Quality indicators for clinical infectious diseases consultations-results from a hybrid Delphi-nominal group approach...

Infectious diseases consultation (IDC) services contribute to optimized infection management and are associated with improved outcomes, particularly in difficult-to-treat infections. However, there is uncertainty on how IDC should best be performed, reported, and communicated to achieve optimal impact and adherence. This consensus paper aims to provide structured expert consensus guidance on possible quality indicators (QIs) for IDC activities and reports.

A systematic literature review was performed but yielded no pertinent findings. Based on experience in clinical practice, the authors proposed 30 potential QIs in four major IDC domains. A Delphi-based anonymous online survey among infectious disease specialists and clinical microbiologists was conducted with two evaluation rounds. QIs were evaluated on 5-point Likert scales (-2, -1, 0, +1, and +2). Five possible QIs were additionally evaluated using scaling bars (from 0: only focused assessment/basic evaluation, to 10: complete assessment/detailed evaluation). Consensus for a QI was reached when ≥80% of the responses showed a strong agreement (+2) in the first round and when ≥80% of responses showed a strong agreement (+2) or ≥85% agreement for +1 or +2 on the Likert in the second round. Three clinical case scenarios were included to estimate the time required for IDC. Additionally, options for (automated) preparation and artificial intelligence (AI) support for IDC reports were assessed.

The survey was completed by 51 IDC experts from 17 different countries in the first round and by 26 experts from ten countries in the second round. Consensus was reached for 25 possible QIs categorized in four major domains (history and risk factors, bedside assessment, recommendations, and reporting), emphasizing a thorough conduct and documentation of IDC activities. Required time for IDC ranged from 35 minutes for simple or follow-up consultations to 55 minutes for complex cases. Almost half of 20 IDC procedures were judged as amenable to benefit from automation and AI support. This consensus paper proposes a comprehensive set of possible QIs for IDC services. The integration of these indicators may standardize evaluation, enhance the effectiveness of IDC, and facilitate international benchmarking. Further research is required to validate these QIs in diverse clinical settings and explore the integration of AI tools in clinical workflows.