Note: This is an edited and shortened version of two articles that appeared in Open Health News co-authored by Karen Gross and Marc Wine at:
Brief bios appear at the end.
Historically, we have left the conversation on data to data experts. We think of data as complex and outside the understanding of the average person whether young or old. We look at statisticians and quiver. We think courses on statistics are for eggheads or math geniuses.
Why are we so willing to abdicate data decision-making and allow others to decide what data matter and what data need to be collected? Part of the answer is, our lack of understanding as to what data can and should be used for and when. Yet another aspect, a critical one too, is that we have done a poor job in our educational system teaching children and adults about data from pre-K onwards.
Even assuming we appreciate the need for data, we have surely not settled on what data are important to collect, what criteria should be used for data collection and what conclusions including public policy recommendations flow from available data.
Now, we know that old adage: garbage in equals garbage out. So, if we use bad or incomplete data, the conclusions we draw will be flawed because they are not based on fulsome information. We are also missing some data; omissions can stem from data unavailability.
Surely, virtually everyone is aware of the risks data present if individual or corporate privacy are not preserved. We know from our own personal experience that revealing data on a form – say in a doctor’s office – leaves us feeling vulnerable (even assuming we answer all the questions accurately). We have seen our financial data compromised. We have read about and perhaps experienced the wrath of hackers and then the myriad of efforts needed to restore systems.
After Fear, What’s Next?
The way we focus on data is, in a sense, very traditional. We see it as inanimate. We collect it; we aggregate it; we interpret it; we report on it; we make changes based on what is suggests. That is how we have become so enamored of the phrase “Data Informed Decision-Making” across the disciplines.
So, what if we changed how we think about data and moved from a static model to an active and engaged model? Indeed, this is consistent with how we are now thinking about education: moving from teachers/ professors being sages on stages to guides on the sides so students can be more actively involved in the learning process.
Picture data as a service provider, meaning that individuals and entities could access the data to get information that would be helpful to them – accurate, private, useful information. Ponder viewing data as a source for engagement where individuals or corporations ask for answers from the data and the data are programmed (with or without artificial intelligence) to provide answers or pathways for decisions (like decision-trees) or even alternative approaches. Think about a warm handoff.
This may be hard to picture in the abstract for many; so, consider this example which is NOT hypothetical and is technologically feasible -- today
Picture that we identified physical indicators of college student distress – rising blood pressure; failure to leave one’s dorm room; absence from class, especially early in the morning; high cortisol levels; rapid change in respiration rate; rise in heart rate; familial conflict or illness; breakup with a romantic partners or friend; roommate dilemmas. Suppose these (or their surrogates) were capable of being measured (which they are) on devices that students would wear on their wrist or their chest (voluntarily). The mind-body connection at work.
And suppose that there was a confidential monitoring system of students who were wearing the devices; then suppose that the presence of certain indicators (or changes) indicated “danger” of varying sorts (depression; suicide; loneliness; disassociation). There could then be appropriate professional, academic, peer or psychosocial intervention.
These data would not just be for suicide prevention though they could play that role. These data would be “signals” enabling colleges to identify students at risk and provide means by which those students could “pivot right.” To be sure, there are key privacy concerns and issues of “paternalism” or “maternalism.”
We Can Do This
The proposed uses of data are possible and some are doable in the near term. And, what they all accomplish is that they enable data to be a service provider at a personalized level. The data are made to work for and work with students among others. There are “warm” numbers.
What limits us now is not technology; it is our own fears, habits and comfort levels. Consider this article a call to action --- namely stepping forward into a new way of thinking and talking about and using data. Just repeat the words: data as service provider. Data as service provider. Data as service provider.
There’s power there.
Karen Gross is an author, educator and higher education consultant based in Washington, DC. She is the author of an award winning book, Failure and Forgiveness, published by Yale University Press and has written a children’s book series titled Lady Lucy’s Quest, and a just released, highly endorsed book on at risk student success across the educational pipeline titled Breakaway Learners published by Columbia Teachers College Press. For 8 plus years, Gross was the President of Southern Vermont College, a small, private, affordable, four-year college located in Bennington, Vermont. From 2011 to 2013, she served as Senior Policy Advisor to the US Department of Education in Washington, DC. Prior to becoming a college president, Dr. Gross was a tenured law professor for more than two decades.
Marc Wine Marc Wine has served for more than 30 years as a senior policy advisor on federal health policy and technology innovations; he has worked across both the public and private sectors, augmenting collaborations and developing IT solutions. His work, including his ground-breaking co-authored book titled Medical Informatics 20/20, has contributed to better health outcomes for patients and their families. Currently, Marc serves within the U.S. Department of Veterans Affairs Central Office as Senior Policy Adviser for Information Technology. Marc provides leadership in the collaboration of the nation’s initial mobile Health Applications including having worked on Blue Button for MyHealtheVet. Marc has taught as an adjunct professor in Health Informatics, The George Washington University School of Public Health.