Microservices Expo Authors: Elizabeth White, Mehdi Daoudi, Pat Romanski, Flint Brenton, Gordon Haff

Related Topics: Linux Containers, Microservices Expo, @CloudExpo, @DXWorldExpo

Linux Containers: Blog Post

The Taming of the Skew | @CloudExpo #Cloud #BigData #Analytics

Two types of skewness: the statistical skew impacts data analysis, and the operational skew impacts operational processes

The Taming of the Skew
By Dr. Laura Gardner, VP, Products, CLARA Analytics

In the famous comedy by William Shakespeare, "The Taming of the Shrew," the main plot depicts the courtship of Petruchio and Katherina, the headstrong, uncooperative shrew. Initially, Katherina is an unwilling participant in the relationship, but Petruchio breaks down her resistance with various psychological torments, which make up the "taming" - until she finally becomes agreeable.

An analogous challenge exists when using predictive analytics with healthcare data. Healthcare data can often seem quite stubborn, like Katherina. One of the main features of healthcare data that needs to be "tamed" is the "skew" of the data. In this article, we describe two types of skewness: the statistical skew, which impacts data analysis, and the operational skew, which impacts operational processes.

The Statistical Skew
Because the distribution of healthcare costs is bounded on the lower end - that is, the cost of healthcare services is never less than zero but ranges widely on the upper end, sometimes into the millions of dollars - the frequency distribution of costs is a skewed distribution. More specifically, in the following plot of frequency by cost, the distribution of healthcare costs is right-skewed because the long tail is on the right (and the coefficient of skewness is positive):

This skewness is present whether we are looking at total claim expense in the workers' compensation sector or annual expenses in the group health sector. Why is this a problem? Simply because the most common methods for analyzing data depend on the ability to assume that there is a normal distribution, and a right-skewed distribution is clearly not normal. It fails to conform to the assumption of normality. To produce reliable and accurate predictions and generalizable results from analyses of healthcare costs, the data need to be "tamed" (i.e., various sophisticated analytic techniques must be utilized to deal with the right-skewness of the data). Among these techniques are logarithmic transformation of the dependent variable, random forest regression, machine learning, topical analysis and others.

It's essential to keep this in mind in any analytic effort with healthcare data, especially in workers' compensation. To get the required level of accuracy, we need to think "non-normal" and get comfortable with the "skewed" behavior of the data.

Operational Skew
There is an equally pervasive operational skew in workers' compensation that calls out for a radical change in business models. The operational skew is exemplified by:

  • The 80/20 split between simple, straightforward claims that can be auto-adjudicated and more complex claims that have the potential to escalate or incur attorney involvement (i.e., 80 percent of the costs come from 20 percent of the claims).
  • The even more extreme 90/10 split between good providers delivering state-of-the-art care and the "bad apples" whose care is less effective, less often compliant with evidence-based guidelines or more expensive for a similar or worse result. (i.e., 90 percent of the costs come from 10 percent of the providers).

How can we deal with operational skew? The first step is to be aware of it and be prepared to use different tactics depending on which end of the skew you're dealing with. In the two examples just given, we have observed that by using the proper statistical approaches:

  • Claims can be categorized as early as Day 1 into low vs. high risk with respect to potential for cost escalation or attorney involvement. This enables payers to apply the appropriate amount of oversight, intervention and cost containment resources based on the risk of the claim.
  • Provider outcomes can be evaluated, summarized and scored, thus empowering network managers to fine-tune their networks and claims adjusters to recommend the best doctors to each injured worker.

Both of these examples show that what used to be a single business process -managing every claim by the high-touch, "throw a nurse or a doctor at every claim" approach, as noble as that sounds - now requires the discipline to enact two entirely different business models in order to be operationally successful. Let me explain.

The difference between low- and high-risk claims is not a subtle distinction. Low-risk claims should receive a minimum amount of intervention, just enough oversight to ensure that they are going well and staying within expected parameters. Good technology can help provide this oversight. Added expense, such as nurse case management, is generally unnecessary. Conversely, high-risk claims might need nurse and/or physician involvement, weekly or even daily updates, multiple points of contact and a keen eye for opportunities to do a better job navigating this difficult journey with the recovering worker.

