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A CKD Clinical Decision Support System: A Cluster Randomized Clinical Trial in Primary Care Clinics
JoAnn Sperl-Hillen1,2, A Lauren Crain1, James B Wetmore3
1HealthPartners Institute, Minneapolis, Minnesota.
Rationale & Objective:
The study aimed to develop, implement, and evaluate a clinical decision support (CDS) system for chronic kidney disease (CKD) in a primary care setting, with the goal of improving CKD care in adults.
Study Design:
This was a cluster randomized trial.
Setting & Participants:
A total of 32 Midwestern primary care clinics were randomly assigned to either receive usual care or CKD-CDS intervention. Between April 2019 and March 2020, we enrolled 6,420 patients aged 18-75 years with laboratory-defined glomerular filtration rate categories of CKD Stage G3 and G4, and 1 or more of 6 CKD care gaps: absence of a CKD diagnosis, suboptimal blood pressure or glycated hemoglobin levels, indication for angiotensin-converting enzyme inhibitor or angiotensin receptor blocker but not prescribed, a nonsteroidal anti-inflammatory agent on the active medication list, or indication for a nephrology referral.
Intervention:
The CKD-CDS provided personalized suggestions for CKD care improvement opportunities directed to both patients and clinicians at primary care encounters.
Outcomes:
We assessed the proportion of patients meeting each of 6 CKD-CDS quality metrics representing care gap resolution after 18 months.
Results:
The adjusted proportions of patients meeting quality metrics in CKD-CDS versus usual care were as follows: CKD diagnosis documented (26.6% vs 21.8%; risk ratio [RR], 1.17; 95% CI, 0.91-1.51); angiotensin-converting enzyme inhibitor or angiotensin receptor blocker prescribed (15.9% vs 16.1%; RR, 0.95; 95% CI, 0.76-1.18); blood pressure control (20.4% vs 20.2%; RR, 0.98; 95% CI, 0.84-1.15); glycated hemoglobin level control (21.4% vs 22.1%; RR, 1.00; 95% CI, 0.80-1.24); nonsteroidal anti-inflammatory agent not on the active medication list (51.5% vs 50.4%; RR, 1.03; 95% CI, 0.90-1.17); and referral or visit to a nephrologist (38.7% vs 36.1%; RR, 1.02; 95% CI, 0.79-1.32).
Limitations:
We encountered an overall reduction in expected primary care encounters and obstacles to point-of-care CKD-CDS utilization because of the coronavirus disease 2019 pandemic.
Conclusions:
The CKD-CDS intervention did not lead to a significant improvement in CKD quality metrics. The challenges to CDS use during the coronavirus disease 2019 pandemic likely influenced these results.
Funding:
National Institute of Diabetes and Digestive and Kidney Diseases (R18DK118463).
Trial Registration:
clinicaltrials.gov Identifier: NCT03890588.
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