetes. Such efforts appear to be yielding results because the developed world has recently witnessed dramatic, and in some ways underappreciated, decreases in deaths attributed to NCDs. For example, between about 2000 and 2012, overall rates of death due to CVD declined approximately 35% in the United Kingdom, France, Canada, and Australia (4); in the United States, rates of death due to CVD have decreased nearly 30%. Indeed, declines in CVD deaths have been so prodigious that cancer is now the leading age-adjusted cause of death in many developed countries.

Because CVD and diabetes are also major causes of ESRD, it is fitting that efforts to reduce deaths among patients receiving maintenance dialysis have also become a public health priority. Although kidney disease–specific goals were first elucidated in HP 2010, the HP 2020 goals explicitly list a series of CKD-related public health targets (5), crystallizing this effort. The World Health Organization has also targeted kidney disease for scrutiny; item 19 of the United Nations Political Declaration on NCDs (6) says that “renal, oral and eye diseases pose a major health burden for many countries and that these diseases share common risk factors and can benefit from common responses to non-communicable diseases.”

Fortunately, during the past decade, the death rate in patients undergoing maintenance dialysis has fallen substantially from 230 per 1000 patient-years in 2001 to 169 in 2013, resulting in a roughly 30% increase in mean survival (7). Nevertheless, challenges remain for the kidney disease community. First, because the reasons for this phenomenon are poorly understood, closing this critical knowledge gap is likely to inform future efforts to increase longevity. Second, determining whether these improvements have been shared uniformly or are concentrated in certain areas is important because societal efforts should aim to assure that all dialysis patients benefit from public health advances. Finally, debating the most appropriate and informative ways to track progress in reducing morbidity and mortality is incumbent on the kidney disease community.

To help inform the discussion of these and other issues, the Peer Kidney Care Initiative (Peer) was formed. Complementing public health efforts, such as the US Renal Data System (USRDS) (8) and the Dialysis Outcomes and Practice Patterns Study (9), Peer was created in 2014 by the chief medical officers (CMOs) of 14 United States dialysis provider organizations to render novel insights, fill important knowledge gaps, and allow provider organizations to learn from one another in order to advance patient care. Certain areas of particular clinical importance were targeted in an attempt to help shape the public health agenda in CKD and ESRD. In this report, we first describe the genesis of the Peer initiative, then demonstrate novel findings from Peer, focusing on the importance of geographic variation on outcomes, the implications of seasonality on hospitalization, and the clinical importance of traditionally underappreciated disorders affecting the dialysis population. Finally, we discuss the strengths and weaknesses of different paradigms that can be used to monitor progress in the care of dialysis patients.

Peer: A New Public Health Initiative for Dialysis Patients

Peer was formed in 2014 when investigators from the Chronic Disease Research Group (CDRG; Minneapolis, Minnesota) approached the CMOs of the organizations providing maintenance dialysis in freestanding units across the United States about avenues of collaboration. In contrast to other public health initiatives focused on the dialysis population, Peer was created as a collaborative venture to study cause-specific issues that could affect patient outcomes and that dialysis providers may be able to address. Peer was specifically interested in studying geographic variation in care, the effect of seasonality on outcomes, and how certain underappreciated disease processes and comorbid conditions affect dialysis patient outcomes. CDRG proposed the collaboration, to which the CMOs of 14 dialysis providers agreed; each provider funds the endeavor in approximate proportion to the size of the population it serves. The 14 geographically diverse providers represent approximately 90% of prevalent dialysis patients in the United States.

CDRG, which held the contract for the USRDS from 1999 to 2014 and currently holds the contract for the Scientific Registry of Transplant Recipients (2010–present), was designated as the analytic center and the investigative arm of Peer. A master services agreement governs the relationship between each provider and the Minneapolis Medical Research Foundation, which has regulatory and legal oversight over CDRG. The collaborative interface between CDRG investigators and the CMOs occurs via a Peer Executive Committee, which meets regularly and includes four of the CMOs. This arrangement provides oversight of the endeavor and establishes the content of deliverables specified by the contract. The contract calls for an annual report and several peer-reviewed manuscripts annually, as well as for analysis of provider-specific data. CDRG investigators proposed the overarching focus areas before Peer was formed, and the CMOs agreed; subsequently, as defined by the contract and master services agreement that govern Peer, both CDRG investigators and the CMOs can propose specific ideas for study. CDRG considers input from the providers and works with the CMOs on the data report, research projects, and policy initiatives but has final control over all content and retains ultimate authority to design studies and to publish.

Although data were initially procured via the USRDS, Peer now has a data use agreement (DUA) in place with the Centers for Medicare & Medicaid Services (CMS) to use CMS data. Data are updated annually and are for use only by the Peer investigators and the providers under the terms specified by the DUA; CDRG and the Peer group are precluded from secondary release of the data under the terms of the DUA. Thus, the data sources are, at present, a reformatting of existing datasets, with the anticipation that provider-specific data may be added at a future date.

Geographic Variation in Kidney Disease Care and Outcomes

Exploring geographic variation in kidney disease care is a major focus of Peer. Variation in care is an issue across all fields of medicine and, broadly speaking, can be partitioned into variation in the distribution of underlying disease processes, variation in care delivery, variation in cost, and variation in outcomes (10). All such variation may be related to historical, social, cultural, economic, and demographic factors and to “natural” factors, such as climate or geologic features. Ultimately, the goal of studying geographic variation is to determine how to achieve the best medical outcomes and then to ascertain which of the preceding factors, if any, may be modifiable toward that end. Study of geographic variation can then help focus the attention of public entities, such as state health departments, ESRD networks, regulatory bodies, and payers (e.g., CMS) to change practice in the hopes of reducing variation in care.

