How to turn Healthcare BigData into BigKnowledge in 3 Simple Steps

What even is BigData anymore? I mean the phrase has been over promoted, overpriced and over tweeted.

Yet, I keep using it. You keep using it. We all use it!

A recent, brilliant article by John de Goes declared that ‘Big Data is Dead. What’s next?‘ To me the answer was blindingly obvious because it’s, in many ways, common sense. It harks back to one of my earlier articles where I explored how we define digital health

What’s the purpose of the Quantified Self movement? What’s the purpose of digital technology in healthcare?

To me medicine and healthcare are and always will be about humans. About the covenant of trust and respect that is the Doctor-Patient relationship. Technology can empower both sides to be more transparent, responsible and accountable than ever before.

We need to give ‘BigData’ meaning and that’s exactly the challenge I’m trying to tackle. Without further remonstrations, wish me luck and let’s begin!

1. Data —> Information —> Knowledge

The wanton collection of data is, by itself, one of the most dangerous acts of 21st century technology. It’s awe inspiring and overwhelming at the same time. We collect because we can. Do we know why we’re collecting it? Do we know what it even means? Who’s going to use it? Does it actually change anything?

When I was practicing medicine I remember one of my professors stating the reasonably obvious, ‘It’s not about testing because we can. It’s about doing the right test when it’s needed.’

That statement is as true today as it ever has been. Healthcare professionals deal with mountains of data on a daily basis and they don’t need more volume. They need to collect data that can have impact, that can inform, insight and effect decision making and management. And by the way, that’s the same for patients as well as doctors.

Next time, you start creating an algorithm or platform for collecting data just take a second to think – ‘Will this data turn into information and knowledge?’

2. Start Listening

It’s one thing to guess about what will and won’t be useful but it’s still a guess and not a fact.

You’re hypothesising. What we need to be doing is talking to each other. For one, as a business you’ll end up creating something that actually helps your end-users and as doctor or patient you’ll have a chance to share your concerns about data collection with someone who could actually solve your problems!

Beyond that are the issues of integration and use. How are you going to make something that a doctor or patient can practically use if you have no idea what their daily lives are like? Do you know that in hospitals doctors still wheel around a computer on wheels (C.O.Ws) whilst doing rounds? What about nurses who have to constantly monitor patients on wards. Are you optimising ‘bigdata’ for them too? Not everyone’s carrying a smartphone or an iPad so what then?

When it comes to patients, well, little widgets are great but people have lives! How many USBs are lost in washing machines every year? What happens to skin patches when people have a shower?

These might sound like mundane and boring questions but they’re reality! How can you collect the right data in the most user friendly way possible? Listening helps.

3. Humans not Robots

I urge you. In fact no, I implore and beseech you  if you remember nothing else remember this.

Medicine and healthcare are about humans. It’s about trust and empathy as much as it is about MRI scans, blood tests and surgery. You might be thinking, ‘What’s this go to do with big data?’.

It’s got everything to do with it. As technology gets more sophisticated in its ability to collect data and detect patterns then teams of healthcare professionals who use it will have greater responsibility than ever before to interpret and manage the delivery of this data as information and knowledge for their patients. Patients’ will be empowered to ask more questions and search for answers but when they’re receiving this raw data it might be so new that no-one has the right answers.

Be considerate. Think about how your technology is going to change and, hopefully, enhance the doctor-patient relationship as well as create new anxieties. How can you make this process easier practically and emotionally?

It Ain’t Easy

I’ll be honest. I haven’t said anything that’s going to revolutionise the role of BigData in healthcare. All I wanted to do is give it a reality check and bring a bit of humanity to it. Big Data is going to change the game and that’s inevitable but maybe if we start thinking about Big Knowledge instead from now we can make that positive effect start sooner.

If you enjoyed my article please Share, Retweet & Comment! @Saif_Abed

Dr Saif F Abed
Founding Partner
AbedGraham Healthcare Strategies Ltd
www.abedgraham.com
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The 5 Laws of Innovation Adoption for Health Startups

It should be pretty simple really shouldn’t it? I mean you’ve got a great product, it makes sense, it works, the feedback you’ve received has been great but you’re sitting by your desk perplexed. 

Where are they?

The droves of customers?

Why aren’t they beating a path to my door?

