What Is Data Visualization?
Data visualization is a principle used to understand a large group of data by humans through the use of graphs and another medium. It is a way to aware the people of the significance of certain data which cannot be understood in raw form. It gives you an insight by cutting down big data. Healthcare industry doesn’t usually understand big data hence the use of data visualization is prioritized.
1. Identify the Project
You need to determine the center point of which data will be collected and visualized. Many organizations are after ambitious projects that has steady momentum and low risk of failing. Mostly short term projects that are under 3 months are the best for consideration. Make sure that the project has some stability and success rate of finding reliable and useful data. The projects can include a wide range of topics about health.
2. Find the Sources for the Data
The current data that is with you will act as the base for more data to come. You need to find the sources of the data and add them to your data visualization chart. This is the most important part of the data fetching process. Keep a record of everything from the data owner to the storage location.
3. Create the Model
After the fetching of data, it is now time to put it under a model for presentation. Brainstorming sessions with the stakeholders is crucial to create a prototype of your data to visualize it. Once you have conducted the interviews, you will see the different graphical representations which may look very in contrast to each other. These different versions of the data can be refined by filtering out the targeted audience and the authenticity of the delivery method. Once the data is refined, they can be put into actual graphical representation in data visualization software.
4. Developing Data Visualization
Preparing the data visualization may require some transformation in the original data to be used. Once the data is prepared, more than half of the development is completed. Mostly the other stuff is done largely through tools and software. It’s up to you what tools you are using. It is recommended to use one that you are familiar with. You can then refine and configure the data even more so that it meets the requirements of the stakeholders.
5. Deployment
The project is then needed to be deployed but not without testing and minor changes. Refreshing live data and other features that you have promised must work fine. Run a beta version first for end users to get familiar with. Once the feedback is positive and the project is accepted. Deploy it for public use. Maintain the system accordingly and be open to feedback.
Advantages of Data Visualization in Healthcare
- It improves the empowerment that is gained through data and promotes easy decision making.
- It makes the staff and executives aware of the live data changes.
- Alerts about the changes and improve flexibility to adjust according to the rising changes gained through insights.
Furthermore, if you need a Mac DICOM viewer for accessing medical data, it’s easy to find it. Search the term ‘Mac DICOM viewer’ or “PACS vs DICOM”. You can get some free and paid options.
