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Kidney Week

Abstract: FR-PO0021

Pilot of the Kidney Mobile Health Registry in the Cure Glomerulonephropathy (CureGN) Study

Session Information

Category: Artificial Intelligence, Digital Health, and Data Science

  • 300 Artificial Intelligence, Digital Health, and Data Science

Authors

  • Modi, Zubin J., University of Michigan, Ann Arbor, Michigan, United States
  • Salmon, Eloise, University of Michigan, Ann Arbor, Michigan, United States
  • Rahimi, Ashley E., University of Michigan, Ann Arbor, Michigan, United States
  • Scherr, Rebecca, University of Michigan, Ann Arbor, Michigan, United States
  • Kolupaeva, Victoria, Columbia University, New York, New York, United States
  • Arbit, Michael, University of Michigan, Ann Arbor, Michigan, United States
  • Desmond, Hailey, University of Michigan, Ann Arbor, Michigan, United States
  • Canetta, Pietro A., Columbia University, New York, New York, United States
  • Massengill, Susan F., Levine Children's Hospital, Charlotte, North Carolina, United States
  • Smith, Abigail R., Northwestern University, Evanston, Illinois, United States
Background

Mobile health (mHealth) has the potential to provide novel solutions to multiple current challenges in clinical research and trials, offering substantial value to study participants. Despite the use of mHealth in other chronic conditions, its implementation in kidney-focused research has been limited. Using the Kidney Mobile Health Registry, we evaluated the feasibility and value of integrating electronic health records (EHR) using mHealth in the Cure Glomerulonephropathy (CureGN) study.

Methods

Adult CureGN participants enrolled in the CureGN Mobile Health Pilot study using the MyDataHelps (CareEvolution; Ann Arbor, MI) application, provided electronic consent, granted permission for MyDataHelps to retrieve their EHR data, and completed a survey. EHR data from the first 11 participants were linked to data collected in the main CureGN cohort study. Data were compared for key variables of interest to assess the potential scientific value of this approach to participant enrollment and data capture.

Results

Among the 11 participants evaluated, 8 had an additional follow-up period of up to 6 years when EHR data were added to existing CureGN data. For key outcomes of urine protein-to-creatinine ratio (UPCR) and serum creatinine (Cr), accuracy was 100% (41 measurements) and 95% (78 measurements), respectively, when EHR and CureGN data were compared for same-day results. EHR data linkage provided an additional 2.3 UPCR values and 2 Cr values per patient per year, on average. EHR identified 6 new acute kidney injury events and 10 new nephrotic syndrome relapses not previously available in the CureGN data set. The data further added 20 medication exposures per patient, on average. Survey responses indicated that more than 80% of participants were interested in providing EHR, survey, and wearable data.

Conclusion

mHealth offers a novel research and disease management approach, with the potential to provide value to clinical studies and trials. We find excellent data reliability and substantial improvement in the amount of data collected. Participants report excitement from the engagement. Further exploration of application value, including the use of natural language processing for clinical note data extraction and pediatric considerations of proxy accounts, is needed.

Funding

  • NIDDK Support

Digital Object Identifier (DOI)