Practice of Improving Data Quality Based on the Intensity of Antimicrobial Drug Use (Preprint)

Abstract

The rational use and clinical application management of antimicrobial drugs is a common problem faced by all medical institutions. Due to abuse and misuse, there are still some problems in the management of antimicrobial drugs that should not be ignored, but due to the lack of effective measures, most of the medical institutions have not achieved the desired results.The deep integration of big data, "Internet+" and other technologies with the healthcare industry has made healthcare big data an important asset, and the effective use of healthcare big data can help hospitals operate in a more refined way, and help doctors treat and research more accurately.Therefore, exploring how to apply medical and healthcare big data to the rational application of antimicrobial drugs so that it can strengthen the management of antimicrobial drugs and standardize the use of antimicrobial drugs is of great significance to improve and optimize all the work of medicine and promote the development of health.Based on the characteristics of healthcare big data itself, healthcare big data quality governance has important research value to promote the output and application of healthcare big data.Therefore, data quality is a task that cannot be ignored in the application process.

In order to optimize the clinical application management of antimicrobial drugs in medical institutions, improve the level of rational use of antimicrobial drugs, and explore methods and paths to improve the quality of data to meet the requirements of high-quality development of hospitals.

Taking the indicator of antimicrobial drug use intensity as an example, it integrates the hospital's human resources, information system, data and other resources, analyzes the problems in the process of applying the existing medical and healthcare big data and gives the corresponding solutions.Combining the PDCA cycle management model, improving the management mechanism, exploring the construction standards, and constructing a set of intelligent full closed-loop antimicrobial rational application management platform integrated with data quality.Relying on the self-research platform, we authorize the corresponding data use authority according to the roles and responsibilities of medical staff, optimize the workflow, improve the assessment system, and realize the closed-loop quality control process of pre-warning, mid-monitoring, and post-assessment for the rational application of antimicrobial drugs.

The platform set indicator data display, detailed data query, target value filling, risk warning, real-time monitoring and other functions in a whole, multi-dimensional presentation of the use of antibacterial drugs, functional supervision departments can real-time monitoring of the indicator data, with or without abnormal cases, health care workers can always view the patient's medication, timely grasp of the condition.Since the platform went live in January 2021, the antimicrobial use intensity indicator has declined year on year from 38 to 34.4, which is much lower than the average intensity of use in the center members of the National Monitoring Network.The unified path of the self-research platform rescues medical staff from the daily tedious manual statistical work, optimizes the workflow and greatly improves the work efficiency, and the comprehensive management measures relying on the self-research platform are effective and have been unanimously praised.

By studying the construction and development of the intelligent management platform for the rational application of antimicrobial drugs, clinicians have been effectively urged to use drugs rationally and safely.At the same time, it explores the techniques and methods to improve data quality, emphasizing that data quality improvement requires multiple measures, not only focusing on the data source, but also focusing on each link in the process of data application, such as data statistical methods and overall management of the hospital, in order to comprehensively improve the quality of the data, and that its practical experience has an important reference significance for the governance and application of medical and healthcare big data, which provides the data support and technical guarantee for scientific, standardized, and clarified management of the hospital.