I’m the founder and CEO of WorkersCompensationOptions.com (WCO), a company dedicated to workers’ compensation (WC) and its legal alternatives. This letter is intended to quell the concerns of employees in our client companies—employees who may have been distressed by the recent (mostly negative) publicity from ProPublica and NPR regarding options to WC in Texas and Oklahoma. In case you only saw one installment from the Insult to Injury series, I’ll provide a quick summary. In 2014, the project's authors started to assimilate massive amounts of data from their research concerning each state’s (and the federal government’s) WC system. In March 2015, the authors began releasing articles with an indisputable premise: Collectively, these systems need improvement. That commendable beginning eventually gave way, however, to a hypothesis that is supported neither by reality nor by the overwhelming quantity of data the authors provide. Their conclusion (that employers are in cahoots with insurers to pressure attorneys, anonymous doctors and legislators into discarding the lives of an unfortunate few for the sake of bolstering corporate profits) completely misses the mark in pinpointing why so many WC systems are broken beyond repair. In fact, attorneys and doctors put at least as much pressure on WC systems as insurers, and any attempt to depict the medical and legal communities as innocent bystanders in the WC feud is simply too naive to be taken seriously.[1] I do not doubt the authors’ sincerity in addressing a serious societal problem, but I also do not believe they are equipped to understand the problem they sought—however earnestly—to demystify for their readers. Worse yet, I fear they have positioned themselves in the WC space in a manner that is only likely to retard the implementation of practical solutions. This letter is prompted by the article on Oct. 14, 2015, which painted an inaccurate—even an irresponsible—picture of both Texas nonsubscription (TXNS) and the Oklahoma option (OKO). As that article’s title (“Inside Corporate America’s Campaign to Ditch Workers’ Comp”) is lengthy, I’ll shorten it to CDWC going forward. Texas Nonsubscribing Employees: What Can We Learn? Texas is exceptional in the WC world because it has, for more than a century, offered employers a viable alternative to WC. Of approximately 380,000 employers in Texas, roughly two-thirds subscribe to a traditional WC system; the other third are nonsubscribers who develop their own models. That’s about 120,000 different systems, and there is plenty to be learned. We’ve seen various organically grown components develop from these disparate systems, many of which superficially resemble WC. Despite those similarities, however, industry experts understand how counterproductive it is to make unilateral comparisons between TXNS and WC. The authors of CDWC didn’t get that memo. Of all the various lessons learned from diverse TXNS models, one runs counter to conventional WC dogma: Employers can protect themselves while delivering superior care for employees at a fraction of the cost of WC. Eliminating the inflated costs associated with abusive practices that run rampant in WC is a critical component of that particular lesson. Because the CDWC authors insist on judging TXNS through the lens of WC, TXNS looks to them like a system that would appeal to skinflint employers who simply do not care whether their employees get hurt. However, because employees of nonsubscribing companies can sue their employers for tort, the decision to opt out of WC is likely to be penny-wise and pound-foolish for employers who do not take measures to ensure the safety of employees. The CDWC authors’ failure to unpack the importance of tort negligence means many readers will come away from the article without understanding that a typical $50,000 payout in WC could easily be either $0 or $5 million in TXNS—depending on who is at fault for the accident. Even more disappointing is CDWC’s attempt, in a one-sentence paragraph, to gloss over one of WC’s most dangerous shortcomings: the extent to which the no-fault arrangement between employers and employees has removed incentives for safety in the workplace throughout the country. If you are an employee of one of our Texas nonsubscribers, rest assured that your employer has every reason to minimize workplace accidents and to take very good care of you if an occupational injury occurs. In a nutshell, your interests are aligned with your employer’s—another critical lesson we’ve learned from TXNS. Oklahoma Option Employees: A Whack-a-Mole WC System Led You Here ProPublica and NPR harp on a consistent theme throughout the Insult to Injury series: WC is broken. We at WCO agree, and Oklahoma may provide the single best example of how and why a state’s WC system becomes unsustainable. The WC ecosystem is made up of five major communities: insurance, medical, legal, employer and employee. Abuse within the system by any of these communities leads to adjustments to the boundaries of the system. Throughout the Insult to Injury series, the authors go out of their way to sidestep the discussion of systemic abuse. They even attempt to dismiss fraud by citing a study that minimizes its role. Abuse and fraud in WC are, in some ways, analogous to speeding on the highway: Almost all drivers abuse the speed limit, but very few are issued citations. Similarly, the cases of clear-cut fraud in WC only reflect a small portion of the amount of abuse going on. But even if we allow the authors to exclude all instances of clear-cut fraud from the WC conversation, we are still left with rampant abuse driven by insidious systemic incentives. For decades, abuses and inefficiencies within the WC system have led to each of the five communities touting the need for major reforms—at the others’ expense. Real reform threatens each community, which leads to stalemates in negotiations. Major upheaval has been avoided via the compromise of pushing and pulling the system’s boundaries, resulting in a decades-long game of whack-a-mole being played across the nation. If one voice cries, “Data shows an alarming trend in opioid abuse,” that mole gets swatted by requiring more medical credentials for prescribing pain killers. When another shrieks, “Overutilization is surging,” that mole is whacked through costly and time-consuming independent medical examinations. When someone else observes, “Our disability payouts are higher than neighboring jurisdictions,” that mole prompts us to lower disability payouts. Immediately, a fourth voice shouts, “Pharmaceutical abuses make up 8.4% of total costs,” and that mole persuades us to introduce drug formularies. But there isn’t even a moment of silence before another voice remarks, “Our analysis shows dismemberment payouts in this jurisdiction are lower than those of our neighboring jurisdiction.” That mole gets whacked by proposing legislation to increase dismemberment payouts—legislation that is dead on arrival.^[2] At some point, we have to realize the moles are multiplying faster than we can whack them. (If my commentary doesn’t apply to other jurisdictions, I’m happy to restrict it to Oklahoma and Texas because writers can best serve their readers by acknowledging the limitations of their own expertise.) Even if we concede that the changes detailed in the paragraph above aren’t necessarily bad (which I’m not conceding; I’m just trying to be polite and move the argument along), they demonstrate a persistent pattern of outcomes, inclusive of abuse, inherent in any hierarchical bureaucratic system. Regulators are busy reacting to entrenched abuses while market participants find new and exciting ways to game the system. This futile game of whack-a-mole is endless. The Sooner State had a front row seat to witness what TXNS accomplished—both the good and the bad.[3] With that first-hand knowledge, the Oklahoma legislature has finally provided the state—and the country—with an opportunity to see whether real change can restore function to a malfunctioning system. While WC stakeholders assure us they are only a few more whacks-at-the-mole away from making WC hum, Oklahoma lawmakers have written a new chapter in the history of workplace accident legislation. The OKO is neither WC nor TXNS. The brilliance of the OKO is that it doesn’t attempt to overhaul a broken WC system. The legislators effectively stepped away from that decades-old stalemate. Instead of an all-out overthrow, they left WC in place and created an option for employers who were willing to try something new—which is exactly how WC itself was introduced a century ago. Because the OKO is substantially modeled on TXNS, it is easy to see why the CDWC writers conflated the two in their analysis. The errors in CDWC concerning ERISA’s applicability, employee benefits and appeals committee processes in Oklahoma are all presumably honest mistakes made by writers who, in their zeal to distinguish TXNS and the OKO from WC, failed to distinguish TXNS and the OKO from each other. Nevertheless, it’s important for employees to understand that TXNS varies dramatically from one employer to another, and many of the rules concerning TXNS do not apply north of the Red River. Although the CDWC authors misleadingly couple TXNS and the OKO with respect to ERISA’s applicability, ERISA plays no direct role in occupational accidents in the OKO.^[4] We’ll be happy to get you a legal opinion on that, but for our purposes regarding CDWC, take my non-legal opinion as on the record. If others disagree, they should go on the record, as well. While ERISA has served employers and employees well in TXNS, its role in the OKO is only implied (if that). We are free to use it where we wish, as long as we are compliant at the state level. Presumably tied to their ERISA misapplication, the CDWC authors assert that “benefits under opt-out plans are subject to income and payroll taxes.” Such tax advice is unusual from investigative journalists without citation, and I have asked the authors to share their source. Although the jury is still out on this tax issue, it is a point the CDWC authors must distort to substantiate their otherwise baffling claim that the workplace accident plans of OKO employers “almost universally have lower benefits.”[5] If any OKO plans really do offer benefits that aren’t at least as good as those provided by WC, they’re illegal. That’s how the legislators have written the law, and it’s what they’re dedicated to achieving for workers, regardless of obfuscations invoking TXNS, ERISA and unresolved tax implications. The authors of CDWC also completely misrepresent appeals committees for at least a majority of OKO employers. The authors overlook a dramatic improvement to employee protection that the OKO makes to TXNS when they claim that appeals committees in Oklahoma work analogously to appeals committees in Texas: “Workers must accept whatever is offered or lose all benefits. If they wish to appeal, they can—to a committee set up by their employers.” That’s dead wrong. Executives at each of our OKO employers are fully aware that, in case of an employee appeal, the employer has nothing to do with the selection of the appeals committee panel members or the work they complete. The process is independent from the employer and extremely fair.[6] The CDWC authors would do well to read Section 211 of the law more carefully. On the subject of benefit denials, I’ll share a single data point from our OKO book: To date, we have denied exactly one claim. This is a nascent system, so we must be very careful in drawing actuarial conclusions. Still, our company has led more employers from traditional WC into the new OKO than any other retailer, so we have a bit of credibility to offer on this subject. The point of the system isn’t to deny benefits to deserving employees but to ensure benefits are delivered more efficiently. The system is working. The CDWC authors only provide one OKO case study, Rachel Jenkins. Strangely, they lump Jenkins in with four TXNS case studies. The Jenkins case is still being tried. We will withhold opinions—as we hope others would—until a more appropriate time. As a reminder, while the OKO law is stronger today than ever, if it were to be deemed unconstitutional by the Oklahoma Supreme Court, we would have 90 days to get everyone back into traditional WC (per Section 213.B.4.). Next: Vigilance and Diligence My comments are mine and mine alone. I do not speak for any associations or lobbyists. I have no interest in debating those who inexplicably assume that any alternatives proposed to a failing system must stem from sinister motives. However, I encourage anyone (from prospective clients to employees of existing clients) with questions or concerns to call me. Another option for learning more is to click here and watch a formal debate regarding the OKO. This footage was shot in September 2015. It features Michael Clingman arguing against the OKO while I, predictably, argue for it. One thing you can’t miss in that video is my desire to oust most attorneys from the scene. To help explain, I’ll adapt a quotation from John F. Kennedy (who was discussing taxation) to my own area of concern (the well-being of employees): “In short, it is a paradoxical truth that employee outcomes from increased WC protections are worse today, while economic results suffer, and the soundest way to create higher and better standards of living for employees is to eliminate these abused protections.” For philosopher kings, the theory of the OKO may not sound as good as the theory of WC, but when it comes to practical realities the results demand everyone’s attention. To summarize my primary criticism of Insult to Injury, it simply hasn’t done enough. The story it tells is insufficient and smacks of partisanship and ideology, two biases that ProPublica’s journalists allegedly avoid. WC is substantially more complex than a corporation-out-to-exploit-its-workforce short story. Ignoring abuse in each of the communities in a five-sided WC debate demonstrates a lack of journalistic impartiality and a stunning deficiency of perception. Moreover, to my knowledge, ProPublica hasn’t crafted any relevant suggestions for legislation, simply leaving its readers with the vague and implicit notion that federal oversight is needed. If that is the goal of Insult to Injury—to provide one-sided, emotional yarns alongside a treasure trove of data, hoping it will all spur some federally elected officials to create real change at long last—then I suspect ProPublica will still be holding this subject up to the light of opprobrium upon the retirement of each of the series’ authors. We do not aspire to win over the authors or even their followers. We will focus our energies each day on providing the best workplace accident programs for employers and employees alike. Our results should speak for themselves. Finally, I am not an attorney, and nothing in this letter should be taken as legal advice. Sincere regards, Daryl Davis Footnotes: [1] With medical providers, overutilization is always a concern. Click here and watch the video from the 12-minute to the 15-minute mark for a detailed description of rampant WC abuse by surgeons who provide unnecessary and damaging back procedures. If the workers weren’t disabled prior to the surgeries, many were afterward. As for the legal community, simply view slide 73 of the NCCI’s 2013 Oklahoma Advisory Forum. WC disability payments, which is where attorneys get their cut, were 38% higher in Oklahoma than in neighboring states—not because jobs are 38% more dangerous in Oklahoma than in Kansas or Texas but because Oklahoma attorneys are 38% more effective at gaming the state’s WC system. [2] Alabama SB 330—which was prompted by Insult to Injury—never got out of conference. From what I could gather, lengthy negotiations between several different interest groups led nowhere, with the Alabama Medical Association at the center of this particular stalemate. Not surprisingly, the two special sessions called by Alabama Gov. Bentley in 2015 were strictly focused on the state’s budgetary crisis; this bill was never discussed. [3] The final Texas case study offered in CDWC deals with Billy Walker, who fell to his death while on the job. The upside to TXNS is his estate’s common law right to pursue a tort lawsuit against his employer. The employer could have been ordered to pay Walker’s estate a settlement in the millions, but the employer filed bankruptcy before any such judgment could be awarded, which is plainly an unacceptable outcome. This demonstrates a lack of surety—the single biggest problem in TXNS. OKO addresses this issue in various ways, most notably in Section 205 of Title 85A, which guarantees surety for injured workers. [4] For the non-occupational components of your OKO program, ERISA does apply. [5] Per Section 203.B. of the statute, compliant plans “shall provide for payment of the same forms of benefits included in the Administrative Workers' Compensation Act for temporary total disability; temporary partial disability; permanent partial disability; vocational rehabilitation; permanent total disability; disfigurement; amputation or permanent total loss of use of a scheduled member; death; and medical benefits as a result of an occupational injury, on a no-fault basis, with the same statute of limitations, and with dollar, percentage and duration limits that are at least equal to or greater than the dollar, percentage and duration limits contained in Sections 45, 46 and 47 of this act.” (Emphasis mine.) [6] Details of OKO appeals committee procedures are generally misunderstood—for now—by plaintiffs’ attorneys (and, apparently, investigative journalists). Attorneys frequently assume that, because the employer foots the bill, the employer controls the process. For a peek at how the appeals committee process really works for a majority of OKO employers, those curious should watch this video.

