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Kidney Week

Abstract: FR-PO342

Electronic Health Record Based Population Health Management for Improving CKD Care: The Kidney-Coordinated Health Management Partnership (CHAMP) Study

Session Information

Category: CKD (Non-Dialysis)

  • 2102 CKD (Non-Dialysis): Clinical, Outcomes, and Trials

Authors

  • Jhamb, Manisha, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
  • Yabes, Jonathan, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
  • Fischer, Gary, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
  • Chang, Chung-Chou H., University of Pittsburgh, Pittsburgh, Pennsylvania, United States
  • Rollman, Bruce L., University of Pittsburgh, Pittsburgh, Pennsylvania, United States
  • Nolin, Thomas D., University of Pittsburgh, Pittsburgh, Pennsylvania, United States
  • Abdel-Kader, Khaled, Vanderbilt University Medical Center, Nashville, Tennessee, United States
Background

Primary care providers (PCPs) care for most CKD patients but report limited knowledge, familiarity with guidelines, and time, leading to suboptimal care and clinical outcomes including progression to end-stage kidney disease (ESKD).

CKD population health management (PHM) using electronic health records (EHRs) can be a sustainable, resource-efficient strategy to overcome clinician- and system-level barriers in the delivery of CKD care. The Kidney CHAMP study will test the effectiveness of a multifaceted EHR-based PHM intervention to improve evidence-based CKD care in patients with high-risk CKD (NCT03832595, www.kidneychamp.pitt.edu).

Methods

This is a 42-month pragmatic, cluster randomized controlled trial comparing an EHR-based PHM intervention versus usual care in 1,650 high-risk CKD patients. Patients are recruited using an opt-out approach from the University of Pittsburgh’s PCP network (>330 PCPs; >480,000 patients). The CKD PHM dashboard uses risk prediction models to identify patients at high risk of CKD progression. The intervention combines timely PCP-targeted nephrology guidance (primarily as E-consults), pharmacist-led medication reviews, and patient-targeted CKD education. This builds on our prior work using EHRs to identify gaps in CKD care (e.g., suboptimal HTN control and RAASi use, unsafe medication use, late nephrology referrals). Primary outcome is a composite of 40% reduction in eGFR or ESKD.

Results

The CKD dashboard has been developed and includes the validated Kidney Failure Risk Equation, patient demographics, dates of PCP visits, lab values, and active medications. Additionally, an internal CKD risk prediction model has been developed and validated. The dashboard will be used to identify eligible patients, track the intervention components, and monitor CKD progression. Study enrollment began in May 2019. We have partnered with 80 practices and randomized the first 8. Enrollment will continue for 18 months, with 4 practices randomized each month.

Conclusion

Our study tests a novel approach to deliver CKD care that minimizes patient and PCP burden. This will inform efforts to use heath IT, risk prediction modeling, and PHM to augment evidence-based CKD care.

Funding

  • NIDDK Support