Managing the medical portion of workers’ compensation claims can be daunting. The variables are endless -- vendors of all types, extraneous and overlapping events and even participants' attitudes. Moreover, injured employees' recoveries lie in the balance, making the effort essential. Tried-and-true methodologies have been in place for 25 years, including bill review, utilization review, discounted medical provider networks, medical case management, fee schedules, guidelines and peer review. That should do the job, but apparently not. The medical portion of claims continues to rise. Basically, the industry is continuing to follow the same pathways while hoping for different outcomes. Enough said. This is not to say we should scuttle the strategies in place. Instead, the focus should be on updating and intensifying the existing processes to achieve their intended results. Workers’ compensation is an industry replete with transactions that are recorded digitally. First reports of injury, bill review, pharmacy benefit programs and claims system paying bills and documenting events: All continually contribute to the data mass for each claim. Effectively analyzing that data on a concurrent basis and making the business knowledge available to claims adjusters and other decision makers is a powerful approach to strengthening current systems. Analyzing data and converting it to useful information is the key to enhancing current medical management techniques. Writing reports and analyzing trends cannot affect outcomes. Such measures focus on the past, but that cannot be changed. Data must be utilized in new ways. The first prerequisite is getting data-derived information to the front lines quickly. The business units should have access to analyzed information as concurrently as possible. Early information sets the scene for early intervention and resolving problematic situations in claims before they spin out of control. Distributing information continuously requires that the data be electronically monitored and analyzed continually, not at the end of the month or quarter. When conditions that portend risk occur, the appropriate person is automatically notified. That might be the claims adjustor, medical case manager, medical director, supervisor or manager. Importantly, the notified person will follow the organization’s approved procedures, thereby lending structure to the process. Monitoring data and notifying the right people when indicators in claims point to risk mobilizes medical management, as I explained in this article. Other data initiatives can be even more compelling. Research in the industry irrefutably shows poorly performing medical providers lead to high cost and poor results. Poorly performing doctors in the workers’ compensation context are those who have little understanding of the system or deliberately abuse the system through overutilization. Indicators of such poor performance are readily found in the data. The data will reveal the poor performers, those who ignore basic workers’ compensation needs such as early return to work, as well as those who bleed the system with excessive treatment practices. Treating doctors essentially cause, influence or control a significant portion of medical costs. Once the injured worker is in the doctor’s care, opportunities to steer the course with medical management methods nearly disappear. Consequently, choosing the right physician at the start is essential. Using data analysis to select the best practice doctors is the way to prevent problems and smoothly lead to the most optimal outcome. In many states, this is possible and encouraged. In other states, directing care is not allowed. Nevertheless, non-traditional applications of analytics can optimize results. When directing care to the best doctors is not possible, the next best option is to change the perpetrating doctors themselves. The fact is, people, and maybe especially doctors, do not like to look bad. Presenting them with analytic representations of their performance compared with others of the same specialty in the state is a powerful behavior-change methodology. Those who are outliers will begin to move toward the mean. Changing medical provider performance is not impossible! Of course, doctors will first attempt to push back. One way they argue is to say they treat only the more serious cases. That could be true. However, the pièce de résistance is to correct for medical severity in performance analytics, leveling the playing field. Those who treat more serious injuries are compared only with others who treat similarly difficult cases. Adjusting for case risk or severity by diagnosis is how to diminish resistance for poorly performing treating physicians. Graphic presentations of comparative performance cannot be disputed. The fairness is built in. As the treating provider outliers move toward the performance mean, they may never achieve best-in-class, but their outcomes will gradually improve. They will also be aware of continued surveillance, so the impact persists. Positioning data in this way is your weapon of choice for a powerful, yet bloodless medical management solution.

The International Association of Industrial Accident Boards and Commissions (IAIABC) publishes an annual Peer Review Journal, and the editor, Robert Aurbach, asked me to participate in a series to be included in this year's edition. This was no ordinary project, either, at least as far as I was concerned. I was asked to pen an article presenting my view on changes the workers' compensation industry should undertake to remain viable and effective for its "second 100 years." That article would be published alongside an article from another author outlining his views. Then both of us would have the opportunity to review the other's work and respond to his suggestions. And the author with whom I would be sparring? Why that would be John Burton, professor emeritus at Rutgers and Cornell, and presidentially appointed chairman of the 1972 Federal Commission on Workmen's Compensation. Yowza. Although the Journal will not be released until later this year, the four-article Point-Counterpoint series has been published in advance. Burton is an intellectual heavyweight in our industry, and I must admit the potential of this exchange left me feeling a bit like the industry's Adm. Stockdale, Ross Perot's hapless vice presidential running mate in 1992, who famously asked in a debate, "Who am I? Why am I here?" Burton is an economist, and his primary article, titled "Should There Be a 21^stCentury National Commission on Workers’ Compensation Laws?", goes into detail regarding the changes he proposes. The article contains the plethora of supporting charts and graphs that one would expect from a professor emeritus at Rutgers and Cornell who was the presidentially appointed chairman of the 1972 Federal Commission on Workmen's Compensation. My article by comparison, "The Case for Workers' Recovery," is a simpler, high-level view of a suggested philosophical change for our industry, to get away from our creeping "disability mindset." My intellectually challenged contribution can best be summed up as "injury bad, recovery good." We engaged in this process several months ago, and while I had seen and responded to Burton’s original article, I had absolutely no idea what his response to my submission was. I have spent months dreading the possibility that he would title his review of my article, “Bob Wilson Is a Blithering Idiot.” Fortunately, that was not the case. Ultimately, while we support the concept of workers’ compensation and its continuation, as well as agree on numerous points and identified problems, Burton and I do have distinct differences of opinion on what solutions would be best employed in the future. We have managed to present both a philosophically based and process-specific viewpoint in the writing of these articles. I was honored to participate in this, and I hope that you will take the opportunity to read these articles. I think they provide an interesting contrast in philosophies and, I hope, will spark further discussion. I certainly thank Dr. Burton, Mr. Aurbach and the IAIABC for allowing me to be a part of the conversation.

