Today’s healthcare is increasingly data-driven, with advances in computing power, wireless technology, miniaturisation, and AI making connected devices ever-more innovative and effective.
As such, healthcare organisations want to harness the power of data to allow them to improve outcomes, increase efficiency, and reduce costs. The clinicians who work for them are now becoming increasingly skilled in data interpretation, ready to exploit the explosion in data to improve diagnosis and treatment for their patients.
For HealthTechs in particular, the advent of data-driven care presents them with a huge opportunity. Yet many face a real problem with their data which they need to resolve right from the start if they are to be successful. HealthTechs obviously know they must prove the clinical usefulness of their device if they are to gain any initial credibility, but they are sometimes less aware of the challenges of making their data meaningful and useful to systems and professionals. In an increasingly data-dominated world, this is a major block to adoption.
In fact, experience shows most HealthTechs lack the critical ability to integrate their solution into clinical workflows. This challenge of solution integration and data interoperability is one that all HealthTechs need to address much earlier in their evolution.
This eBook will explore the best way to overcome these significant barriers and explain why implementing a data strategy from the outset, rather than considering it as an afterthought, is essential.