healthcare_trends
The project aims to understand the trends and patterns in the healthcare system over the years, and how changes in hospital infrastructure and patient metrics have influenced each other.
Science Score: 44.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
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✓.zenodo.json file
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○Scientific vocabulary similarity
Low similarity (11.3%) to scientific vocabulary
Repository
The project aims to understand the trends and patterns in the healthcare system over the years, and how changes in hospital infrastructure and patient metrics have influenced each other.
Basic Info
- Host: GitHub
- Owner: hemababy
- License: mit
- Language: Jupyter Notebook
- Default Branch: main
- Size: 855 KB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Healthcare Trends Analysis
This project analyzes healthcare trends using data from destatis Genesis online portal sources. The goal is to provide insights into the healthcare industry and identify areas for improvement.
This project conducts an in-depth analysis of healthcare system metrics in Germany from 1991 to 2022. The dataset includes information on the number of hospitals, hospital beds, patients, occupancy rates, and other relevant indicators. The project aims to understand the trends and patterns in the healthcare system over the years, and how changes in hospital infrastructure and patient metrics have influenced each other.
Key research questions addressed in this project include the evolution of the number of hospital beds and beds per 100,000 inhabitants, changes in the number of hospitals, correlation between the average length of stay and the average occupancy of hospital beds, differences in hospital bed occupancy and average length of stay between different years, changes in occupancy rate over time, and trends in the number of patients and patients per 100,000 inhabitants.
The project uses Python for data analysis, with libraries such as pandas for data manipulation, and matplotlib and seaborn for data visualization. The results of the analysis provide insights that can inform resource allocation decisions and help optimize the healthcare system.
Please refer to the healthcare_analysis.ipynb Jupyter notebook for the detailed analysis and code.
Usage Guide
To use this project, you will need to have Python and the following libraries installed:
- pandas
- matplotlib
- seaborn
Once you have installed the required libraries, you can run the Jupyter notebook healthcare_analysis.ipynb placed in 'bin' folder to analyze the healthcare data.
License
This project is licensed under the MIT License - see the LICENSE.MD file for details.
Citation
Citation information for this project could be found in CITATION.cff file.
Acknowledgments
Thanks to the following sources for providing the data used in this project:
Contact Information
For any questions or feedback, don't hesitate to get in touch with hematechie@gmail.com. Name: Hemalatha Sekar.
Owner
- Name: HEMALATHA SEKAR
- Login: hemababy
- Kind: user
- Location: Germany
- Website: https://crackchallenges.wordpress.com/
- Repositories: 1
- Profile: https://github.com/hemababy
I am a Master's student specializing in Data Science who is passionate about discovering patterns in data.
Citation (CITATION.cff)
cff-version: 1.2.0 message: Please cite this project as follows: Hemalatha Sekar. (2024). Healthcare Trends Analysis. Retrieved from https://github.com/hemababy/healthcare_trends.git type: software title: Healthcare Trends Analysis authors: - family: sekar given: Hemalatha license: MIT version: 1.0 date-released: 2024-05-13