This article will walk you through how to analyze and gain insights from a typical healthcare patient dataset.
Gain insights from patient records, treatment plans, costs, and outcomes. Vast amounts of healthcare data, while complex and often unwieldy, is a treasure trove of information that can provide valuable insights to improve care delivery and patient outcomes. The dataset can be accessed here. Below is a preview of the dataset:
The first step to getting started in Julius is to upload your data. The AI can read data in multiple formats, including CSV, Excel, and Google Sheets, among others. Once your data is uploaded, Julius will automatically assess and understand the nature of the data.
Once your data is successfully imported, you can start your conversation with Julius.
For instance, we want to know the number of patients by department, we can simply ask Julius:
Prompt: “Plot the number of patients by department."
Next, we want to take a deeper look at the Surgery department. Let's ask Julius:
Prompt: “Inside the surgery department, what is the breakdown by age group and average stay?”
Now, let's say we're interested in understanding the length of stay for younger patients who undergo surgery at the hospital. We ask:
Prompt: “For patients under the age of 50 who get a surgery, what is the breakdown of how long they stay in the hospital?”
Finally, if we want to look at the gynecology patients and understand the total average time spent in the hospital by them, we ask the AI:
Prompt: 'What is the average time spent by patients in the gynecology department?”
Julius's ability to understand natural language commands is a game-changer. It makes complex data analytics accessible to anyone, eliminating the need for advanced technical knowledge or expertise.