BI can assist business decision-making, either at the operational level or at the tactical and strategic levels. In order to turn data into knowledge, you need to leverage technologies such as data warehousing, online analytical processing (OLAP) tools, and data mining. Therefore, from a technical perspective, BI is not a new technology, it is just a comprehensive application of data warehouse, OLAP and data mining technologies.
The hospital BI system is based on the integration of the existing system of the hospital, the application of BI tools, the deep processing of hospital information resources. Through the integration, integration and expansion of cross-platform and multi-heterogeneous systems within the hospital, data collection and mining are fully realized, and medical personnel and managers are assisted in data analysis.
HIMSS 7 has a clear requirement for hospital BI construction, using data warehouses to analyze clinical data and provide clinical decision support. Specific applications include: validation of medical quality management through BI applications; effective implementation and control of clinical guidelines; data standardization integration and utilization; medical safety event initiative warning and analysis; formal BI strategy, use of scorecards and meters The disk implements data drilling of the relevant data layer, and the like.
Hospital BI system construction
To build a hospital BI system, it is necessary to integrate different sources of information to establish data centers, including HIS, LIS, RIS, PACS, surgical anesthesia, structured medical records, and financial charges.
Through the BI system, the hospital management can obtain the hospital's data information anytime and anywhere, and analyze the hospital's economic operation dynamic data. Operational data information includes medical operations, financial management, economic operations, bed resources, assets, work indicators, health workforce resources, infrastructure, large equipment resources, outpatient operations, hospitalization operations, medical quality indicators, and medical efficiency indicators. . Dynamic query and comparison of indicators such as emergency department visits, hospital attendance, hospital discharges, number of operations, per capita expenses of outpatients, per capita hospitalization expenses, average hospitalization days, inpatient infection rates, and bed occupancy rates can be achieved. At the same time, by setting the target value, the completion value is compared with the target value. The goal achievement is represented by red, yellow and green lights. The trend is represented by arrows of different directions and colors, and the target achievement rate and trend are clear at a glance.
Through the hospital portal, as well as dashboards, decision trees, dynamic reports and other forms, to meet the timely use of end-user information and flexible analysis needs.
Application display
Data drilling includes up and down drilling [5]. Drilling is a process of summarizing low-level detail data to a high level in a certain dimension, that is, a process of summarizing data; on the contrary, it is to refine the data of the superior level and go deeper to the next level. Process. Data drilling is also a hierarchical change of dimensions, such as time dimension. The design can be divided into four levels, namely, annual, quarterly, monthly, and daily, so that drilling up in the analysis can display the number of cases of the annual disease, and drill down. Can be specific to the admission of a certain day. The analysis can be thick and thin, flexible and changeable.
To analyze the composition of disease costs in different departments and their trends with the year, it can be easily solved with decision trees. First, the average cost is selected as the metric value, and it is divided according to the path of the first-grade disease→second-grade disease→third-grade disease→cost category→department→annual. It can be seen that for coronary stenting (1 In this disease, the average material fee is the highest in one subject and the lowest in the five subjects. The medical service fee reflecting the labor value of medical staff is the lowest in the first section, and the top five in the department. The vertical comparison of the internal subjects shows that the medical service in 2015 The fee is significantly higher than in 2014. It shows that although the horizontal comparison is poor, the self is constantly improving.
Case introduction
Hospital application BI systems can transform large amounts of data into useful information, predict trends and early warning analysis of medical quality, and assist hospital administrators to identify problems to improve work efficiency and quality of medical safety. At the same time, it monitors the quality indicators related to patient safety, analyzes key issues, and achieves targeted and improved quality management efficiency.
Taking the continuous improvement of the balloon-to-balloon expansion time (DtoB time) as an example, the information utilization value of the BI system in clinical quality management is explained. Through the DtoB average time monitoring of the BI system, the hospital conducted data tracking and effect evaluation. The monitoring data showed that: (1) the average DtoB time of the internal department was shortened to 62.36min, and remained at the level of 60min in the following months; (2) From the July-October monitoring data, the informed consent time was improved. The effect was obvious, from 93.3min in May to 24.4min.
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