If you are a CFO or HR professional reading this article, you are probably familiar with the typical renewal discussion with your employee benefits broker. It goes something like this: Broker: "Well, the insurance company initially wanted a 12% increase." You: "How can that be? We have performed fairly well this year." Broker: "I agree, so we went back to the insurance company and negotiated the increase down to 5%. That is two percentage points below the industry average, so I suggest we lock it in and wrap up the renewal." This conversation happens all too often. Cost increases are the norm in the health insurance industry, and employers are satisfied with merely beating industry averages (while brokers are receiving pay raises because of commissions on the higher premiums). By accepting these terms, employers may be overlooking a big problem. See Also: 7 Tools for Cutting Insurance Costs in 2016 Let's pretend the data below is your three-year insurance summary. Take a look and determine if you have had a successful run.

• Enrolled employees: 300
• Total health plan costs: $3.5 million
• Average annual cost increase: 2.5%

At first glance, it would appear that you had a pretty successful stint. A 2.5% average over the past three years is definitely beating industry averages. So what is the problem? A closer look shows you are spending more than $10,000 per-employee-per-year (PEPY). Was this really a successful three-year run?  No. You should be ticked off with this performance. because YOU WERE PAYING TOO MUCH TO BEGIN WITH. For comparison, the average cost of providing a group medical plan in the state of Colorado is $8,160 PEPY. The average cost of providing a group medical plan in the U.S. is $9,504 PEPY.. By spending more than $10,000 PEPY, you are spending more than the average U.S. employer and significantly more than the average employer in Colorado. Now, plan costs can differ based on industry and location, but the message here is clear. Do not be satisfied with merely beating industry averages. It is too easy to be satisfied when you are only comparing your current costs with your previous costs. If you are an employer that is already spending too much, it is time to challenge your broker and the status quo. Dig in and find out why you are paying too much, and begin implementing the appropriate cost-containment strategies that will help you reverse the cost increases (albeit small) that have affected your plan for far too long.

In my last post, I described the state of the life insurance industry, including the pain points where InsurTech entrants are poised for impact. The life insurance industry is suffering from a dying (literally) distribution model, complex products and a flawed purchase funnel. New entrants can transform the industry by bringing a clean-sheet approach to:

• Putting the client at the center of the business
• Prioritizing the direct-to-client experience, including simpler products and path-to-purchase
• Launching businesses on a back-end that enables low-cost, fast issuance and personalized underwriting and offers
• Creating business models that align carrier and client interests and flex beyond protection-after-the-fact to providing value through prevention services
• Supporting multi-channel servicing and claims management that satisfy clients
• Using data responsibly to be proactive, personalized, timely, cost-effective and relevant
• Treating life insurance as part of the client’s broader financial plan, including the connection to anticipating one’s healthcare requirements and managing the drivers, to the extent these are controllable, of health problems
• Aligning with the demographic trends (the boomer handoff to the millennial generation and the emergence of the new majority in the U.S.) and the technology trends (mobile as the main screen; the role of social media in the client experience; and the application of big data to change the experience and business model)
• Disproving orthodoxies that have become barriers to innovation for the sector, i.e., “insurance is sold not bought,” “the agent is the customer,” et al.