Earlier this year, the European Court of Justice ruled that Google is a "data controller" under the 19-year-old European data protection law, which gives individuals rights over data about them that others control. This ruling could effectively limit certain information on the Internet in Europe, and also which information would be allowed in the U.S. For example, in Spain, nearly 100 citizens would like to have information about themselves deleted from the Web. Some are embarrassed about misdemeanor arrests years ago when they were in college. Others have been victims of identity thieves or violent crimes and, understandably, don’t want their home addresses to be easily determined. The issue comes up because the official Spanish government gazette, published for 350 years every weekday, contains data required to be published publicly about bankruptcy, crime and other potentially sensitive subjects. It has been difficult to access this publication in years past and was typically unread, gathering dust at a library. But two years ago the government gazette information went online, making old and potentially embarrassing data easy to find. The Spanish government has ordered Google to stop indexing information concerning the 100 citizens who filed complaints with the Spanish Data Protection Agency. These cases are now in Spanish courts. American law is based on the concepts of free speech, the public’s right to know and unfettered debate. U.S. courts have determined that the right to publish true statements by one about the past of another person outweighs the other person’s right to privacy. In Europe, there is no general right to say anything about anyone, even when the statement in question is true. International law experts have declared that the American and European cultures are headed in different directions as to legal notions of privacy. Europeans seek to balance freedom of speech and the public’s right to know against the personal rights of privacy of others. The European perspective has been shaped by the experience of individuals as victims in data collection and use by dictators like Franco, Mussolini and Hitler, and by Soviet authorities. In Germany, two persons who murdered someone 20 years ago have recently sued to suppress their identity as criminals on the basis of their own rights of privacy and their so-called “rights to be forgotten” after their criminal sentences have been served. Google has faced suits in Germany, Switzerland and the Czech Republic over its “Street View” feature, collecting photographs of streets and private homes and businesses. In Germany, citizens are allowed an option to not have their home or business photographed, and more than one quarter million have chosen this option. By contrast, this issue has resulted in little debate in the U.S. where persons may take pictures of anything in plain sight from a public street. European Union surveys have found that three in four persons worry about how Internet companies use their information and want the right to delete personal data at any time. Ninety percent believe the European Union should formalize in law the “right to be forgotten.” These individuals want to retain some limited rights to their own data, even if it is in cyberspace – they want, in effect, a right to withdraw from others permission to store their personal data. The U.S. recognizes no such rights to be forgotten or deleted. But the Federal Trade Commission has recommended that companies collect only the data about persons they need and to delete information that is no longer necessary. Congress has introduced a “Do Not Trace Kids Act of 2011,” which would require companies to allow parent and child users to delete publicly available information about minors from a web site. The bill remains pending. Some parents have been shocked to learn that their minor children have accumulated large amounts of debt because of the unlawful use of their Social Security numbers by others. There were more than 4,000 cases of child identity theft found in 2010 from a random pool of 40,000 American children age 18 and younger, a higher rate than for adults. Criminals like to use children’s Social Security numbers because adults have their own existing credit records under their own names. Google and other search engine companies have argued that the Spanish consumers and others should not seek to hold search engines responsible for information they extract from the Web, but should instead seek redress against those parties that posted the allegedly private information in the first place. But many European legal experts expect the search engines to nonetheless become more regulated because they are the ones effectively spreading the information that otherwise would likely not be found.

