Data and Analytics in healthcare… The revolution is coming.

Technology is sitting right at the heart of the healthcare efficiency drive and it’s easy to see why.

Data-sharing and analytics, collaboration and digital practices will be the driving force behind delivering healthcare services predictively.

Ahead of Australian Healthcare Week 2014, I took a look at some of the biggest emerging areas where technology is driving efficiency to find out what’s on the horizon.

There’s huge potential for information to help bridge the steps towards improving patient safety and quality of care.

To gain an insight on some of the key developments in Big Data and analytics, I caught up with two people on the forefront of driving the change Michael Draheim, Chief Information Officer at Metro Health South and Sarah Dods, Health Services Research Leader at CSIRO.

What are the key areas where data and analytics are impacting efficiency?

Sarah Dods: A lot of what we do in health at the moment is on paper. You can’t do analytics without data and we don’t have big data in health at the moment, in terms of the healthcare system and how it’s delivered, those data fits are only just starting to appear.

We see three efficiency gains that are likely to happen through this process; one is prevention, if you’ve got decision support, crosschecks based on data and information that’s already in the system, there’s the opportunity to prepare and prevent things from happening.

Secondly, using data and analytics operationally, in terms of people,  understanding how the business itself runs and gaining quality assurance,  we see patient flow as being a huge opportunity in that space and one that we’re very interested in.

Finally, digital health delivery, which is another way of talking about telehealth, it’s acknowledging the data that’s collected, telehealth is not videoconferencing. There’s so much possibility because when you do things online, you’re creating data, and you can create data about the information that was shared and use it later on.

Michael Draheim: Service efficiency, service planning, meeting KPIs, predictive analytics and data modelling are a few areas that stand out as opportunities to help us adjust our existing service models to support future health care service delivery.

The richness of the data that we have will help us to understand more about our patients and services which in turn will give clinicians the right information to support the prevention and prediction of disease and treatment options. The impact of this is significant benefits on both social and welfare outcomes along with opportunities for the vendor market to have tools that support this approach.

Where do you see the biggest barriers to growth?

Sarah Dods: A lot of the things that need to be changed to improve efficiency aren’t actually technology related,  but what big data in analytics can do is point you to the problem areas and demonstrate the improvements in flow on to the rest of the system if it was fixed, data is evidence for making change.

There are certainly some funding pressures in  both the primary and the acute healthcare systems, the fact that our primary care system is a straight fee for service regardless of outcome basis, I’m not sure it’s sustainable. But that is a very disruptive change to the way the Australian health system is run, if that ever happens.

Michael Draheim: Historically, we’ve got a whole range of systems that are very disparate, built on data structures that aren’t interoperable and often duplicate the data. It’s difficult to get data out of those old fields as they were mostly free text. You may have a font of knowledge but you can’t extract it without a significant amount of cleansing. We’re now looking at better relational databases and more structure. The big advantage of that is real time categorised information flow. The challenge is dealing with our legacy and the cost of replacing that. There’s also significant organisational change involved.

You also have balance the technology, you don’t want to overwhelm people with thousands of alerts which make their life really difficult. For preventative health, it’s adding those fail safes, but not making too much more work. It’s a fine balance.

Have you any examples of results where you’ve seen technology directly impact healthcare efficiency?

Sarah Dods: One is in terms of cancer reporting where the cancer information that’s currently reported across Australia is a manual process, it’s somewhere between two and five years out of date depending on where you look. When a cancer occurs, a piece of paper gets sent to the cancer authority, there’s about a three year backlog, and somebody then eventually manually enters it into a database. We’ve got some research that we’ve been doing working with a couple of the state cancer agencies about automating that processing of the reporting data, and it’s now getting to the point where the research certainly indicates that there’s potential to do that real-time.

That’s an example where people making policy decisions or looking for unexplained outbreaks of cancer, or carrying out research will have access to be able to make an up-to-date data, it’s a huge advantage. You can then start to look at forecasting.

The second example is around patient flow, we’ve been working with the Gold Coast Hospital for a few years now, and that started out working with their emergency department about predicting who was going to turn up, the question was, can you predict who is going to turn up in an emergency department? We found that using the hospital’s own historic data we can predict with about 90% accuracy in any four hour block who’s going to turn up, what the triage categories are going to be, what the specialist categories are going to be, and how many of those people are going to be admitted.

Michael Draheim: We see significant results where we’ve digitalised existing practices. There’s one example where we’ve saved (from a workforce point of view) about $5 million for a couple of hundred thousand dollar investment – over 18 months, by digitalising a process.

We’ve also put in voice recognition badge software which has allowed clinicians to have more time for patient care – there are direct things that have improved the overall experience.

You can’t measure everything but we’re building a benefit delivery framework into all our projects post go live. We make value estimations and then we measure against that to see how we’re tracking.

What’s next for big data, how do you see healthcare of the future?

Sarah Dods: I’m actually going to be releasing a report on the digital healthcare system of the future at the Healthcare Efficiency Through Technology conference.

I’ve been leading the work that we’re doing at CSIRO around the sustainability of the Australian Healthcare system, it’s about providing evidence for innovation, improving access to services, improving efficiency and improving the quality of care that patients get through using digital tools.

We’re going to be talking about patient flow and information flow and information sharing.

Michael Draheim: It’s about more improving access and the ability to collect, report, read and analyse data on the run. We’ll be taking real time data which will often predict what’s likely to happen and provide this information to clinicians at the point of care to support their decision making. The key is to support the human elements of the way our workforce deliver services with quality real time data –  the challenge in the future is that we’ll have more information, it’s important to make sure this is provided in a way that adds to the quality our services provided by our staff.

Healthcare Efficiency through Technology provides the ideal forum to hear from facilities who have implemented technologies to improve patient care and realise operational benefits. Don’t re-invent the wheel – network, benchmark, learn and succeed.

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