Automating Data Analysis for Clinica Moguillansky with Python and Streamlit
To protect the privacy and security of patient and clinic data, all names and numbers used in the screenshots and videos of the Streamlit app I developed for Clinica Moguillansky are fictitious.
Introduction
I had the opportunity to work with Clinica Moguillansky, one of the best diagnostic imaging clinics in the south of Argentina, specifically in the Neuquen province. The clinic faced the challenge of not being able to gain insights from their patient data and diagnostic study information due to the lack of visualisations and data analysis features in their existing software system.
To address this challenge, I developed a user-friendly application using Python and Streamlit that allowed the clinic to analyse a large volume of diagnostic study data. The application generates exportable tables and dynamic graphs, enabling the clinic staff to gain meaningful insights. It provides information on various aspects of the clinic’s operations, such as the volume of studies conducted on different days and times, patient demographics and location, and financial performance.
The application has proven to be useful to a wide range of clinic staff, including administrators, financial analysts, medical practitioners, and marketers, among others. It has allowed the clinic to better understand their operations and make data-driven decisions to improve patient outcomes and profitability.
Sergio Moguillansky, Director of Clinica Moguillansky states: “The data analytics tool developed by Juan Pedro has been a game-changer for our clinic. We are now able to quickly and efficiently analyse patient data, which has helped us to make more informed decisions about our operations. The tool is easy to use, and the interface is visually appealing”
Raw data snapshot
Below is a snapshot of the raw data provided by Clinica Moguillansky, which was obtained directly from their existing software system. The system allows for the export of data to Excel, which was then used as the basis for the analysis and visualization performed in this project.
User Interface
The user interface created for the Clinica Moguillansky data analysis application was designed to be intuitive and user-friendly, providing easy access to the insights and visualizations generated from the raw data. The application includes a range of tools and features to allow for efficient exploration of the data.
Users can filter the data using various tools such as checkboxes, dropdown menus, and sliders, allowing for customised views of the data that are relevant to the user’s needs. The graphs and charts generated using Plotly are interactive, allowing for a deeper understanding of the data, and can be exported as PNG or HTML files to preserve the interactivity.
All tables generated by the application can be exported to Excel, providing users with a convenient way to work with the data outside of the application. The use of Streamlit as a framework for the interface ensures that the application is responsive and easy to use, allowing for a seamless experience for users. Overall, the user interface provides a valuable tool for the clinic staff to gain insights and make data-driven decisions, contributing to improved patient outcomes and profitability.
Conclusion
In conclusion, this project highlights the importance of data analysis and visualization in healthcare operations, and demonstrates how powerful tools can be utilized to provide insights and improve decision-making. The application developed for Clinica Moguillansky has been a successful example of how data-driven insights can contribute to better patient outcomes and a more profitable business. By utilizing tools like Python, Pandas, Plotly, and Streamlit, the application provides an intuitive and user-friendly interface that allows for efficient exploration of diagnostic study data. This project serves as a reminder of the tremendous potential of data analysis and visualization in healthcare, and how it can be used to drive positive change and improve patient care.
