I recently joined industry colleagues in exploring the changing space of analytics in healthcare during the webinar, Data Liberation & Actionable Insights with the National Institutes of Health Informatics (NIHI). In my previous blog we explored the shift towards the citizen data analyst, and now I will explore the role consumers can play in their own data analytics.

Despite a wonderful blitz of technology enablement for analytics over the past few years, many healthcare leaders continue to find themselves trying to answer questions without having a firm grasp on the underlying data required to support decisions. This is true at both the public policy development level and at the health delivery, patient encounter decision support level.

I have led several technical teams in creating masterful data warehousing mountains, holding lots of big data, which mimicked Fort Knox in having a wealth of data, well concealed behind tight security, accessible by a select few data wizards. Yet, we must now shift towards developing systems that allow not only healthcare leaders to derive insights, but the consumer as well.

In the webinar, I highlighted to participants the website called Patients Like Me (PLM). If you have not yet checked it out, I recommend doing so. PLM is an analytics platform that is fuelled by publicly contributed personal health information.  I first joined from curiosity, posted a few observations about my journey through life as a person with hearing difficulties. Today, PLM has over 500,000 contributors with range of over 2,700 conditions and one simple mission: to put patients first. Jamie Haywood as co-founder of PLM, stated that "We started with the assumption that patients had knowledge we needed, rather than we had knowledge they needed. We didn't have the answers, but patients had the insights that could help us collectively find them." PLM is a remarkable example of putting data to work at the hands of citizen data analysts who want to make a difference in the world.   

It’s not solely independent organisations that see the benefit of this shift. The U.S. Centres for Medicare & Medicaid (CMS) and the Office of the National Coordinator for Health IT regulatory requirements, specifically Stage 3 meaningful use program, has identified January, 2018 as the date requirement for health providers to give consumers direct connectivity to their healthcare data using application program interfaces. Digital health emphasis in Canada will echo U.S. efforts.   

I could spend the remainder of this article describing for you the complexity of health data and analytics, but I would rather raise a call to action for each of us to gain personal experience in analytics. 

As a colleague of mine who is a national healthcare analytics leader described to me, analytics can be as straightforward as a three-step process for realising real benefits without waiting years for results:

  1. Instead of focusing on building a data mountain, start by framing the question or outcome or business problem that is most pressing to you;

  2. Explore and discover and learn with the data that is available within your reach, working with tools that could be a simple spreadsheet, a web site with visual dash-boarding, or an embedded machine learning model that has been prepared by others;

  3. Capture and record useful knowledge from step two that yields information on the question, outcome or business problem from step one. AND, with your new knowledge from step two, identify some gaps in your data set, use your acquired knowledge to collect, expand data and rewind to step one. Repeat this three-step process.

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