Anyone who’s ever tried to bring their idea to market will have had to deal with the harsh reality of adoption. It’s one thing to hear positive comments about the virtues of your prototype but quite another to have the mass market embrace you. Now this is a subject which is constantly studied in the world of business academia often best exemplified by Geoffrey Moore’s ‘Crossing the Chasm’ (1991) but before that came Roger’s elegant masterpiece ‘The Diffusion of Innovations’ in 1962 and that’s what I want to share with you today. In fact I want to share 5 simple ‘laws’ which I think every startup should be mindful of and use. So without further ado let’s begin!

1. Relative Advantage

I mean this should be the easiest part shouldn’t it? Especially when it comes to digital technology and apps in healthcare. I mean it’s mobile, fast, effective and relatively inexpensive.

Words aren’t good enough though.

In my recent blog discussing venture capital I strongly emphasised getting frontline data to demonstrate the strength of your assertions and I repeat it here. Your mhealth app or device might clearly offer unparalleled advantages compared to the incumbent technologies and systems but perceptions and familiarity are difficult foes to overcome so wherever possible gather evidence to tangibly demonstrate the clinical and cost advantages of your invention.

Quite simply you can’t deny the facts especially when they save money AND lives.

2. Compatibility

One thing that I believe is extremely ironic about digital technology and the language that follows it is that we have an obsession with causing ‘disruption’ and ‘destruction’. Now that’s all well and good and I support it and all other Schumpeterian talk but let’s get real for a second. 

These aren’t the friendliest sounding words. The reality is that your idea and invention needs to be remarkably easy to use and should fit into the workflow and lives of its users be they doctors or patients. Now, peoples’ habits and daily routines might inevitably change especially if your product is effective but that shouldn’t be your opening gambit. Beyond that though, your concept should fit with the thoughts and values of its users and that couldn’t be simpler in healthcare.

We’re here to empower patients to improve their health and to work with doctors to prevent, detect and manage health, wellbeing and disease. Get that message across.

3. Complexity

Or you can call it simplicity. You may love talking about algorithms but not everyone else does. Take your idea and distil it into its fundamental function. What’s the problem that it’s going to solve? Does it make sense? Quite simply is it intuitive? Will a doctor or patient or any other healthcare stakeholder see it and just get it?

With the advent of smartphones we’re all getting far more tech savvy which is a great advantage for would be technology ‘disrupters’ but don’t assume that’s the case for everyone so try and make sure people can either get your product or that it’ll be as straightforward as possible to learn to use.

4. Trialability

Changing age old habits are hard. Hospital wards have run the way they run for such a long time, doctors’ rotas are still managed the same way as they were 20 years ago and we practice medicine using even older methodologies.

Despite, all that you’re standing here in my office telling me I should be doing things differently? Or perhaps I am a busy professional and you’re telling me to spend my hard earned cash to use an app or sensor to share my vitals with my doctor? Hmmm not sure about that…

Now getting a chance to trial a new piece of technology for free won’t necessarily ensure that everyone will use it but at the very least it gives people an opportunity to experiment and provide feedback and at best it can create a viral effect with positive word of mouth spreading and subsequent adoption so just consider it…that’s all I’m saying.

5. Observability

If I can see it working and delivering on its promises then I’m probably going to be pretty satisfied. If it delivers well beyond my expectations then I’ll definitely be satisfied and even start developing loyalty! If the feeling is strong enough then I might just start sharing my experiences and then maybe, just maybe, we might get a viral effect.  What’s even better is if those who aren’t using your product can directly see its’ benefits. Well, I must have some of that then!

Start thinking about your product design and how it demonstrates its effects whether its’ by eliciting feedback or through a graphic display of results or whether it’s through your own work to develop new measures and metrics of effects. The more observable the positive effects then the more incentive to adopt.

A Whirlwind Tour

So that’s a brief synopsis of the infamous Roger’s Five Factors. Rogers seemed to love describing things in 5s but I think this particular set of 5 ‘laws’ as I call them I think are essential for any startup or inventor to include in their strategy from Day 1. Having an idea or invention is great and be passionate about it but adoption is the key to turning ideas into innovations and that means you need to be thinking about the long game.

Questions or Comments? Tweet me @Saif_Abed

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Dr Saif F Abed
Founding Partner 
AbedGraham Healthcare Strategies Ltd
www.abedgraham.com