As much as start-ups are emerging and being funded aiming at health, home and auto, much less attention is being paid to either life insurance or its sibling, long-term care. One founder/CEO with whom I spoke this week had two possible explanations: (1) Life insurance is the stepchild of the sector, and (2) the “sold not bought” orthodoxy is embedded, even among start-ups, which are typically seen as better not only at casting aside such self-imposed obstacles but seizing upon them as open doors for disruption. These factors may be deflecting entrepreneurial energy and attention in other directions. See Also: InsurTech Can Help Fix Drop in Life Insurance Long-term care has been a challenging product for traditional carriers, with players either abandoning the product or re-pricing and reconfiguring their products as flaws in earlier underwriting have become clear. According to Consumer Reports, between 2007 and 2012, 10 of the 20 top long-term-care providers stopped selling the product, and those in the business began raising rates, some reportedly as much as 90%, to address high claims projections. That said, there are new ventures worth watching, and the good news about the relatively low level of attention being paid to life insurance, for those who see ignored space as white space, is that there could be more opportunity to succeed for those who engage. Here are a few start-ups focused on the valuable white spaces: In stealth mode are three companies worth keeping an eye on:

• Sureify Labs is focused on “bridging the gap between insurers and their current and future policyholders” through a B2B offering aimed at helping traditional carriers move into the new world. The company’s site states that the platform “starts with consumer web and mobile applications that drive engagement through device-integrated wellness, savings and rewards programs tied to a policy. Behind the scenes, we give you as the carrier all the tools necessary to engage, communicate and up-sell your policyholders through digital mediums.” This sounds as though it would be a dream come true for carriers that are serious about building client-centric businesses.

• Ladder, formed just a year ago (see: CB Insights report) is reportedly starting with a mobile value proposition built around easier and faster access to term life insurance, using available, permissible data sources to improve the underwriting process. If, as the name suggests, the company is building a value proposition that redefines the traditional notion of an insurance ladder – a construct that lets you plan for extra coverage when you'll need it the most and taper off coverage at other times – I would expect them to develop more dynamic, effective relationships with clients than those propagated by the traditional one-and-almost-always-done insurance sales model.

• Human Condition Safety (HCS’ site is under construction) is an example of a start-up focused on expanding the value a life insurance carrier can provide by offering prevention services in addition to protection. AIG became a strategic investor in the company earlier this year. HCS is said to be “developing wearable devices, analytics and systems to improve worker safety.”

A number of start-ups are building capabilities to solve carrier problems improving on the traditional distribution and product models. An investor might ask if these are businesses or features:

• Force Diagnostics is focused on “combining science and a customer-centric streamlined process” to transform health and wellness screening. The expense (to the carrier), hassle (to the applicant) and elapsed time (a burden to all) associated with today’s underwriting requirements for blood and urine samples are ripe for reinvention.

• Insurance Social Media, part of Serious Social Media, is offering a “set it and forget it” capability to improve agent effectiveness on social media. Given the demographic profile of the average agent (57 years old, and accustomed to pushing product), kick-starting their social media presence and providing relevant content solve pain points for today’s distributors. Of course, two questions regarding any start-up aiming to mass-produce content are: first, can such content come across as authentic, and second, how does this model scale?

• Insquik offers agents a white label solution to create their own online stores. The focus is on term life automatic issuance up to $350,000 face value, and, according to the company’s site, aims specifically to serve the sub-segment of agents who “have access to large populations of consumers i.e., focused on Worksite Employee Benefits, Affinity Groups, Unions, Groups and Associations.”

• Fitsense is a start-up coming out of StartupBootcamp that is building a data analytics platform focused on enabling insurance companies to reduce premiums “for anyone with a smartphone or wearable device.”

• Sure provides a digital front-end and a more real-time experience for an old idea – a micro-duration life insurance policy that provides coverage during air travel. (In the pre-digital era, this was simply called “per trip coverage”.) American Express is one company that for more than 30 years offered air flight life insurance policies at varying face amounts, as part of a portfolio of travel-related protection benefits.

The opportunity for Insurtech to expand efforts in the life insurance category is not simply the commercial potential of disrupting a model that has proven its limitations. It is also the prospect of addressing a societal need that has been neglected for decades. These are two compelling reasons to encourage more participation by investors and entrepreneurs, stimulating a bigger pipeline of entrants to take on the reinvention of the category.

The Institute of Leadership & Management (ILM) published a report titled “Coaching for Success: The key ingredients for coaching delivery and coach recruitment.” There’s plenty of interesting snippets of research findings and practical advice. If you have time, it is well worth a read, but the points that caught my eye were a three-stage process for coach selection. I agree with the ILM that the selection of coaches often still lacks a robust structured process and so am going to share their recommended process as a good example. This process can be used by individuals for themselves or by someone selecting on behalf of an organization. It assumes that a long list of possible coaches has already been found. To achieve that, you could go as Wild West as a general Google search on "coach"/"leadership coach"/"executive coach." However, I’d recommend starting with a pre-qualified list like the Association for Coaching (AfC) directory of coaches or equivalents from other coaching bodies. Here are the stages that the ILM recommends, to be used like a checklist of questions to ask (I've added what I’d say if asked): Stage 1: Long-list to Short-list

• What experience of coaching does the coach have? (I could evidence my number of coaching hours and cite previous mentoring experience within a large corporation)
• Can the coach demonstrate an understanding of the leadership challenges in your industry? (I’ve found some clients value my experience in customer insight leadership or within the insurance industry)
• What training do they have? (I could evidence my ILM Level 7 qualification in Executive Coaching and Mentoring)
• What ethical standards do they work to? (I share with clients a copy of the AfC code of ethics and explain that I abide by that)
• What supervision does the coach have in place? (I use AfC/University of South Wales co-coaching forums)

Stage 2: Getting down to the last few

• What coaching methodologies does the coach use, when and why? (my primary tools are active listening, Socratic questioning, goal-oriented models and, where relevant, positive psychology tools like Strength Finders)
• What price do they charge? (average fees can vary around the country, but between £100-250 per hour is typical; I normally charge £150 per hour)

Stage 3: Final selection

• What does the coach he can achieve for the individual coachee/client? (this is where a free introductory meeting can help me clarify where I may be able to help or if another intervention other than coaching might help more)
• What do they believe they can achieve for the organization? (it’s always worth doing your homework on an organization and discussing context with a client, before you can offer a view on this)
• Will the coach and the coachee/client get on? (at the end of the day, a lot comes down to personal chemistry, so I will meet up for a chat over a coffee and let us both assess if we feel it can work)

I hope you find that helpful, especially if you are facing this challenge. The ILM also suggests that competency frameworks from leading global coaching bodies can help, but I like the clear simplicity of the above list. Has anyone found another approach to selecting a coach worked for them? Please share your experience.

