By Robbie Hughes
Big data, analytics and other forms of ‘using a database for stuff that databases are good for’ is a hugely popular theme right now in healthcare, and in industry more broadly, but what does it all actually do?
It’s easy to jump on the latest bandwagon, but big data is actually a highly specialised data science and requires not only highly trained operators to get the best out of it, but a considerable degree of thought to be put in to actually determine the right questions to ask.
Many of our customers have, for some time, had data warehouses where they essentially ‘extract’ the data from their operational systems, ‘transform’ it into simpler forms that analysts can work with, and then ‘load’ it into a separate database which is better suited to the kinds of questions that people might ask. This ‘ETL’ process is usually batched and run overnight and then all the data is consolidated into a single picture which a highly skilled analyst can then work, some weeks or months after the insight might have actually been useful for the operations team.
Our view on this stuff is somewhat different. Learning why bad things happen is a helpful academic exercise, but it’s the implementation of the behaviour change to prevent it reoccurring that is the real trick, ideally coupled with some sort of solution that will prevent it from happening again.
Having worked in this industry now for 10 years, the single biggest challenge we’ve identified is not getting access to the data, or in fact working with clinicians to identify what good looks like, but in fact operationalising that best practice and scaling it.
For us therefore, access to big data is only one part of the problem. In a value based care model, where providers are paid a fixed fee for delivering care, the data to drive this will be useful, but the ability to operationalise the learnings from this data will be critical. Ideas are cheap, execution is everything…to coin a phrase.
In a similar vein, there is a lot of noise being made about health apps, telemedicine, wearable technology, bio-implants etc. and how these might be assimilated as useful tools for population analytics. The challenge, however, is not necessarily the decisions we take with the data, but how we go about the decision-making process in a consistent way in order to help patients earlier in their journey.
To that end, release updates coming to Care Pathway Manager later this winter, our focus has been on providing our customers with the tools, to not only analyse what happens to their patients, but actually to have the system intervene and alert providers to behaviour that breaches SLAs or falls off the course of best practice.
In order to be able to operationalise analytics you need to integrate clinical, financial and operational data. Our analytics application provides near real-time data insight across your organisation and SLAs, timers and workflows that allow you to precisely metric your internal delivery pipeline – making sure that the right action is taken by the right people at the right time. As we look to the new year, we’ll be supplementing that with beautiful new portals and Apps, making it easy to include the patient and referrer in these workflows. This will mean not only that your key customers are better engaged and more loyal, but the quality of your information will go up as data flows into your system from these key stakeholders.
It’s going to be a fun winter and we look forward to showing you how all of these exciting features can be put to work in your business.