In a geography-based approach, the size of the geographic unit of analysis must be carefully considered. Small units, such as areas defined by zip (postal) codes or counties, might be subject to fluctuations based on small numbers of events, compromising the value of inferences. Although the optimal size of the geographic unit selected for analysis depends on the specific question being asked, US state might be the smallest area that could be routinely used with confidence. An additional benefit is that state boundaries correspond to the boundaries of many regulatory bodies, such as state departments of health. Census regions are also an obvious choice; these traditional groupings were initially selected because they share historical, economic, cultural, and transportation features.

With these considerations in mind, Peer has presented detailed information on geographic variation in kidney disease care, typically at the level of the US Census regions (11). Although longevity while undergoing dialysis has improved substantially over the past decade, major differences in ESRD incidence, hospitalization, and care remain. For example, although the ESRD incidence rate has stabilized in the United States as a whole (8), rates vary considerably by US Census region (12) and remain troublingly high in many areas. Figure 1 shows the standard United States health service areas, with the data smoothed using a Bayesian spatial hierarchical model, as has been done previously (13). The highest absolute regional incidence rates are nearly double the lowest, and although the data are unadjusted, it is unlikely that case mix could account for all of the variation present. Regarding hospitalization rates in incident dialysis patients, some regions experienced steady improvement between about 2003 and 2009, whereas others, most notably the East North Central region, saw little improvement during this period; fortunately, hospitalization rates subsequently improved from 2010 to 2012, although geographic differences remain, as shown in Figure 2 (12). Even closer examination, as provided by the Peer data, shows that substantial geographic variation is present for several key reasons for hospitalization, such as CVD, infectious disorders, chronic obstructive pulmonary disease (COPD), and gastrointestinal (GI) bleeding.

Figure 1.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 1.

Geographic variation in dialysis incidence rates in 2012 by United States health service area.

Figure 2.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 2.

First-year hospital admission rates among incident dialysis patients, overall and by US Census division.

A particularly striking finding in pre-ESRD care is the variation in the percentages of patients who are under nephrologist care before starting dialysis. As of 2011, nearly 80% of patients in New England had seen a nephrologist before initiating dialysis, compared with only 62% in the West South Central region (12). Even if case-mix adjustment were to attenuate some of these differences, increased emphasis should be placed on facilitating nephrologist care before dialysis initiation in all regions, especially in regions that may be underperforming.

Study of geovariation is essential to patients, health care providers, payers, and other stakeholders to identify which practices lead to the best outcomes (14). Ample opportunity exists for Peer and other research endeavors to identify underperforming regions and to leverage the findings of well performing regions to improve the care of all patients receiving maintenance dialysis.

Seasonality

With few exceptions (15), potential effects of ambient environmental conditions have been underexplored in the dialysis literature. The importance of seasonality is, however, given substantial treatment in Peer, as shown in Figure 3. Hospitalizations were ascertained from Medicare Part A claims for inpatient care and were categorized by the principal discharge diagnosis, as was done for the 2014 Peer Report (12). The report demonstrates substantial seasonal variation in hospital admissions in prevalent dialysis patients (patients currently undergoing dialysis at a freestanding facility who had been doing so for at least 3 continuous months previously). Some of these findings are intuitive: Hospitalizations for certain infections, such as pneumonia and influenza, primarily peak in colder months, a phenomenon generally consistent with occurrences in the general population (16,17).

Figure 3.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 3.

Seasonal variation in hospital admissions in prevalent United States dialysis patients for a variety of infectious and noninfectious causes. Vertical lines represent the transition between calendar years, thereby demarcating the winter season. C. difficile, Clostridium difficile; COPD, chronic obstructive pulmonary disease; CVD, cardiovascular disease; PY, patient-year.

However, Figure 3 demonstrates that admissions for cardiovascular causes also increase during the winter. This suggests that other, less obvious factors may influence the relationship between seasonality and outcomes. One area of intense recent interest in the public health community is influenza-like illnesses (ILIs). Noninfluenza viruses that can infect the upper and lower respiratory tracts, such as rhinovirus, adenovirus, respiratory syncytial virus, parainfluenza virus, and human metapneumovirus, may contribute to morbidity and lead to hospitalizations for infection. Data suggest that substantially <50%, perhaps as low as 25%–30%, of ILIs may be due to true influenza (18,19). ILIs may, in part, explain a less intuitive link between seasonality and hospitalization, and perhaps even with the patterns of death in incident patients. For example, although exacerbations of COPD occur more frequently in winter (20) (as expected), other conditions that might appear to have more tenuous associations with season also manifest more dramatically in winter months. Admissions for overall cardiovascular diseases, acute coronary syndrome, and heart failure/cardiomyopathy also appear to spike in colder months. This suggests a possible link in dialysis patients between cardiovascular events—and perhaps other ostensibly noninfectious events—and seasonally related environmental conditions. One hypothesis proposed by the Peer investigators is that subclinical and incompletely diagnosed infections such as ILI, and the systemic inflammation they promote, might “provoke” or “unmask” cardiovascular events in poorly defined ways, but this is far from certain and requires future study.

