| BackgroundThere were problems in clinical trials management such as difficulties in enrolling subjects,inadequate supervision,poor compliance,human errors,lagging monitoring,and high input costs.The advent of the era of intelligence had ushered in a new approach to manage clinical trials,and it was crucial to explore whether intelligent tools can improve the efficiency and quality of clinical trial management and reduce the cost of clinical trials.ObjectivesIn view of the widespread use of intelligent tools in clinical trials,this study describes the current status of the implementation of the model in an example study by constructing an intelligent clinical trial management model,measuring the cost of the model and comparing it with the traditional model,and evaluating the management effects of both models for cost-effectiveness analysis.MethodsThis study adopted a parallel control design,and the research subjects were from the "Type 2 Diabetes Intelligent Optimization Comprehensive Management System and Social and Economic Benefit Evaluation" project,and subjects who entered the trial from April 2020 to February 2022 and completed the observation of the main outcome indicators were included.As the subjects of this study,they were divided into experimental group and control group according to whether they used intelligent tools for management.The relevant cost information and management effect indicators(data integrity rate,follow-up completion)of the clinical trial were collected through questionnaires and expert consultation,and the management effects of the two groups were compared by the chi-square test,and the costeffectiveness analysis was carried out in combination with the cost.Results1.Management applicationThe intelligent management of subjects’ management(follow-up and supervision)and data management(collection,entry and verification)in the empirical study of a clinical trial of type 2 diabetes was basically realized.2.Management costThe total cost of the experimental group was 246,877 RMB and the per capita cost was 3248 RMB,while the total cost of the control group was 197,354 RMB and the per capita cost was 2597 RMB.Compared with the control group,the experimental group increased the cost of these intelligent tools.Comparing the clinical institution costs of the two groups,the labor costs,operation costs and subsidy costs of the experimental group were lower than those of the control group.3.Management effectivenessThere was no statistically significant difference between the experimental group and the control group in the complete rate of all indicators(38.16%vs31.56%),the complete rate of major outcome indicators(85.53%vs80.26%),the complete rate of secondary outcome indicators(43.42%vs35.53%),the follow-up over-window rate(26.32%vs38.16%),and the total rate of follow-up over-window rate(10.86%vs12.50%),and there was a statistically significant difference between the follow-up completion rate(86.84%vs71.05%),number of follow-up completed(66 vs 54)and the total rate of follow-up completion rate(92.76%vs86.84%).4.Cost-effectiveness analysisThese intelligent tools had a cost-effectiveness advantage.In the costeffectiveness analysis,per 1%increase in the follow-up completion rate and the number of follow-up completers in the experimental group cost 37.40 RMB and 49.21 RMB,respectively,while per 1%increase in the above indicators in the control group cost 36.55 RMB and 48.09 RMB,respectively;compared with the control group,the additional cost for each unit effect increase in the above indicators in the experimental group was 41.23 RMB and 54.25 RMB;the incremental costeffectiveness ratio was evaluated using the number of follow-up completions as an indicator,and the results were smaller than the willingness to pay(per capita cost of the control group).In the sensitivity analysis,for follow up completion rate,the factors that had an impact on the cost-effectiveness ratio were the subject allowance,the number of concurrent administrations of these intelligent tools,and for follow-up completions,the factors that had a greater impact on the incremental costeffectiveness ratio were the number of concurrent administrations,the number of physicians in the experimental group and the control group The range of variation was within acceptable limits.In the scenario analysis,the results showed that the per capita cost of the experimental group(4063 RMB)was lower than the per capita cost of the control group(4206 RMB),and these intelligent tools had an absolute cost-effective advantage.ConclusionsThis study confirms the potential role of intelligent tools in reducing the cost of clinical trial management,as well as improving the effectiveness and costeffectiveness of clinical trial management,and provides a reference for the future innovation of clinical trial management mode. |
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