This is the third in a series of four articles that offer a “road less traveled” to Agency 2020. The first article focused on your agency in the marketplace’s current reality. The second article considered the world as it might be in 2020. Today, we address the processes necessary to ensure you have the “seed corn” to grow the culture and structure necessary to produce Agency 2020 and win in the marketplace of tomorrow. Mohan Nair, in his book, Strategic Business Transformation, diagrams a world of yesterday where 80% of change was incremental/cyclical and 20% was structural/transformational. Today, he says, “When the unknown are threatening every variable we have counted on, 80% of the variables that shift are structural while 20% are predictable. We cannot use the strategic data used in the past to find our ‘true north.'” Your successful organization today is driven by its culture: “the house rules,” “what’s tolerated.” This organization and culture were created for the world of yesterday (“Daddy, may I?”) and today ("What do our carriers say?"). If you believe the world of 2020 will be different, you must create a culture appropriate for that new world. The Gospel of Mark (3:25) and then Abraham Lincoln stated that “a house divided cannot stand.” This was true in their world of incremental change. Theirs was a world that moved at the pace of a tortoise. Tomorrow’s world will move at the pace of the hare (but never stop for a coffee break).  As has been said: “It’s not the big that eat the small. It’s the fast that eat the slow!” Most people are reluctant to change. As Maxine puts it, “Change is good as long as I don’t have to do anything different!” In your organization, most folks are comfortable in their jobs, see the world as it is and are terrified that things will change. A minority of folks who are enthusiastic about the new, virtual world and global economy see the world as it will be and are terrified that your organization won’t change. Your house is already divided.  What you need to do is merely focus each segment on the role right for them. Both groups are necessary for success, but you must answer one question for each group and each individual. WIIFM? – What’s in it for me? Do this, and they’ll embrace your plan; ignore WIIFM, and they’ll sabotage your future. Be respectful of all. Understand that there are different “tolerances” for risk and that people discover, learn and adapt at different speeds. Gather your team. Put them at ease. Make the environment safe for them. Explain that you want to structure change to give every contributor an opportunity to continue their success today and find the right fit in the world of tomorrow. Celebrate your past and thank them for their participation. Clearly articulate your embrace of the inevitable change necessary for tomorrow and your commitment to your team's success in the future. Announce your plans to begin an Agency 2020 initiative. Explain that to build a foundation for success you need two teams. This process will not be instead of their existing roles but as an extracurricular activity. This initiative is about assuring a future with opportunities for each other. This is about each voice being heard. The first group will immediately focus on the existing organization – making it more efficient and effective to create the “seed corn” (profits) necessary to finance tomorrow. The group’s task will be to create an operational “to do list” defining and acting on what is necessary for enhanced success today and to quit doing those things carried forward from yesterday but no longer needed today – “we’ve always done it this way.” The “tomorrow team” will be the young at thought and the young at heart. They will be your pioneers. They will be charged with discovering tomorrow as it will be and creating a blueprint to build your organization as it must be to fit in 2020. This process is not intended to exclude the traditionalists. Both teams will be encouraged to share their discoveries and enthusiasms - to create excitement about today’s improvements and refinements and tomorrow’s innovations. Don’t create competition between the teams – encourage collaboration so that respect and trust will build. This will work because each group is focusing where “they live” – their comfort zone -- and you are not forcing them, at this time, to go to where they don’t want to be. Assure all team members that, as the blueprint for 2020 is designed and new roles are defined, each person on staff will have the right to be considered for jobs right for them and your organization. Promise them the training necessary for success. If they can’t or won’t fit into the world of 2020, facilitate their exit. Make it as painless as possible. For the Today Team, some ideas to consider and questions to ask (there are more):

1. Focus – take out the microscope and study every function you perform.
2. If “we’ve always done it this way” – it can be changed for the better.
3. What are five things we do today that no longer need to be done?
4. What are five things we do today that remain important and can be improved?
5. What are the jobs skills that remain important today? How do we improve these?
6. What are skills no longer needed in the world of today? How do we let them go?
7. Do we have the technology (systems and social media) needed for today?
8. What and how can we maximize our results from this technology?
9. Does our “client experience” differentiate us, or are we “the same old same old?”
10. Are we capturing the data available and converting this to actionable knowledge?
11. Where must we invest our time and energy?
12. What must we leave behind?

Please remember – the Today Team is about updating (remodeling) the organization you have. Its role is small steps – process improvement. Think outside of the box. Remember the words of Einstein – insanity is “continuing to do what you’ve always done and expecting a different result.” The world has changed more in the past 10 years than the previous 50, yet most agencies continue to do what they’ve always done. Don’t be crazy. Discover and do what needs to be done today to prepare for tomorrow. The Tomorrow Team is about designing a blueprint and facilitating the building of the organization and culture you’ll need for the future. The team's role is “giant leaps” – innovation. You are moving from the mechanical processes of yesterday to a new “living” system for tomorrow. Be bold. Don’t be afraid to fall – just do it, and learn from the experience. For the Tomorrow Team, some directions and innovations to consider (there are more):

1. Scan the horizon of the world and technology. Look outside your comfort zone.
2. Determine if “place” will matter -- where you, your employees and clients are.
3. Determine if “time” will matter? Is “Working 9 – 5” only right for Dolly Parton?
4. Determine the role of cultures and generations for buyers and those who influence decisions.
5. What are the talents needed? Prioritize communication, technology, insurance, etc.
6. What will be client needs? How can you deliver solutions profitably?
7. Shift your focus from products sold in the past – to client needs in the future.
8. What will be the demographics and psychographics of the populations served?
9. What will be the industries/market niches in collapse/decline? Avoid them.
10. What will be the industries/market niches in ascendancy? Focus on these.
11. How do you manage in a “virtual” (no time, place and more non-verbal) world?
12. What will be the role of big data? What will be your ability to use it effectively

The questions are offered as a starting point for discovery. You have many more questions to ask and answer. Yours is a world yet to be – not a world that is. Nonetheless, the better you ponder and plan, the better your head start on the future – the New World of 2020 - will be. Learn from the great change architect Peter Drucker, who said, “The best way to predict the future is to create it.”

