20,000 sand grains. 33 rocks. 18.5 umbrellas.

This is data, and it’s meaningless. Does it describe a beach? Maybe. But there isn’t enough of a story here for anyone to even care what it describes.

When presented in isolation, data communicates nothing of actionable value. This has become a significant problem in healthcare. We capture more health data than ever, yet not much has improved in the way we make meaning of it and act on it.

For all the hype surrounding big data and the glamour of data-centric cultures, the truth is that the story is what’s important. Data is simply a useful tool to help tell that story. In the case of your health data, the important question is what story does this tell me about my health? Like any good story, the state of your health at this very moment has a setting, a plot, an interesting backstory, and all sorts of paths you can take which will have different conclusions.

The core tool that you can use to tell a story with your data is context. Here are five important elements of context that you can apply to any health data to make it meaningful and actionable.


1. Range: Typically, there are data guidelines for any specific health topic. Consider a cholesterol level of 210, for example. Finding the established range is the first step in making this data point useful for you.

2. Trend: Examining the same measure repeatedly over time is crucial to understanding the meaning of health data because it shows where you’ve been. Cholesterol at 210 today has a much different meaning if it was 240 a year ago vs. 180 a year ago.

3. Related Data: Data is always related to other data. Sometimes those relationships are causal, but even when they are not these relationships are important to understand. Since cholesterol level is often used to measure risks for heart disease, related data will also likely include weight, blood pressure, medications, diet, and exercise. When examining the trend of cholesterol against the trend of these related measures, correlations may appear that can be further explored with your doctor. For example, a drop from 240 to 210 over the past year might coincide with the fact that you are currently taking a cholesterol-lowering medication. But it might also correlate with greater levels of exercise and developing a leaner body.

4. Risks: So what’s the big deal? We don’t worry about high cholesterol simply because it’s out of the normal range. We worry about prolonged high cholesterol because it greatly increases the risk of heart attack. You can know that a value is out of range, but you must know its implications to understand its clinical significance.

5. Remedies: If there is a desire for improvement, what are the options? Knowing the treatment options enables you to choose the best course of action based on your understanding of the data, lifestyle preferences, benefits, and risk. For instance, high cholesterol can be alleviated with regular exercise and healthy eating or may require medications for a more chronic or severe case.

Using these elements of context will empower you to work with you doctors and family to understand and act competently on your data. Whether you are fighting a health care battle or are looking to optimize your fitness, we encourage you to use these five data context tools to tell your story and make empowered choices.