How might this information be used to improve patient care? Perhaps increased efforts to clean surfaces and touchpoints within the dialysis unit during the winter months are warranted; this hypothesis should be tested. Second, clinicians might consider altering their index of suspicion for certain events, including cardiovascular events, during less temperate months. Although they may be difficult, efforts to improve the detection of impending cardiovascular events during periods of increased inflammatory potential, such as colder months, should be discussed by the kidney disease community.

Novel Disease Findings

Peer also seeks to explore the clinical and public health implications of morbidities that have traditionally been underemphasized. Close examination of congestive heart failure (CHF) and volume overload, intestinal infection with Clostridium difficile, chronic lung disease, and GI bleeding provides new insights.

CHF is one of the most common reasons for admission in both the general (21,22) and the dialysis (12) populations; because of high readmission rates, CHF is a major target of CMS quality improvement efforts (23). As a clinical entity, CHF in dialysis patients is a wholly different phenomenon than in the general population. Many admissions for “heart failure” in dialysis patients might more properly be termed “circulatory overload,” reflecting inadequate ultrafiltration rather than true compromised left ventricular systolic function. Inability to achieve a patient’s true dry weight, resulting in an ultrafiltration-requiring admission, might therefore more properly be coded as “fluid overload,” a diagnosis with its own International Classification of Diseases, Ninth Revision, Clinical Modification code. However, close inspection of the data demonstrates the dangers present in attempts to draw informed conclusions.

Peer showed that admissions for heart failure decreased nearly 40% in prevalent patients between 2004 and 2013, from roughly 16.3 (95% confidence interval [95% CI], 16.1 to 16.5) admissions per 100 patient-years to 9.8 (95% CI, 9.6 to 9.9), a welcome development (12). However, admissions for fluid overload during this time increased nearly 2.5-fold, from roughly 2.1 (95% CI, 2.0 to 2.2) admissions per 100 patient-years to 5.2 (95% CI, 5.1 to 5.3), suggesting that the decline in CHF admission rates is not as great as it might first appear. Whether this change in coding pattern represents a genuine effort to apply greater specificity to diagnoses or reflects attempts by facilities to avoid penalties for 30-day readmissions is uncertain.

Infection with C. difficile, a major focus for hospitalized patients in the general population (24–26), was also specifically examined in the Peer report (12). Admissions for C. difficile infections among dialysis patients within the first 12 months of initiation increased nearly 44% between 2004 and 2012, from approximately 1.6 (95% CI, 1.5 to 1.7) to 2.3 (95% CI, 2.1 to 2.4) admissions per 100 patient-years. This is important because C. difficile infection can contribute to malnourishment at a time (initiation) when patients are especially vulnerable to illness and death. Likewise, C. difficile admissions in prevalent patients have also increased. This pattern shows evidence of seasonality, perhaps as a “trailing phenomenon” relative to other infections that require treatment with broad-spectrum antibiotics. Given increased scrutiny afforded readmissions by payers, C. difficile should be a target for quality improvement efforts, given the high recurrence and readmission rates (27,28).

COPD was also examined in detail in Peer (12). Whereas rates of admission for both incident and prevalent patients have been fairly stable since approximately 2008, there is a substantial (greater than two-fold) unadjusted geographic variation across regions, the reasons for which should be investigated. Not unexpectedly, this disorder also showed substantial seasonality, whether coded as the primary or leading secondary diagnosis, with admissions rising sharply during the coldest months. COPD is an important area for study because it may be associated with preventable deaths. In addition to the seasonality implications described above, treatments for COPD can be hypothesized as potentially exposing patients to risk: β-Adrenergic agonists can cause cardiac excitability, and commonly used antibiotics, such as trimethoprim-sulfamethoxazole, quinolones, and macrolides are associated with QT prolongation and sudden cardiac death. Therefore, decreasing occurrences of COPD exacerbations in dialysis patients might reduce the death rate in several ways; this should be further studied.

GI bleeding is an increasingly common cause of hospital admissions in dialysis patients (29–31). On the basis of billing claims data, admissions attributed to GI bleeding have gradually increased since at least 2004 and began a more pronounced rise after 2010. Indeed, the rate among prevalent patients increased by approximately 21% between 2004 and 2013, from about 1.9 (95% CI, 1.9 to 2.0) to 2.3 (95% CI, 2.3 to 2.4) admissions per 100 patient-years. Notably, 2011 corresponds to the introduction of the revised Prospective Payment System (PPS), a bundled payment system designed to control costs that included services previously reimbursed separately, such as erythropoiesis-stimulating agents, intravenous iron, activated vitamin D analogues, and certain laboratory tests. How admissions for GI bleeding and the PPS introduction might be linked is uncertain, but it is possible that the lower mean hemoglobin levels in evidence since the introduction of the PPS (32–36) may have “revealed” subclinical GI bleeding, the main signal for which may be decreased hemoglobin levels. Another possibility is that lower hemoglobin levels prompt a clinical workup for presumed GI bleeding, which may be diagnosed “empirically” in the absence of endoscopically proven findings. Whether GI bleeding is truly increasing and if so whether this is associated with lower mean hemoglobin levels is uncertain but should be studied further. A final possibility that could be explored is whether and how use of agents such as aspirin, antiplatelet agents, warfarin, and the novel thrombin inhibitors may be related to the increased frequency of GI bleeding, given that the underlying pathophysiologic processes that cause GI bleeding (such as gastric ulcers, angiodysplasia, diverticulitis, and others) are unlikely to have become substantially more common in recent years.

