Five Critical Predictive Modeling Questions to Ask a Prospective HCRM Partner

This is the second post in a two-part series that discusses healthcare predictive and propensity modeling and selecting the optimal analytics partner to support your growth and engagement efforts. The first post in this series shares five best practices in healthcare propensity modeling.

Big Data for HealthcareIn our last post, we talked about big data, healthcare, and predictive modeling: How can you leverage your data, analytics, and modeling to get the “biggest bang” for your marketing dollars?

However, as we mentioned, the million-dollar question is: With so many variables (and so much data) at play, how can healthcare marketers ensure they are effectively leveraging propensity and other predictive modeling?

We provided five guidelines for consideration when you commence predictive modeling: 

  • Define target/goal
  • Use best data
  • Use multiple data sources and most appropriate analytics
  • Ensure data are vetted/validated
  • Deploy validated analytics and employ follow-up testing

If you decide to use predictive modeling, you must ensure you are engaging with a HCRM partner that can support best-in-class analytics. There are several components to consider when doing your due diligence on a potential partner. For example, some provide in-house modeling and analytics; sometimes as a menu of options, other times as custom services for a fee. Others outsource their modeling and analytics to (usually) industry agnostic companies; however, there are also many smaller, boutique/niche analytics companies that provide some specialization. More

Dr. William Disch

Dr. William Disch

As Director of Analytics at Evariant, Bill’s focus is on design, execution, and implementation of optimal analytics. Maximizing ROI as a result of multivariate predictive modeling is a primary goal. Bill has been a presenter at major marketing, analytics, and academic conferences including the DMA, AMA, APA, APHA, and GSA. His background as an experimental and health psychologist has included teaching as well as several years of clinical work. His specialty areas include older adults, community-based research, HIV/AIDS, sexual behavior and risk, environmental stress, influenza and pneumonia vaccination, depression and mental health, medication and health literacy. Dr. Disch earned his Ph.D. in experimental psychology from the University of Rhode Island, with a specialty in quality of life and well-being, and mixed-methods (quant, qual, mixed).

Five Best Practices in Healthcare Propensity Modeling

This is the first post in a two-part series that discusses healthcare predictive and propensity modeling and selecting the optimal analytics partner to support your growth and engagement efforts. The second post in this series shares five critical predictive modeling questions to ask a prospective HCRM vendor.

When we talk about big data, the numbers can get overwhelming – and fast. The 4.4 zettabytes of data that exists today is expected to grow to 44 zettabytes by the year 2020. This means that, in just three years’ time, roughly 1.7 megabytes of new information will be created, every second, for every human being on the planet.

The healthcare industry greatly impacts the growth of big data but many healthcare systems find themselves lagging behind as data-rich yet analytics-poor. Big data offers opportunities for hospitals and health systems to better understand patient populations and behavior, ultimately leading to improved health outcomes.

But, as we’ve written about previously, it’s not enough to simply have the information. What’s critical for healthcare marketers is figuring out what they’re going to do with the information – and how to make data actionable.

Enter propensity modeling. More

Dr. William Disch

Dr. William Disch

As Director of Analytics at Evariant, Bill’s focus is on design, execution, and implementation of optimal analytics. Maximizing ROI as a result of multivariate predictive modeling is a primary goal. Bill has been a presenter at major marketing, analytics, and academic conferences including the DMA, AMA, APA, APHA, and GSA. His background as an experimental and health psychologist has included teaching as well as several years of clinical work. His specialty areas include older adults, community-based research, HIV/AIDS, sexual behavior and risk, environmental stress, influenza and pneumonia vaccination, depression and mental health, medication and health literacy. Dr. Disch earned his Ph.D. in experimental psychology from the University of Rhode Island, with a specialty in quality of life and well-being, and mixed-methods (quant, qual, mixed).

What Is Predictive Analytics (and Why Do You Need It)?

Try this statistic on for size: The 500 petabytes of digital healthcare data that existed in 2012 is predicted to reach 25,000 petabytes by the year 2020. That’s an increase of nearly 50 times the amount of data from just eight years prior!Diagrams projecting from tablet

Healthcare marketers may be swimming in data, but what’s important is to not drown in it. The key, in other words, is to not just have the data – but to figure out what you’re going to do with the data.