Arthur C. Clarke, who knew a thing or two about futuristic technology, observed, “Any sufficiently advanced technology is indistinguishable from magic.” His observation certainly applies to driverless cars. In a recent Forbes article, I made the case that strategists, policy makers, regulators and other stakeholders needed to exercise “patient urgency” in balancing the hope and fear inspired by driverless cars. It is worth highlighting the hope—in the form of the seven huge societal benefits that driverless cars would deliver. It is a magical list. 1.  Reduce injuries and deaths Americans were in more than 6 million police-reported car crashes in 2014. As a result, more than 2.3 million individuals suffered serious injuries, and 32,675 were killed. Worldwide, more than 50 million people are injured each year, and more than 1.2 million are killed. Globally, road traffic crashes are a leading cause of death among young people, and the main cause of death among those aged 15–29 years. Human error caused more than 90% of those crashes, and, in recent years, accident and fatality rates have gone up—due in large part to distracted driving. See Also: How to Picture the Future of Driverless Driverless cars, which promise to see better and react faster than humans while never getting sleepy, drunk or distracted, offer the possibility of dramatically reducing driver error and the resultant human suffering. Consider the relative magnitude of success: A 25% reduction in auto-accident-induced fatalities would save more lives than curing leukemia; a 75% reduction would save more lives than eliminating suicide. 2.  Lower accident-inflicted costs The economic cost of driver error is also horrific. NHTSA estimated in 2010 that vehicle accidents inflicted $242 billion in economic costs (medical costs, property damage, lost productivity, legal and court costs, emergency service costs, insurance administration costs, congestion costs and workplace losses). The total cost rises to $836 billion when the impact to quality of life is taken into account. Globally, the World Health Organization estimates that 3% of GDP is lost to road traffic deaths and injuries. These costs are inflicted not just on those involved but also on society as a whole. Each year, in the U.S., more than $218 billion is spent on auto insurance premiums. Motor vehicle accidents also make up one of the largest categories of disability and workman’s compensation claims. Worldwide, approximately $700 billion is spent on auto insurance. 3.  Reduce resource consumption Driverless cars offer the hope of tremendous savings beyond the high price of accidents. Donald Shoup estimates that 30% of urban center traffic is due to drivers looking for parking. Driverless cars could deliver their passengers to their destination and drive away, eliminating the need to hunt for parking or walk back to the office. Morgan Stanley estimates that avoiding congestion due to the hunt for parking could translate into $11 billion in fuel savings across the U.S. each year. This $11 billion is the smallest category of efficiency and accident cost avoidance delivered by this technology. By Morgan Stanley’s estimate, the total savings in the U.S. could reach $1.3 trillion. 4.  Reduce transportation cost Driverless cars could enable driverless taxi services at prices much lower than individual car ownership or human-driven car services. KPMG, for example, estimates that such services could cost 48% less than the cost of individual car ownership on a per-mile basis—while also eliminating the high up-front cost and the time required for maintenance and regulatory compliance. Similarly, in a study at Columbia University’s Earth Institute, Larry Burns and William Jordon estimate that driverless taxis would offer 90% savings over human-driven car services. Considering that the average American household spends 19% of income on transportation (the largest category after housing), these cost savings will make a tangible difference in every American’s life. 5.  Enhance quality of life The reduced cost of mobility coupled with the availability of high-quality, on-demand, point-to-point transportation would enhance freedom, independence and self-reliance for many seniors and people with disabilities. It would also reduce the substantial burden on the individual, family and community caregivers. An estimated 8.4 million seniors in the U.S. cannot drive. As baby boomers age, the number of seniors is expected to grow quickly, effectively doubling from 43 million in 2012 to 82.3 million in 2040. 12% of the roughly 50 million Americans with disabilities report difficulty getting the transportation that they need, with the reason cited most often being no or limited public transportation. Those who could otherwise drive would benefit, as well, through increased productivity and reduced stress as chauffeured passengers instead of drivers. The typical American commuter, for example, could use the 50-minute daily commute for in-car work and leisure rather than having to focus on driving. For America’s 120 million workers, that adds up to 6 billion minutes per day. 6.  Increase economic mobility For the poor and economically disadvantaged, more affordable mobility would enable increased economic mobility by allowing faster and cheaper transportation to jobs in a wider geographical region—especially to those areas not well-served by public transportation. A longitudinal study conducted by Raj Chetty and Nathaniel Hendren at Harvard has shown that commuting time is the most important factor to the odds of escaping poverty. New York University’s Rudin Center for Transportation conducted a study that came to a similar conclusion. Autonomous vehicles would not only give disadvantaged Americans access to better job opportunities, but also better access to schools, stores and services. 7.  Accelerate Vehicle Electrification 92% of American transportation is dependent on petroleum. Not only does burning this fuel create pollution, but it also makes America dependent on foreign suppliers. Autonomous vehicles offer a remedy, because they will in most cases be electric. There is a virtuous cycle in which autonomous vehicles lead to vehicle sharing, which in turn leads to high vehicle utilization, favoring the low marginal cost of electric vehicles. This would not only cut emissions and pollution from vehicles but also dramatically cut petroleum dependency.

* * *

As I’ve previously acknowledged, a vast number of technical and implementation challenges have to be overcome before these societal benefits can be reaped. World-class engineers and scientists stand on either side of the question about whether these challenges can be adequately addressed. Arthur C. Clarke was one of the believers. Clarke predicted in 1962 that “the automobile of the day-after-tomorrow will not be driven by its owner, but by itself.” See Also: Lack of Enthusiasm for Driverless Cars? More generally, Clarke also had something to say about seemingly impossible challenges. He observed, “The only way of discovering the limits of the possible is to venture a little way past them into the impossible.” As to the arguments of world-class engineers and scientists, Clarke had this to offer: When a distinguished but elderly scientist states that something is possible, he is almost certainly right. When he states that something is impossible, he is very probably wrong. Let’s hope that the distinguished Arthur C. Clarke was right.

Election-year politics are dominating legislative action this year as both parties lay down policy agendas for 2017 and beyond. President Obama and the Republican leaders of Congress are offering competing plans on how to reform the U.S. tax system and how to promote other policies intended to increase economic growth and make American companies more competitive. At the same time, both Democratic and Republican candidates seeking their party’s presidential nomination are advancing tax reform plans. During his final year in office, President Obama likely will continue to rely on his administration’s regulatory authority and the presidential veto to preserve the 2010 Affordable Care Act (ACA)—as well as other legislative and regulatory actions taken during his years in office. Obama administration action On Feb. 9, President Obama submitted an FY 2017 budget to Congress that reaffirmed his support for “business tax reform” that would lower the top U.S. corporate tax rate to 28%, with a 25% rate for domestic manufacturing income. Significant international tax increase proposals that have been re-proposed include a 19% minimum tax on future foreign income and a one-time mandatory 14% tax on previously untaxed foreign income. The president’s budget, again, reserves revenue from a large number of previously proposed tax increases to support business tax reform—including specific proposals affecting insurance taxation (discussed below)—but his budget identifies only part of the revenue that would be needed to support his proposed corporate rate reductions. Congressional action House Speaker Paul Ryan (R-WI) has called for House Republicans to vote in 2016 on comprehensive tax reform legislation and on changes to federal entitlement programs as a way to define and build support for a conservative legislative agenda. Senate Majority Leader Mitch McConnell (R-KY) is also expected to advance a conservative legislative agenda with a focus on demonstrating an ability to govern and with an eye on protecting the Republican Senate majority. See Also: 19 Specific Taxes Directly Related to Healthcare Reform House Ways and Means Committee Chairman Kevin Brady (R-TX) recently outlined his goals for producing a blueprint for comprehensive tax reform and plans to “move forward immediately to draft international tax reform legislation.” Chairman Brady has said he hopes the Obama administration and Congress can reach common ground on some policies and build on the momentum from the last year’s “tax extender” legislation, which included a provision making permanent Subpart F exceptions for active financing income. Chairman Brady said comprehensive tax reform “will not happen until we have a new president,” but he is “hopeful that, next January, we will have a president—Republican or Democrat—who is committed to making pro-growth tax reform a reality for the American people.” The chairman outlined several principles for comprehensive tax reform, including a “competitive tax rate” and a “permanent, modern territorial-type system that helps American companies compete and win overseas.” He also said the Ways and Means Committee will look, “with fresh eyes,” at a range of tax ideas, including “consumption tax, cash flow tax, reformed income tax and any other approach that will be pro-growth.” On international tax reform, Chairman Brady said “developments in the global environment demand our immediate attention.” He pointed to OECD  “base erosion and profit shifting” (BEPS) proposals that “disproportionately burden American companies” and the European Commission anti-tax avoidance package that would provide EU member countries with an “arsenal of new revenue-grabbing tax measures.” He also discussed the growing number of corporate inversions and foreign acquisitions involving U.S. companies: "We will send a clear signal to American companies and shareholders that help is on the way—that we won’t stand idly by while our tax code drives them overseas or makes them a target for a foreign takeover." Senate Finance Chairman Orrin Hatch (R-UT) has said he “doubts very much” that international-only tax reform can be enacted this year. The Finance Committee Republican majority staff has been working on options for corporate integration tax reform proposals that would seek to eliminate the double taxation of corporate earnings. Corporate integration proposals generally have focused on approaches providing that any distributions made by such entities would either be deductible by the entity (dividends paid deduction) or would be excludable by the recipient (dividend exclusion). A December 2014 report prepared by the Senate Finance Committee Republican staff stated that a dividends-paid deduction “would generally be easy to implement and would largely equalize the treatment of debt and equity.” Chairman Hatch recently asked Treasury Secretary Jack Lew to “keep an open mind” to a corporate integration proposal that might help to make U.S. corporations more competitive globally and could reduce inversions. Although there is bipartisan agreement that the U.S. corporate tax rate should be lowered significantly and that our international tax system should be updated, there is significant disagreement over key business tax issues, including how to offset the cost of a corporate rate reduction. See Also: How a GOP Congress Could Fix Obamacare Insurance-related revenue raisers The Obama administration’s FY 2017 budget re-proposes several revenue-increasing measures specific to insurance companies. The proposed legislative changes generally would apply for tax years beginning after Dec. 31, 2016. Among the insurance-related measures are provisions that would:

• Disallow the deduction for non-taxed reinsurance premiums paid to affiliates — This proposal would disallow any deduction to covered insurance companies for the full amount of reinsurance premiums paid to foreign affiliated insurance companies with respect to reinsurance of property and casualty risks if the premium is not subject to U.S. income taxation. The proposal would provide a corresponding exclusion from income for reinsurance recovered, with respect to a reinsurance arrangement for which the premium deduction has been disallowed. The proposal would also provide an exclusion from income for ceding commissions received with respect to a reinsurance arrangement for which the premium deduction has been disallowed. The exclusions are intended to apply only to the extent the corresponding premium deduction is disallowed. The proposal would provide that a foreign corporation that is paid a premium from an affiliate that would otherwise be denied a deduction under this provision may elect to treat those premiums and the associated investment income as income effectively connected with the conduct of a trade or business in the U.S. If that election is made, the disallowance provisions would not apply.
• Conform net operating loss rules of life insurance companies to those of other corporations — This proposal would modify the carry-back and carry-forward periods for losses from operations of life insurance companies to conform the treatment to that of other taxpayers. Under the proposal, losses from operations of life insurance companies could be carried back up to two taxable years prior to the loss year and carried forward 20 taxable years following the loss year.
• Modify rules that apply to sales of life insurance contracts, including transfer for value rules — This proposal would create a reporting requirement for the purchase of any interest in an existing life insurance contract with a death benefit equal to, or exceeding, $500,000. The proposal would also modify the transfer for value rule to ensure that exceptions to that rule would not apply to buyers of policies.
• Modify dividends received deduction for life insurance company separate accounts — This proposal would repeal the present-law proration rules for life insurance companies and apply the same proration regime separately to both the general account and separate accounts of a company. Under the proposal, the policyholders’ share would be calculated based on a ratio of the mean of the reserves to the mean of the total assets of the account. The company’s share would be equal to one less than the policyholders’ share.
• Expand pro rata interest expense disallowance for company-owned life insurance (“COLI”) — This proposal would curtail an exception to a current law interest disallowance of a pro rata portion of a company’s otherwise-deductible interest expense, based on the un-borrowed cash value of COLI policies. As modified, the exception would apply only to policies covering the lives of 20% owners of the business. The proposal would apply to contracts issued after Dec. 31, 2016, in tax years ending after that date.
• Repeal special estimated tax payment provision for insurance companies under section 847 — This proposal would repeal IRC Section 847 and would include the entire balance of an existing special loss discount account in income in the first tax year after 2016. Alternatively, the proposal would permit an election to include the balance in income ratably over four years. Existing special estimated tax payments would be applied.

Insurance Developments: Judicial and Administrative A number of judicial and administrative developments occurred in 2015 concerning insurance companies. These developments affected insurers in various lines of business:

• Life insurers: The most significant development for life insurers was not solely a tax development. Life principal-based reserves (PBR) will be effective when 42 states representing 75% of total direct written premiums amend their standard valuation law. At the current rate of adoption, Life PBR is expected to be effective Jan. 1, 2017, for contracts issued on or after that date. Life PBR will implicate a number of tax issues, and, for the first time, the IRS and Treasury included guidance on Life PBR in its annual Priority Guidance Plan. Also during 2015, the Tax Court decided in Webber v. Commissioner, 144 T.C. No. 17 (June 30, 2015) that a policyholder was liable for taxes on income earned on assets supporting a variable life insurance contract based on the policyholder’s control over the assets. The case accorded deference to a number of the IRS’s “investor control” revenue rulings and could result in closer attention to variable life insurance and annuity contracts that are privately placed.
• Non-life insurers: In 2015, the Tax Court addressed what qualifies as insurance risk for purposes of classifying contracts as insurance contracts. In R.V.I. Guaranty Co., Ltd v. Commissioner, 145 T.C. 9 (September 21, 2015), the court held that residual value insurance (RVI) contracts that protect against an unexpected decline in the market value of leased personal property qualify as insurance contracts for federal income tax purposes. The case’s reasoning relies heavily on the treatment of the contracts by non-tax regulators, and it provides taxpayers further guidance for distinguishing between investment risk and insurance risk.
• Health insurers: In 2015, a Treasury Inspector General for Tax Administration (TIGTA) report criticized the IRS for the “finality” requirement that prevents the service from assessing health insurers that inadvertently or otherwise were not assessed the correct amount (or any) of the health insurance provider fee, which is apportioned among all covered health insurers. Other health insurance providers still wait for the IRS to act on refund requests of the fee in 2015. The ultimate resolution remains uncertain.
• Captive insurance companies: During 2015, the IRS issued two Chief Counsel Advice (CCA) that analyze whether specific types of policies issued by captive insurance companies constitute insurance for federal income tax purposes. In CCA 201511021, the IRS determined that contracts indemnifying the policyholder for loss of earnings resulting from foreign currency fluctuations did not satisfy the three-prong test to be considered insurance because foreign currency risk is not an insurance risk. The CCA was issued before the tax court’s decision in R.V.I. Guaranty Co., Ltd., so it did not take the tax court’s approach into account. In CCA 201533011, the IRS concluded that excess loss policies issued by a captive insurance company that covered healthcare risks of members of unrelated HMOs are not insurance contracts because they lacked the requisite element of risk shifting. Based on the facts as presented, the CCA analyzed the arrangement as an interest-bearing deposit, but it then concluded that receipts were included in income and deductions were allowed for future claim payments when made. Also in 2015, the IRS issued IR 2015-19, which added section 831(b) companies to the “Dirty Dozen” list of tax scams, indicating the IRS would target these companies in examination.
• PFIC exception for income derived in the active conduct of an insurance business: Again during 2015, the IRS proposed regulations that would provide guidance on investment income that is treated as derived in the active conduct of an insurance business and, therefore, not treated as “passive income” under the passive foreign investment company (PFIC) rules. In particular, Prop. Reg. §1.1297-4 would provide that “active conduct” requires that an insurer conduct its activities through its own officers and employees and that investment income be earned on assets held to meet obligations under insurance and annuity contracts. Several comments were submitted on these issues and on the use of a bright line test for whether assets are held to meet obligations under insurance contracts.
• Cross-border reinsurance: The Court of Appeals for the District of Columbia Circuit ruled in Validus Reinsurance, Ltd v. United States of America, 786 F.3d 1039 (2015) that the Federal Excise Tax (FET) on insurance premiums does not apply to retrocessions between two foreign insurers, regardless of whether the underlying risks are U.S.-based. Accordingly, the IRS issued Rev. Rul. 2016-3, 2016-3 I.R.B. 282, which revokes the ruling setting forth the IRS’s prior position on the application of FET on a cascading basis to either reinsurance or retrocession arrangements between two foreign insurers. The Validus decision and Rev. Rul. 2016-3 mark the end of the controversy with the IRS on this issue, and most companies already have submitted claims for refund of previously-paid excise tax on a cascading basis, or they plan to do so.
• Inversions: In 2014, the Treasury Department and the IRS issued Notice 2014-52, which describes regulations the Treasury and IRS intend to issue concerning transactions sometimes referred to as “inversions.” The notice included a “cash box” rule, which targeted taxpayers who engage in certain inversion transactions with foreign corporations and their subsidiaries with substantial liquid assets. As a follow up to that notice, the Treasury and IRS issued Notice 2015- 79, providing more information about the intended regulations. In particular, Notice 2015-79 describes regulations that the IRS and the Treasury intend to issue addressing transactions that are structured to avoid the purposes of §7874 (concerning expatriated entities) and addressing “post-inversion tax avoidance transactions.” The latter notice clarifies that property held by a U.S. insurance corporation and a foreign corporation that is engaged in the active conduct of an insurance business will be exempted from the “cash box” rule. As in prior years, the IRS and Treasury jointly issued a Priority Guidance Plan outlining guidance it intends to work on during the 2015-16 year. The plan continues to focus more on life than property and casualty insurance companies. The following insurance-specific projects were listed as priority items. Many carried over from last year’s plan, including:

• Final regulations under §72 on the exchange of property for an annuity contract. Proposed regulations were published on Oct. 18, 2006;
• Regulations under §§72 and 7702 defining cash surrender value;
• Guidance on annuity contracts with a long-term care insurance feature under §§72 and 7702B;
• Guidance under §§807 and 816 regarding the determination of life insurance reserves for life insurance and annuity contracts using principles-based methodologies, including stochastic reserves based on conditional tail expectations;
• Guidance under §833 (expected to address de minimis MLR relief);
• Guidance on exchanges under §1035 of annuities for long-term care insurance contracts; and
• Guidance relating to captive insurance companies.

Implications

• Election year politics and disagreements between President Obama and Congressional Republicans (notably on how to offset any corporate tax reductions) make domestic or international tax reform unlikely in the coming year.
• President Obama’s FY2017 budget proposes several revenue-increase measures specific to insurance companies. However, it remains to be seen which, if any, of the measures will come into effect.
• Multinational insurers and reinsurers should closely monitor legislative and regulatory developments pertaining to taxation of overseas profits. Both the PFIC regulation and the promised regulations on inversions could have a significant effect on some companies and their shareholders.
• Life insurers should consider the effect of Life PBR tax issues on product development, financial modeling and compliance as they prepare for the Jan. 1, 2017, effective date.
• Non-life insurers with non-traditional lines of business should consider the effect, if any, that the R.V.I. Guaranty Co. case and the two chief counsel advice memoranda on the nature of insurance risk and the presence of risk shifting may have on insurance qualification.
• Captive insurers should be prepared for additional IRS scrutiny as a result of the Priority Guidance Plan item promising guidance, and the inclusion of §831(b) companies in the IRS “Dirty Dozen” list.