The new FAQS About Affordable Care Act Implementation, published Nov. 6, 2014, confirm that employers can’t reimburse employees for purchasing individual coverage, even though various vendors are promoting that approach in lieu of group health plan coverage. FAQ XXII makes clear that the departments of Labor, Health and Human Services and Treasury object to this practice. FAQ XXII makes clear that the departments consider ACA’s market reforms to outlaw any arrangement pursuant to which an employer provides cash reimbursement to employees for the purchase of an individual market policy, regardless of whether the reimbursement is paid on a pre- or after-tax basis. This position is consistent with previous guidance that the departments have published, that health reimbursement arrangements (HRAs), health flexible spending arrangements (health FSAs) and certain other employer and union health care arrangements where the employer promises to reimburse health care costs are: considered group health plans subject to the Public Health Service Act (PHS Act) § 2711 annual limits, PHS Act § 2713 preventive care with no cost-sharing and other group market reform provisions of PHS Act §§ 2711-2719 and incorporated by reference into the Employee Retirement Income Security Act (ERISA) and the Internal Revenue Code (Code). HRA or other premium reimbursement arrangements do not violate these market reform provisions when integrated with a group health plan that complies with such provisions. However, an employer health care arrangement cannot be integrated with individual market policies to satisfy the market reforms. Consequently, such an arrangement may be subject to penalties, including excise taxes under section 4980D of the Internal Revenue Code (Code). (See, DOL Technical Release 2013-03; IRS Notice 2013-54; Insurance Standards Bulletin, Application of Affordable Care Act Provisions to Certain Healthcare Arrangement; IRS May 13, 2014 FAQs.) FAQ XXII reinforces this prior guidance, stating, “Such employer health care arrangements cannot be integrated with individual market policies to satisfy the market reforms and, therefore, will violate PHS Act sections 2711 and 2713, among other provisions, which can trigger penalties such as excise taxes under section 4980D of the Code. Under the departments’ prior published guidance, the cash arrangement fails to comply with the market reforms because the cash payment cannot be integrated with an individual market policy.” (See, DOL Technical Release 2013-03; IRS Notice 2013-54; Insurance Standards Bulletin, Application of Affordable Care Act Provisions to Certain Healthcare Arrangements, Sept. 16, 2013.) FAQ XXII also confirms the departments’ view that arrangements where a vendor markets a product to employers claiming that employers can cancel their group policies, set up a Code section 105 reimbursement plan that works with health insurance brokers or agents to help employees select individual insurance policies, and allow eligible employees to access the premium tax credits or other HRA dollars to pay for Marketplace coverage are illegal. According to FAQ XXII, these arrangements are problematic for several reasons, including: The arrangements themselves are group health plans. Therefore, employees participating in such arrangements are ineligible for premium tax credits (or cost-sharing reductions) for Marketplace coverage. The mere fact that the employer does not get involved with an employee’s individual selection or purchase of an individual health insurance policy does not prevent the arrangement from being a group health plan. Department of Labor guidance indicates that the existence of a group health plan is based on many circumstances, including the employer’s involvement in the overall scheme and the absence of an unfettered right by the employee to receive the employer contributions in cash. Under DOL Technical Release 2013-03, IRS Notice 2013-54 and the two IRS FAQs addressing employer health care arrangements, such arrangements are subject to the market reform provisions of the Affordable Care Act, including the PHS Act § 2711 prohibition on annual limits and the PHS Act § 2713 requirement to provide certain preventive services without cost sharing. Such employer health care arrangements cannot be integrated with individual market policies to satisfy the market reforms and, therefore, will violate PHS Act §§ 2711 and 2713, among other provisions, which can trigger penalties such as excise taxes under Code § 4980D. FAQ XXII also confirms the department’s position that an employer violates the ACA provisions of PHS Act § 2705, ERISA § 715 and Code § 9815, as well as the Health Insurance Portability & Accountability Act (HIPAA) nondiscrimination provisions of ERISA section 702 and Code § 9802 prohibiting discrimination based on one or more health factors if it offers selectively only to employees with high claims risk a choice between enrollment in its standard group health plan or cash. FAQ XXII clarifies that while the departments’ regulations allow more favorable rules for eligibility or reduced premiums or contributions based on an adverse health factor (sometimes referred to as benign discrimination), in the departments’ view this position does not extend to cash-or-coverage arrangements offered only to employees with a high claims risk. Accordingly, FAQ XXII states such arrangements will violate the nondiscrimination provisions, regardless of whether (1) the cash payment is treated by the employer as pre-tax or post-tax to the employee, (2) the employer is involved in the selection or purchase of any individual market product or (3) the employee obtains any individual health insurance. Beyond these concerns stated in FAQ XXII, employers and others contemplating offering such a choice also should discuss potential exposures under the Americans With Disabilities Act (ADA) and, depending on the nature of the condition, Medicare law. In light of this new guidance and previous guidance published by the departments, employers and others sponsoring or contemplating engaging in these arrangements are encouraged to contact competent counsel for assistance in understanding the potential concerns raised by involvement in these practices and their resolution.

