A multi-site randomized trial of a clinical decision support intervention to improve problem list completeness

Area of Science:

• Health Informatics
• Clinical Decision Support Systems
• Electronic Health Records

Background:

• Accurate patient problem lists are crucial for effective healthcare delivery.
• Gaps in problem list documentation can impact care quality and patient comprehension.
• Existing methods for problem list maintenance may not capture all patient conditions.

Purpose of the Study:

• To enhance problem list documentation accuracy within electronic health records (EHRs).
• To assess the impact of a clinical decision support (CDS) intervention on problem list completeness.
• To evaluate if improved problem list accuracy correlates with better clinical quality measures.

Main Methods:

• Developed algorithms to identify unrecorded patient problems from EHR structured data.
• Implemented a CDS intervention to prompt clinicians for missing problem additions.
• Conducted a randomized trial across four healthcare systems with diverse EHRs.
• Measured alert acceptance, problem addition rates, and National Committee for Quality Assurance Healthcare Effectiveness Data and Information Set (NCQA HEDIS) clinical quality measures.

Main Results:

• The CDS intervention significantly increased the addition of missing problems to patient records.
• The problem addition acceptance rate was 22.1% across 288,832 opportunities.
• No significant differences were observed in NCQA HEDIS clinical quality measures between the intervention and control groups.

Conclusions:

• The EHR-embedded CDS intervention effectively improved problem list completeness.
• Improved problem list accuracy did not directly translate to measurable improvements in NCQA HEDIS quality measures.
• Accurate problem lists offer benefits beyond quality measures, including improved clinical care and patient understanding.