How Automation Can Help with Healthcare's "Messy" Data Problem

Efficient data processing and data sharing are essential functions across healthcare--from patient care, clinical research, and health services planning to billing and government reporting for funding and research. But most of the data that the industry is processing is human-generated, meaning it's messy and riddled with errors, and often manually inputted from Excel spreadsheets into various disparate platforms and technology systems. In some cases, our healthcare system is running on infrastructure that is over 20 years old. There are many instances across the system that are overly burdensome from an administrative standpoint, which pulls crucial resources from patients. For example, a single national U.S. insurer that I worked with had more than 500 employees manually keying in provider and facility data--information needed by its members to find doctors covered by their insurance.