Doctor reviewing medical chart while assisting a patient in a hospital bed.
Doctor reviewing medical chart while assisting a patient in a hospital bed. Photo: Tima Miroshnichenko/Pexels

A recent trial in Stockholm found that chronic kidney disease (CKD) alerts did not lead to increased clinician action at any stage of care. Antoine Créon, MD, a PhD student at Karolinska Institutet, suggests that alert fatigue and interface design may be contributing factors.

Créon discussed the trial’s limitations in an interview. He noted that it did not prove the alerts improved earlier detection, nor did it show that earlier detection led to more referrals or treatment. The alerts failed to prompt more action in screening, retesting, treatment, or referral.

Despite these findings, the approach has potential for large-scale use because it integrates with existing electronic health records. Once implemented, it can identify care gaps across many patients without requiring manual review of every record. However, Créon emphasized that successful deployment does not guarantee improved care.

The trial’s results may not apply to other settings, as it involved only one region, one health record software, and one user interface. He noted that the clinical logic is transferable, but its effectiveness requires local evaluation.

Alert fatigue is a plausible explanation for the lack of clinician response. Créon explained that clinicians often receive many messages, and the CKD alert may compete with other consultation results. Additionally, interface design likely plays a significant role. Recommendations should appear when clinicians can act without distraction and with minimal effort.

Even when an alert identifies a task, completing it involves multiple steps. Testing requires an order, patient participation, and result review. Follow-up treatment may need discussion and monitoring, while referral depends on specialist capacity and patient attendance.

The trial also revealed wide variations in testing rates between centers, with creatinine testing ranging from 27% to 84%. This suggests that local organization and routines are critical factors. His team is analyzing usage data to better understand how the system was used and what may have led to the negative findings.