As will be discussed during today’s Evariant webinar, analytics in healthcare is critical for making effective use of data. Predictive analytics can help drive improved health outcomes for patients and give you the biggest bang for your marketing buck.

But the question is: What, exactly, is predictive analytics? More

Dr. William Disch

Dr. William Disch

As Director of Analytics at Evariant, Bill’s focus is on design, execution, and implementation of optimal analytics. Maximizing ROI as a result of multivariate predictive modeling is a primary goal. Bill has been a presenter at major marketing, analytics, and academic conferences including the DMA, AMA, APA, APHA, and GSA. His background as an experimental and health psychologist has included teaching as well as several years of clinical work. His specialty areas include older adults, community-based research, HIV/AIDS, sexual behavior and risk, environmental stress, influenza and pneumonia vaccination, depression and mental health, medication and health literacy. Dr. Disch earned his Ph.D. in experimental psychology from the University of Rhode Island, with a specialty in quality of life and well-being, and mixed-methods (quant, qual, mixed).

Understanding Extended 360° Views of Patients and Physicians

This is the first in a series of three blog posts that discusses how you can achieve Extended 360° (X-360°) views of patients and physicians through big data analytics. The second post in this series will discuss the three primary rules of X-360° views and best practices to develop them. The third post in the series will discuss how you can achieve Extended 360° (X-360°) views of patients and physicians through big data analytics.

Hospitals and health systems have some of the most complex and contextually rich data sets of any industry, yet these institutions struggle to optimize the power of their data to deliver a more patient-centric approach to care. Now, technology is available that
can efficiently process, manage, and analyze massive amounts of disparate data across a health system — what we call “big data” and “big data analytics.” Big data analytics will have an immense impact on the healthcare industry because it provides the ability to “uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful business information … <that> can lead to more effective marketing, new revenue opportunities, better customer service, improved operational efficiency, competitive advantages over rival organizations, and other business benefits.” More

Dr. William Disch

Dr. William Disch

As Director of Analytics at Evariant, Bill’s focus is on design, execution, and implementation of optimal analytics. Maximizing ROI as a result of multivariate predictive modeling is a primary goal. Bill has been a presenter at major marketing, analytics, and academic conferences including the DMA, AMA, APA, APHA, and GSA. His background as an experimental and health psychologist has included teaching as well as several years of clinical work. His specialty areas include older adults, community-based research, HIV/AIDS, sexual behavior and risk, environmental stress, influenza and pneumonia vaccination, depression and mental health, medication and health literacy. Dr. Disch earned his Ph.D. in experimental psychology from the University of Rhode Island, with a specialty in quality of life and well-being, and mixed-methods (quant, qual, mixed).

How We Use Big Data Analytics in Healthcare to Create Patient and Customer Intimacy

We’ve discussed in previous blogs the sheer volume of data that is available to – and underutilized by – healthcare organizations. However, this wealth of customer information can (and should) be used by health systems to build and foster customer and patient relationships, with the ultimate goal of optimizing business, marketing, and clinical outcomes.

In order for key healthcare players to truly engage their customers and create a unique, intimate experience on a large scale, they must take advantage of and contextualize “big data analytics.”

1. What is Big Data Analytics?

By 2020, the amount of information stored worldwide will equal 44 zettabytes. This number is unfathomable to most, and rightly so – it is 50 times larger than the amount stored today.

Big data analytics in healthcare is the process of dynamically deriving patterns and insights from consumer and patient data and using that information to make better healthcare decisions. More

Dr. William Disch

Dr. William Disch

As Director of Analytics at Evariant, Bill’s focus is on design, execution, and implementation of optimal analytics. Maximizing ROI as a result of multivariate predictive modeling is a primary goal. Bill has been a presenter at major marketing, analytics, and academic conferences including the DMA, AMA, APA, APHA, and GSA. His background as an experimental and health psychologist has included teaching as well as several years of clinical work. His specialty areas include older adults, community-based research, HIV/AIDS, sexual behavior and risk, environmental stress, influenza and pneumonia vaccination, depression and mental health, medication and health literacy. Dr. Disch earned his Ph.D. in experimental psychology from the University of Rhode Island, with a specialty in quality of life and well-being, and mixed-methods (quant, qual, mixed).