Uncertain Health in
an Insecure World – 39
“49 Reasons, All in a
Line…”
“… Some of them good
ones, some of them lies.” These Crosby, Stills, Nash & Young song
lyrics critiqued the dirty politics of the Richard M. Nixon administration.
The lie of modern data science, according to IBM big data
evangelist James Kobeilus, is “overfitting”.
He opines that statistical models of historical datasets do not guarantee their
future predictive value in the same domain of interest. Data scientists are
trained to regularly score their statistical models, but resulting overfitting
biases may introduce skewed data that cause predictive modeling failures. Such pseudo-data are often spurious – like
the age of Miss America correlating with the incidence of murders by hot steam
and hot objects!
This is one just example of how the digital world that tries
to help us can hurt us.
Can we make good decisions from sifting through the 2.4
quintillion bits of digital data generated daily from the big data stream in
the Cloud? And when an estimated 50% of the digital data generated on
individuals and their personal interests is inaccurate, is the aggregated big
data a giant solution, or a giant problem?
Who decides what of this data is actually relevant, or “A solution looking for a problem”.
Uber uses Google Map as its customer locator solution. But
Uber CEO Travis Kalanick (below) has just put in a $3 billion offer to buy Nokia’s mapping product, Here, because nobody wants to entrust
the future of a data-driven business to the privacy-mining Google
platform.
If patients’ individual little data is being protected by
public interest policy, who is assuring that the constraints of privacy and
surveillance are balanced in the private sector?
More than half of Kaiser-Permanente patients will willingly
trade their healthcare privacy for better care. Who is to say that they don’t
have the right to waive their government-given right to privacy? But caution is
warranted when the private sector is involved – recall what happened to the Obamacare
Healthcare.gov signup website last
fall, when it was revealed that Google and Twitter were sharing enrollees’
personal information.
Subjects enrolled in clinical trials are protected by strict
research ethics and rules of conduct designed to guard their confidentiality.
But pharma is now encountering & managing the reality that some research
subjects are self-identifying on social media, demanding to know whether they
received the active drug or a placebo. Does such enlightened self-interest
spoil it for others, and could such disclosures render an expensive clinical
trial ineligible for regulatory review and new drug approval?
Analytics firms can render big data meaningful, making order
of chaos and even predicting the probability of bad (or good) health outcomes.
But who makes the call as to the right question for the predictive model to
attack… especially when healthcare providers are increasingly viewed by data
collectors and analyzers as ‘disintermediaries’,
marginalized in the process of care?
Big data analytics do not replace competency.
Big companies, including large healthcare systems, must possess
business competencies in order to derive a benefit from what their big data warehouses
might reveal. Daily decision-making based on good operating information cannot
be replaced by digital data analytics. Customer and patient experiences provide
experiential information about system performance at many levels.
When aggregated and thoughtfully analyzed, these little data bytes may provide insights on process improvement that can foster real change. Performance management using big data metrics derived from little data events can be a difference-maker, but only if the organization’s culture allows for people and patients on the ground to understand their roles in making change happen.
When aggregated and thoughtfully analyzed, these little data bytes may provide insights on process improvement that can foster real change. Performance management using big data metrics derived from little data events can be a difference-maker, but only if the organization’s culture allows for people and patients on the ground to understand their roles in making change happen.
Kaiser-Permanente makes this happen, but most other
healthcare systems fall woefully short.
Financial services companies use big data analytics to
identify prospective ATM machine locations. When it takes me three tries to
process an ATM transaction, should somebody at the bank alert my doctor to
early signs of Alzheimer’s dementia?
Fitbit’s business success in personal fitness tracking
analytics has just prompted it to seek a $100M IPO filing with the U.S.
Securities & Exchange Commission (SEC). When I fall below 10,000 steps for
three consecutive Fibit days, should the company alert my health insurer of
impending type-2 diabetes due to physical inactivity?
Sound absurd? Perhaps...
A Future Watch world of little data collecting and big data analytics is
being responsibly applied in the present by progressive employers and healthcare
insurers.
In the Square, we can speak freely about the lies – intended
and unintentional – that surround this new data movement.
Richard Nixon is no longer the U.S. President, but threats
to our personal freedom persist!
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