The U.S. has seen an explosion in what is often referred to as the emerging “sharing economy” or “collaborative consumption.” In an increasingly connected society where most people have access to mobile communication devices, peer-to-peer services are springing up, based on mobile apps that consumers can use to access transportation services that historically have either not existed or were controlled by often highly regulated business or government entities. One might argue that this is not a new concept, given that hitchhiking has been around since not long after the wheel was invented and was quite common in the 1950s and 1960s until it fell out of vogue as its inherent dangers gained more attention from the media and increasing numbers of consumers owned or had access to automobiles or mass transit. But what we’re witnessing today is a relatively new phenomenon. Uber, Zimride, Lyft, ZipCar, Turo, GetAround, TaskRabbit, JollyWheels, RentMyCar, Zilok, CityCarShare, bla, bla, bla, bla, bla…. Which brings us to BlaBlaCar, the latest incarnation of car sharing. Founded in France in 2006, BlaBlaCar now claims to operate in about a dozen European countries and is exploring expanding into other countries, such as India and Brazil. BlaBlaCar bills itself as a “ride sharing” mechanism, as opposed to “car sharing.” That falls somewhere between fee-based hitchhiking and a somewhat irregular share-the-expense car pooling arrangement. Details on how the system operates can be found at the company's web site. BlaBlaCar currently does not operate in the U.S. There is some question as to whether it can be as successful in the U.S. as it claims to be in Europe. Owning and operating a vehicle in Europe is far more costly than it is in the U.S. There is also a perception that Europeans may be more trusting of, or accustomed to, riding with strangers than Americans are. In addition, there are social issues to consider in the U.S. For example, a BlaBlaCar driver can refuse to transport particular passengers. If such a driver is white and a declined passenger applicant is black, would there be civil rights issues that could be addressed by claims or suits for discrimination? The question addressed by this article is, if BlaBlaCar were to begin operations in the U.S., would the personal auto insurance policies of its drivers cover this type of activity? According to the terms and conditions on BlaBlaCar’s web site and media articles about their service, most auto insurance in Europe covers this exposure because there is no “profit” involved. The passenger fee is referred to as a way to share the cost of a trip. The terms and conditions include a stringent hold-harmless provision and a liability cap to protect BlaBlaCar. However, the company's position on how personal auto insurance responds in Europe would be immaterial if it were to commence operations in the U.S. Many, if not most, personal auto policies in the U.S. may exclude BlaBlaCar activities regardless of whether a “profit” is sought or made. The decision could depend on the facts of each situation and the exclusion wording in the policy. The first question is whether there can be assurance that a driver is not making a profit. Second, the policy language may not consider profit to be an issue. For example, these are the two most common exclusions found in U.S. personal auto policies:

• We do not provide liability coverage for any "insured"...for that "insured's" liability arising out of the ownership or operation of a vehicle while it is being used as a public or livery conveyance. This Exclusion (A.5.) does not apply to a share-the-expense car pool.

• We do not provide liability coverage for any person...for that person's liability arising out of the ownership or operation of a vehicle while it is being used to carry persons or property for a fee. This exclusion (A.5.) does not apply to a share-the-expense car pool.

This language is taken from two different edition dates of the “ISO-standard” personal auto policy. In the case of use as a “public or livery conveyance,” ISO’s filing memorandum stated that the intent of this exclusion is to preclude coverage for vehicles available for “hire” to the general public for the transportation of people or cargo (e.g., taxis, sightseeing vans and package delivery services). The exclusion is not contingent on the profitability of the person or enterprise holding their vehicle out to the general public for hire. In the case of a vehicle used to “carry persons or property for a fee,” there is no mention whatsoever of whether this fee generates a profit for the owner/driver. In one case, this exclusion was held to apply to someone who used his pickup truck to transport a friend’s son’s belongings to college in exchange for gas money. However, both exclusions admittedly exempt a “share-the-expense car pool.” So what is meant by a “car pool”? One dictionary definition describes it as: "an arrangement between people to make a regular journey in a single vehicle, typically with each person taking turns to drive the others." Note the reference to “regular” and alternating as drivers. On the other hand, Wikipedia’s discussion of the term “carpool” implies a potentially broader concept that could include how BlaBlaCar operates. This muddies the water to the point that no blanket statement can be made about how U.S. personal auto policies might respond to claims arising from BlaBlaCar and similar ride-sharing services. If this were to become a significant exposure, one might expect U.S. insurers to define “car pool” in a way that precludes coverage for these services. In the past year or two, we have seen various forms of “car sharing” exclusionary endorsements introduced by ISO and individual insurers, though many of them still do not fully address the “share-the-expense car pool” situation. The only conclusion we can reach at this point is that how a vehicle is being used and how that use fits with an insurance policy’s insuring agreements and exclusions are becoming much more important and more difficult to determine. The insurance industry is not known for its innovation nor its ability to respond quickly to emerging social changes. The usual reaction is to exclude an unanticipated exposure until the industry can reasonably measure and predict the risk of loss. The growth of car- and ride-sharing (not to mention home-sharing) is something that will need to be closely monitored by the industry.

