97 Things About Ethics Everyone in Data Science Should Know

Chapter 38. Securing Your Data Against Breaches Will Help Us Improve Health Care

Fred Nugen

Data Science Instructor, UC Berkeley

When you go to a new health care clinic in the United States, doctors and nurses pull up your patient record based on your name and birthdate. Except sometimes it’s not your chart they pull up. This is not only a health care problem; it’s also a data science problem.

Two things (at least) contribute to this error: a lack of consistent and uniform patient records and public mistrust in protection of data. Both of them hold health care back from data science revolutions.

When patient records are transferred from one major hospital system to another, patient data passes through health information exchanges. The current rate of correctly matching patients between systems is estimated to be around 30%.¹ With considerable effort from data scientists put into data cleaning and better algorithms, we could potentially match as often as 95%. This is an important opportunity for data science to improve health care! It’s called “master data management” or “data governance,” and while we have a long way to go, we’re getting better.

The health care industry works hard to prevent misidentification. It is standard practice to use at least two patient identifiers, such as name and birthdate.² Unfortunately, name and birthdate do not uniquely identify a patient; a third ...