Who survives the operating room?

Who needs surgery?

The risk of needing surgery varies significantly with age. In early childhood, surgeries are rare and include tonsillectomies and appendectomies. In middle age, gallbladder removal and joint repairs become prevalent. Elderly patients often need cardiac or cancer-related surgeries.

Sex also plays a role in surgical needs. Women may require gynecological procedures, while men face higher rates of certain cardiovascular surgeries.

We hope this tool will help you understand the likelihood of needing surgery at your particular age, the type of surgery you might need, and the potential risks associated with the surgery. If you know what type of surgery you already need, you can see how likely that surgery is to be needed at your age.

Exploring specific surgical procedures

Every surgical procedure has its own unique profile of risk factors, resource requirements, and outcomes. The Surgery Explorer lets you dive deep into individual procedure types from the VitalDB dataset.

Start by selecting a specific procedure from the dropdown menu. You can search for procedures by name to quickly find the ones you're interested in. The dataset includes hundreds of different surgical procedures across various specialties.

Once you select a procedure, the dashboard will update to show a comprehensive profile of that specific surgery type, revealing demographic patterns, operative details, resource utilization, and outcomes specific to that procedure.

This will help inform you about the unique characteristics of each procedure type, which will be useful for planning and for understanding what you can expect from the surgery.

Exploring multiple dimensions: surgery duration vs. BMI

The following section involves a more complex visualization that encodes multiple dimensions simultaneously: X-axis, Y-axis, color, and point size. Although you cannot alter the dimensions now (this is to prevent issues with overwhelming you with too many options), at the end of the section you will be able to do so yourself. However, you are free to filter by surgery or by mortality result.

Here, there's an interesting relationship between a patient's BMI and how long their surgery takes. Although the distribution of BMI here is relatively uniform, we can see that the abnormally long surgeries tend to be associated with lower BMIs, and that these surgeries are more likely to be of a higher ASA score (i.e. higher-risk).

Color indicates ASA score, a measure of a patient's physical status before surgery. Notice how higher ASA scores (shown in darker colors) tend to cluster in certain regions, suggesting relationships between physical condition, BMI, and surgical complexity.

Exploring multiple dimensions: operation time vs. ICU stay duration

This visualization uses operation time as the X-axis and ICU stay duration as the Y-axis. While there is no correlation between the two, it is helpful in seeing trends within the color and size encodings of this visualization. We can see that longer ICU stays are significantly rarer, and those stays often have high ASA scores and are more likely to result in mortality. Surprisingly, patients with the longest surgeries often have low ASA scores and low ICU stay durations.

The size of each circle represents blood loss during surgery. In general, morality cases more often have abnormally high blood loss, but this is not always the case. In general, lower ASA scores have lower blood loss and typically have little-to-no ICU stay duration.

Exploring multiple dimensions: your turn!

Now it's your turn to explore! Using the controls on the left, select different dimensions for the X and Y axes to discover new patterns in surgical outcomes.

You can investigate relationships between BMI, blood loss, ICU days, and surgery duration. Try different combinations to reveal insights that we haven't shown you yet.

Add even more dimensions by using color and size to encode additional variables. For example, color points by department to see specialty-specific patterns, or size points by ICU days to highlight high-resource cases.