“Know your customers” is the new data mantra for the 21^st century. Clean, high-quality customer data gives insurers powerful marketing and service advantages and prevents expensive headaches. A well-conceived data warehouse is a good place to start, but, as core insurance systems develop problems over time, data-quality issues grow undetected in the data warehouse. These problems usually only show up when reports are generated from the warehouse and business people question the validity of the data. By then it is too late, and correcting the problem will take much time and money. So how do you avoid this problem? The answer lies in searching for small data problems before they get bigger. And, once they’ve been found, fix them right away. The same principles for running a great data warehouse apply to property/casualty, life and health insurers. All have complex challenges, but health insurers, which deal with patients, providers, employers and brokers, may face the biggest data challenges. To avoid data integrity issues, carriers should consider establishing a simple yet effective four-step program. 1. Control totals The standard approach is to keep track of the number of records in the file and make sure that same number end up in the warehouse. That's a good start, but take this concept further and use it with individual fields that are important for the business. For example, while loading patient data, we can get the control counts for male/female and match them with the membership system. Another example would be to get the control count based on age bands and make sure they match the membership system. 2. Aggregate data and check for trends Your system should aggregate certain data to make sure that the percentage is as expected and lies within a trend. For example, in a typical month, 18% of members may have claims. If that number is suddenly showing up as 8% or 28%, you know you probably have a data problem. To track the change, calculate the percentage that matched upfront and store it in the aggregate table. Storing of the aggregated data helps identify problems with the data quickly if trends change. 3. Set up automatic alerts Your system should automatically issue alerts whenever it detects a problem: controls totals that do not match or a percentage that’s outside the range of expected results. 4. Build and empower data teams Build a team whose job is to identify the data-quality issues. This team has to be knowledgeable about the business and understand trends. Data-quality team members should include representatives of various business departments and IT. When any problems arise, the data-quality team will report them to the data steward/governance team. The latter team is empowered to take prompt corrective action. The key to making any data warehouse successful is to continually build trust and credibility in the data. Checking for data anomalies is not a one-time thing. It needs to be done continuously as part of a healthy data program. Having a set of strategies for automating data-quality checking helps maintain the trust in data over time. Building a support team that is vigilant about finding data-quality issues is a must for continuing data quality.

While the Internet of Things (IoT) accounts for approximately 1.9 billion devices today, it is expected to be more than 9 billion devices by 2018—roughly equal to the number of smartphones, smart TVs, tablets, wearable computers and PCs combined. But, for the IoT to scale beyond early adopters, it must overcome specific challenges within three main categories: technology, privacy/security and measurement. Following are 12 hurdles that are hampering the growth of the IoT: 1. Basic Infrastructure Immaturity IoT technology is still being explored, and the required infrastructure must be developed before it can gain widespread adoption. This is a broad topic, but advancement is needed across the board in sensors themselves, sensor interfaces, sensor-specific micro controllers, data management, communication protocols and targeted application tools, platforms and interfaces. The cost of sensors, especially more sophisticated multi-media sensors, also needs to shrink for usage to expand into mid-market companies. 2. Few Standards Connections between platforms are now only starting to emerge. (E.g., I want to turn my lights on when I walk in the house and turn down the temperature, turn on some music and lock all my doors – that’s four different ecosystems, from four different manufacturers.) Competing protocols will create demand for bridge devices. Some progress is emerging in the connected home with Apple and Google announcements, but the same must happen in the enterprise space. 3. Security Immaturity Many products are built by smaller companies or leverage open source environments that do not have the resources or time to implement the proper security models. A recent study shows that 70% of consumer-oriented IoT devices are vulnerable to hacking. No IoT-specific security framework exists yet; however, the PCI Data Security Standard may find applicability with IoT, or the National Institute of Standards and Technology (NIST) Risk Management Guide for ITS may. 4. Physical Security Tampering IoT endpoints are often physically accessible by the very people who would want to meddle with their results: customers interfering with their smart meter, for example, to reduce their energy bill or re-enable a terminated supply. 5. Privacy Pitfalls Privacy risks will arise as data is collected and aggregated. The collation of multiple points of data can swiftly become personal information as events are reviewed in the context of location, time, recurrence, etc. 6. Data Islands If you thought big data was big, you haven’t see anything yet. The real value of the IoT is when you overlay data from different things -- but right now you can’t because devices are operating on different platforms (see #2). Consider that the connected house generates more than 200 megabytes of data a day, and that it’s all contained within data silos. 7. Information, but Not Insights All the data processed will create information, eventually intelligence – but we aren’t there yet. Big data tools will be used to collect, store, analyze and distribute these large data sets to generate valuable insights, create new products and services, optimize scenarios and so on. Sensing data accurately and in timely ways is only half of the battle. Data needs to be funneled into existing back-end systems, fused with other data sources, analytics and mobile devices and made available to partners, customers and employees. 8. Power Consumption and Batteries 50 billion things are expected to be connected to the Internet by 2020 – how will all of it be powered? Battery life and consumption of energy to power sensors and actuators needs to be managed more effectively. Wireless protocols and technologies optimized for low data rates and low power consumption are important. Three categories of wireless networking technologies are either available or under development that are better suited for IoT, including personal area networks, longer-range sensors and mesh networks and application-specific networks. 9. New Platforms with New Languages and Technologies Many companies lack the skills to capitalize on the IoT. IoT requires a loosely coupled, modular software environment based on application programming interfaces (APIs) to enable endpoint data collection and interaction. Emerging Web platforms using RESTful APIs can simplify programming, deliver event-driven processes in real time, provide a common set of patterns and abstractions and enable scale. New tools, search engines and APIs are emerging to facilitate rapid prototyping and development of IoT applications. 10. Enterprise Network Incompatibility Many IoT devices aren’t manageable as part of the enterprise network infrastructure. Enterprise-class network management will need to extend into the IoT-connected endpoints to understand basic availability of the devices as well as manage software and security updates. While we don’t need the same level of management access as we do to more sophisticated servers, we do need basic, reliable ways to observe, manage and troubleshoot. Right now, we have to deal with manual and runaway software updates. Either there’s limited or no automated software updates or there are automatic updates with no way to stop them. 11. Device Overload Another issue is scale. Enterprises are used to managing networks of hundreds or thousands of devices. The IoT has the potential to increase these numbers exponentially. So the ways we currently procure, monitor, manage and maintain will need to be revisited. 12. New Communications and Data Architectures To preserve power consumption and drive down overall cost, IoT endpoints are often limited in storage, processing and communications capabilities. Endpoints that push raw data to the cloud allow for additional processing as well as richer analytics by aggregating data across several endpoints. In the cloud, a "context computer" can combine endpoint data with data from other services via APIs to smartly update, reconfigure and expand the capabilities of IoT devices. The IoT will be a multi-trillion industry by 2020. But entrepreneurs need to clear the hurdles that threaten to keep the IoT from reaching its full potential. This article was co-written with Daniel Eckert. The article draws on PwC's 6th Annual Data IQ Survey. The article first appeared on LinkedIn.

