What are some of the challenges with regards to all of this data generation?
1) Volume & Format
The sheer amount of data produced everyday might be a lot, but not all of it is valuable or actionable. In most cases, data needs to be properly cleansed and normalised to reduce noise and extract value. Data sets are not all created equally and they are not all necessarily reliable either. Understanding these data sets and finding patterns and trends requires strong knowledge of both biology and data analytics, and without this double-pronged approach, progress is guaranteed to be limited. Additionally, for many healthcare organisations, companies, and institutions, data is collected in such large volumes that these organisations can no longer store, process, or send data efficiently.
There is also a risk of data overload. Yes, it is nice that there is an option to look at additional health data, but is all of it necessary, and at what point does the volume of data go from being helpful to overwhelming? When it comes to things like consumer DNA testing, there are many people who prefer to know their results and take any action if necessary, but for others it just creates unnecessary anxiety.
Infrastructure is one of the biggest obstacles in this space. Healthcare infrastructure needs a serious makeover and it was needed years ago. According to a recent report by Health Information and Management Systems Society (HIMSS) Analytics, on average, hospitals use 16 distinct EHR platform, leading to major gaps in data interconnection and transmission.
Electronic health records (EHRs) are not particularly interoperable and lead to issues with synthesising old and new information, multiple data formats, increased physician hours, and inefficient workflows among many others. Unlike other industries, healthcare has requirements for reporting and regulatory compliance — the burden of this becomes exacerbated with additional data points. To add to the burden, many healthcare providers have started building new infrastructure but are keeping a lot of their old software, which leads to additional confusion and lack of advancement towards a truly integrated system.
The concern here is that the exponential growth of health data is sharply outpacing any sort of integration efforts — there is a great opportunity here for enhancement of these systems.
Privacy and data protection, especially when it comes to health data, are critical when it comes to patient care. Most consumers have some concern over how their personal health information might be used by tech companies or even by their employers. The progress in digital health has been much faster than accompanying cybersecurity measures, as evidenced by multiple instances of data breaches and hacks over the last couple of years.
Extracting value from volume