Welcome!

Java IoT Authors: Yeshim Deniz, Liz McMillan, Zakia Bouachraoui, Elizabeth White, William Schmarzo

Related Topics: @DXWorldExpo, Java IoT, @CloudExpo

@DXWorldExpo: Blog Feed Post

Healthcare Industry and Big Data By @Schmarzo | @BigDataExpo [#BigData]

Impending Business Metamorphosis?

Healthcare Industry and Big Data: Impending Business Metamorphosis?

I'm struck by what's happening in the healthcare industry - between healthcare providers such as hospitals, and healthcare payers such as insurance companies - and how that industry is ripe for a metamorphosis into something much more efficient, effective and customer (patient)-centric. And within this metamorphosis, new power brokers are likely to emerge; those players who are able to leverage new sources of patient, physician, clinical, medication and care data to optimize key operational processes and dramatically reduce inefficient and unnecessary processes and procedures.

We are seeing from industry to industry the transformational power of organizations leveraging data - in the form of new customer, product and operational insights. We only need to look at the revolution started by Billy Beane and "Moneyball" - who set into motion a data and analytics revolution in how professional sports teams and players are evaluated, drafted, developed and managed.

But let's review a history lesson from another industry that has already gone through this metamorphosis process - the Retail and Consumer Packaged Goods (CPG) industry - and what the ramifications for that metamorphosis might mean to the healthcare industry.

History Lesson: Metamorphosis of Retail - CPG Industries
In the 1970s and early 1980s, Consumer Package Goods (CPG) manufacturers based much of their marketing decisions on bimonthly store audit data. Companies such as A.C. Nielsen would send auditors into a sample of stores in 13 markets to conduct physical audits-to count how much product was on the shelf, price of the product, shelf space, and other data. The results of the audits were then packaged and delivered bimonthly to CPG manufacturers, who painstakingly integrated this data with their own sources of primary research and household panel data, in the hopes of improving inventory management, production, product mix and other basic CPG disciplines.

Then in the late 1980s, Information Resources Inc. (IRI) introduced their Infoscan product, which combined retail Point of Sale (POS) scanner systems with barcodes (universal product codes or UPCs) to revolutionize the Retail-CPG value chain.  Companies like Procter & Gamble, Frito Lay, Tesco, and Walmart leveraged this new POS scanner data to create new business applications such as demand forecasting, supply chain optimization, trade promotion effectiveness, category management, and customer loyalty programs.  But more importantly, the POS scanner data eventually upset the balance of power in the Retail-CPG industries by redistributing where the actionable insights lay.  Let me explain.

Up until this POS scanner data revolution, CPG manufacturers called the shots. CPG manufacturers had the financial resources to buy third-party market research data and integrate that data with their own primary research and household panel data to understand how consumers were using their products. CPG manufacturers hired some of the early data scientists to build analytic models around key value drivers of the business including pricing, product forecasting, promotional and advertising effectiveness and new product introductions. CPG manufacturers dictated terms to the retailers including how much product they were going to be "allocated," and where and how to price, promote and place their products within the retailers' establishments.

However, leading retailers realized that the POS scanner data yielded more insights about their customers' behaviors, tendencies and usage patterns than CPG manufacturers knew.  And when combined with loyalty programs, the retailers could leverage this POS scanner data to uncover insights about individual customers such as:

  • What products does Bill Schmarzo buy in what product combinations?
  • At what stores does Bill Schmarzo primarily shop?
  • What times of day and days of the week does Bill Schmarzo primarily shop?
  • For what products did Bill Schmarzo use coupons and rebates?
  • Which products does Bill Schmarzo always buy on discount?
  • To which promotions is Bill Schmarzo most responsive?
  • What is the impact of in-store merchandising on Bill Schmarzo's market basket?
  • How price sensitive is Bill Schmarzo to the different products?
  • What products did Bill Schmarzo tend to buy based upon factors such as seasonality, holidays and special events?

And finally, with the inclusion of some external data sources, the retailers knew:

  • What products did Bill Schmarzo buy under what weather conditions (rain, snow, extreme cold, extreme heat)?
  • What products did Bill Schmarzo buy under what economic conditions (stock market changes, GNP changes, how the Chicago Cubs faired)?

Walmart was one of the first to realize that POS scanner data was a game-changer.  As highlighted in a Fortune article titled "The 12 Greatest Entrepreneurs of Our Time":

"He [Sam Walton] shared the real-time data with suppliers to create partnerships that allowed Wal-Mart to exert significant pressure on manufacturers to improve their productivity and become ever more efficient. As Wal-Mart's influence grew, so did its power to nearly dictate the price, volume, delivery, packaging, and quality of many of its suppliers' products. The upshot: Walton flipped the supplier-retailer relationship upside down."

