Four-step process delivers specific, reliable clinical rules

By Joanna Lyford, Senior medwireNews Reporter

Dutch researchers have developed a four-step strategy for formulating clinical decision support systems (CDSS), which they say could help reduce "alert fatigue."

CDSS, or clinical rules, harness information technology to integrate patient and clinical information, and are increasingly used to direct healthcare decisions. However, high rates of alert overrides ("alert fatigue") and low rates of alert adherence can hinder the success of well-designed CDSS, explain Anne-Marie Scheepers-Hoeks (Catharina Hospital Eindhoven) and co-authors.

Scheepers-Hoeks and team therefore sought to improve the relevance of alerts to individual patients, using lithium therapy as their test case. Lithium was chosen as it is a potentially hazardous drug with a narrow therapeutic window that requires monitoring of multiple parameters.

The development strategy had four stages, each of which was monitored according to the "Plan-Do-Check-Act" (PDCA) cycle for quality control, write Scheepers-Hoeks et al in the European Journal of Hospital Pharmacy. The first stage was retrospective technical validation, designed to determine whether the parameters in the CDSS - in this instance, the lithium blood level - were linked to the correct parameters in the electronic health record.

The second stage was retrospective therapeutic validation, which checked whether all alerts were clinically relevant, actionable, and judged to be useful by an expert team. "Therapeutic validation is most important for gaining user acceptance," note the authors.

Stage three was prospective pre-implementation validation, in which the clinical rule was prepared for routine application in daily practice. This involved linking the CDSS to the electronic health record database and adapting the rule to assure "prospective timely alerting, integrated in the clinical workflow."

The final stage was prospective post-implementation validation, in which the rule was operational but under continuous monitoring, and subject to technical and therapeutic maintenance.

"We found that, after implementation in practice, adjustments were needed for every clinical rule that were not foreseen during the development phase (steps 1-3)," write Scheepers-Hoeks and colleagues.

Having developed their strategy, the team then used it to develop nine further clinical rules in various settings, including heart failure, hypo/hyperkalemia, gastroprotection, and anticoagulation. The positive predictive values of the rules ranged from 89% to 100%, while the negative predictive value was 100% in each instance.

Noting that CDSS are the next generation of medication safety systems and are able to narrow the gap between evidence-based medicine and practice, the team concludes: "The proposed strategy is effective for creating specific and reliable clinical rules that generate relevant recommendations.

"The crucial value of our approach lies in the consultation of an expert team in the development of the clinical rules, together with continuous monitoring of the technical correctness and clinical relevance during the development."

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