Monitoring Progress: What Is the Most Appropriate Framework?

Substantial progress has been made regarding the outcomes of dialysis patients, with a decrease in the incidence rate (after adjustment for age, sex, race, and cause of ESRD) observed circa 2003. The HP 2020 goal CKD-8 (5), which calls for “reduc[ing] the number of new cases of ESRD per million population,” has been met, with new cases falling from 385 per million population in 2003 to 344 in 2012, a decline of >6%. Even more striking are the findings in certain disadvantaged groups. For example, for blacks, the decline has been 15%; for Native Americans, 24%; for Hispanics, 17%; and for women, 12% (8). The declines in incidence rates in these at-risk groups, which are greater than the overall decline, are the opposite of what might be expected.

Likewise, improvements have occurred in the outcomes of prevalent dialysis patients. The annualized mortality rate has declined by about 30% relative to 1999. The death rate, which was 237 per 1000 patient-years, substantially exceeded the target of 190 per 1000 patient-years set only 5 years ago (HP goal CKD-14.1) (5), and was 181 as of 2012 (12). Likewise, other targets have been exceeded: The death rate during the first 3 months after dialysis initiation fell from 387 per 1000 patient-years in 2003 to 312 per 1000 patient-years in 2012, exceeding the target of 328.7 (HP goal CKD-14.2) (5), while the death rate from CVD fell from 116 to 76 per 1000 patient-years over the corresponding interval (8), again exceeding the HP goal (CKD-14.3) (5) of 80.9.

Given these fairly dramatic improvements across the dialysis landscape, it is incumbent on the kidney care community to frankly debate how progress is best measured. One metric commonly used in attempts to measure quality of care is the standardized morality ratio (SMR), which relies on direct or indirect standardization to adjust for case-mix differences (37,38). SMRs are commonly used to assess whether there are differences in outcomes between, for example, hospitals that perform coronary artery bypass surgery (39) or in all-cause mortality between hospitals (40). Indeed, SMRs have been used by the USRDS to compare standardized mortality and hospitalization ratios among the large dialysis providers (41). An SMR-based approach can be useful in determining whether large variations in care exist (42) across regions, such as those defined by the US Census Bureau. SMR-based comparisons can highlight potential disparities within a country to highlight underperforming regions. For example, Peer reported that the East North Central region of the United States (encompassing Illinois, Indiana, Michigan, Ohio, and Wisconsin) has seen little progress in mortality compared with other regions over the past decade, a situation that only now appears to be improving. Contrasts between regions with high and low SMRs present an opportunity to discern whether differences in practice patterns across regions can be leveraged to improve care for all. In this way, SMRs can assist efforts to improve consistency of care by narrowing variation in outcomes.

However, overreliance on SMRs can be uninformative and perhaps even misleading. For example, recent criticisms have been expressed regarding the appropriateness of using SMRs for measuring care quality. Hogan et al. argue that when the units being assessed are relatively small, such as hospitals, there is poor correlation between hospital SMRs and avoidable deaths, as judged by experts conducting chart review (40), and in so doing challenge established paradigms about the utility of SMRs. They argue that SMRs are best used under conditions in which case-fatality rates are high and causes of death can be relatively easily determined. This suggests that use of SMRs may be suboptimal when small units of measure, such as individual outpatient dialysis facilities, are being compared. Additionally, and perhaps more profoundly for public health, overall societal progress cannot be adequately measured by SMRs because it is by nature cross-sectional and by definition centered (e.g., at 1.0 or 100) (43). SMRs are not especially informative when care is likely to be improving across a population as a whole, as in the case of United States dialysis patients since the turn of the millennium. An alternative approach, used by the World Health Organization (4), measures progress over time within a geographic region, with each region serving as its own control over time. Although not unique in reporting trends over time (13), Peer heavily emphasizes the importance of time trends, as can be seen throughout the 2014 report (14). Use of time trends does not invoke adjustments, essential when calculating SMRs, use of which is often incomplete or unsatisfying. While straightforward adjustments for factors such as age, sex, race, and cause of ESRD are common, these provide little insight to guide opportunities for improvement because such factors are unmodifiable.

Another benefit of trending improvements over time is that geographic factors that likely affect care, such as socioeconomic factors, environmental factors (e.g., pollution), local factors (e.g., barriers to care), and idiosyncrasies of care delivery systems, are poorly captured in SMRs. In contrast, these are inherently accounted for, at least over the short term, when a facility is compared with itself over time because these factors are unlikely to change rapidly within a geographic unit. In this way, “unfair” comparisons, such as between an affluent population base in the northeastern United States and a more socioeconomically depressed area in the Deep South of the United States, and unrealistic expectations that might accompany them, are avoided.

Conclusions

Peer was formed by 14 United States dialysis providers (who collectively provide care for roughly 90% of all patients undergoing dialysis in the United States) and CDRG in an attempt to present key issues facing the dialysis community and to foster quality-improvement efforts from which all dialysis patients can benefit. To this end, Peer has reported on geographic variation in care between regions, presented novel data on the potential role of seasonality on outcomes, and highlighted the clinical implications of traditionally underappreciated conditions affecting patients receiving maintenance dialysis. Future studies will investigate these and many other areas. Additionally, given the limitations of SMRs in judging long-term trends in the progress of care, the Peer effort highlights the importance of tracking and understanding trends over time, a process that may provide insights to foster improvements in the care of patients receiving dialysis.

