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Li K, Pirabhahar S, Thomsett M, Turner K, Wainstein M, Ha JT, Katz I. Use of kidney failure risk equation as a tool to evaluate referrals from primary care to specialist nephrology care. Intern Med J 2024. [PMID: 38532529 DOI: 10.1111/imj.16377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 01/04/2024] [Indexed: 03/28/2024]
Abstract
BACKGROUND With rising costs and burden of chronic kidney disease (CKD), timely referral of patients to a kidney specialist is crucial. Currently, Kidney Health Australia (KHA) uses a 'heat map' based on severity and not future risk of kidney failure, whereas the kidney failure risk equation (KFRE) score predicts future risk of progression. AIMS Evaluate whether a KFRE score assists with timing of CKD referrals. METHODS Retrospective cohort of 2137 adult patients, referred to tertiary hospital outpatient nephrologist between 2012 and 2020, were analysed. Referrals were analysed for concordance with the KHA referral guidelines and, with the KFRE score, a recommended practice. RESULTS Of 2137 patients, 626 (29%) did not have urine albumin-to-creatinine ratio (UACR) measurement at referral. For those who had a UACR, the number who met KFRE preferred referral criteria was 36% less than KHA criteria. If the recommended KFRE score was used, then fewer older patients (≥40 years) needed referral. Positively, many diabetes patients were referred, even if their risk of kidney failure was low, and 29% had a KFRE over 3%. For patients evaluated meeting KFRE criteria, a larger proportion (76%) remained in follow-up, with only 8% being discharged. CONCLUSIONS KFRE could reduce referrals and be a useful tool to assist timely referrals. Using KFRE for triage may allow those patients with very low risk of future kidney failure not be referred, remaining longer in primary care, saving health resources and reducing patients' stress and wait times. Using KFRE encourages albuminuria measurement.
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Affiliation(s)
- Katherine Li
- Faculty of Medicine and Health, University of New South Wales, Sydney, New South Wales, Australia
| | - Saiyini Pirabhahar
- Department of Renal Medicine, St George Hospital, Sydney, New South Wales, Australia
| | - Max Thomsett
- Department of Renal Medicine, St George Hospital, Sydney, New South Wales, Australia
| | - Kylie Turner
- Department of Renal Medicine, St George Hospital, Sydney, New South Wales, Australia
| | - Marina Wainstein
- Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
| | - Jeff T Ha
- Faculty of Medicine and Health, University of New South Wales, Sydney, New South Wales, Australia
- The George Institute for Global Health, Sydney, New South Wales, Australia
| | - Ivor Katz
- Faculty of Medicine and Health, University of New South Wales, Sydney, New South Wales, Australia
- Department of Renal Medicine, St George Hospital, Sydney, New South Wales, Australia
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Ooi YG, Sarvanandan T, Hee NKY, Lim QH, Paramasivam SS, Ratnasingam J, Vethakkan SR, Lim SK, Lim LL. Risk Prediction and Management of Chronic Kidney Disease in People Living with Type 2 Diabetes Mellitus. Diabetes Metab J 2024; 48:196-207. [PMID: 38273788 PMCID: PMC10995482 DOI: 10.4093/dmj.2023.0244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 11/25/2023] [Indexed: 01/27/2024] Open
Abstract
People with type 2 diabetes mellitus have increased risk of chronic kidney disease and atherosclerotic cardiovascular disease. Improved care delivery and implementation of guideline-directed medical therapy have contributed to the declining incidence of atherosclerotic cardiovascular disease in high-income countries. By contrast, the global incidence of chronic kidney disease and associated mortality is either plateaued or increased, leading to escalating direct and indirect medical costs. Given limited resources, better risk stratification approaches to identify people at risk of rapid progression to end-stage kidney disease can reduce therapeutic inertia, facilitate timely interventions and identify the need for early nephrologist referral. Among people with chronic kidney disease G3a and beyond, the kidney failure risk equations (KFRE) have been externally validated and outperformed other risk prediction models. The KFRE can also guide the timing of preparation for kidney replacement therapy with improved healthcare resources planning and may prevent multiple complications and premature mortality among people with chronic kidney disease with and without type 2 diabetes mellitus. The present review summarizes the evidence of KFRE to date and call for future research to validate and evaluate its impact on cardiovascular and mortality outcomes, as well as healthcare resource utilization in multiethnic populations and different healthcare settings.