A Lyft passenger was killed over the weekend near Sacramento, an incident that underscores inadequacies in California's insurance laws. As reported in Forbes, the Lyft driver saw a stalled Kia on Interstate 80 and swerved to the right, hitting a tree. One passenger died. The second passenger and the Lyft driver were injured. An incident like this causes one to ponder the arbitrary rules governing life, death and the arbitrary rules governing uninsured and underinsured motorist coverage (UM/UIM) in California. For example, the news article asserts that “if the death had been caused by a hit-and-run driver, the accident would be covered under Lyft’s $1 million uninsured/underinsured motorist policy.” Not so. Lyft does not disclose on its web site the provisions of its UM/UIM coverage, so let’s assume it tracks California Ins. Code sec. 11580.2 governing UM/UIM coverage. Subsection (b)(1) requires “physical contact” with the UM/UIM vehicle. If the Lyft driver hit a tree rather than the car, there is no physical contact with the UM/UIM vehicle. The nimble driver who avoids the pile-up but comes to grief on a tree receives no UM/UIM coverage. Neither do the passengers.  It makes no difference whether a convention of 20 bishops saw the hit-and-run vehicle, or even if the accident were recorded on video. Many jurisdictions (about half) find this restriction unnecessary, so why should California leave the passengers and driver unprotected? Assume the hit-and-run driver is discovered and the driver carries $1 million in liability coverage (highly improbable). The pile-up included a number of cars, plus a big rig, and caused numerous injuries. By the time this $1 million is spread around, there may only be leftovers for the occupants of the Lyft car. Because the coverage is inadequate to compensate their injuries, they can, then, call on Lyft’s $1 million UM/UIM coverage, right?. Not so. UM/UIM coverage is triggered only when the underinsured party’s limits are “less than the uninsured motorist limits carried on the motor vehicle of the injured person [the Lyft car in this case].” Subsection (p)(2). It makes no difference that the responsible party is grossly underinsured with respect to the damages. Again, this is a restriction many states (e.g., Arkansas) find unnecessary. Now assume the responsible driver has a $50,000 limit, and a gravely injured Lyft passenger accepts $49,500 in settlement with the underinsured driver. Now the passenger may look to Lyft’s $1 million UM/UIM policy for compensation, right?. Not so. By failing to collect the remaining $500, the passenger has forfeited any claim to the $1 million UM/UIM coverage. Subsection (p)(3) provides that UIM coverage does not apply “until the limits of bodily injury liability  policies applicable to all insured motor vehicles causing the injury have been exhausted by payments of  judgments or settlement . . . .” Thus, the passenger must go to trial against the intransigent party to collect the remaining $500. Once again, many states (e.g., Nevada, Idaho) do not follow this restriction. Once a gravely injured Lyft passenger has collected the $50,000 limit from the responsible party, the passenger may recover any remaining damages up to the $1 million limit of Lyft’s UM/UIM policy, right? Not so. California allows the UM/UIM carrier to subtract from its limits any recovery from other parties regardless of the extent of the passenger’s injuries, according to Subsection (p)(4)(A). Yes, once again, many states (e.g., Nevada, Utah) do not endorse this setoff rule. California’s UM/UIM rules fall well below best practices in other states. If Arkansas can have better UM/UIM coverage, why not California? California should follow the lead of other states and scrap these arbitrary restrictions. Even if California's rules were tolerable with respect to private automobile insurance, in commercial settings the public is entitled to more protection (otherwise, why must Lyft carry $1 million bodily injury and $1 million UM/UIM coverage when only $15,000/$30,00 is required for private auto, and UM/UIM is optional?) Changes could be accomplished either by legislation or possibly by the California Public Utilities Commission's specifying the commercial UM/UIM coverage requirements for charter party carriers. After all, if Uber, Lyft and others are to operate in other states, they must purchase UM/UIM policies that do not have these restrictions.

