Healthcare’s analytics market is flourishing and is expected to be worth upwards of $50 billion in half a decade. This explosion couldn’t be better timed, as healthcare organizations need to harness every available resource to improve patient care experience, reduce the cost of healthcare, and improve the overall health of populations.
As emerging technologies continue to mature and new data sources are explored, how can they be effectively united to benefit the industry? Let’s explore four distinct ways healthcare decision-makers should be looking to use analytics.
A Holistic View of the Patient
The healthcare industry has made it a goal to achieve a holistic view of patients and, thanks to artificial intelligence and better data, this goal could soon be met. Data has often held back analytics and artificial intelligence, which is why providers are working to link patient data across disparate sources. Having a single, comprehensive source for patient data makes it much easier to improve healthcare for patients.
Another step toward achieving a 360-degree view of patients is in using technology to analyze messages, images, and videos of patients. Since healthcare doesn’t always happen in a face to face setting, it’s vital that technology can document and analyze this information. Technology is only effective if it has good data, after all.
A Strong Foundation
Part of the issue with healthcare data has been that organizations focus on single sources, like specific care encounters, instead of a patient’s entire history. In order to build the foundation necessary for better healthcare analytics, health systems must work to create longitudinal records for patients. These records cannot be limited to one site or episode of care; they must cover the full spectrum of a patient’s care.
Once longitudinal records become the norm, hospitals and health systems will be able to use that data for advanced analytics. These analytics can help eliminate high costs or poor outcomes by pinpointing a caregiver or site of care’s inefficiencies. This level of information can help analytics be predictive – as they should be – instead of reactive or simply descriptive. The result will be tangible and sustainable improvements to healthcare quality.
New Tech and More Data
If health systems want to work with more data, they must employ technologies that can effectively handle the workload. The industry is already seeing a merger of high performance computing and artificial intelligence due to the complexity of data sets.
Another technological shift the healthcare industry must prepare for is the emergence of 5G. There’s already an increasing trend of care being delivered outside the four walls of the hospital, and 5G is only going to accelerate it. With new services potentially being offered to patients from the comfort of their homes, there will be more data to analyze and analytics strategies will have to incorporate said data. Though 5G isn’t going to be widely used for some time, it’s on the horizon and the industry must be ready for it.
Structure is Important
As important as next-generation analytics are for hospitals and health systems, structure is the key to success. Jumping into analytics too early, before data acquisition is complete, will only create problems. The process itself is dull, but it’s imperative to identify potential data sources – EHRs, claims, billing files – in order to have a holistic view of care. If the data isn’t all there or isn’t consistent, it will be impossible to improve performance.
Instead of wasting energy by moving forward with incomplete data, create a uniform dataset that includes everything necessary for the job at hand. As analytics and their corresponding technologies continue to advance, hospitals and health systems will have to make significant financial investments. However, the ROI on these investments should prove to be even more significant.