Disclosures

None.

Acknowledgments

The authors gratefully acknowledge the efforts of Eric Weinhandl, Suying Li, Charles Herzog, Yi Peng, Susan Everson, Stephan Dunning, and Adrine Chung for contributions to the Peer endeavor. The authors also thank Chronic Disease Research Group colleagues Delaney Berrini for manuscript preparation and Nan Booth, MSW, ELS, for manuscript editing.

This study was supported by the Peer Kidney Care Initiative, a consortium of 14 participating dialysis provider organizations: American Renal Associates, Atlantic Dialysis Management Services, Centers for Dialysis Care, DaVita HealthCare Partners, Dialysis Clinic, Inc., DSI Renal, Fresenius Medical Care, Independent Dialysis Foundation, Northwest Kidney Centers, Renal Ventures Management, the Rogosin Institute, Satellite Healthcare, US Renal Care, and Wake Forest-Emory Universities.

Footnotes

  • Published online ahead of print. Publication date available at www.cjasn.org.

  • Copyright © 2016 by the American Society of Nephrology

References

  1. ↵
    National Institutes of Health: US National Library of Medicine: The Reports of the Surgeon General: Public Health and Disease Prevention. 2015. Available at: http://profiles.nlm.nih.gov/ps/retrieve/Narrative/NN/p-nid/63. Accessed February 2, 2016
  2. ↵
    US Department of Health and Human Services: Healthy People 2020. Available at: http://www.healthypeople.gov/2020/leading-health-indicators/Leading-Health-Indicators-Development-and-Framework. Accessed February 2, 2016
  3. ↵
    World Health Organization: About Health 2020. Available at: http://www.euro.who.int/en/health-topics/health-policy/health-2020-the-european-policy-for-health-and-well-being/about-health-2020. Accessed February 2, 2016
  4. ↵
    World Health Organization: Noncommunicable diseases: country profiles. 2014. Available at: http://apps.who.int/iris/bitstream/10665/128038/1/9789241507509_eng.pdf. Accessed February 2, 2016
  5. ↵
    US Department of Health and Human Services: Healthy People 2020 Topics and Objectives: Chronic kidney disease. Available at: http://www.healthypeople.gov/2020/topics-objectives/topic/chronic-kidney-disease. Accessed February 2, 2016
  6. ↵
    United Nations: Resolution adopted by the General Assembly: Annex, 66th Session, Agenda Item 117. 2015. Available at: http://www.who.int/nmh/events/un_ncd_summit2011/political_declaration_en.pdf. Accessed February 2, 2016
  7. ↵
    US Renal Data System: 2015 USRDS annual data report: Epidemiology of kidney disease in the United States. 2015 Ed., Bethesda, MD, National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, 2015
  8. ↵
    1. Saran R,
    2. Li Y,
    3. Robinson B,
    4. Ayanian J,
    5. Balkrishnan R,
    6. Bragg-Gresham J,
    7. Chen JT,
    8. Cope E,
    9. Gipson D,
    10. He K,
    11. Herman W,
    12. Heung M,
    13. Hirth RA,
    14. Jacobsen SS,
    15. Kalantar-Zadeh K,
    16. Kovesdy CP,
    17. Leichtman AB,
    18. Lu Y,
    19. Molnar MZ,
    20. Morgenstern H,
    21. Nallamothu B,
    22. O’Hare AM,
    23. Pisoni R,
    24. Plattner B,
    25. Port FK,
    26. Rao P,
    27. Rhee CM,
    28. Schaubel DE,
    29. Selewski DT,
    30. Shahinian V,
    31. Sim JJ,
    32. Song P,
    33. Streja E,
    34. Kurella Tamura M,
    35. Tentori F,
    36. Eggers PW,
    37. Agodoa LY,
    38. Abbott KC
    : US Renal Data System 2014 Annual Data Report: Epidemiology of Kidney Disease in the United States. Am J Kidney Dis 66[Suppl 1]: S1–S305, 2015
    OpenUrlCrossRefPubMed
  9. ↵
    Arbor Research Collaborative for Health: Annual report of the Dialysis Outcomes and Practice Patterns Study: Hemodialysis data 1997-2011. 2013. Available at: http://www.dopps.org/annualreport/. Accessed February 2, 2016
  10. ↵
    1. Wennberg J,
    2. Gittelsohn A
    : Variations in medical care among small areas. Sci Am 246: 120–134, 1982
    OpenUrlCrossRefPubMed
  11. ↵
    US Census Bureau: Geographic terms and concepts – census divisions and census regions. 2016. Available at: https://www.census.gov/geo/reference/gtc/gtc_census_divreg.html. Accessed February 2, 2016
  12. ↵
    1. Weinhandl E,
    2. Constantini E,
    3. Everson S,
    4. Gilbertson D,
    5. Li S,
    6. Solid C,
    7. Anger M,
    8. Bhat JG,
    9. DeOreo P,
    10. Krishnan M,
    11. Nissenson A,
    12. Johnson D,
    13. Ikizler TA,
    14. Maddux F,
    15. Sadler J,
    16. Tyshler L,
    17. Parker T 3rd.,
    18. Schiller B,
    19. Smith B,
    20. Lindenfeld S,
    21. Collins AJ
    : Peer kidney care initiative 2014 report: Dialysis care and outcomes in the United States. Am J Kidney Dis 65[Suppl 1]: S1–S140, 2015
    OpenUrlCrossRef
  13. ↵
