Tag Archives: stroke

How to Live Longer? Drink More Coffee

This idea is taken from The Doctor Weighs In post by Dov Michaeli.

As the article says, “Coffee drinkers have a reduced risk of dying prematurely from all causes, and consequently live longer.” Coffee is a “vice” that is most worthy, and one to be embraced.

Some health attributes of coffee include reduced risks of death from:

  • Cardiac arrhythmia
  • Type 2 diabetes
  • Dementia
  • Pneumonia
  • Lung disease
  • Accidents
  • Strokes

That’s quite a list. The good news is that a 50-cent cup of coffee works as well as a five-dollar cup. Any amount of coffee is better than none. According to results of a study by the National Institutes of Health (NIH), “Compared with people who drank no coffee at all, men and women who drank six or more cups per day were 10% and 15% less likely, respectively, to die during the study.”

Don’t tell wellness true believers about this. They may want to start charging coffee-free employees a higher health payroll deduction.

2 Ways to Innovate in Life Insurance

Individual life insurance ownership in U.S. has been decreasing over the past decade, and the figures are even more depressing when we look at the figures over the past 50 years. Life insurance ownership (both group and individual) among U.S. adults has dropped from 70% of individuals in 1960 to 59% in 2010. The number of individual policies owned by U.S. adults has dropped from 59% in 1960 to 36% in 2010, according to the Life Insurance and Market Research Association (LIMRA). The world has seen accelerated change over the past several decades, and, as entire industries transform, even leading and innovative companies can get trampled. The life insurance industry is no exception. The figures clearly demonstrate the slowing demand for life insurance. Are we seeing the “death” of life insurance, or is this just a temporary “blip” as the industry re-designs itself for changing demographics? Are there innovative business models that can change the situation?

The Case for Big Data and Analytics

The life insurance industry needs to innovate and needs to innovate fast. Innovation has to come from understanding end consumer needs better, reducing distribution costs in addressing these needs and developing products that are less complex to purchase. By leveraging new technologies, particularly new sources of data and new analytics techniques, insurers will be able to foresee some of these changes and prepare for disruptive change.

There are at least two distinct ways in which new sources of data and analytics can help in the life insurance sector.

  • Underwriting: Identifying prospects who can be sold life insurance without medical underwriting (preferably instantaneously) and speeding up the process for those who do require medical underwriting
  • New non-standard classes: Identifying and pricing prospects who have certain types of pre-existing conditions, e.g., cancer, HIV and diabetes.

Predictive Modeling in Underwriting

A predictive model essentially predicts a dependent variable from a number of independent variables using historically available data and the correlations between the independent variables and the dependent variable. This type of modeling is not new to life insurance underwriters as they have always predicted mortality risk for an individual, based on variables of historical data, such as age, gender or blood pressure.

With the availability of additional data about consumers, including pharmacy or prescription data, credit data, motor vehicle records (MVR), credit card purchase data and fitness monitoring device data, life insurers have potentially a lot of data that can be used in the new business process. Because of privacy and confidentiality considerations, most insurers are cautious in using personally identifiable data. However, there are a number of personally non-identifiable data (e.g., healthy living index computed by zip code) or household level balance sheet data that can be used to accelerate or “jet-underwrite” certain classes of life insurance.

Some insurance companies are already using new sources of sensor data and applying analytics to personalize the underwriting process and are reaping huge benefits. For example, an insurer in South Africa is using analytics to underwrite policies based on vitality age, which takes into account exercise, dietary and lifestyle behaviors, instead of calendar age. The insurer combines traditional health check-ups with diet and fitness checks, and exercise tracking devices to provide incentives for healthy behavior. Life insurance premiums change on a yearly basis. The company has successfully managed to change the value proposition of life insurance from death and living benefits to “well-being benefits,” attracting a relatively healthier and younger demographic. This new approach has helped this company progressively build significant market share over the past decade and exceed growth expectations in the last fiscal year, increasing profits by 18% and showing new-business increases of 13%.

Pricing Non-Standard Risk Classes

In the past, life insurers have excluded life insurance cover for certain types of conditions, like AIDS, cancer and stroke. With the advances in medical care and sensors that monitor vital signs of people with these conditions on a 24×7 basis, there is an opportunity to price non-standard risk classes. Websites that capture a variety of statistics on patients with specific ailments are emerging. Medical insurers and big pharmaceutical companies are leveraging this information to understand disease progress, drug interaction, drug delivery, patient drug compliance and a number of other factors to understand morbidity and mortality risks. Life insurers can tap into these new sources of data to underwrite life insurance for narrower or specialized pool of people.

