Welcome!

Linux Containers Authors: Zakia Bouachraoui, Yeshim Deniz, Elizabeth White, Liz McMillan, Pat Romanski

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.

IoT & Smart Cities Stories
Digital Transformation and Disruption, Amazon Style - What You Can Learn. Chris Kocher is a co-founder of Grey Heron, a management and strategic marketing consulting firm. He has 25+ years in both strategic and hands-on operating experience helping executives and investors build revenues and shareholder value. He has consulted with over 130 companies on innovating with new business models, product strategies and monetization. Chris has held management positions at HP and Symantec in addition to ...
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...
The challenges of aggregating data from consumer-oriented devices, such as wearable technologies and smart thermostats, are fairly well-understood. However, there are a new set of challenges for IoT devices that generate megabytes or gigabytes of data per second. Certainly, the infrastructure will have to change, as those volumes of data will likely overwhelm the available bandwidth for aggregating the data into a central repository. Ochandarena discusses a whole new way to think about your next...
CloudEXPO | DevOpsSUMMIT | DXWorldEXPO are the world's most influential, independent events where Cloud Computing was coined and where technology buyers and vendors meet to experience and discuss the big picture of Digital Transformation and all of the strategies, tactics, and tools they need to realize their goals. Sponsors of DXWorldEXPO | CloudEXPO benefit from unmatched branding, profile building and lead generation opportunities.
All in Mobile is a place where we continually maximize their impact by fostering understanding, empathy, insights, creativity and joy. They believe that a truly useful and desirable mobile app doesn't need the brightest idea or the most advanced technology. A great product begins with understanding people. It's easy to think that customers will love your app, but can you justify it? They make sure your final app is something that users truly want and need. The only way to do this is by ...
DXWorldEXPO LLC announced today that Big Data Federation to Exhibit at the 22nd International CloudEXPO, colocated with DevOpsSUMMIT and DXWorldEXPO, November 12-13, 2018 in New York City. Big Data Federation, Inc. develops and applies artificial intelligence to predict financial and economic events that matter. The company uncovers patterns and precise drivers of performance and outcomes with the aid of machine-learning algorithms, big data, and fundamental analysis. Their products are deployed...
Cell networks have the advantage of long-range communications, reaching an estimated 90% of the world. But cell networks such as 2G, 3G and LTE consume lots of power and were designed for connecting people. They are not optimized for low- or battery-powered devices or for IoT applications with infrequently transmitted data. Cell IoT modules that support narrow-band IoT and 4G cell networks will enable cell connectivity, device management, and app enablement for low-power wide-area network IoT. B...
The hierarchical architecture that distributes "compute" within the network specially at the edge can enable new services by harnessing emerging technologies. But Edge-Compute comes at increased cost that needs to be managed and potentially augmented by creative architecture solutions as there will always a catching-up with the capacity demands. Processing power in smartphones has enhanced YoY and there is increasingly spare compute capacity that can be potentially pooled. Uber has successfully ...
SYS-CON Events announced today that CrowdReviews.com has been named “Media Sponsor” of SYS-CON's 22nd International Cloud Expo, which will take place on June 5–7, 2018, at the Javits Center in New York City, NY. CrowdReviews.com is a transparent online platform for determining which products and services are the best based on the opinion of the crowd. The crowd consists of Internet users that have experienced products and services first-hand and have an interest in letting other potential buye...
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...