    US Renal Data System: USRDS 2013 Annual Data Report: Atlas of Chronic Kidney Disease & End-Stage Renal Disease in the United States, 2013 Ed., Bethesda, MD, National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, 2013, p. 218
  14. ↵
    1. Birkmeyer JD,
    2. Reames BN,
    3. McCulloch P,
    4. Carr AJ,
    5. Campbell WB,
    6. Wennberg JE
    : Understanding of regional variation in the use of surgery. Lancet 382: 1121–1129, 2013
    OpenUrlCrossRefPubMed
  15. ↵
    1. Lok CE,
    2. Thumma JR,
    3. McCullough KP,
    4. Gillespie BW,
    5. Fluck RJ,
    6. Marshall MR,
    7. Kawanishi H,
    8. Robinson BM,
    9. Pisoni RL
    : Catheter-related infection and septicemia: Impact of seasonality and modifiable practices from the DOPPS. Semin Dial 27: 72–77, 2014
    OpenUrlCrossRefPubMed
  16. ↵
    1. Murdoch KM,
    2. Mitra B,
    3. Lambert S,
    4. Erbas B
    : What is the seasonal distribution of community acquired pneumonia over time? A systematic review. Australas Emerg Nurs J 17: 30–42, 2014
    OpenUrlCrossRefPubMed
  17. ↵
    1. Simmerman JM,
    2. Chittaganpitch M,
    3. Levy J,
    4. Chantra S,
    5. Maloney S,
    6. Uyeki T,
    7. Areerat P,
    8. Thamthitiwat S,
    9. Olsen SJ,
    10. Fry A,
    11. Ungchusak K,
    12. Baggett HC,
    13. Chunsuttiwat S
    : Incidence, seasonality and mortality associated with influenza pneumonia in Thailand: 2005-2008. PLoS One 4: e7776, 2009
    OpenUrlCrossRefPubMed
  18. ↵
    1. Bellei N,
    2. Carraro E,
    3. Perosa A,
    4. Watanabe A,
    5. Arruda E,
    6. Granato C
    : Acute respiratory infection and influenza-like illness viral etiologies in Brazilian adults. J Med Virol 80: 1824–1827, 2008
    OpenUrlCrossRefPubMed
  19. ↵
    1. Thomas RE
    : Is influenza-like illness a useful concept and an appropriate test of influenza vaccine effectiveness? Vaccine 32: 2143–2149, 2014
    OpenUrlCrossRefPubMed
  20. ↵
    1. Almagro P,
    2. Hernandez C,
    3. Martinez-Cambor P,
    4. Tresserras R,
    5. Escarrabill J
    : Seasonality, ambient temperatures and hospitalizations for acute exacerbation of COPD: A population-based study in a metropolitan area. Int J Chron Obstruct Pulmon Dis 10: 899–908, 2015
    OpenUrlPubMed
  21. ↵
    1. Ross JS,
    2. Chen J,
    3. Lin Z,
    4. Bueno H,
    5. Curtis JP,
    6. Keenan PS,
    7. Normand SL,
    8. Schreiner G,
    9. Spertus JA,
    10. Vidán MT,
    11. Wang Y,
    12. Wang Y,
    13. Krumholz HM
    : Recent national trends in readmission rates after heart failure hospitalization. Circ Heart Fail 3: 97–103, 2010
    OpenUrlAbstract/FREE Full Text
  22. ↵
    1. Jencks SF,
    2. Williams MV,
    3. Coleman EA
    : Rehospitalizations among patients in the Medicare fee-for-service program. N Engl J Med 360: 1418–1428, 2009
    OpenUrlCrossRefPubMed
  23. ↵
    Centers for Medicare & Medicaid Services: Readmissions Reduction Program. 2012. Available at: http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Readmissions-Reduction-Program.html. Accessed February 2, 2016
  24. ↵
    1. Magill SS,
    2. Dumyati G,
    3. Ray SM,
    4. Fridkin SK
    : evaluating epidemiology and improving surveillance of infections associated with health care, United States. Emerg Infect Dis 21: 1537–1542, 2015
    OpenUrlCrossRefPubMed
    1. Snydman DR,
    2. McDermott LA,
    3. Jacobus NV,
    4. Thorpe C,
    5. Stone S,
    6. Jenkins SG,
    7. Goldstein EJ,
    8. Patel R,
    9. Forbes BA,
    10. Mirrett S,
    11. Johnson S,
    12. Gerding DN
    : U.S.-Based National Sentinel Surveillance Study for the epidemiology of Clostridium difficile-associated diarrheal isolates and their susceptibility to fidaxomicin. Antimicrob Agents Chemother 59: 6437–6443, 2015
    OpenUrlAbstract/FREE Full Text
  25. ↵
    1. Vindigni SM,
    2. Surawicz CM
    : C. difficile infection: Changing epidemiology and management paradigms. Clin Transl Gastroenterol 6: e99, 2015
    OpenUrlCrossRef
  26. ↵
    1. Olsen MA,
    2. Yan Y,
    3. Reske KA,
    4. Zilberberg M,
    5. Dubberke ER
    : Impact of Clostridium difficile recurrence on hospital readmissions. Am J Infect Control 43: 318–322, 2015
    OpenUrlCrossRefPubMed
  27. ↵
    1. Chopra T,
    2. Neelakanta A,
    3. Dombecki C,
    4. Awali RA,
    5. Sharma S,
    6. Kaye KS,
    7. Patel P
    : Burden of Clostridium difficile infection on hospital readmissions and its potential impact under the Hospital Readmission Reduction Program. Am J Infect Control 43: 314–317, 2015
    OpenUrlCrossRefPubMed
  28. ↵
    1. Yang JY,
    2. Lee TC,
    3. Montez-Rath ME,
    4. Paik J,
    5. Chertow GM,
    6. Desai M,
    7. Winkelmayer WC
    : Trends in acute nonvariceal upper gastrointestinal bleeding in dialysis patients. J Am Soc Nephrol 23: 495–506, 2012
    OpenUrlAbstract/FREE Full Text
    1. Yang JY,
    2. Lee TC,