For example, a life insurance company in South Africa is using this approach to underwrite life insurance for HIV or AIDS patients. They use extensive data and research on their HIV patients to determine mortality and morbidity risks, combine their offering with other managed care programs to offer non-standard HIV life insurance policies. They have been operating over the past four years and are branching out into new classes of risk including cancer, stroke and diabetes.

Surviving and Thriving in the World of Big Data

The examples we have provided are just scratching the surface of what is likely to come in the future. Insurers that want to leverage such opportunities should change their mindset and address the challenges facing the life insurance sector. Specifically, they should take the following actions:

  • Start from key business decisions or questions
  • Identify new sources of data that can better inform the decision-making process
  • Use new analytic techniques to generate insights
  • Demonstrate value through pilots before scaling
  • Fail forward — institute a culture of test-and-learn
  • Overcome gut instinct to become a truly data-driven culture

In summary, life insurance needs to innovate to be a relevant product category to the younger and healthier generation. Using new sources of big data and new analytic techniques, life insurers can innovate with both products and processes to bring down the cost of acquisition and also open up new growth opportunities.

What cycle-time improvements have you been able to achieve in the life new-business process? How well are you exploiting new data and analytic techniques to innovate in the life insurance space?

What Features Of Long-Term Care Policies Should I Focus On?

Where May Care Occur?
The best policies pay for care in a nursing home, assisted living facility, or at home. Benefits are typically expressed in daily amounts, with a lifetime maximum. Some policies pay half as much per day for at-home care as for nursing home care. Others pay the same amount, or have a “pool of benefits” that can be used as needed.

Under What Conditions Will The Policy Begin Paying Benefits?
The policy should state the various conditions that must be met.

  • The inability to perform two or three specific “activities of daily living” without help. These include bathing, dressing, eating, toileting and “transferring” or being able to move from place to place or between a bed and a chair.
  • Cognitive impairment. Most policies cover stroke and Alzheimer’s and Parkinson’s disease, but other forms of mental incapacity may be excluded.
  • Medical necessity, or certification by a doctor that long-term care is necessary.

What Events Must Occur Before The Policy Begins Paying Benefits?

  • Some older policies require a hospital stay of at least three days before benefits can be paid. This requirement is very restrictive — you should avoid it.
  • Most policies have a “waiting period” or “elimination” period. This is a period that begins when you first need long-term care and lasts as long as the policy provides. During the waiting period, the policy will not pay benefits. If you recover before the waiting period ends, the policy doesn’t pay for expenses you incur during the waiting period. The policy pays only for expenses that occur after the waiting period is over, if you continue to need care. In general, the longer the waiting period, the lower the premium for the long-term care policy.

How Long Will Benefits Last?
A benefit period may range from two years to lifetime. You can keep premiums down by electing coverage for three to four years — longer than the average nursing home stay — instead of lifetime.

Indemnity vs. Reimbursement
Most long-term care policies pay on a reimbursement (or expense-incurred) basis, up to the policy limits. In other words, if you have a $150 per day benefit but spend only $130 per day for a home long-term care provider, the policy will pay only $130. The “extra” $20 each day will, in some policies, go into a “pool” of unused funds that can be used to extend the length of time for which the policy will pay benefits. Other policies pay on an indemnity basis. Using the same example as above, an indemnity policy would pay $150 per day as long as the insured needs and receives long-term care services, regardless of the actual outlay.

Inflation Protection
Inflation protection is an important feature, especially if you are under 65, when you buy benefits that you may not use for 20 years or more. A good inflation provision compounds benefits at 5 percent a year. Without inflation protection, even 3 percent annual inflation will, over 24 years, reduce the purchasing power of a $150 daily benefit to the equivalent of $75.

Six Other Important Policy Provisions

  1. 1=7 Elimination period. Under some policies, if the insured has qualifying long-term care expenses on one day during a seven-day period, he or she will be credited with having satisfied seven days toward the elimination period. This type of provision reflects the way home care is often delivered — some days by professionals and some days by family members.
  2. Guaranteed renewable policies must be renewed by the insurance company, although premiums can go up if they are increased for an entire class of policyholders.
  3. Waiver of premium, so that no further premiums are due once you start to receive benefits.
  4. Third-party notification, so that a relative, friend or professional adviser will be notified if you forget to pay a premium.
  5. Nonforfeiture benefits keep a lesser amount of insurance in force if you let the policy lapse. This provision is required by some states.
  6. Restoration of benefits, which ensures that maximum benefits are put back in place if you receive benefits for a time, then recover and go for a specified period (typically six months) without receiving benefits.