Consensus-Based Recommendations for Optimizing Diversified TCM Data Collection during Clinical Work (Preprint)

BACKGROUND Background: An increasing amount of TCM clinical data can be collected by software and equipment, forming diversified TCM data, which should typically be collected alongside clinical work. TCM diagnosis and treatment data collection is conducted concurrently with clinical work, typically. However, with the limited time, space, and human resources available in clinical work, collecting diversified TCM Data is difficult, which may affect the quality of the collected data. OBJECTIVE Objective: To develop recommendations for optimizing diversified traditional Chinese medicine (TCM) data collection. METHODS Method: A working group comprising 12 members was established. Based on previous survey findings regarding the burden of clinical data collection, the group developed a preliminary list of recommendations for optimizing diversified TCM data collection. A Delphi survey was conducted to investigate consensus levels(using a 5-point Likert scale for importance evaluation) on the list items, and open-ended opinions were also surveyed. If experts in the first round propose additions, deletions, or modifications, or if there is a lack of consensus on certain items, a next round of surveys will be conducted to obtain the experts' agreement rate on the related items. RESULTS Results: A total of 86 experts from China, the United Kingdom, and Singapore completed two rounds of surveys. Following the first Delphi survey, all items achieved agreement scores above 4, with coefficients of variation(CV) below 0.2. The working group revised 12 items based on open-ended opinions and resubmitted them for agreement assessment. All revised items achieved agreement rates of over 95%. Following the two-round survey process, the final version of the recommendations comprises 5 primary domains, 11 sub-domains, and 25 items. CONCLUSIONS Conclusion: This study formulated recommendations for optimizing diversified TCM data collection. It is hoped that these recommendations will help clinical data collectors consider data collection in advance during the design phase