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Role of data analytics in service planning

Can we harness big data/ open data platforms to change EOL experience?

Photo of Pearl Sequeira
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The Capital Area Food Bank (CAFB) in Washington DC, works with over 400 local community groups, to feed the hungry. Like most food banks, CAFB faces challenges in predicting where help is needed. Planning for food is a complex process, especially when you have to consider nutritional and cultural-relevancy concerns.

CAFB works with APT, a company that specializes in predictive analytics, to understand what the actual supply and demand curves looked like. Consequently, the clients can receive more nutritious meal options, and achieve better health outcomes. 

Big Data/Open Data platforms are starting to revolutionize service offerings in many domains of health. What about dying/end of life?


References:
- Guardian Article: "Open data feeds the poor 20,000 tonnes of food per year in Washington DC", May 2016 

- McKinsey Article: "The big-data revolution in US health care: Accelerating value and innovation", April 2013

 - McKinsey Article: "Big data: The next frontier for innovation, competition, and productivity", May 2011

- Sas White Paper: "Big Data in Big Companies", May 2013

What is a provocation or insight that might inspire others during this challenge?

1) How might Open Data/ Big Data help in understanding what services/products are utilized? What are the data sources? What barriers exist to access these databases?
2) How can healthcare & community care providers use predictive analytics to develop better services/experiences for EOL? Who are the players?
3) What policies and enablers are required to integrate analytics into service delivery?

This inspired (1)

Learning from analogy

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Photo of Marije Haas

Pearl Sequeira Super interesting questions! Do you have any answers? Or ideas on how big data could be used for such personal experiences?

Photo of Pearl Sequeira

Marije de Haas -  I am not inclined to provide answers, but rather will share my thoughts  on how big data/open data can be used.  

Data gives us the opportunity to understand patterns. The value of big data, is the ability to analyze diverse data sources and provide a more holistic picture of the problem at hand. Juxtapose this with qualitative insights - ie stories and wisdom from front-line service delivery, patients, families, legal services, financial advisors etc, and I am confident that we will see opportunities to re-position the problem we are solving, and by that very stroke, redesign services/products.

The problem is that data exists in different databases, held by different organizations and sectors, in various formats, not easily accessible - may be they are expensive or provide interoperability challenges to organizations. (I recently worked on a civic innovation hackathon project, and can speak to some of the issues.) This is a huge public policy and governance piece, and governments are vital stakeholders here. Without this buy-in, I don't think a lot of progress can be made. On related note, progressive governments recognize this issue, and are reaching out to citizens and businesses to tackle these issues. 

A key component of course to making all of this work, is patient-access to electronic medical records. This would be a central point to collect and share data across patients & physicians. I know of some physicians who tackle poverty in their clinical practice, and want community demographics to be mentioned in medical records. Big data can play a huge role here to map out system inequities (eg access to grocery stores, public transport and financial services), and create real advocates for policy changes.

Finally, I would argue that death is not the only personal experience in our lives. In my opinion, so is  maternal and infant care, transportation,  and education. I have started seeing governments and education providers post job opportunities for folks with data analytics capabilities. While this challenge is dedicated to end-of-life, I would also look at initiatives in the above mentioned domains, that could be applicable for this discussion. 

Marije de Haas - I am interested in hearing your thoughts on how big data can be used for this EOL and other personal & complex challenges?

Photo of Marije Haas

Dear Pearl Sequeira , thanks for your response. I understand the problems with data not being shared or sharable. I know that recently all glaciologists around the world shared their data and came to some shocking conclusions. The glacier they were individually studying could not have possibly informed about the global state of glaciers. But I am veering off.

If we imagine that all data would be connected and accessible, then it is really important that we ask the right questions of this data. For big data to reveal interesting or useful patterns it does require to be collected in a certain way, and we need to be asking the right questions to reveal the useful patterns. What sometimes worries me with big data, is that it may reveal a problem/solution that is not actually that helpful. For example, in the case of End Of Life Experiences, it could reveal something like "people want to die at home, but most are dying in hospitals". This we could fix, right? Offering more care at home. But I think here the underlying idea is, with wanting to die at home, is that we may want to die healthy. This one would be harder to fix... Do you see the problem? It could be the classic case of "if we asked people what they wanted they would have said faster horses" (debatably Henry Ford), thus having to ask the right questions to get the useful data.

I am interested in what kind of questions we would ask, if, in an ideal world, we would have access to this data. Within the inspiration offered here I think we can detect a lot of good questions already to do with being in control of your own death, offering a more informed experience before and after dying, a need for support, control, legacy. I wonder what other data sets would be useful to connect to this? Religion, political convictions, previous experiences...? I am sure I am only starting to see the tip of what is potentially useful here. Really interesting!

Pearl Sequeira with your extensive knowledge in the field, please share what kind of demographic you would look at or investigate?

Thanks for opening up this train of thought!

Photo of Pearl Sequeira

Hi Marije de Haas - Thanks for your response. Off the bat, I am not an expert in data analytics or end-of-life. I just started swimming in the civic tech space, and have tonnes to learn! :) 

I really love the example you share re: glaciologists. This reminds me of President Obama's final State of the Union speech, in which he talks about a 'moonshot' approach to cancer. The analogy of a moonshot has stirred a lot of debate (i.e. moon exploration and cancer are not the same problem, etc). However, I think the real value in the 'moonshot' approach, is the opportunity to break down barriers that currently exist to collaborate across breadth and scale.  I hear more about the science barriers with the moonshot, but less about the patient engagement. The latter needs more emphasis, else we will not have made any progress from Nixon's War Against Cancer.
In understanding EOL, may be we start where silo-busting activity has federal, philanthropic and civic engagement, and has infrastructure in place. I suggest cut across 2 domains - cancer and poverty. For most governments, these are big issues, and we already know that marginalized individuals suffer more unnecessarily and also are expensive to treat. For example, Acumen just launched its Acumen America initiative to tackle poverty in the US, with an amazing healthcare partner, the Robert Woods Foundation. http://www.csrwire.com/press_releases/38961-Acumen-Launches-Acumen-America-to-Tackle-Poverty-in-the-United-States-in-Partnership-with-the-Robert-Wood-Johnson-Foundation-Barclays-and-The-Hitachi-Foundation

With respects to challenges of big data - you are right in questioning the validity and quality of the data, and how we utilize it. Data or science by itself does not get us far, and I am wary of folks thinking they can only rely on quantitative data to point us in a direction. Hence, my initial hesitation to add this post. It is important to bring experts across many domains to work together with data analytics to ask the right questions. Here is an interesting article I came across a few weeks ago that shows how big data can negatively affect vulnerable populations.
http://www.theatlantic.com/technology/archive/2016/04/how-big-data-harms-poor-communities/477423/

Maybe we shall see a new hybrid role - eg data analytics and medicine - and shifts in our education system to start training people across domain thinking? I will leave this topic for another discussion!

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