Health Data Analysts

Various types of data have been collected since the early days of civilization, most commonly via censuses. Archaeologists have translated ancient Egyptian hieroglyphic inscriptions and papyri that detail medical records of patients. These translations provide information on "remedies to treat symptoms of a range of illnesses and physical conditions, although some also discuss the Egyptian notion of the cardiovascular system," according to "The Art of Healing in Ancient Egypt: A Scientific Reappraisal," an article in The Lancet.

In the health care sector, data about patients, health outcomes, and other topics has been collected for many decades. The development of computers in the 1950s and 1960s greatly increased the amount of data that could be gathered and the ways it could be studied. In the 1960s, the Mayo Clinic in Rochester, Minnesota, became one of the first large health systems to use electronic health records. In 2004, the Office of the National Coordinator for Health Information Technology (within the U.S. Department of Health and Human Services) created a plan to transition all paper medical records to electronic health records within the next 10 years. This increased the amount of digital medical data that was available for analysis. In recent decades, advances in computing power, the emergence of artificial intelligence (including machine learning), the use of wearable technology connected to the Internet of Things, and increases in the number and effectiveness of data and predictive analytics tools have created vast collections of medical data that are studied to improve health outcomes, worker performance, and meet other goals. The COVID-19 pandemic further fueled a drive toward the use of medical data to better treat patients, develop vaccines, improve health care services, and obtain a better understanding of the virus. As a result, demand has increased for health data analysts in recent years.