Robotic Process Automation (RPA) is very much today's buzz phrase. If you are to believe the press, everyone is afraid robots will take all our jobs—even the popular media is reporting on the "Rise of Robots." (Daily Mail estimated robots will take over five million jobs by 2020, and the Financial Times also threw AI into the mix.) McKinsey says 25% of jobs are likely to go because of this new technology. The War of the Worlds begins! See Also: Of Robots, Self-Driving Cars and Insurance But robots/automation have been part of every stage of industrialization, evolution and revolution. From horses to motor vehicles and auto assembly lines, from bank agents to ATMs, from manual work to macros—there are so many things we have done that automate and ultimately save time by doing things in a more efficient way. In every one of these scenarios, we have moved to new jobs and created new categories. Today is no different. In fact, there are many jobs that didn't exist 10 years ago. This from David Hamman: Regarding robotics, a quick summary from me would include: What it means for insurance (and most other industries)

• Reduced error rate from human processing
• Improved process speed (today you can still only run at the pace of the slowest machine)
• Increased speed—robots don't take coffee, lunch or holiday breaks, so there's a lot less to deal with

Why it works:

• Allows the focus to be on the customer, while the robot does all the "swivel chair integration" (updating lots of systems with the same stuff)

Don't forget:

• Ultimately, you are adding more layers to the ecosystem/architecture. This may give you great full-time equivalent (FTE) improvements, productivity gains and reduced error rates, but long-term strategy should be to switch stuff off and reduce run cost.
• If the underlying systems change, do you need to change your robot configuration?
• The "happy path" is always easiest to map. It's when that path doesn't work that things starts to get more difficult.
• If your remaining FTE are only dealing with exceptions, they likely need to be more skilled and experienced. They also need to be able to pick up in the middle of process quickly to understand the exception and complete the task or set the robot on its way again.
• Automate only the right process. Not everything will be a good candidate, just because you could automate it.
• Don't mistake "rules" with RPA for human judgment' I don't think we are quite there yet, but, with AI, we are learning. It won't be long.

Of course, we just launched the first Robot-Run Insurance Agency, which moves from robotics to robo advice—a whole new world indeed.

For now, there is plenty to dance about and plenty of opportunity and ways how this can be used to drive significant benefit and opportunity. What's your take? Where do you see these best used, and why? Where can we see the positive side of this in terms of exciting new jobs and better experience for employees, agents and customers?

Explosion of data volumes. Interoperability of systems. Large servers in the sky that can analyze enormous amounts of data, compute complex algorithms in real time and communicate in microseconds. Mobile communication through devices that patients, providers and staff all carry all the time. What does this all mean for hospital operations? Based on our work with dozens of hospitals and conversations with 100-plus others, we think the near future of hospital operations is quite exciting. Call it what you will—“Hospital 2.0,” “No Waiting Rooms,” “Hospital Operations Center”—the basic building blocks to enable the future of hospital operations are already here. Today, two major shifts are putting pressure on hospitals to rethink how they deliver care: (a) increased demand for care from the Affordable Care Act and the growing number of people with chronic illnesses and (b) the move toward value-based care. See Also: 5 Trends in Health IT These shifts have big implications across the board but, most importantly, in operations. Hospitals are under constant pressure to do more with less. Every day, they face an operational paradox: Scarce resources are both overbooked and underutilized within the same day. This leads to several undesirable outcomes: long patient waiting times, overworked staff, millions of dollars of unnecessary operational costs and an insatiable appetite for expanding existing facilities or constructing entirely new ones. For specialty services like chemotherapy, it could take days or weeks for a new patient to be given a slot, yet the typical infusion chair is occupied less than 60% of the time between 7 a.m. and 7 p.m. The same is true of operating rooms; study after study shows that hospitals don’t utilize their resources optimally. Historically, process improvement efforts in hospitals worked with small, historical snapshots of data from which the core operational issues were identified. From this, strategies were developed, implementation plans were executed and disciplines for continuous improvement were established. This was the best approach when all that was available were rear-view mirror data snapshots and Microsoft Excel as the analytic engine of choice. Today, there’s a lot more data to learn from. On average, health systems produce as much as two terabytes of data per patient every year. Combined with the explosion of smart devices, computational power in the cloud and the growing pervasiveness of data science and machine learning algorithms, an entirely different realm of operational optimization has suddenly become possible. It is similar to the realization that, decades ago, general surgeons did the best they could with the insight they gleaned from grainy X-ray images. Today, armed with high-resolution MRI/PET images and fiber-optic cameras, the same surgeons can execute surgeries an order of magnitude more complex than those they could have imagined being able to do when they were surgical residents a few decades ago.

• Hospitals are working on optimizing access to treatments such as chemotherapy. By looking at historical demand patterns and operational constraints, sophisticated forecasting algorithms can predict the daily volume and mix of patient volume and can orchestrate appointment slots so there are no “gaps” between treatments. This radically improves chair utilization, lowers patient waiting times and reduces the overall cost of operations. Doing this without sophisticated data science is hard — for example, just arranging the order in which 70 patients can be slotted for their treatments in a 35-chair infusion center is a number exceeding 10^100, as this analysis shows. Trying to solve this problem with pen, paper or Excel is a pointless exercise.

• Operating rooms are key resources within the hospital. Study after study shows that the OR utilization at most large hospitals is, at best, 50-60%. In most hospitals, operating rooms are allocated to surgeons using “blocks." (For simplicity, the blocks are often either half-day or full-day blocks.) Even the most prolific and productive surgeons often don’t fully utilize the blocks they are given, and the process for reallocating blocks on a monthly basis—or even for last-minute block swaps—is cumbersome and manual. Using data science and machine learning, hospitals can monitor utilization, identify pockets for improvement, automatically reallocate underutilized blocks and improve overall operating room utilization. A three to five point improvement in block utilization is worth $2 million per year for a surgical suite with just four operating rooms.

• In-patient bed capacity is a constraining bottleneck in most hospitals, yet virtually every hospital solves this problem with an arithmetic-based “huddle” approach that reviews the patient census from the overnight stay in each unit, adds known incoming patients, subtracts known discharges and then decides if the unit is flirting with the limits of its available capacity. This cycle repeats itself, often several times a day, with a planning horizon of the day at hand. On the other hand, Google completes the search bar while we are typing because it has analyzed millions of search terms similar to the one you are entering, and it automatically presents the four or five highest probability queries you intend to submit. Imagine looking at each overnight patient, finding the 1,000 patients over the last two years who entered the hospital with a similar diagnostic or procedure code and then reviewing their “flight path” through the hospital (i.e., number of days spent in each of the units prior to discharge). Then, an aggregate probabilistic assessment of the likely occupancy of each unit could be developed. Not only would it provide a better answer for today, it would help anticipate the evolving unit capacity situation over the next five to seven days, thereby leading to smarter operational decisions on transfers, elective surgery rescheduling, etc.

• A similar machine-learning approach can help orchestrate patient flows at clinics, labs, the pharmacy and any unit within the hospital network that struggles with the operational paradox of being overbooked and underutilized at the same time.

An interesting metaphor for the future of hospital operations is how airport operations, air traffic control and sophisticated scheduling have transformed air travel for passengers. They, too, have enormous complexity and the mission-critical requirement of passenger safety in the face of challenging external conditions. Three direct parallels:

• For a single flight to transport passengers safely from point A to point B, it requires the “above the wing” services (boarding, food, crew) and “below the wing” services (baggage, fuel, tire check, other inspections) to come together seamlessly. Similarly, to perform even a routine surgery, services like labs, pharmacy, the clinician, the surgeon and the supporting team all need to come together to be able to safely and successfully treat the patient.

• Every day, at any busy airport, tens of thousands of passengers  navigate their personal journey across connecting flights while relying on “invisible supporting services” such as bag transfers and re-bookings in the case of delays, weather systems, etc. Similarly, on any given day in a busy hospital, thousands of patients navigate their personal journey across a continuum of care while relying on the supporting services of labs, pharmacy, etc. to be timely and accurate.

• The volume of airline passengers has grown from a few thousand to a few million per day, and airports and airlines have been forced to do “more with less.” Similarly, the Affordable Care Act and a growing and aging population combined with the increased incidence of chronic disease will require hospitals to do “more with less.”