The balance of power in the Retail-CPG industry had shifted to the retailers because the retailers knew more about their customers' shopping patterns, behaviors and tendencies than the CPG manufacturers.

Ramifications for the Healthcare Industry
There is definitely friction between healthcare providers (doctors, hospitals, clinics) and the healthcare payers (insurance companies, government agencies).  Today, the healthcare payers seem to control the cost of medical services by dictating how much they are willing to reimburse for particular types of care under, under particular conditions.

However, the healthcare providers are capturing more of their patient data; such as structured data from operational systems such as Epic and Cerner, to unstructured data sources including nurses notes and patient comments, and external data sources like WebMD, Fitbit, MyFitnessPal, Yelp, Lumosity and a wide variety of other website and mobile apps.  Leading healthcare providers are integrating and analyzing these data sources to create predictive scores about their patents' overall wellness and stress, as well as calculate scores about the patient's likelihood for strokes, heart attacks, diabetes and other maladies (see Figure 1).

bill1

Figure 1:  Patient Analytic Profile

If we apply the Retail-CPG historical lesson to the healthcare industry, then it's likely that healthcare providers will be able to leverage their superior insights into patients, physicians, drugs and procedures in order to exert significant pressure on the insurance companies with respect to what procedures should be reimbursed and for how much because the healthcare providers will know which procedures and medications work best for which patients in what situations.

Let's drill into this potential metamorphosis in more details, and outline how the healthcare providers can leverage new sources of patient data to uncover actionable insights

First, healthcare providers are going to have a wide range of patient, physician, quality of care, cost procedures and medication data including:

  • Hospital care data (Epic, Cerner)
  • Financials (Lawson, Oracle)
  • Hours Worked (Kronos)
  • Physician notes
  • Nurse & Technician notes
  • Pharmacy/prescriptions
  • Medication Usage
  • Patient comments
  • HCAHPS / Surveys
  • Social media comments
  • Yelp ratings
  • WebMD
  • Lumosity
  • Nike FuelBand/Fitbit
  • Apple iWatch

 

  • MapMyRun
  • MyFitnessPal
  • Strava
  • Smart toilets
  • "Smart" blood pressure monitors
  • "Smart" glucose monitors
  • Apple Health
  • Indeed.com
  • CDC
  • Healthcare.gov
  • Google Trends
  • Traffic patterns
  • Weather forecasts
  • Holiday schedules
  • ...

Second, healthcare providers can leverage this growing wealth of data to uncover new patient, care and operational insights including:

  • Which medical procedures and medications work best with what types of patients in what situations?
  • What is the optimal level of in-hospital care versus in-home care to deliver the best medical quality of care and the optimal prices given the type of care and the patient situation?
  • What patterns of diet, sleep, stress and exercise reduce the risk of maladies such as diabetes, strokes and heart attacks?
  • What doctor, nurse and technical combinations are most cost effective in different surgical situations?
  • Which medications are most effective in treating different health conditions regardless of the price?
  • What are the optimal combinations of rehab, medication and diet that deliver the most cost effective patient recovery?

With this patient, medication, quality of care and cost insights in hand, the healthcare providers will be able to tell the healthcare payers:

  • What are the optimal treatments given a patient's conditions and history and how much the payer should reimburse?
  • What is the value of preventive care (diet, exercise, sleep, medication) and how much should healthcare payers cover to incentive more healthy and more profitable behaviors?

Summary

Industries as diverse as professional sports, consumer package goods, retail, and healthcare are going through business model metamorphosis by leveraging the wealth of rich data sources about their customers, products and operations.  And leading organizations are learning to leverage the resulting analytic insights to change the balance of power within their industry.

In the healthcare industry, healthcare providers that know the most about their patients' and physicians' behaviors, tendencies, and usage patterns are in the best position to "correct the fuzzy math that healthcare payers have been using to set their reimbursement rates".

Bottom-line across all industries: the companies that know the most about their customers' behaviors, tendencies, and usage patterns are in the best position to monetize those insights and exert control over those organizations within their value chains that lack those customer, product and operational insights.

Healthcare Industry and Big Data: Impending Business Metamorphosis?
Bill Schmarzo

Read the original blog entry...

More Stories By William Schmarzo

Bill Schmarzo, author of “Big Data: Understanding How Data Powers Big Business” and “Big Data MBA: Driving Business Strategies with Data Science”, is responsible for setting strategy and defining the Big Data service offerings for Hitachi Vantara as CTO, IoT and Analytics.

Previously, as a CTO within Dell EMC’s 2,000+ person consulting organization, he works with organizations to identify where and how to start their big data journeys. He’s written white papers, is an avid blogger and is a frequent speaker on the use of Big Data and data science to power an organization’s key business initiatives. He is a University of San Francisco School of Management (SOM) Executive Fellow where he teaches the “Big Data MBA” course. Bill also just completed a research paper on “Determining The Economic Value of Data”. Onalytica recently ranked Bill as #4 Big Data Influencer worldwide.

