WP Upgrade Block testing

Some of my fondest memories on road trips as a child were the games we were able to play. I’m sure many kids played “I Spy” and did “Sing-a-longs,” but my go-to game was “Slug Bug” (It’s a game where you get points for spotting a Volkswagen Beetle). While it’s been quite some time since I’ve played the game, I still find myself very aware of the different types of vehicles around me. As a matter of fact, if I were to play the game today, I’d probably rack up a number of points for the amount of cross-over utility vehicles (CUVs) I’ve seen on the road lately. There are quite a few. After reviewing Experian Automotive’s most recent Market Trends and Registration analysis, it all made sense. During the first quarter of 2015, the entry-level CUV was the top new registered vehicle segment, up 6.3 percent from a year ago. It also marked the fifth consecutive quarter that the entry-level CUV was the top selling new vehicle segment. It was followed by the small economy car and full-sized pickup truck. The analysis also found that it wasn’t just the CUV that saw an uptick in new registrations. In fact, seven of the top 10 new registered vehicle segments saw increases in sales from a year ago, and 16.6 million new vehicles overall found their way onto U.S. roads in the first quarter of 2015. The spike in new registrations combined with fewer vehicles going out of operation drove the number of vehicles on the road to nearly 253 million, its highest level since the second quarter of 2008. As CUVs continue to stand on top of the mountain of new vehicle sales, and small economy cars sprint pass the full-sized pickup truck, you might think similar patterns have emerged in the overall number of vehicles on the road. But it’s not necessarily the case. Despite falling to the third most purchased new vehicle segment, full-sized pickup trucks remain the most popular vehicle on the road, making up roughly 15 percent of the market. That said, entry-level CUVs have seen the most dramatic increase, rising 12.2 percent from a year ago. Trends in the automotive market can sometimes appear to be cyclical, which is why it’s important for the industry to pay close attention to the data sets available to them. By leveraging the data, dealers, retailers and manufacturers can benefit from the insights to make better business decisions, whether it’s relocating inventory or adapting to consumer demand. Similarly, identifying what vehicles consumers are driving, can do more than help you win in “Slug Bug,” it can help you win in the market.

Health information security breaches and identity theft have become an epidemic with losses occurring across the country. In fact, according to a recent Ponemon Institute study sponsored by the Medical Identity Fraud Alliance, medical ID theft has increased by 21.7 percent since 2013. Additionally, data from the Department of Health and Human Services indicates that health data on more than 120 million people has been compromised in more than 1,100 separate breaches since 2009. In May 2015, CareFirst BlueCross BlueShield, the largest health insurer in the Mid-Atlantic region, reported a cyber-attack that affected 1.1 million past and present customers. This comes on the heels of the February 2015 data breach at Anthem, the second-largest health insurer in the United States that affected about 80 million customers, and Premera Blue Cross’ reported cyber-attack that may impact as many as 11 million people. These attacks reflect an unsettling pattern in cybercrime as identity thieves expand their target from the financial sector into healthcare.The mere fact that health records are now digital makes them a prime target. Providers have now moved rapidly into the digital space and many don’t deploy the same robust security measures taken by their banking counterparts. Furthermore, patients now have unprecedented access to their health information thanks to the widespread use of patient portals. With providers, payers, pharmacies, labs and patients all having access to sensitive records, information security becomes vulnerable to the weakest link in the data chain. To compound the issue, stolen medical identity information is extremely valuable. While a purloined credit card number might fetch $10 on the black market, a stolen medical identity can bring in more than five times that amount. So, what’s the solution? Other major industries including financial services, telecommunications and insurance have been using Big Data and analytics for years to protect their online portals, minimize risk and reduce fraud losses. When applied in a healthcare setting, it is these same techniques that will enable professionals to gain insights that can be turned into actions to protect patient data. For example, identity-matching tools can confirm whether a patient or a physician is who they claim to be, and analyzing data and usage characteristics can more effectively assess the risk of a patient’s remote interaction. In essence, by utilizing these techniques, data can be a force for good – good for the patient, good for the healthcare provider and good for the industry.

With rising insurance costs, deductibles and copays, some people struggle to afford the out-of-pocket expense that can come with seeking medical treatment. Because of this, some consumers decide not to seek treatment, which could have negative effects on their health and overall well-being. While it’s true healthcare organizations do provide financial assistance and often have charity programs to help offset the costs, most do not have the financial resources to absorb a substantial increase in patient debt that is being driven by consumers selecting high deductible health insurance plans then not being able to pay. The additional challenge is that many hospitals and healthcare providers do not have the means to quickly and accurately determine which patients qualify for charity programs, which are able to pay for care, and which patients need payment plans to help them soften the blow from an unforeseen healthcare event. To help address the problem, Experian provides hospitals, medical offices and clinics with unique data and analytics to provide insight into each patient’s financial situation. By leveraging healthcare-specific predictive models, Experian enables healthcare organizations to easily and efficiently determine which patients qualify for financial assistance programs. In short, Experian is using its data for good by helping make patients aware that they qualify for federal benefits or financial assistance, and effectively pairing them with the right program. From a provider standpoint, the data and insight that we provide not only enables them to determine which patients meet the requirements for Medicaid and other grant or charity programs, but also allows them to do so during the registration process, saving them time and effort on the back-end. Gaining insight into a patient’s financial situation also enables healthcare organizations to minimize or avoid potential bad debt, and improve reimbursement rates by connecting patients with financial programs or setting up a payment plan that fits within their current budget. The bottom line is, in order for healthcare organizations to continue to exist and assist patients in need, it’s important for them to remain financially secure. When healthcare organizations are better able to identify the difference between the patients who can pay versus those that are truly in need of and qualify for financial assistance, everybody wins. The patient doesn’t have to worry about a financial burden that they can’t afford and the healthcare organization can operate without the threat of closure. In order to protect their financial well-being, it’s important for healthcare organizations to identify those patients who qualify for financial assistance and those who can afford treatment. Dan Johnson, Experian’s Executive Vice President of Healthcare Strategy, discusses how big data can help answer that question.