In 2015, I led a team that built a data science driven product called Action. Action predicted people who might need care in the near future and helped them understand their benefits and their conditions better. Tens of leading companies in the US have Action now. Many more are in the process of implementing it.
The second data science driven project that I led at Castlight health was to address a seemingly simple problem that is very difficult to solve. This is the problem. How do you find a good doctor? How do you know if that doctor has treated many people for similar conditions before? Has the doctor kept up with advances in medicine. Does the doctor provide quality service? While these sound like simple questions, the answers are not easy to get. Information about quality of health care providers such as doctors are very hard to find. You can find reviews on sites such as Yelp. While those reviews are helpful, they may not provide the necessary information to make an informed decision. For example, you may not get information about the number of times a doctor has performed a procedure. You may not get information about the quality of outcomes. This is compounded by the fact that many doctors work at multiple hospitals and healthcare facilities.
The good news is such information is available from multiple sources and we have been adding such information to providers' profiles in Castlight Health for a long time. The bad news is such information is hard to decipher and verify. The data comes from varied sources in various intervals with varying levels of data quality. This is where data science comes in. Data from multiple sources can be combined and matched with healthcare providers such as physicians, using rules generated based on machine learning models. Data scientists and product managers train the models to match data using a training data set and then apply the model to vast quantities of data.
After spending a few months on this problem, our product and data science teams made the first release recently. We made significant improvements to coverage and accuracy. We will continue to make meaningful improvements every month to help people find a good doctor. It is important to note that there is nothing like clean data. Experienced data scientists and product managers in the data domain know that there is only less dirty data.
I am very pleased with the mission of the second project. I know that when the millions of people who use Castlight Health choose a doctor, there is a higher likelihood that they will pick a better doctor and as a result get a better outcome. When my daughter asks me what I do for a living, I plan to tell her that I help mommies and daddies find a good doctor for their children so that their children can be healthier. I am pretty sure she is going to be impressed.
If you do not have Castlight Health at work, ask you benefits leader. It is a useful product to understand your benefits and make the best of it.
The second data science driven project that I led at Castlight health was to address a seemingly simple problem that is very difficult to solve. This is the problem. How do you find a good doctor? How do you know if that doctor has treated many people for similar conditions before? Has the doctor kept up with advances in medicine. Does the doctor provide quality service? While these sound like simple questions, the answers are not easy to get. Information about quality of health care providers such as doctors are very hard to find. You can find reviews on sites such as Yelp. While those reviews are helpful, they may not provide the necessary information to make an informed decision. For example, you may not get information about the number of times a doctor has performed a procedure. You may not get information about the quality of outcomes. This is compounded by the fact that many doctors work at multiple hospitals and healthcare facilities.
After spending a few months on this problem, our product and data science teams made the first release recently. We made significant improvements to coverage and accuracy. We will continue to make meaningful improvements every month to help people find a good doctor. It is important to note that there is nothing like clean data. Experienced data scientists and product managers in the data domain know that there is only less dirty data.
I am very pleased with the mission of the second project. I know that when the millions of people who use Castlight Health choose a doctor, there is a higher likelihood that they will pick a better doctor and as a result get a better outcome. When my daughter asks me what I do for a living, I plan to tell her that I help mommies and daddies find a good doctor for their children so that their children can be healthier. I am pretty sure she is going to be impressed.
If you do not have Castlight Health at work, ask you benefits leader. It is a useful product to understand your benefits and make the best of it.
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