    3. Montez-Rath ME,
    4. Chertow GM,
    5. Winkelmayer WC
    : Risk factors of short-term mortality after acute nonvariceal upper gastrointestinal bleeding in patients on dialysis: a population-based study. BMC Nephrol 14: 97, 2013
    OpenUrlCrossRefPubMed
  29. ↵
    1. Weinhandl E,
    2. Constantini E,
    3. Everson S,
    4. Gilbertson D,
    5. Li S,
    6. Solid C,
    7. Anger M,
    8. Bhat JG,
    9. DeOreo P,
    10. Krishnan M,
    11. Nissenson A,
    12. Johnson D,
    13. Ikizler TA,
    14. Maddux F,
    15. Sadler J,
    16. Tyshler L,
    17. Parker T III.,
    18. Schiller B,
    19. Smith B,
    20. Lindenfeld S,
    21. Collins AJ
    : Peer kidney care initiative 2014 report: dialysis care and outcomes in the United States. Am J Kidney Dis 65[Suppl 1]: s73, 2015
    OpenUrl
  30. ↵
    1. Brunelli SM,
    2. Monda KL,
    3. Burkart JM,
    4. Gitlin M,
    5. Neumann PJ,
    6. Park GS,
    7. Symonian-Silver M,
    8. Yue S,
    9. Bradbury BD,
    10. Rubin RJ
    : Early trends from the Study to Evaluate the Prospective Payment System Impact on Small Dialysis Organizations (STEPPS). Am J Kidney Dis 61: 947–956, 2013
    OpenUrlCrossRefPubMed
    1. Hirth RA,
    2. Turenne MN,
    3. Wilk AS,
    4. Wheeler JR,
    5. Sleeman KK,
    6. Zhang W,
    7. Paul MA,
    8. Nahra TA,
    9. Messana JM
    : Blood transfusion practices in dialysis patients in a dynamic regulatory environment. Am J Kidney Dis 64: 616–621, 2014
    OpenUrlCrossRefPubMed
    1. Collins AJ,
    2. Foley RN,
    3. Herzog C,
    4. Chavers B,
    5. Gilbertson D,
    6. Herzog C,
    7. Ishani A,
    8. Johansen K,
    9. Kasiske B,
    10. Kutner N,
    11. Liu J,
    12. St Peter W,
    13. Ding S,
    14. Guo H,
    15. Kats A,
    16. Lamb K,
    17. Li S,
    18. Li S,
    19. Roberts T,
    20. Skeans M,
    21. Snyder J,
    22. Solid C,
    23. Thompson B,
    24. Weinhandl E,
    25. Xiong H,
    26. Yusuf A,
    27. Zaun D,
    28. Arko C,
    29. Chen SC,
    30. Daniels F,
    31. Ebben J,
    32. Frazier E,
    33. Hanzlik C,
    34. Johnson R,
    35. Sheets D,
    36. Wang X,
    37. Forrest B,
    38. Constantini E,
    39. Everson S,
    40. Eggers P,
    41. Agodoa L
    : US Renal Data System 2012 Annual Data Report. Am J Kidney Dis 61[Suppl 1]: A7, e1–e476, 2013
    OpenUrlCrossRefPubMed
  31. Centers for Medicare & Medicaid Services: ESRD Prospective Payment System (ESRD PPS) overview of 2011 and 2012 claims-based monitoring program. 2012. Available at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/ESRDpayment/Spotlight.html. Accessed February 2, 2016
  32. ↵
    1. Gilbertson DT,
    2. Collins AJ,
    3. Foley R
    : Transition in service utilization: Vascular access, injectables, hemoglobin levels, and transfusions. 2013. Available at: http://www.usrds.org/2012/pres/ASN2H/Gilbertson_USRDS_2-hour_Full.pdf. Accessed February 2, 2016
  33. ↵
    1. Wolfe RA
    : The standardized mortality ratio revisited: Improvements, innovations, and limitations. Am J Kidney Dis 24: 290–297, 1994
    OpenUrlCrossRefPubMed
  34. ↵
    1. Van den Broeck J,
    2. Brestoff J
    1. Van den Broeck J,
    2. Brestoff J,
    3. Kaulfuss C:
    Statistical estimation. In: Epidemiology: Principles and Practical Guidelines. , edited by Van den Broeck J, Brestoff J, Dordrecht, The Netherlands, Springer, 2013, pp 417–438
  35. ↵
    1. Rathore SS,
    2. Epstein AJ,
    3. Volpp KG,
    4. Krumholz HM
    : Hospital coronary artery bypass graft surgery volume and patient mortality, 1998-2000. Ann Surg 239: 110–117, 2004
    OpenUrlCrossRefPubMed
  36. ↵
    1. Hogan H,
    2. Zipfel R,
    3. Neuburger J,
    4. Hutchings A,
    5. Darzi A,
    6. Black N
    : Avoidability of hospital deaths and association with hospital-wide mortality ratios: Retrospective case record review and regression analysis. BMJ 351: h3239, 2015
    OpenUrlAbstract/FREE Full Text
  37. ↵
    US Renal Data System: USRDS 2013 Annual Data Report: Atlas of Chronic Kidney Disease & End-Stage Renal Disease in the United States. 2013 Ed., Bethesda, MD, National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, 2013, p 322, Figure 10.10
  38. ↵
    1. Liu J,
    2. Li S,
    3. Gilbertson DT,
    4. Monda KL,
    5. Bradbury BD,
    6. Collins AJ
    : Development of a standardized transfusion ratio as a metric for evaluating dialysis facility anemia management practices. Am J Kidney Dis 64: 608–615, 2014
    OpenUrlCrossRefPubMed
  39. ↵
    1. van Gestel YR,
    2. Lemmens VE,
    3. Lingsma HF,
    4. de Hingh IH,
    5. Rutten HJ,
    6. Coebergh JW
    : The hospital standardized mortality ratio fallacy: A narrative review. Med Care 50: 662–667, 2012
    OpenUrlCrossRefPubMed
View Abstract
PreviousNext
Back to top

