On Feb 18, the White House appointed Dr. DJ Patil to the newly created position of Chief Data Scientist for our nation. This is a really, really big deal, especially for healthcare.
The former LinkedIn data sciences honcho is a well know name in data sciences circles, and is the co-author of a widely quoted HBR article that proclaimed data scientist is the “sexiest job” of the century. Hyperbole aside, there has been compelling evidence of how advanced analytics has been driving everything from Netflix and Amazon’s recommendations engines to President Obama’s highly successful election campaigns.
The one area in which there is enormous scope for public benefit from this new appointment is healthcare. The Center for Medicare and Medicaid Services (CMS) and the Center for Disease Control (CDC) are just two of several federal government agencies that gather and store vast amounts of information related to public health and healthcare costs. Increasingly, this data is being made available in the public domain, and now we have the opportunity to understand what the data is trying to tell us.
Consider some early benefits from the analysis of big data in healthcare:
--There have been some interesting revelations about variations in healthcare costs across the nation , such as this one that tell us that the cost of knee replacement can be $11,317 in Montgomery, Alabama and $69,654 in New York, New York. Armed with this kind of information, insurance companies and public alike can now make informed decisions about what their medical procedures should cost.
--Another example of how big data can be used for public health management is how Google Flu Trends (GFT) uses search keyword trends from Google.com to produce a daily estimate, or nowcast, of the occurrence of flu two weeks in advance of publication of official surveillance data.
While these are in early stages, the potential for improved healthcare and lower overall costs of public health to the economy cannot be disputed. After all, we actually started collecting weather data long before we were able to use it to develop sophisticated weather prediction tools. No one today questions the economic benefits of having a National Weather Service.
So, why is the appointment of a bona fide data scientist in the White House a big deal for healthcare?
Firstly, let us understand what a data scientist is, how this role is different from that of an analyst, and why we should care.
In an excellent article published recently, MIT Sloan Management Review discusses these differences and what makes data scientists special. The key here is to note that data scientists use an interdisciplinary set of skills, focused primarily on anticipating or predicting outcomes based on an application of statistics, technology and business domain knowledge. Knowing what could happen with a high level of confidence empowers us to make decisions that will help us address or litigate these outcomes.
In the field of healthcare, we have already started seeing the following trends:
--Large healthcare enterprises have appointed senior executives to the role of Chief Analytics Officers and Chief Data Officers. They are analyzing their own as well as external data to predict health outcomes and costs.
--Healthcare is increasingly using advanced analytics models such as health risk profiling and risk stratifications to determine early interventions and prevention of hospitalizations in population health management
--The use of sophisticated segmentation models now drives targeted marketing efforts by both pharmaceutical companies as well as health plans that are looking at individual markets and Accountable Care Organization (ACO) models
We are now in an era of big data, wherein data is pouring in from all kinds of sources, including but not limited to:
--Electronic Health Records ( EHR)
--Demographic Data ( credit reports, purchasing histories)
-- Machine to Machine ( M2M) and Internet of Things ( IoT)
--Wearables ( Fitbit, Jawbone)
And last, but not least:
--Public health data
While the private sector in healthcare has taken the lead in harnessing the vast quantities of data available, the government is in early stages and this is why the appointment of a Chief Data Scientist becomes very important. The mere appointment of someone to this role will provide the necessary focus on healthcare data that can unleash the huge potential for improved treatments and cost control.
We are in an exciting but an early stage of unleashing the power of big data for overall improvements in standard of living and quality of life – and healthcare stands to benefit greatly from a rigorous application of advanced analytics. This is not to say that everything is in place for the great leap forward. Some of the headwinds right now are:
--Poor quality of public data: the vast amounts of data with the federal government are, for the most part, not easy to use, and require a significant amount of data preparation and standardization before they can be analyzed or combined with other data sources. Several companies in the private sector have started doing this and have built business models around the same. However, this will ultimately need to be addressed by the office of the Chief Data Scientist for the Government.
--Data integration challenges: New sources of data, such as M2M and IoT data, are not easy to integrate with EHR and other proprietary data sources (read my blog on this).
--Privacy concerns and resistance from vested interests: will prevent the release of too much data in the public domain, and will hamper the effective use of the data for public interest.
Ultimately, this is the beginning of an exciting journey towards improved healthcare for all. The appointment of the Chief Data Scientist for our nation could not have come at a better time.
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