The aviation industry has diligently invested in the required technology, systems and processes to monitor, measure, collaborate and orchestrate. Similarly, hospitals are beginning to invest in the technology, systems and processes to maximize patient access at each “node” and to streamline the linkages across nodes. Just as the advent of air traffic control and fine-grained scheduling transformed airports like JFK from handling only a few hundred flights each day in the 1960s to managing thousands of takeoffs and landings a day within the same airspace, modern technologies and predictive analytics will lead to the creation of a similar air-traffic-control capability for hospitals. Assets like the OR, inpatient beds, clinics, infusion chairs and MRI machines will be far better utilized throughout the day. Many more patients will be treated within the same facilities, and they will need to wait far less between the “legs of their flight” across the continuum of care. This post was written by Mohan Giridharadas, the CEO of LeanTaaS. 

Why are long-term care insurance premiums rising faster than a speeding elevator? And what will become of the long-term care insurance marketplace? If you are interested in long-term care insurance, what's going on and what may happen, read on.  If you have no interest in long-term insurance, then this is not the article you are looking for. (The next edition will take a closer look at the insurance consumer Bill of Rights). Why Would Anyone Want Long-Term Care Insurance? One of the largest projected expenses for the average American in retirement is medical expenses, with estimates approaching a total of $250,000. Medicare and Medicare supplements provide coverage for medical expenses that are typically short-term or one-time, such as an annual physical, medical test or surgical procedure. Long-term care insurance provides coverage to pay the costs of service such as nursing home, in-home care and skilled nursing facilities that are not covered by Medicare or Medicare supplements. These costs are quite high—hundreds of dollars a day.  To see what the average cost of care in your area is, visit the Genworth Cost of Care page here. The odds of needing some form of long term-care insurance can reach 50% or more, with an average claim period of two to three years (depending on the statistics you look at). According to the U.S. Department of Health and Human Services (HHS), by 2020, about 12 million Americans will require long-term care. See Also: What Features of Long-Term Care Should You Focus On? Long-term care insurance premiums will typically be in the thousands of dollars a year. However, just like with any other type of insurance, it is about the leverage of protecting against a risk—a simple financial calculation: Can you afford to pay for the risk in the event of a claim out of pocket and can you afford to pay the premiums? In terms of leverage, if you have a long-term care insurance policy with a total benefit pool of $250,000 and an annual premium of $5,000, the annual premium is 2% of the total benefit pool. If 2% sounds like good leverage to you, this policy makes sense. The Big Question: Why Are Long-Term Care Insurance Premiums Rising?  There are multiple layers to this questions, but the main underlying factor is that the first long-term care insurance policies offered by insurance companies had unlimited benefit periods on a type of coverage where they had minimal historical data. Think about it this way: If I offered you a bet on a football game this weekend with the provision that, if you win, I'll pay you $100, and, if I win, you'll pay me a $1 a month for the rest of my life. Now, that's a great bet for me if my team consists of all-pros and your team consists of benchwarmers. Without knowing who is on your team, would you make this bet? There's no need to answer; of course you wouldn't.  Yet this is exactly the bet insurance companies made, just with much bigger numbers. And, unsurprisingly, this business model hasn't been profitable for them. There are some other major factors to consider, such as the prolonged historically low-interest-rate environment where insurance companies have not been able to make their historical investment returns. (This is something that no one could have foreseen.) Another major factor is that insurance companies counted on a certain percentage of people lapsing (terminating) their policies at some point. Again, the insurance companies made this prediction without much historical data. And guess what? Policy owners actually liked and valued the coverage they purchased, and they have kept their long-term care insurance policies in force, despite some significant rate increases. Premiums have had to be increased because, at the end of the day, it is in everyone's best interest for insurance companies to be profitable. If an insurance company is not profitable, it will go out of business and will not be able to pay claims, which is definitely a problem. Rate Increase Oversight and Perspective Rates for in-force policies have been increased and will almost certainly face future increases; older policies still are priced lower than what a current policy would cost. Premium increases on long-term-care insurance policies have to be approved, in most states, by the state insurance commissioner. When faced with a rate increase, policyholders will need to consider whether their benefit mix makes sense and fits their budget. These are the "visible" rate increases. If you have a long-term care insurance policy with a mutual insurance company where the premium is subsidized by dividends, you may not have noticed (or been informed) of a reduced dividend scale. When an insurance company reduces its dividend scale, it does not have to get approval from anyone or disclose that it has reduced its dividends. Reduced dividends mean a higher premium. This is a hidden rate increase. As mentioned, policies issued today have significantly higher premiums than those issued in the past. Some rate increases are attributed to companies "catching up" on premiums to get closer to current premiums they hope are more accurate. The bottom line is that insurance companies are trying to bring the premiums on older policies into line with their current pricing on new products. The closer that pricing gets, the less likely it is there will be future premium increases. So, if you have an older policy (even if you're faced with a significant premium increase), keep in mind you've gotten a discount on past premiums. While that's not comforting in the face of a premium increase, it will help put things into perspective. Insurance departments will approve premium increases so that they are sufficient to meet anticipated claims. Any increase granted must apply equally to all policy owners from the requested class of policies, and the carrier must keep the policy in force if the premium payments are made. Changes in age or health have no bearing on the contract premiums once issued; the policy may only be canceled if premiums are not paid. Nearly all existing long-term-care insurance policies have had one or more rate increases granted. Please keep in mind that rates on other types of insurance also increase over the years, some slowly like auto insurance and homeowners insurance and some rapidly like health insurance.  Inflation affects everything. There are no nickel candy bars any more. This is all about the value of the coverage and the leverage of your premium to the total benefit pool. Options When You Have A Premium Increase When you have a premium increase, you should always start by reviewing your coverage and deciding whether you still need the current coverage or whether you can make changes. For example, because the average claim period is two to three years and there is a much longer benefit period, is the trade-off in premiums for the longer benefit period worth it? It is important to understand that, once a change is made, it cannot be undone, so be sure you are comfortable with any modifications. The following are options when you have a premium increase:

• Pay the increased premium.
• Reduce the daily/monthly benefit amount.
• Increase the waiting period.
• Shorten the benefit period.
• Change the inflation rider
(e.g. go from compound to simple or reduce inflation percentage from 5% to 4%).
• Change/remove other riders.
• Terminate the policy.
• If your policy has a non-forfeiture benefit that allows for a "paid-up reduced benefit," consider this option: You'll get at least some value for the premiums you've paid. But remember, once you accept the option, the policy will not be reinstated. Some states are now requiring all new policies to include this feature. (It's relatively rare in older policies.)

New Long-Term Policy Designs (Hybrid/Combination Products) With all the issues in the traditional long-term care insurance marketplace, there are very few companies selling individual long-term care insurance policies. Instead, insurance companies have come out with whole new types of products: hybrids and combinations. For instance, you can purchase a life insurance policy or an annuity with a long-term-care insurance rider. Other options are a life insurance policy or annuity that is combined with a long-term-care policy. (Rather than the long-term-care insurance being part of the rider, it is part of the policy.) While, in theory, these sound like great ideas, they ignore some simple facts:

• There may be no need for life insurance or an annuity, but you will be paying for the life insurance or annuity in addition to the long-term care insurance component.
• Some require an up-front lump-sum premium payment.
• These policies are complex and opaque. There are multiple variables to these policies that the insurance company can change and that will affect the performance of the policy—many of which do not have to be disclosed to the policy owner and do not show up anywhere. The more complex the product, the greater the chance that something won't work properly.

Considering that insurance companies are still working on accurately pricing long-term-care insurance products and that universal life insurance policies are having issues (see: Will Your Life Insurance Policy Terminate Before You?), it is hard to imagine that combining two problematic products will magically work out. The big selling point for these policies is that, with a traditional long-term-care insurance policy, the policy owner does not get anything back if there is no claim made. However, there is no expectation with any other type of insurance (except for life insurance) that there is a return if a claim does not occur, and most homeowners, for example, are happy when their house doesn't burn down even though they don't get any payout from their insurer. Lessons Learned and a Positive Outlook For Long-Term Care Insurance? There is no doubt of the importance of a thriving private sector long-term-care insurance marketplace. Public policy would seem to favor long-term-care insurance paid for by the private sector. The Internal Revenue Service (IRS) is increasing the amount people may deduct from their tax returns this year when buying long-term-care insurance or paying monthly premiums. Check out the IRS page on long-term care Insurance premium deductibility here . The Bipartisan Policy Center (BPC) released its first set of recommendations calling for increasing access to the private insurance market. BPC initiatives call for increasing access to the private insurance market, improving public programs such as Medicaid and pursuing a catastrophic insurance approach for individuals with significant long-term-care needs such as Alzheimer's or a debilitating physical impairment. These proposals were developed by former U.S. Senate Majority Leader Tom Daschle along with Bill Frist, another former U.S. Senate majority leader, former U.S. Secretary of Health and Human Services Secretary and Wisconsin Gov. Tommy Thompson and Alice Rivlin, the former director of the Office of Management and Budget. They aim to address the needs of America's seniors and specifically target middle- and lower-income individuals and families. Daschle said, "Today, families and caregivers are becoming impoverished by the financial demands of long-term care ... Since there is no single, comprehensive solution to solve this unsustainable situation, our strategy calls for a combination of actions that could help ease the extraordinary financial burdens Americans are facing." If the BPC has its way, these retirement long-term-care policies would be sold on federal and state health insurance exchanges. The question is whether this can be accomplished. Part of the Affordable Care Act (ACA, aka Obamacare), the Community Living Assistance Services and Supports (CLASS) program established a national, voluntary insurance program for purchasing community living services and supports that is designed to expand options for people who become functionally disabled and require long-term help. Unfortunately, this program was abandoned because it wasn't financially feasible. History repeats itself Back in the 1980s, insurance companies made similar poor product design decisions with individual disability income insurance. Unsurprisingly, claims experience was not great, and a number of companies left the marketplace. Is this sounding familiar?  The current individual disability insurance marketplace has returned with more sensible products, where the companies do full underwriting, offer benefits that are less than earnings and do not guarantee the premiums. A great read on this is: IDI Déjà Vu: Optimism For The LTCI Industry, by Xiaoge Flora Hu and Marc Glickman. The long-term-care insurance industry is making similar changes to its products, which should buoy the marketplace. Products are being priced based on actual experience, policies are being fully underwritten and unlimited benefits are no longer available. Smarter product design, better risk selection and a strong need should result in a solid long-term-care insurance marketplace. As America continues to age, there will be a stronger need for the coverage. It may take a few years, but there is a future for long-term-care insurance. The only real question is when. Let me know what you think.