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Affiliation(s)
- Ying-Guat Ooi
- Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Tharsini Sarvanandan
- Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Nicholas Ken Yoong Hee
- Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Quan-Hziung Lim
- Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | | | - Jeyakantha Ratnasingam
- Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Shireene R. Vethakkan
- Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Soo-Kun Lim
- Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Lee-Ling Lim
- Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China
- Asia Diabetes Foundation, Hong Kong SAR, China
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Hirsch JS, Danna SC, Desai N, Gluckman TJ, Jhamb M, Newlin K, Pellechio B, Elbedewe A, Norfolk E. Optimizing Care Delivery in Patients with Chronic Kidney Disease in the United States: Proceedings of a Multidisciplinary Roundtable Discussion and Literature Review. J Clin Med 2024; 13:1206. [PMID: 38592013 PMCID: PMC10932233 DOI: 10.3390/jcm13051206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 02/07/2024] [Accepted: 02/10/2024] [Indexed: 04/10/2024] Open
Abstract
BACKGROUND Approximately 37 million individuals in the United States (US) have chronic kidney disease (CKD). Patients with CKD have a substantial morbidity and mortality, which contributes to a huge economic burden to the healthcare system. A limited number of clinical pathways or defined workflows exist for CKD care delivery in the US, primarily due to a lower prioritization of CKD care within health systems compared with other areas (e.g., cardiovascular disease [CVD], cancer screening). CKD is a public health crisis and by the year 2040, CKD will become the fifth leading cause of years of life lost. It is therefore critical to address these challenges to improve outcomes in patients with CKD. METHODS The CKD Leaders Network conducted a virtual, 3 h, multidisciplinary roundtable discussion with eight subject-matter experts to better understand key factors impacting CKD care delivery and barriers across the US. A premeeting survey identified topics for discussion covering the screening, diagnosis, risk stratification, and management of CKD across the care continuum. Findings from this roundtable are summarized and presented herein. RESULTS Universal challenges exist across health systems, including a lack of awareness amongst providers and patients, constrained care team bandwidth, inadequate financial incentives for early CKD identification, non-standardized diagnostic classification and triage processes, and non-centralized patient information. Proposed solutions include highlighting immediate and long-term financial implications linked with failure to identify and address at-risk individuals, identifying and managing early-stage CKD, enhancing efforts to support guideline-based education for providers and patients, and capitalizing on next-generation solutions. CONCLUSIONS Payers and other industry stakeholders have opportunities to contribute to optimal CKD care delivery. Beyond addressing the inadequacies that currently exist, actionable tactics can be implemented into clinical practice to improve clinical outcomes in patients at risk for or diagnosed with CKD in the US.
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Affiliation(s)
- Jamie S. Hirsch
- Northwell Health, Northwell Health Physician Partners, 100 Community Drive, Floor 2, Great Neck, NY 11021, USA
| | - Samuel Colby Danna
- VA Southeast Louisiana Healthcare System, 2400 Canal Street, New Orleans, LA 70119, USA
| | - Nihar Desai
- Section of Cardiovascular Medicine, Yale School of Medicine, 800 Howard Avenue, Ste 2nd Floor, New Haven, CT 06519, USA
| | - Ty J. Gluckman
- Providence Heart Institute, Center for Cardiovascular Analytics, Research, and Data Science (CARDS), 9205 SW Barnes Road, Suite 598, Portland, OR 97225, USA
| | - Manisha Jhamb
- Division of Renal-Electrolyte, University of Pittsburgh, 3550 Terrace St., Scaife A915, Pittsburgh, PA 15261, USA
| | - Kim Newlin
- Sutter Health, Sutter Roseville Medical Center, 1 Medical Plaza Drive, Roseville, CA 95661, USA
| | - Bob Pellechio
- RWJ Barnabas Health, Cooperman Barnabas Medical Center, 95 Old Short Hills Rd., West Orange, NJ 07052, USA
| | - Ahlam Elbedewe
- The Kinetix Group, 29 Broadway 26th Floor, New York, NY 10006, USA
| | - Evan Norfolk
- Geisinger Medical Center—Nephrology, 100 North Academy Avenue, Danville, PA 17822, USA
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Alexiuk M, Elgubtan H, Tangri N. Clinical Decision Support Tools in the Electronic Medical Record. Kidney Int Rep 2024; 9:29-38. [PMID: 38312784 PMCID: PMC10831391 DOI: 10.1016/j.ekir.2023.10.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 10/23/2023] [Indexed: 02/06/2024] Open
Abstract
The integration of clinical decision support (CDS) tools into electronic medical record (EMR) systems has become common. Although there are many benefits for both patients and providers from successful integration, barriers exist that prevent consistent and effective use of these tools. Such barriers include tool alert fatigue, lack of interoperability between tools and medical record systems, and poor acceptance of tools by care providers. However, successful integration of CDS tools into EMR systems have been reported; examples of these include the Statin Choice Decision Aid, and the Kidney Failure Risk Equation (KFRE). This article reviews the history of EMR systems and its integration with CDS tools, the barriers preventing successful integration, and the benefits reported from successful integration. This article also provides suggestions and strategies for improving successful integration, making these tools easier to use and more effective for care providers.