There is an old line in Silicon Valley: “Never confuse a clear view with a short distance.” We should keep that in mind as we think about wearable devices such as the Apple watch that are designed, among other things, to help us monitor and improve our health. The view is crystal clear, but we’re still a long way from getting to the destination.

The vision is idyllic: Some day, a wearable device will monitor all our vital signs and relay the information second by second to a healthcare provider, where some combination of computers and doctors will monitor it. We’ll know two weeks ahead of time that we’re about to have a heart attack and will be able to head it off. Doctors, who currently spend only about seven minutes a year with the average patient, will mine the stream of information, spot chronic issues in more people and get them treatment for, say, high blood pressure. Our knowledge about health will increase exponentially because so many aspects of so many people will be tracked, and in real time.

Researchers say the change in health will be like what has happened with cars. We used to wait until we saw steam coming out from under the hood, then fix whatever was wrong. Those cars lasted 60,000 or 70,000 miles. Now we have sensors all over the place in cars, learn about problems before they become acute and gather voluminous data on what works and what doesn’t, so cars can keep getting better. As a result, many cars last more than 200,000 miles. With people, once we can get those sensors “under the hood,” we should also see huge improvements in health and life expectancy – engine performance, too.

But three major things have to happen before we achieve that idyllic vision, and only one is even close to reality.

The one change that could at least plausibly happen soon is that people adopt wearables en masse. No more of this buy a Fitbit, wear it for a couple of months and then set it aside. At least millions of people, and maybe tens of millions, will have to buy wearable devices and keep them on 24/7 for basically forever, just to really get the movement started. That sort of adoption will require smaller and better-designed wearables and far better battery life – the early line on the Apple watch is that it won’t even go a full day on a charge. Makers of wearables will also have to agree on standards so that all health data can be integrated into any software and analyzed by any healthcare provider. At the moment, every wearable maker wants to own the standard, and standards fights can take years to sort out, but with Apple working its magic on consumers and with Microsoft introducing a well-regarded device, it’s at least possible to imagine mass adoption within a few years.

That’s the easiest problem.

The most severe problem is that wearables aren’t yet close to collecting the really useful information. Wearables can monitor your pulse and provide a reasonable estimate of how many steps you take, but that’s not the good stuff, as far as medicine is concerned.

I got a tutorial on this almost 15 years ago from Astro Teller, who cofounded Body Media, a pioneer in the wearables field. He said the data he really needed was blood pressure and information from blood tests. Astro is a seriously smart fellow – the grandson of the principal developer of the hydrogen bomb, Edward Teller, Astro has since 2010 been directing the Google X laboratory, meaning he has the Google Glass, driverless car and many other cutting-edge projects reporting to him – but Body Media never cracked the code before being acquired by Jawbone for $110 million, principally for its patents, in 2013. While there are glimmerings of progress all over, no breakthrough seems especially close.

Google, for one, has a project in the Google X lab that puts sensors in contact lenses that can measure blood sugar and send a constant, wireless signal to a wearable device, giving diabetics a noninvasive way to monitor themselves. But the technology must now be calibrated for different conditions. What if the wearer is crying? What if the weather is dry? What if it’s raining? It’s not clear how close to market the technology is.

Others talk about having people swallow sensors that would roam the bloodstream and report on all kinds of conditions, including watching out for cancer, but those are far enough out that they still read like science fiction.

A company has a prototype of a device that would measure blood pressure constantly, but, even if that proves workable, the device needs to go through multiple iterations and become tiny enough that it can fit into a general-use device – people may wear one health-related device on an arm, but they won’t wear two or three or four.

The final hurdle that has to be cleared is doctors and other practitioners. When I talk to doctors about the idyllic vision for the future of healthcare, they look at me like I have two heads. They’re feeling swamped just trying to keep up in a world where they see the average patient a few minutes a year, and their problems will only get worse if talk of a physician shortage proves true. Now we want them to go from seven minutes a year to 525,600 (the number of minutes in a year) for each patient? Yeah, right.

Even if doctors and other practitioners sign up for this new world of healthcare, every support system will have to change. Computer systems will have to be set up to do the vast majority of monitoring. Software will have to be written. A new class of data analysts will have to be developed. Health practices will have to reshape themselves around data streams. Insurers will have to adjust coverage. Courts will have to sort out where liability for mistakes falls – with a programmer, a doctor, someone else?

You could start the clock now on all these changes in medical practices, and they’d still take years to sort out.

The key issue to monitor in the progress of wearables is the sensors. Once someone can easily capture blood pressure information or conduct some important blood test without breaking the skin, well, then we’re talking. At that point, consumer adoption will be a solvable problem. So will adoption by medical professionals, though that will be a long slog.

In the meantime, we will soon be able to buy our Apple watches, and we’ll have fun with them. We might even get a little healthier if we keep wearing the things and somehow feel the need to walk a bit more. But that shiny vision of a world where care, insurance and everything else about health changes because of wearables? That’s still a long way out there.