DEVELOPMENT OF ELECTRONIC EDUCATIONAL-METHODICAL COMPLEXES OF DISCIPLINES STORAGE SUBSYSTEM OF UNIVERSITY INFORMATION SYSTEM

2018 ◽  
pp. 53-58
Author(s):  
Yu. S. Nosova ◽  
A. N. Molchanov ◽  
A. V. Burmistrov ◽  
S. S. Grishunov
Keyword(s):  
Information System ◽  
User Interface ◽  
Relational Database ◽  
Management System ◽  
Database Management ◽  
Database Management System ◽  
Application Server ◽  
File Storage ◽  
Python Language ◽  
The University

The article poses the problem of storage, systematization and organization of access to the educational methodological complexes of disciplines (Emcd) in the university. The architecture of the electronic EMCD storage subsystem of the university's information system, consisting of a file storage, a relational database and an application server, is described. The choice of the database management system (dbms) is substantiated and the eer-diagram with the description of the main tables is given. The tools used to develop the server and client parts of the subsystem are described. In particular, the developers used the Python language with the Flask microframework and the CSS framework Bootstrap to create a responsive user interface. The interface of the main pages for working with the subsystem is given, as well as the main types of reports construction.

Relational Database Management System

2021 ◽  
pp. 47-78
Author(s):  
Jagdish Chandra Patni ◽  
Hitesh Kumar Sharma ◽  
Ravi Tomar ◽  
Avita Katal
Keyword(s):  
Relational Database ◽  
Management System ◽  
Database Management ◽  
Database Management System ◽  
Relational Database Management System ◽  
Relational Database Management

Automating Quality Oncology Practice Initiative Quality Measure NHL78a

2017 ◽  
pp. 1-6
Author(s):  
Richard Mansour ◽  
Samip Master
Keyword(s):  
Hepatitis B ◽  
Relational Database ◽  
Management System ◽  
Database Management ◽  
Quality Measurement ◽  
Database Management System ◽  
Quality Measure ◽  
Relational Database Management System ◽  
Oncology Practice ◽  
Relational Database Management

Purpose Quality measurement and improvement is a focus of ASCO. In the era of electronic health records (EHRs), computerized order entry, and medication administration records, quality monitoring can be an automated process. The EHR data are usually stored within tables in a relational database management system. ASCO Quality Oncology Practice Initiative measure NHL78a (hepatitis B virus antigen test and hepatitis B core antibody test within 3 months before initiation of obinutuzumab, ofatumumab, or rituximab for patients with non-Hodgkin lymphoma) presents an opportunity for automation of a quality measure using existing data in the EHR. Methods We used a locally developed Structured Query Language (SQL) language procedure in the Microsoft SQL Query Manager to access the EPIC CLARITY database. Access to the relational database management system of the EHR permits rapid case identification (the denominator set) of the unique ID of all of the patients who have received one of the target medications (ie, obinutuzumab, ofatumumab, or rituximab). Then, we went through a six-step process to find the number of patients who passed or failed the quality measure. Results When the final SQL procedure executes, it takes < 5 seconds to see the result set for a 12-month period. The procedure can be changed to incorporate a desired date range. Once the SQL procedure is created, there is essentially no labor and low costs to run the procedure at specific time intervals. Conclusion Our method of quality measurement using EHRs is cost effective, fast, and precise, and can be reproduced at other centers.

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