Drug resistance is a huge problem for healthcare and to face it a monitoring system based on collection and analysis of laboratory epidemiological data is required. The PHD project was focused on the development of a web application, which we called ResMon2, for management of such type of data (drug resistance of bacteria present in clinical isolates) useable in a hospital. A web platform associated with a relational database was created in order to have an application easy to update inserting new data without directly editing the HTML pages of the application. The open-source MySQL database was chosen since it has many assets: extremely stable, high performance, supported by a huge online community and it is free. The dynamic content of the web application is generated using a scripting-type programming language: PHP. It is an open-source language precisely developed for construction of dynamic-content web pages perfect for automation of inserting, editing, deleting and displaying functions of data. Besides, it integrates easily with MySQL database thanks to many integrated functions for dynamic data manipulation. A new database was designed creating tables and relations among them: registries, samples, isolated microorganisms and antibiogram data (sensitive, resistant, intermediate). Once defined the database the PHP and HTML code composing the main functions of the application was written. Such functions are: manual insert of single antibiogram, multiple antibiograms importing from specific instruments data files, edit/delete of previously inserted antibiograms, data analysis for trends detection of specific microorganisms species prevalence and of their drug resistance, with attached cake-type graphics and histograms. All functions were tested with real sample clinical data and were provided with specific controls, and simple and clean graphics were added to the application.

Sviluppo di un'applicazione bioinformatica per la gestione dei dati di antibiotico sensibilità  di isolati clinici

2012

Abstract

Drug resistance is a huge problem for healthcare and to face it a monitoring system based on collection and analysis of laboratory epidemiological data is required. The PHD project was focused on the development of a web application, which we called ResMon2, for management of such type of data (drug resistance of bacteria present in clinical isolates) useable in a hospital. A web platform associated with a relational database was created in order to have an application easy to update inserting new data without directly editing the HTML pages of the application. The open-source MySQL database was chosen since it has many assets: extremely stable, high performance, supported by a huge online community and it is free. The dynamic content of the web application is generated using a scripting-type programming language: PHP. It is an open-source language precisely developed for construction of dynamic-content web pages perfect for automation of inserting, editing, deleting and displaying functions of data. Besides, it integrates easily with MySQL database thanks to many integrated functions for dynamic data manipulation. A new database was designed creating tables and relations among them: registries, samples, isolated microorganisms and antibiogram data (sensitive, resistant, intermediate). Once defined the database the PHP and HTML code composing the main functions of the application was written. Such functions are: manual insert of single antibiogram, multiple antibiograms importing from specific instruments data files, edit/delete of previously inserted antibiograms, data analysis for trends detection of specific microorganisms species prevalence and of their drug resistance, with attached cake-type graphics and histograms. All functions were tested with real sample clinical data and were provided with specific controls, and simple and clean graphics were added to the application.
2012
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/334388
Il codice NBN di questa tesi è URN:NBN:IT:BNCF-334388