Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Aug 22:2022:5371575.
doi: 10.1155/2022/5371575. eCollection 2022.

The Intervention of Data Mining in the Allocation Efficiency of Multiple Intelligent Devices in Intelligent Pharmacy

Xiaohua Li  1 , Benren Tan  1 , Jinkun Zheng  1 , Xiaomei Xu  1 , Jian Xiao  1 , Yanlin Liu  1
Affiliations

The Intervention of Data Mining in the Allocation Efficiency of Multiple Intelligent Devices in Intelligent Pharmacy

Xiaohua Li et al. Comput Intell Neurosci. .

Abstract

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.

PubMed Disclaimer

Conflict of interest statement

The authors declare are no conflicts of interest.

Figures

Figure 1
Figure 1
The basic working process of data mining.
Figure 2
Figure 2
The running process of apriori algorithm.
Figure 3
Figure 3
Structure and distribution diagram of the intelligent pharmacy control system.
Figure 4
Figure 4
The framework of intelligent pharmacy management system based on association rule mining.
Figure 5
Figure 5
Outpatient prescription dispensing process after system optimization.
Figure 6
Figure 6
Emergency prescription dispensing process after system optimization.
Figure 7
Figure 7
Average waiting time of patients before building the data platform.
Figure 8
Figure 8
Average waiting time of patients after building the data platform.
See this image and copyright information in PMC

References

    1. Xu Y. F., Wang L. X. Discussion on the pharmacy service under the background of new medical reform. World Latest Med. Inf . 2017;17(29):99–100.
    1. Yu K. B. How to Improve the Quality of traditional Chinese medicine decoction of basic level hospital. China Health Ind . 2019;16(3):20–22.
    1. Yu C., Liu H. L. Research and development of information platform based on distribution and quality control of traditional Chinese medicine decoction pieces. China Med. Educ. Technol . 2016;30(1):98–100.
    1. Martín D., Alcarria R., Sánchez-Picot Á., Robles T. An ambient intelligence framework for end-user service provisioning in a hospital pharmacy: a case study. Journal of Medical Systems . 2015;39(10):116–210. doi: 10.1007/s10916-015-0298-z. - DOI - PMC - PubMed
    1. Cor M. K., Peeters M. J. Using generalizability theory for reliable learning assessments in pharmacy education. Currents in Pharmacy Teaching and Learning . 2015;7(3):332–341. doi: 10.1016/j.cptl.2014.12.003. - DOI

LinkOut - more resources