One size doesn’t fit all in healthcare. Especially when it comes to patient data. Some people are healthy, others are chronically ill, while others are acutely ill. Some people have full access to healthcare, while others struggle to get care. Being healthy is a priority at our most basic human level, which is why patient data is a critical topic in the health tech space. 

Healthcare records and patient data have historically been kept in files, charts, archives, folders and notes for decades. Now, with an abundance of digital healthcare options – computers, mobile apps, telehealth and other available technology – data is critical to patient outcomes and research. However, most of the data is trapped in documents and silos, which are not connected, and therefore, the entire patient health history is not easily accessible in a comprehensive view.

Artificial intelligence (AI) and machine learning are changing the landscape of accessing data to benefit patients. Computers and software programs can’t give a complete health picture without having accessible data in the right format. Since most of the data (over 80% according to Gartner) is what we call “unstructured data”, it must either be manually keyed into another system or database or digitally transformed using intelligent capture to change it into a structured, usable format. Once it’s in a structured format, practitioners can begin compiling a more comprehensive view of patient data. 

AI technology is even being used to create and enhance software beyond existing patient data. Dr. Poppy Crum, Chief Scientist at Dolby Laboratories, shared some incredible medical and scientific breakthroughs using AI and machine learning technology at a recent conference, showing how different senses can yield better outcomes. For example, new devices that study hearing and voice can find statistical patterns, the tone and create predictions. These devices will know more than we do, based on the algorithms. Through hearing and voice recognition, along with longitudinal data on multiple devices, it can predict disease, psychosis, schizophrenia, diabetes and other relationships through algorithms. This type of technology will provide even more context to patient data as health tech companies continue to innovate.

This sounds great, right? However, with HIPAA and other regulations, patient data is more sensitive than ever. Is it practical to digitize our data with all the risks? In a 2019 Gartner report “Healthcare Provider CIOs: Get Control of Patient Data Across All Partners,” they warn CIOs about getting ahead of expanding data risks. In the next 3 to 5 years, health delivery organization CIOs will continue to wrestle with growing issues surrounding patient health data management, including privacy, integrity, protection and sharing. In fact, they predict that by 2023, 60% of healthcare consumers will have access to and control of their health data using a technology of their own choosing. They contribute these trends to include a rise in digital processes that capture more data, more forms, consumerization and a healthcare ecosystem of digitally connected partners and vendors that create more sources of patient data. Therefore, CIOs must make a concerted effort and strategy to get control of patient data in all its forms and places.

Working with trusted vendors will be critical to this move of unlocking your data. Using innovative, AI and machine learning-based technology will also be important in your quest to find better patient outcomes. There’s no one size in technology either – finding a scalable, flexible solution is key, whether it’s in the cloud, hybrid or on-premises. But with the fast-paced movement of health tech companies that are solving for new apps, mobile and telehealth, consumer experience improvements, interoperability and the other myriad of opportunities to build better patient outcomes, healthcare organizations will be forced to examine and unlock their data. 

For more information on how Ephesoft can help build better patient outcomes by securely unlocking data with AI and machine learning tools, contact us at or visit our healthcare solutions page.