Electronic Clinical Decision Support Tools to Manage Patients with Lower Respiratory Tract Infection: Clinicians’ Perspectives in Sri Lanka

TL;DR

This study explores how electronic clinical decision support tools could help Sri Lankan doctors manage lower respiratory infections better and reduce unnecessary antibiotic use.

Contribution

The study identifies clinician perspectives on eCDST features and requirements in a low-resource setting for managing LRTIs.

Findings

All clinicians expressed interest in using eCDSTs but emphasized clinical judgment should override tool recommendations.

Desired eCDST features included pathogen information, treatment guidance, severity assessment, and patient monitoring.

Design priorities included simplicity, time-saving functionality, and internet independence.

Abstract

In low-resource settings, providers often manage lower respiratory tract infections (LRTIs) without diagnostic tests, which may cause antibacterial overuse. Electronic clinical decision support tools (eCDSTs) can support evidence-based decision-making and judicious use of antibacterials. This study aimed to explore the potential of an eCDST to help providers in Sri Lanka effectively manage LRTI. Semi-structured interviews were conducted with 15 clinicians, including 10 males and five females, with an average of 11.6 years (range: 4–25 years) of clinical practice. The interview guide covered clinicians’ interest in an eCDST to manage LRTI and their feedback regarding the desired features of such a tool. Interviews were audio-recorded, transcribed, and coded for themes related to: interest in an eCDST for LRTI, desired tool capabilities, development concerns, and tool design characteristics. All expressed interest in incorporating eCDSTs into their practice. However, the majority emphasized that clinical judgment must supersede recommendations from an eCDST. Four themes emerged regarding desired tool capabilities: information about the pathogen, treatment recommendations, severity of the LRTI, and monitoring of patient progress. Six themes emerged regarding tool development considerations: validated algorithms, regional specificity, seasonality, inclusion of patient’s risk factors, scalability, and the importance of updated and locally relevant recommendations. Participants stressed that the tool design should be simple, timesaving, and internet-independent. Electronic clinical decision support tools are capable of improving patient care and reduce antibiotic overuse, which may impact downstream antibacterial resistance. Future research should develop an eCDST for LRTI with local input and evaluate its impact on appropriate antibacterial use and patient outcomes.