Bill has over three decades of experience in data warehousing, BI and analytics. Bill authored the Vision Workshop methodology that links an organization’s strategic business initiatives with their supporting data and analytic requirements. Bill serves on the City of San Jose’s Technology Innovation Board, and on the faculties of The Data Warehouse Institute and Strata.

Previously, Bill was vice president of Analytics at Yahoo where he was responsible for the development of Yahoo’s Advertiser and Website analytics products, including the delivery of “actionable insights” through a holistic user experience. Before that, Bill oversaw the Analytic Applications business unit at Business Objects, including the development, marketing and sales of their industry-defining analytic applications.

Bill holds a Masters Business Administration from University of Iowa and a Bachelor of Science degree in Mathematics, Computer Science and Business Administration from Coe College.

IoT & Smart Cities Stories
Bill Schmarzo, author of "Big Data: Understanding How Data Powers Big Business" and "Big Data MBA: Driving Business Strategies with Data Science," is responsible for setting the strategy and defining the Big Data service offerings and capabilities for EMC Global Services Big Data Practice. As the CTO for the Big Data Practice, he is responsible for working with organizations to help them identify where and how to start their big data journeys. He's written several white papers, is an avid blogge...
Nicolas Fierro is CEO of MIMIR Blockchain Solutions. He is a programmer, technologist, and operations dev who has worked with Ethereum and blockchain since 2014. His knowledge in blockchain dates to when he performed dev ops services to the Ethereum Foundation as one the privileged few developers to work with the original core team in Switzerland.
René Bostic is the Technical VP of the IBM Cloud Unit in North America. Enjoying her career with IBM during the modern millennial technological era, she is an expert in cloud computing, DevOps and emerging cloud technologies such as Blockchain. Her strengths and core competencies include a proven record of accomplishments in consensus building at all levels to assess, plan, and implement enterprise and cloud computing solutions. René is a member of the Society of Women Engineers (SWE) and a m...
Andrew Keys is Co-Founder of ConsenSys Enterprise. He comes to ConsenSys Enterprise with capital markets, technology and entrepreneurial experience. Previously, he worked for UBS investment bank in equities analysis. Later, he was responsible for the creation and distribution of life settlement products to hedge funds and investment banks. After, he co-founded a revenue cycle management company where he learned about Bitcoin and eventually Ethereal. Andrew's role at ConsenSys Enterprise is a mul...
In his general session at 19th Cloud Expo, Manish Dixit, VP of Product and Engineering at Dice, discussed how Dice leverages data insights and tools to help both tech professionals and recruiters better understand how skills relate to each other and which skills are in high demand using interactive visualizations and salary indicator tools to maximize earning potential. Manish Dixit is VP of Product and Engineering at Dice. As the leader of the Product, Engineering and Data Sciences team at D...
Dynatrace is an application performance management software company with products for the information technology departments and digital business owners of medium and large businesses. Building the Future of Monitoring with Artificial Intelligence. Today we can collect lots and lots of performance data. We build beautiful dashboards and even have fancy query languages to access and transform the data. Still performance data is a secret language only a couple of people understand. The more busine...
Whenever a new technology hits the high points of hype, everyone starts talking about it like it will solve all their business problems. Blockchain is one of those technologies. According to Gartner's latest report on the hype cycle of emerging technologies, blockchain has just passed the peak of their hype cycle curve. If you read the news articles about it, one would think it has taken over the technology world. No disruptive technology is without its challenges and potential impediments t...
If a machine can invent, does this mean the end of the patent system as we know it? The patent system, both in the US and Europe, allows companies to protect their inventions and helps foster innovation. However, Artificial Intelligence (AI) could be set to disrupt the patent system as we know it. This talk will examine how AI may change the patent landscape in the years to come. Furthermore, ways in which companies can best protect their AI related inventions will be examined from both a US and...
Bill Schmarzo, Tech Chair of "Big Data | Analytics" of upcoming CloudEXPO | DXWorldEXPO New York (November 12-13, 2018, New York City) today announced the outline and schedule of the track. "The track has been designed in experience/degree order," said Schmarzo. "So, that folks who attend the entire track can leave the conference with some of the skills necessary to get their work done when they get back to their offices. It actually ties back to some work that I'm doing at the University of San...
When talking IoT we often focus on the devices, the sensors, the hardware itself. The new smart appliances, the new smart or self-driving cars (which are amalgamations of many ‘things'). When we are looking at the world of IoT, we should take a step back, look at the big picture. What value are these devices providing. IoT is not about the devices, its about the data consumed and generated. The devices are tools, mechanisms, conduits. This paper discusses the considerations when dealing with the...