Healthcare delivery around the globe is undergoing radical transformation. Part of this transformation is out of necessity, because in many ways healthcare has become unsafe and unsustainable. Part of this transformation, however, is a result of how technology has impacted healthcare delivery, providing better and more intelligent medical devices and information systems to aid in diagnosis, clinical decision-making, and overall management and administration. The challenge facing healthcare organizations is to leverage advances in both clinical and information technology to improve quality and performance while containing costs.
Data, in particular, can help organizations gain deeper insight into their organization’s performance than was ever possible before. Healthcare organizations face the very real risk of data overload, however, as nearly every aspect of healthcare becomes in some way computerized and “data-generating”. For example, Radio Frequency Identification (RFID) devices can report the location of every patient, staff member, and equipment within a facility; sampled every second, this location information adds up quickly. Also, portable diagnostic equipment can now capture and store important patient clinical data such as vital signs, and those with “labs-on-a-chip” perform point-of-care testing for many blood-detectable diseases, are also now generating enormous volumes of data. The current term for these vast amounts of data being generated is “big data”. Healthcare information technology, however, is really in its infancy – it is not unimaginable that we will run out of superlatives to describe the volumes of data being generated and stored once healthcare information technology becomes ubiquitous across all facets of healthcare in all organizations.
Healthcare organizations must find a way to harness this data and use it in a way that can improve clinical and organizational performance. If they do not, not only will they risk having a poor return on investment for such technologies, but worse, failure to adapt and adopt new ways of leveraging data may ultimately result in failure as an organization.
Data analytics is touted as the solution for gaining knowledge, insight, and actionable information from these vast data repositories. Indeed, analytics consists of the tools and techniques to explore, analyze, and extract value from healthcare data. And without analytics, such insight would be impossible. But insight without action does not lead to change – and the data overload that is now becoming quite possible can risk impeding, not improving, the decision-making ability of healthcare leaders, managers, and quality improvement teams.
In my experience, the true potential of analytics is realized only when they are combined with, and integrated into, a rigorous, structured quality improvement framework. This powerful combination helps to ensure that a robust feedback loop exists such that analytics help to maintain QI and management teams’ focus on achieving the quality and business goals of an organization, but also that analytics can be used to explore the available data an possibly identify new opportunities for improvement or suggest innovative ways to address old challenges. When a healthcare organization can use analytics to focus improvement efforts on existing goals and use analytics to identify new opportunities, healthcare transformation becomes truly possible.
Note: This is a sample from my upcoming book, “Healthcare Analytics for Quality and Performance Improvement“, to be published by Wiley later in 2013. To receive updates about the book and to receive a purchase discount code when available, please sign-up for email-updates on the right side-bar.