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Affiliation(s)
- Mackenzie Alexiuk
- Chronic Disease Innovation Centre, Winnipeg, Manitoba, Canada
- Community Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Heba Elgubtan
- Chronic Disease Innovation Centre, Winnipeg, Manitoba, Canada
- Community Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Navdeep Tangri
- Chronic Disease Innovation Centre, Winnipeg, Manitoba, Canada
- Department of Internal Medicine, Max Rady College of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada
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Samal L, D’Amore JD, Gannon MP, Kilgallon JL, Charles JP, Mann DM, Siegel LC, Burdge K, Shaykevich S, Lipsitz S, Waikar SS, Bates DW, Wright A. Impact of Kidney Failure Risk Prediction Clinical Decision Support on Monitoring and Referral in Primary Care Management of CKD: A Randomized Pragmatic Clinical Trial. Kidney Med 2022; 4:100493. [PMID: 35866010 PMCID: PMC9293940 DOI: 10.1016/j.xkme.2022.100493] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
Abstract
Rationale & Objective To design and implement clinical decision support incorporating a validated risk prediction estimate of kidney failure in primary care clinics and to evaluate the impact on stage-appropriate monitoring and referral. Study Design Block-randomized, pragmatic clinical trial. Setting & Participants Ten primary care clinics in the greater Boston area. Patients with stage 3-5 chronic kidney disease (CKD) were included. Patients were randomized within each primary care physician panel through a block randomization approach. The trial occurred between December 4, 2015, and December 3, 2016. Intervention Point-of-care noninterruptive clinical decision support that delivered the 5-year kidney failure risk equation as well as recommendations for stage-appropriate monitoring and referral to nephrology. Outcomes The primary outcome was as follows: Urine and serum laboratory monitoring test findings measured at one timepoint 6 months after the initial primary care visit and analyzed only in patients who had not undergone the recommended monitoring test in the preceding 12 months. The secondary outcome was nephrology referral in patients with a calculated kidney failure risk equation value of >10% measured at one timepoint 6 months after the initial primary care visit. Results The clinical decision support application requested and processed 569,533 Continuity of Care Documents during the study period. Of these, 41,842 (7.3%) documents led to a diagnosis of stage 3, 4, or 5 CKD by the clinical decision support application. A total of 5,590 patients with stage 3, 4, or 5 CKD were randomized and included in the study. The link to the clinical decision support application was clicked 122 times by 57 primary care physicians. There was no association between the clinical decision support intervention and the primary outcome. There was a small but statistically significant difference in nephrology referral, with a higher rate of referral in the control arm. Limitations Contamination within provider and clinic may have attenuated the impact of the intervention and may have biased the result toward null. Conclusions The noninterruptive design of the clinical decision support was selected to prevent cognitive overload; however, the design led to a very low rate of use and ultimately did not improve stage-appropriate monitoring. Funding Research reported in this publication was supported by the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health under award K23DK097187. Trial Registration ClinicalTrials.gov Identifier: NCT02990897.
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Affiliation(s)
- Lipika Samal
- Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, MA
- Harvard Medical School, Boston, MA
- Address for Correspondence: Lipika Samal, MD, MPH, Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, 1620 Tremont St, Boston, MA 02120.
| | | | - Michael P. Gannon
- Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, MA
| | - John L. Kilgallon
- Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, MA
| | - Jean-Pierre Charles
- Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, MA
| | - Devin M. Mann
- New York University School of Medicine, New York, NY
| | - Lydia C. Siegel
- Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, MA
- Harvard Medical School, Boston, MA
- Mass General Brigham Digital Health eCare, Boston, MA
| | - Kelly Burdge
- Nephrology, Mass General Brigham-Salem Hospital, Salem, MA
| | - Shimon Shaykevich
- Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, MA
| | - Stuart Lipsitz
- Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, MA
- Harvard Medical School, Boston, MA
| | - Sushrut S. Waikar
- Nephrology, Mass General Brigham-Salem Hospital, Salem, MA
- Section of Nephrology, Boston University School of Medicine and Boston Medical Center, Boston, MA
| | - David W. Bates
- Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, MA
- Harvard Medical School, Boston, MA
| | - Adam Wright
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN
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Reaves AC, Weiner DE. Value-Based Care in Chronic Kidney Disease: Missing Albuminuria is a Missed Opportunity. Clin J Am Soc Nephrol 2022; 17:14-16. [PMID: 34969701 PMCID: PMC8763161 DOI: 10.2215/cjn.15031121] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
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