{"id":4026,"date":"2019-10-21T08:00:57","date_gmt":"2019-10-21T08:00:57","guid":{"rendered":"http:\/\/803.557.mywebsitetransfer.com\/?p=4026"},"modified":"2019-11-07T17:43:45","modified_gmt":"2019-11-07T17:43:45","slug":"healthcare-2030-part-3","status":"publish","type":"post","link":"https:\/\/pwer.com\/?p=4026","title":{"rendered":"Healthcare 2030 (Part 3)"},"content":{"rendered":"\n

Healthcare\n2030 (Part 3)<\/strong><\/p>\n\n\n\n

Our last\nblog, Healthcare 2030 (Part 2), ended with the prediction of a new \u201cgolden age\nof healthcare.\u201d  I realize it is\nimpossible to predict a golden age before it has happened, however, in this\ncase, we may have one exception. <\/p>\n\n\n\n

Once\nreferred to as \u201cThe Maestro,\u201d Allan Greenspan once said or wrote something like\n\u2018demography is history.\u2019  His premise was\nthat if you have great demographic information, with historical perspective and\nbehavior economics (my injection, not his), you could predict just about\nanything. <\/p>\n\n\n\n

A simple\nexample is, if you know how many children in the U.S. are born each year, you\ncan predict the current trends (net migration) of how many new adults will\nenter college in their 18th<\/sup> year.  While there are variables, you can predict going\nforward by observing the past behavior.  In\nhealthcare, we know that the complexity and amount of care increases with age.  There are actuarial predictions, and the Law\nof Large Numbers is quite accurate. <\/p>\n\n\n\n

As\ndefined by Investopedia:[1]<\/a> <\/p>\n\n\n\n

Understanding\nthe Law of Large Numbers in Insurance<\/p>\n\n\n\n

In\nthe insurance industry, the Law of Large Numbers produces its axiom. As the\nnumber of exposure units (policyholders) increases, the probability that the\nactual loss per exposure unit will equal the expected loss per exposure unit is\nhigher. To put it in economic language, there are returns to scale in insurance\nproduction.<\/p>\n\n\n\n

In\npractical terms, this means that it is easier to establish the correct premium\nand thereby reduce risk exposure for the insurer as more policies are issued\nwithin a given insurance class. An insurance company is better off issuing 500\nrather than 150 fire insurance policies, assuming a stable and independent probability\ndistribution for loss exposure.<\/p>\n\n\n\n

To\nsee it another way, suppose that a health insurance company discovers that five\nout of 150 people will suffer a serious and expensive injury during a given\nyear. If the company insures only 10 or 25 people, it faces far greater risks\nthan if it can ensure all 150 people. The company can be more confident that\n150 policyholders will collectively pay sufficient premiums to cover the claims\nfrom five customers who suffer serious injuries.<\/p>\n\n\n\n

We believe\nhistory will look back a hundred years from now and label the next decade as a\ntransformational decade for healthcare in the United States.<\/p>\n\n\n\n

We\nbelieve that just as Baby Boomers have changed everything they have been a part\nof since 1946 through 1966 \u2013 whether it was changed by them directly, by their\nparents, or their offspring \u2013 the Baby Boomers, at least economically, have\nimpacted American history more than any other generation to date.  It will be interesting to see what legacy the\nMillennials create.<\/p>\n\n\n\n

Sociologists\nhave debated, and will continue to debate, why the Baby Boomer generation has\nhad such an impact.  Was it the\nindependence that our parents gave us?  Was\nit the era that we grew up in?  Or, was\nit just that the sheer size of our generation \u2013 all seeking, acquiring and\nwanting the same thing at the same time?  Even as we look back to the stock market\ngrowth since the early 1980s through the early 2000s, it is hard to totally\ngrasp the impact Baby Boomers had in getting married, buying their first home,\nor having children.  Were the high\ninflation years of the late 1970s and early 1980s a direct impact of that\ngeneration of 77 million people all wanting something at the same time? <\/p>\n\n\n\n

Today, this\ngeneration is between the ages of 54 and 72 years old, and they\u2019re entering\ntheir high healthcare consumption years. \nThe entire generation will be eligible for Medicare (as currently\nstructured) by 2030.  We can\u2019t project\nsome things however, this generation can and will likely change healthcare in a\nway that is totally unpredictable today.<\/p>\n\n\n\n

In the\nnext couple of weeks, we\u2019re going to start a podcast to supplement these blogs\nnamed Healthcare 2030.  <\/strong>We expect that healthcare in 2030 will\nchange in meaningful ways \u2013 well beyond what is completely predictable today!<\/p>\n\n\n\n

We\nexpect there will be certain leading trends through this transformational\ndecade including Internet of Things devices, Artificial Intelligence, Telemedicine,\nPrice and Contract Transparency, and most importantly, the shifting of the\ncenter of care from the provider to the consumer, who will be demanding control\nof their healthcare.<\/p>\n\n\n\n

Be sure\nto follow our site and social media pages for the official launch announcement\nof our  podcast, Healthcare 2030.<\/p>\n\n\n\n

-Noel J.\nGuillama, President
<\/p>\n\n\n\n

\n\n\n\n

[1]<\/a> https:\/\/www.investopedia.com\/articles\/personal-finance\/081616\/behind-law-large-numbers-insurance-industry.asp<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Healthcare 2030 (Part 3) Our last blog, Healthcare 2030 (Part 2), ended with the prediction of a new \u201cgolden age of healthcare.\u201d  I realize it is impossible to predict a golden age before it has happened, however, in this case, we may have one exception. Once referred to as \u201cThe Maestro,\u201d Allan Greenspan once said or wrote something like \u2018demography is history.\u2019  His premise was that if you have great demographic information, with historical perspective and behavior economics (my injection, not his), you could predict just about anything. A simple […]<\/p>\n","protected":false},"author":6,"featured_media":4028,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-4026","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"jetpack_sharing_enabled":true,"jetpack_featured_media_url":"https:\/\/pwer.com\/wp-content\/uploads\/2019\/10\/AdobeStock_238387607.jpeg","_links":{"self":[{"href":"https:\/\/pwer.com\/index.php?rest_route=\/wp\/v2\/posts\/4026","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/pwer.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/pwer.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/pwer.com\/index.php?rest_route=\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"https:\/\/pwer.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=4026"}],"version-history":[{"count":4,"href":"https:\/\/pwer.com\/index.php?rest_route=\/wp\/v2\/posts\/4026\/revisions"}],"predecessor-version":[{"id":4033,"href":"https:\/\/pwer.com\/index.php?rest_route=\/wp\/v2\/posts\/4026\/revisions\/4033"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/pwer.com\/index.php?rest_route=\/wp\/v2\/media\/4028"}],"wp:attachment":[{"href":"https:\/\/pwer.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4026"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/pwer.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4026"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/pwer.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4026"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}