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Abstract: FR-PO103

Acute Kidney Disease in Outpatient Setting: Epidemiological Insights from National Digitalized Big Data Practice

Session Information

Category: Acute Kidney Injury

  • 101 AKI: Epidemiology, Risk Factors, and Prevention


  • Chiang, Hsiu-Yin, China Medical University Hospital, Taichung, Taiwan
  • Lin, Zi-Han, China Medical University Hospital, Taichung, Taiwan
  • Chang, David R., China Medical University Hospital, Taichung, Taiwan
  • Kuo, Chin-Chi, China Medical University Hospital, Taichung, Taiwan

The burden of acute kidney disease in outpatients (AKDOPT) is largely unknown due to health data silos and its asymptomatic nature. We established an Acute Kidney Injury Detection System (AKIDS) that integrates local electronic medical records and National Health Insurance Cloud to screen for AKDOPT, and enable risk-based referrals in real-time.


AKIDS was integrated into the backend of outpatient HIS during 2017.12-2020.05. AKDOPT within 180 days prior to a clinic visit is defined as the percent change between the max and min of (1) serum creatinine (SCr) >50%, or (2) eGFR >35%. AKDOPT is considered deteriorating if the last two SCr decreased by >0.3 mg/dL; otherwise, it’s termed stable. We ensured a 1-year follow-up by including adult patients with the first AKDOPT occurring during 2017.12-2019.06 and without ESRD or cancer. One-year composite kidney outcome (CKO) was defined as having ESRD or ≥40% drop of outpatient eGFR during follow-up. All-cause mortality was determined by National Death Registry. Multivariable Cox proportional modeling was used to estimate the risk of outcomes associated with AKDOPT.


The monthly cumulative incidence density of AKDOPT was 6.9 to 8.1% (Figure). AKDOPT patients had significantly higher 1-year CKO (1.8 vs 0.2%) and mortality (8.2 vs 1.4%), compared with those without. Of 79838 outpatients, 15.7% had AKDOPT (12.7% stable; 3.0% deteriorating). Multivariable analysis found that AKDOPT was significantly associated with increased 1-year risk of CKO by 5-fold (adjusted HR [aHR]=5.2; 95% CI=4.0-6.8) and mortality by 3-fold (2.6 [2.4-2.9]). The risk of 1-year CKO for deteriorating AKDOPT (7.6 [5.5-10.5]) was higher than that for stable AKDOPT (4.4 [3.3-5.8]).


By integrating national–local data and creating a kidney data ecosystem, we conducted the first study to fully characterize the epidemiologic profile of AKDOPT—a obscured AKI phenotype. This study illustrates the potential of healthcare big data in transforming global approaches to AKD patterns and prevention.


  • Government Support – Non-U.S.