The Affiliated Yuebei People's Hospital of Shantou University Medical College, Shaoguan 512026, Guangdong, China.
Comput Intell Neurosci. 2022 Aug 22;2022:5371575. doi: 10.1155/2022/5371575. eCollection 2022.
With the wide application of artificial intelligence and big data technology in the medical field, the problems of high cost and low efficiency of traditional pharmacy management were becoming more and more obvious. Therefore, this paper proposed to use data mining technology to design and develop the dispensing process and equipment of intelligent pharmacy. Firstly, it summarized the existing data mining technology and association rule methods and expounded its application value in the related fields. Secondly, the data standard and integration platform of dispensing in intelligent pharmacy were established. Web service technology was used to design the interactive interface and call it to the intelligent device of pharmacy. Finally, an intelligent pharmacy management system based on association rule mining was constructed through the data mining of intelligent pharmacy equipment, in order to improve the intelligence and informatization of modern pharmacy management. For the emergency dispensing process of intelligent equipment failure, data mining was used to optimize the intelligent pharmacy equipment and dispensing process and change the pharmacy management from traditional prescription to patient drug treatment, so as to improve the dispensing efficiency of intelligent pharmacy equipment. Through the systematic test and analysis, the results showed that through the real-time risk prevention and control, the formula accuracy and operation speed of the intelligent dispensing machine were improved and the dispensing time was shortened. Through intelligent drug delivery, the unreasonable drug use of patients was reduced, the safety and effectiveness of clinical drug use were ensured, and the contradiction between doctors and patients was reduced. This study can not only optimize the medical experience of patients and provide patients with more high-quality and humanized pharmaceutical technical services but also provide some support for the intelligent management of modern hospitals.
随着人工智能和大数据技术在医疗领域的广泛应用，传统药房管理成本高、效率低的问题日益突出。因此，本文提出利用数据挖掘技术设计和开发智能药房的配药流程和设备。首先，总结了现有的数据挖掘技术和关联规则方法，并阐述了其在相关领域的应用价值。其次，建立了智能药房配药的数据标准和集成平台。采用 Web 服务技术设计交互接口，并调用智能药房的智能设备。最后，通过智能药房设备的数据挖掘构建了基于关联规则挖掘的智能药房管理系统，以提高现代药房管理的智能化和信息化水平。针对智能设备故障的应急配药流程，利用数据挖掘优化智能药房设备和配药流程，将药房管理从传统的处方转变为患者药物治疗，提高智能药房设备的配药效率。通过系统测试和分析，结果表明，通过实时风险防控，提高了智能配药机的配方准确率和操作速度，缩短了配药时间。通过智能发药，减少了患者不合理用药，保证了临床用药的安全性和有效性，减少了医患矛盾。本研究不仅可以优化患者的就医体验，为患者提供更优质、人性化的药剂技术服务，还可以为现代医院的智能化管理提供一定的支持。