In this issue

Clinical Journal of the American Society of Nephrology: 11 (7)
Clinical Journal of the American Society of Nephrology
Vol. 11, Issue 7
July 07, 2016
  • Table of Contents
  • Table of Contents (PDF)
  • About the Cover
  • Index by author
View Selected Citations (0)
Print
Download PDF
Sign up for Alerts
Email Article
Thank you for your help in sharing the high-quality science in CJASN.
Enter multiple addresses on separate lines or separate them with commas.
Improving Outcomes in Patients Receiving Dialysis: The Peer Kidney Care Initiative
(Your Name) has sent you a message from American Society of Nephrology
(Your Name) thought you would like to see the American Society of Nephrology web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Improving Outcomes in Patients Receiving Dialysis: The Peer Kidney Care Initiative
James B. Wetmore, David T. Gilbertson, Jiannong Liu, Allan J. Collins
CJASN Jul 2016, 11 (7) 1297-1304; DOI: 10.2215/CJN.12981215

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Request Permissions
Share
Improving Outcomes in Patients Receiving Dialysis: The Peer Kidney Care Initiative
James B. Wetmore, David T. Gilbertson, Jiannong Liu, Allan J. Collins
CJASN Jul 2016, 11 (7) 1297-1304; DOI: 10.2215/CJN.12981215
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like

Jump to section

  • Article
    • Abstract
    • Introduction
    • Peer: A New Public Health Initiative for Dialysis Patients
    • Geographic Variation in Kidney Disease Care and Outcomes
    • Seasonality
    • Novel Disease Findings
    • Monitoring Progress: What Is the Most Appropriate Framework?
    • Conclusions
    • Disclosures
    • Acknowledgments
    • Footnotes
    • References
  • Figures & Data Supps
  • Info & Metrics
  • View PDF

More in this TOC Section

  • New Organ Allocation System for Combined Liver-Kidney Transplants and the Availability of Kidneys for Transplant to Patients with Stage 4–5 CKD
  • Consolidation in the Dialysis Industry, Patient Choice, and Local Market Competition
  • New Opportunities for Funding Dialysis-Dependent Undocumented Individuals
Show more Public Policy Series

Cited By...

  • Seasonal and Secular Trends of Cardiovascular, Nutritional, and Inflammatory Markers in Patients on Hemodialysis
  • Google Scholar

Similar Articles

Related Articles

  • No related articles found.
  • PubMed
  • Google Scholar

Keywords

  • dialysis
  • end-stage renal disease
  • outcomes
  • Death
  • Sudden
  • Cardiac
  • hospitalization
  • Humans
  • Incidence
  • morbidity
  • patient care
  • renal dialysis
  • renal insufficiency
  • chronic

Articles

  • Current Issue
  • Early Access
  • Subject Collections
  • Article Archive
  • ASN Meeting Abstracts

Information for Authors

  • Submit a Manuscript
  • Trainee of the Year
  • Author Resources
  • ASN Journal Policies
  • Reuse/Reprint Policy

About

  • CJASN
  • ASN
  • ASN Journals
  • ASN Kidney News

Journal Information

  • About CJASN
  • CJASN Email Alerts
  • CJASN Key Impact Information
  • CJASN Podcasts
  • CJASN RSS Feeds
  • Editorial Board

More Information

  • Advertise
  • ASN Podcasts
  • ASN Publications
  • Become an ASN Member
  • Feedback
  • Follow on Twitter
  • Password/Email Address Changes
  • Subscribe

© 2021 American Society of Nephrology

Print ISSN - 1555-9041 Online ISSN - 1555-905X

Powered by HighWire