For an industry that’s always producing amazing tech innovations, the healthcare industry has been lagging when it comes to big data. Big data may be revolutionizing the retail, tech, and other consumer industries, but little has been done to make healthcare more effective or efficient based on the enormous amount of data available. One hurdle to widespread data use in healthcare has to do with the strict controls on sensitive patient data—data that’s protected by law. Most people aren’t too eager to see that data shared, either, even in the service of advancing the quality of healthcare. The good news? That’s changing as people prioritize information over full privacy.
Despite the challenges of getting usable data, some passionate visionaries are determined to make difference in healthcare with big data. Women’s health in particular could get a boost from big data—here are some ways startups and medical researchers are tackling the issue.
Since breast cancer affects women almost exclusively, it’s one of the diseases under the greatest scrutiny using big data analysis. The Breast Cancer Registry at Baystate Medical Center in Massachusetts is just one example of big data working to make cancer treatments more successful. By collecting data from women of all demographics who have breast cancer, researchers are able to isolate patterns based on different factors like age and ethnicity. By recording the effectiveness of the treatments they provide, doctors can gain insights on how best to treat individual women, and make clinical predictions based on historical data.
The Susan G. Komen Foundation is also interested in the benefits big data could provide in the fight against breast cancer. In October of 2015, the Foundation’s Big Data for Breast Cancer (BD4BC) Initiative convened in a think tank in New York to examine the current capabilities of big data and explore how best to leverage them in clinical settings, with the goal of providing better treatment options and driving research in cancer treatment. To further the conversation about how best to proceed, another meeting will take place, this time on the west coast.
Glow, a company that has developed an app to help women track their cycle, is busy mining their database for information on women’s health, while giving users the power to share only the personal information they want to. They are particularly interested in getting more information about women’s fertility, and answering questions about what factors might affect it. So far, the data they have collected shows patterns in when women tend to start their menstrual cycle, and what types of birth control they use most often.
Clue, another app in the menstrual health space, is focused on helping women throughout their lives, and aims to remove the stigma of menstruation. The app is not only used for tracking a woman’s cycle, but using data collected from the user, the app is able to predict when the user is most fertile, helpful for women who want to get pregnant. Ida Tin, the company’s founder, envisions that the app will one day become more personalized, catering to women from their early menstrual cycles through menopause. Users have made some astounding observations through Clue, including a woman who detected an abnormal pregnancy with her data, potentially saving her life.
Early detection is crucial for successful cancer treatment, and ColorGenomics is working to make that process easier using big data. Using genetic testing, they’re looking for patterns in data to help their customers predict whether or not they’re prone to specific types of cancer. Isolating genes has the added benefit of collecting more information about how many people have the genes that predispose them to develop cancer. While the company’s services aren’t currently accessible to everyone (it’s a private genetic testing company and services wouldn’t be covered by insurance, especially those on government programs), it’s a step in the right direction for using data to predict cancer risk. Now that specific genes have been isolated to indicate breast cancer risk, genetic testing and data analysis is a big step forward for women’s health.
Cancer is incredibly difficult to treat in many cases, which is why much of the big data innovations in healthcare focus on cancer research. MD Anderson’s Bioinformatics and Computational Biology department works to analyze mountains of data and gain insights into how cancer might form and behave. This is big data analysis on a molecular level, and researchers believe that it could be the key to developing new cancer therapies.
Getting the Data
So how are these startups getting the data they need for analysis? Simple. They’re just asking for it—and they’re providing value in exchange. Glow has an interface in their app allowing users to input as much (or as little) information as they’re comfortable with, and the data is anonymized for analysis purposes. As the database grows, the company will be able to get better insights on different demographics of women.
Electronic health record systems are becoming much more common in hospitals all over the country, helping doctors manage individual patients’ care more effectively, but that data isn’t readily available to analysts. For now, manual collection is the best choice for startups working with big data in healthcare. Only those willing to offer personal information are providing these companies with the data they need—which doesn’t provide a comprehensive view of women’s health in the United States.