How to make sense of advanced analytics ?

How to use the brainpower of an academic hospital to prevent of becoming obsolete in 10 years

Advanced analytics is the next big thing in healthcare. Large amounts of data in combination with deep learning and artificial intelligence will change the way we perform healthcare. As an university hospital we should be leading the pack and in fact we have a dozen of experiments trying to experiment with advanced analytics to build predictive models, create decision support tools, etc. But, we are only doing this at the individual level. And the thing is, adv. analytics will not only change the way we perform care in the process as it is right now, it will change those processes and change the whole system. Doing experiments on the individual, disease specific level does not get us in a leading position. And it will not prevent us of becoming obsolete in 10 years !

To prevent this we should start to innovate at the organizational level. And although innovation is in the genes of the organization, innovation as an organization is not. So the question is: ‘how can we start making sense of advanced analytics as an organization ?’

I would love to receive your thoughts on how to deal with this problem.


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Participant comments on How to make sense of advanced analytics ?

  1. This is a very difficult but also a very relevant question
    To me it comes down to anticipating disruption of our healthcare model in academia. The best way to achieve that is to be the ones in charge of that disruption!
    However the endeavor here is so large that it will only work if you implement a strategic retreat that will allow the key stakeholders of the institution to understand what is at stake and the need for them to free resources for this program

  2. Our early approach has been to begin the process of creating an enterprise data repository and put in place data management standards. Since we have grown through acquisition, our heath care system has interested a tremendous number of disparate data management methodologies. Having a standard approach to data collection and management has been an important first step.

    Our next step was to put usable data into the hands of more clinicians and managers. We use a data visualization tool, Tableau ( [I have nothing to disclose], that allows end users to navigate large data sets in a way that makes them easier to digest. By creating more dashboards and visualization tools we are starting to create a culture that relies on data for decision making instead of anecdote.

  3. Such a huge project has to be kicked off by CEO (as a sponsor) giving it startegic weight.
    As a manager you can prepare standards as measuretwice 🙂 outlined above, having right data is essential as well as having data right, to get meaninful results.
    Having the reason – Why one should start the project? … is a must! There should be really something urgent or big enough ideally on the clinical level to give the people down the line the reason to be involved / stay overtime and experiment.

    Early adoption has many pro’s, first movers might have considerable advantage but you need to secure sufficient resources (financial and mental) to deal with such “academic” innovations.
    There are also some disadvantages as the results might not bring expected value for your organization… i.e. attacking the project that one is playing with “fancy toys” with huge financial budgets.

    I don’t believe that you can move the organization forward (adopting such technologies) by TOP DOWN approach. This is like a nation, it is based on community values, on families and their leaders on every level. It all needs to start there, so before you move your organization forward you have to ignite the individuals, make them recognise the potential of future benefits for their daily work.

    As a example there is a link to the nice overview of the disruptive technologies and their hype cycle:

    I trully belive that it won’t take more than 10 years to see practical examples of implementation in Health Care, which is going to change the system significantly bringing the value to all stakeholders.

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