The same is true for managing your network. It would be nice if all providers could be treated alike, but in fact, a small percentage of providers drives the bulk of the opioid prescribing, attorney involvement, liens and independent medial review (IMR) requests. These "bad apples" are difficult to reform and are best avoided, using a sophisticated provider scoring system that focuses on multiple aspects of provider performance and outcomes.

Once you have tamed your statistical skew with the appropriate data science techniques and your operational skew with a new business model, you will be well on your way to developing actionable insights from your predictive modeling. With assistance from the appropriate technology and operational routines, the most uncooperative skewness generally can be tamed. Are you ready to "tame the skew"?

Read Dr. Gardner's first two articles in this series:

Five Best Practices to Ensure the Injured Workers Comes First

Cycle Time is King

As first published in Claims Journal.


Laura B. Gardner, M.D., M.P.H., Ph.D., is an expert in analyzing U.S. health and workers' compensation data with a focus on predictive modeling, outcomes assessment, design of triage and provider evaluation software applications, program evaluation and health policy research. She is a successful entrepreneur with more than 20 years of experience in starting and building Axiomedics Research, Inc.

Dr. Gardner earned her bachelor's degree in biology (magna cum laude) from Brandeis University, her M.D. from Albert Einstein College of Medicine and both an M.P.H. in health policy and a Ph.D. in health economics from the University of California at Berkeley. As a physician, she is board certified in General Preventive Medicine and Public Health and is a fellow of the American College of Preventive Medicine.

For more information, visit http://www.claraanalytics.com/ and follow CLARA Analytics on LinkedInFacebook and Twitter.

More Stories By CLARA Analytics

CLARA analytics empowers workers’ compensation claims teams to rapidly get injured workers back on track with easy-to-use artificial intelligence (AI)-based products. Its CLARA providers search engine is an award-winning provider scoring engine that helps rapidly connect injured workers to the right providers, while CLARA claims is an early warning system that helps frontline claims teams efficiently manage claims, reduce escalations and understand the drivers of complexity. CLARA’s customers include a broad spectrum — from the top 25 insurance carriers to small, self-insured organizations.