The first machine age, the Industrial Revolution, saw the automation of physical work. We live in the second machine age, where there is increasing augmentation and automation of manual and cognitive work. This second machine age has seen the rise of artificial intelligence (AI), or “intelligence” that is not the result of human cogitation. It is now ubiquitous in many commercial products, from search engines to virtual assistants. AI is the result of exponential growth in computing power, memory capacity, cloud computing, distributed and parallel processing, open-source solutions and global connectivity of both people and machines. The massive amounts and the speed at which structured and unstructured (e.g., text, audio, video, sensor) data is being generated has made a necessity of speedily processing and of generating meaningful, actionable insights from it. Demystifying Artificial Intelligence The term “artificial intelligence” is often misused. To avoid any confusion over what AI means, it’s worth clarifying its scope and definition.

• AI and Machine Learning—Machine learning is just one area or sub-field of AI. It is the science and engineering of making machines “learn.” That said, intelligent machines need to do more than just learn—they need to plan, act, understand and reason.

• Machine Learning and Deep Learning—"Machine learning" and "deep learning" are often used interchangeably. Deep learning is actually a type of machine learning that uses multi-layered neural networks to learn. There are other approaches to machine learning, including Bayesian learning, evolutionary learning and symbolic learning.

• AI and Cognitive Computing—Cognitive computing does not have a clear definition. It can be viewed as a subset of AI that focuses on simulating human thought process based on how the brain works. It is also viewed as a “category of technologies that uses natural language processing and machine learning to enable people and machines to interact more naturally to extend and magnify human expertise and cognition.” Cognitive computing is a subset of AI, not an independent area of study.

• AI and Data Science—Data science refers to the interdisciplinary field that incorporates statistics, mathematics, computer science and business analysis to collect, organize and analyze large amounts of data to generate actionable insights. The types of data (e.g., text, audio, video) and the analytic techniques (e.g., decision trees, neural networks) that both data science and AI use are very similar.

Differences, if any, may be found in the purpose. Data science aims to generate actionable insights to businesses, irrespective of any claims about simulating human intelligence, while the pursuit of AI may be to simulate human intelligence. Self-Driving Cars When the U.S. Defense Advanced Research Projects Agency (DARPA) ran its 2004 Grand Challenge for automated vehicles, no car was able to complete the 150-mile challenge. In fact, the most successful entrant covered only 7.32 miles. The next year, five vehicles completed the course. Now, every major car manufacturer plans to have a self-driving car on the road within five to 10 years, and the Google Car has clocked more than 1.3 million autonomous miles. See Also: What You Must Know About Machine Learning AI techniques—especially machine learning and image processing— help create a real-time view of what happens around an autonomous vehicle and help it learn and act from past experience. Amazingly, most of these technologies didn’t even exist 10 years ago. Emerging risk identification through man-machine learning “People worry that computers will get too smart and take over the world, but the real problem is that they’re too stupid and they’ve already taken over the world.” —Pedro Domingos, author of The Master Algorithm Emerging Risks & New Product Innovation Identifying emerging risks (e.g., cyber, climate, nanotechnology), analyzing observable trends, determining if there is an appropriate insurance market for these risks and developing new coverage products in response historically have been creative human endeavors. However, collecting, organizing, cleansing, synthesizing and even generating insights from large volumes of structured and unstructured data are now typically machine learning tasks. In the medium term,  combining human and machine insights offers insurers complementary, value-generating capabilities. Man-Machine Learning Artificial general intelligence (AGI) that can perform any task a human can is still a long way off. In the meantime, combining human creativity with mechanical analysis and synthesis of large volumes of data—in other words, man-machine learning (MML)—can yield immediate results. For example, in MML, the machine learning component sifts through daily news from a variety of sources to identify trends and potentially significant signals. The human-learning component provides reinforcement and feedback to the ML component, which then refines its sources and weights to offer broader and deeper content. Using this type of MML, risk experts can identify emerging risks and monitor their significance and growth. MML can further help insurers identify potential customers, understand key features, tailor offers and incorporate feedback to refine product introduction. Computers That “See” In 2009, Fei-Fei Li and other AI scientists at Stanford AI Laboratory created ImageNet, a database of more than 15 million digital images, and launched the ImageNet Large Scale Visual Recognition Challenge (ILSVRC). The ILSVRC awards substantial prizes to the best object detection and object localization algorithms. The competition has made major contributions to the development of “deep learning” systems, multilayered neural networks that can recognize human faces with more than 97% accuracy, as well as recognize arbitrary images and even moving videos. Deep learning systems can now process real-time video, interpret it and provide a natural language description. Artificial Intelligence: Implications for Insurers AI’s initial impact relates primarily to improving efficiencies and automating existing customer-facing, underwriting and claims processes. Over time, its impact will be more profound; it will identify, assess and underwrite emerging risks and identify new revenue sources.

• Improving Efficiencies—AI is already improving efficiencies in customer interaction and conversion ratios, reducing quote-to-bind and FNOL-to-claim resolution times and increasing speed to market for products. These efficiencies are the result of AI techniques speeding up decision-making (e.g., automating underwriting, auto-adjudicating claims, automating financial advice, etc.).

• Improving Effectiveness—Because of the increasing sophistication of its decision-making capabilities, AI will soon improve target prospects to convert them to customers, refine risk assessment and risk-based pricing, enhance claims adjustment and more. Over time, as AI systems learn from their interactions with the environment and with their human masters, they are likely to become more effective than humans, and the AI systems will replace them. Advisers, underwriters, call center representatives and claims adjusters will likely be most at risk.

• Improving Risk Selection and Assessment—AI’s most profound impact could well result from its ability to identify trends and emerging risks and assess risks for individuals, corporations and lines of business.

Its ability to help carriers develop new sources of revenue from risk- and non-risk-based information will also be significant. See Also: How Machine Learning Changes the Game Starting the Journey Most organizations already have a big data and analytics or data science group. (We have addressed elsewhere how organizations can create and manage these groups.) The following are specific steps for incorporating AI techniques within a broader data science group:

1. Start from business decisions—Catalogue the key strategic decisions that affect the business and the related metrics that need improvement (e.g., better customer targeting to increase conversion ratio, reducing claims processing time to improve satisfaction, etc.).

2. Identify appropriate AI areas—Solving any particular business problem will, very likely, involve more than one AI area. Ensure that you map all appropriate AI areas (e.g., NLP, machine learning, image analytics) to the problem you want to address.

3. Think big, start small—AI’s potential to influence decision making is huge, but companies will need to build the right data, techniques, skills and executive decision-making to exploit it. Have an evolutionary path toward more advanced capabilities. AI’s full power will become available when the AI platform continuously learns from both the environment and people (what we call the “dynamic insights platform”).

4. Build training data sets—Create your own proprietary data set for training staff and measuring the accuracy of your algorithms. For example, create your own proprietary database of “crash images” and benchmark the accuracy of your existing algorithms against them. You should consistently aim to improve the accuracy of the algorithms against comparable human decisions.

5. Pilot with parallel runs—Build a pilot of your AI solution using existing vendor solutions or open-source tools. Conduct parallel runs of the AI solution with human decision makers. Compare and iteratively improve the performance/accuracy of the AI solution.

6. Scale and manage change—Once the AI solution has proven itself, scale it with the appropriate software/hardware architecture and institute a broad change management program to change the internal decision-making mindset.