Improving CKD Screening and Care in Diabetes Using Clinical Decision Support in a Large Healthcare System

Background: Guidelines recommend screening for chronic kidney disease (CKD) in patients with diabetes with annual urinary albumin creatinine (ACR) and serum creatinine (Scr). However, screening rates were low in Kaiser Permanente Northwest, a large integrated healthcare system. We implemented a quality improvement project using clinical decision support (CDS) tools to increase ACR and Scr testing. We examined whether increased CKD screening resulted in improvement in CKD quality metrics, specifically ACEi/ARB (Angiotensin converting enzyme inhibitors or angiotensin receptor blocker) and SGLT2i (sodium-glucose cotransporter 2 inhibitor) use. Methods: In May 2022, we implemented CDS tools to increase ACR/Scr testing consisting of automated lab ordering, best practice alerts (BPAs), and automated lab reminders to patients via letters, texts, and phone calls in tandem with provider education on best practice recommendations for CKD. A SGLT2i BPA targeting patients with type 2 diabetes with ACR > 300 mg/gm and eGFR ≥ 30 ml/min was rolled out in June 2022 and expanded to include patients with eGFR > 60 ml/min regardless of CKD diagnosis in February 2023. Trends were reviewed monthly using statistical process control charts and changes in slope using segmented regression analysis. Results: After three years, ACR/Scr testing done within one year increased from 35 to 72%. ACEi/ARB use increased slightly from 74% to 76% but nephrology co-management for high-risk CKD patients remained unchanged at 53%. The rate of SGLT2i use steadily increased by 0.6% each month up until 6 months after introduction of the BPA, after which the rate increased to 1.7%. Amongst patients not co-managed with nephrology, the adjusted rate of increase was 7% higher in the BPA group compared to patients with CKD in the non-BPA group. Conclusions: Our study shows that use of CDS tools improve CKD screening in patients with diabetes but with mixed results in CKD quality metrics.

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Publication Details

Journal
Kidney360
Published
2025-04-24
DOI
https://doi.org/10.34067/kid.0000000829
Primary Topic
Artificial Intelligence in Healthcare
Type
article
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article

Improving CKD Screening and Care in Diabetes Using Clinical Decision Support in a Large Healthcare System

Frank Chen, Ken Park, Eric S. Albright, Shaun Flerchinger et al.
Kidney360
Artificial Intelligence in Healthcare
article

Improving CKD Screening and Care in Diabetes Using Clinical Decision Support in a Large Healthcare System

Frank Chen, Ken Park, Eric S. Albright, Shaun Flerchinger, Lisa J. Nakashimada, Michalah K. Tandy, Kathryn J. Glassberg
article en

Abstract

Background: Guidelines recommend screening for chronic kidney disease (CKD) in patients with diabetes with annual urinary albumin creatinine (ACR) and serum creatinine (Scr). However, screening rates were low in Kaiser Permanente Northwest, a large integrated healthcare system. We implemented a quality improvement project using clinical decision support (CDS) tools to increase ACR and Scr testing. We examined whether increased CKD screening resulted in improvement in CKD quality metrics, specifically ACEi/ARB (Angiotensin converting enzyme inhibitors or angiotensin receptor blocker) and SGLT2i (sodium-glucose cotransporter 2 inhibitor) use. Methods: In May 2022, we implemented CDS tools to increase ACR/Scr testing consisting of automated lab ordering, best practice alerts (BPAs), and automated lab reminders to patients via letters, texts, and phone calls in tandem with provider education on best practice recommendations for CKD. A SGLT2i BPA targeting patients with type 2 diabetes with ACR > 300 mg/gm and eGFR ≥ 30 ml/min was rolled out in June 2022 and expanded to include patients with eGFR > 60 ml/min regardless of CKD diagnosis in February 2023. Trends were reviewed monthly using statistical process control charts and changes in slope using segmented regression analysis. Results: After three years, ACR/Scr testing done within one year increased from 35 to 72%. ACEi/ARB use increased slightly from 74% to 76% but nephrology co-management for high-risk CKD patients remained unchanged at 53%. The rate of SGLT2i use steadily increased by 0.6% each month up until 6 months after introduction of the BPA, after which the rate increased to 1.7%. Amongst patients not co-managed with nephrology, the adjusted rate of increase was 7% higher in the BPA group compared to patients with CKD in the non-BPA group. Conclusions: Our study shows that use of CDS tools improve CKD screening in patients with diabetes but with mixed results in CKD quality metrics.

Kidney360Vol. 6(9)
Kaiser Permanente (US)
Openalex Percentile: Top 90%
Artificial Intelligence in Healthcare
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