@MicroservicesExpo Stories
The dynamic nature of the cloud means that change is a constant when it comes to modern cloud-based infrastructure. Delivering modern applications to end users, therefore, is a constantly shifting challenge. Delivery automation helps IT Ops teams ensure that apps are providing an optimal end user experience over hybrid-cloud and multi-cloud environments, no matter what the current state of the infrastructure is. To employ a delivery automation strategy that reflects your business rules, making r...
"We started a Master of Science in business analytics - that's the hot topic. We serve the business community around San Francisco so we educate the working professionals and this is where they all want to be," explained Judy Lee, Associate Professor and Department Chair at Golden Gate University, in this SYS-CON.tv interview at 21st Cloud Expo, held Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA.
For over a decade, Application Programming Interface or APIs have been used to exchange data between multiple platforms. From social media to news and media sites, most websites depend on APIs to provide a dynamic and real-time digital experience. APIs have made its way into almost every device and service available today and it continues to spur innovations in every field of technology. There are multiple programming languages used to build and run applications in the online world. And just li...
There is a huge demand for responsive, real-time mobile and web experiences, but current architectural patterns do not easily accommodate applications that respond to events in real time. Common solutions using message queues or HTTP long-polling quickly lead to resiliency, scalability and development velocity challenges. In his session at 21st Cloud Expo, Ryland Degnan, a Senior Software Engineer on the Netflix Edge Platform team, will discuss how by leveraging a reactive stream-based protocol,...
The general concepts of DevOps have played a central role advancing the modern software delivery industry. With the library of DevOps best practices, tips and guides expanding quickly, it can be difficult to track down the best and most accurate resources and information. In order to help the software development community, and to further our own learning, we reached out to leading industry analysts and asked them about an increasingly popular tenet of a DevOps transformation: collaboration.
We call it DevOps but much of the time there’s a lot more discussion about the needs and concerns of developers than there is about other groups. There’s a focus on improved and less isolated developer workflows. There are many discussions around collaboration, continuous integration and delivery, issue tracking, source code control, code review, IDEs, and xPaaS – and all the tools that enable those things. Changes in developer practices may come up – such as developers taking ownership of code ...
Cloud Governance means many things to many people. Heck, just the word cloud means different things depending on who you are talking to. While definitions can vary, controlling access to cloud resources is invariably a central piece of any governance program. Enterprise cloud computing has transformed IT. Cloud computing decreases time-to-market, improves agility by allowing businesses to adapt quickly to changing market demands, and, ultimately, drives down costs.
Modern software design has fundamentally changed how we manage applications, causing many to turn to containers as the new virtual machine for resource management. As container adoption grows beyond stateless applications to stateful workloads, the need for persistent storage is foundational - something customers routinely cite as a top pain point. In his session at @DevOpsSummit at 21st Cloud Expo, Bill Borsari, Head of Systems Engineering at Datera, explored how organizations can reap the bene...
How is DevOps going within your organization? If you need some help measuring just how well it is going, we have prepared a list of some key DevOps metrics to track. These metrics can help you understand how your team is doing over time. The word DevOps means different things to different people. Some say it a culture and every vendor in the industry claims that their tools help with DevOps. Depending on how you define DevOps, some of these metrics may matter more or less to you and your team.
"CA has been doing a lot of things in the area of DevOps. Now we have a complete set of tool sets in order to enable customers to go all the way from planning to development to testing down to release into the operations," explained Aruna Ravichandran, Vice President of Global Marketing and Strategy at CA Technologies, in this SYS-CON.tv interview at DevOps Summit at 21st Cloud Expo, held Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA.
"We are an integrator of carrier ethernet and bandwidth to get people to connect to the cloud, to the SaaS providers, and the IaaS providers all on ethernet," explained Paul Mako, CEO & CTO of Massive Networks, in this SYS-CON.tv interview at 21st Cloud Expo, held Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA.
"Grape Up leverages Cloud Native technologies and helps companies build software using microservices, and work the DevOps agile way. We've been doing digital innovation for the last 12 years," explained Daniel Heckman, of Grape Up in this SYS-CON.tv interview at 21st Cloud Expo, held Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA.
"NetApp's vision is how we help organizations manage data - delivering the right data in the right place, in the right time, to the people who need it, and doing it agnostic to what the platform is," explained Josh Atwell, Developer Advocate for NetApp, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"Outscale was founded in 2010, is based in France, is a strategic partner to Dassault Systémes and has done quite a bit of work with divisions of Dassault," explained Jackie Funk, Digital Marketing exec at Outscale, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"I focus on what we are calling CAST Highlight, which is our SaaS application portfolio analysis tool. It is an extremely lightweight tool that can integrate with pretty much any build process right now," explained Andrew Siegmund, Application Migration Specialist for CAST, in this SYS-CON.tv interview at 21st Cloud Expo, held Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA.
Let's do a visualization exercise. Imagine it's December 31, 2018, and you're ringing in the New Year with your friends and family. You think back on everything that you accomplished in the last year: your company's revenue is through the roof thanks to the success of your product, and you were promoted to Lead Developer. 2019 is poised to be an even bigger year for your company because you have the tools and insight to scale as quickly as demand requires. You're a happy human, and it's not just...
The enterprise data storage marketplace is poised to become a battlefield. No longer the quiet backwater of cloud computing services, the focus of this global transition is now going from compute to storage. An overview of recent storage market history is needed to understand why this transition is important. Before 2007 and the birth of the cloud computing market we are witnessing today, the on-premise model hosted in large local data centers dominated enterprise storage. Key marketplace play...
Cavirin Systems has just announced C2, a SaaS offering designed to bring continuous security assessment and remediation to hybrid environments, containers, and data centers. Cavirin C2 is deployed within Amazon Web Services (AWS) and features a flexible licensing model for easy scalability and clear pay-as-you-go pricing. Although native to AWS, it also supports assessment and remediation of virtual or container instances within Microsoft Azure, Google Cloud Platform (GCP), or on-premise. By dr...
With continuous delivery (CD) almost always in the spotlight, continuous integration (CI) is often left out in the cold. Indeed, it's been in use for so long and so widely, we often take the model for granted. So what is CI and how can you make the most of it? This blog is intended to answer those questions. Before we step into examining CI, we need to look back. Software developers often work in small teams and modularity, and need to integrate their changes with the rest of the project code b...
Kubernetes is an open source system for automating deployment, scaling, and management of containerized applications. Kubernetes was originally built by Google, leveraging years of experience with managing container workloads, and is now a Cloud Native Compute Foundation (CNCF) project. Kubernetes has been widely adopted by the community, supported on all major public and private cloud providers, and is gaining rapid adoption in enterprises. However, Kubernetes may seem intimidating and complex ...