Healthcare & Insurance

Hans Rosling, age 68, died earlier this month. He contributed more than almost anyone to helping people truly understand the world as it is. In an era when we have gone overboard for the glitziest data visualization techniques – frequently at the expense of comprehensibility or of any meaning whatsoever – Rosling’s presentations are informative but still imaginative and entertaining. His work demonstrates the potential that data visualization can have, but all too often doesn’t – we’ll see one of his best examples here.

At this time of year, many of us face choices about health insurance plans for the upcoming year. Depressingly large premium increases have been typical, and 2017 will be no exception. BUT WAIT – there may be a HIDDEN premium increase as well.

For a course I teach at U.C. Berkeley about presenting numbers, I ask students to write a blog for this website. I don’t always get one I choose to post, but this term Lyman Yip’s paper, “How Do Vegetarians Get Their Protein?”, was definitely worthy. Lyman presents his numbers clearly, carefully, and effectively, the text is well-written, and the words in the text and the numbers in the exhibits work well together. Enjoy!

(I posted this blog exactly one year ago, and I post it again as a public service.) It’s that time of year again, when we have to figure out our best health insurance alternative in the face of wildly gyrating prices and complex competing plans. If you’re a finance professional, you’ll be doing your coworkers and your friends a huge favor if you can help them through this important and expensive decision. And data visualization plays a big part in this task.

An interesting headline on the front page of a recent USA Today: “Drastic drop in Medicare deaths, costs.” The story cites a JAMA article reporting significant drops from 1999 to 2103 in death rates, hospitalization rates, and cost-per-patient among Medicare patients. That great news! Now, from that headline, you might infer that Medicare had something to do with the improvements, but should you really?

In a Washington Post op-ed piece, Catherine Rampell takes on presidential candidates pledging to “run government like a business,” as they advocate inane policies like 10% across-the-board cutbacks. She identifies several federal government situations where they should be spending more money, not less. She’s right, but it’s not just about spending money to make money. Well-run businesses use metrics intelligently.

In the last post, we discussed a problem related to health insurance subsidies under the Affordable Care Act (ACA) caused by the legislation’s failure to address the impact of significant income fluctuations throughout the year. An approach that could deal with this takes a page from “accelerated” sales commission plans, where commission rates increase as sales volume increases.

Prof. Annette Nellen describes a problematic consequence of the Affordable Care Act (ACA). The problem and some proposed resolutions will resonate with anyone who thinks deeply about designing incentive compensation plans, and illustrates what can happen when our legislators attempt to bake incentives and motivations into the laws they write.

I frequently write about the importance of using words properly in order to make numbers understandable. An article about recent trends in health insurance premiums – a critically important subject, and in a prestigious publication – has several statements that are unsupported by the facts. The problem isn’t that the author misunderstands the information, it’s that he’s mischaracterizing it. This is where proper use of words comes in.

Let’s take a little more time to consider the question of choosing a health insurance policy. In my last post we looked at these choices:

We shift gears from recent posts to address a critical – and extremely timely – decision: choosing a health insurance plan, which you must do by 12/15 if you want a new plan in place by 1/1/15. If you’re a finance professional, you will be doing your coworkers and your friends a huge favor if you can help them through this important and expensive decision. And data visualization plays a big part in this task.

“Chartjunk” is a term coined by Edward Tufte to describe elements in graphs or approaches to graphing that detract from the meaning of the graph or even skew the depiction of the graph to the point where it will get misinterpreted. For the interested observer, the media efforts to present information on Obamacare and its rollout have created a veritable goldmine of chartjunk.

One of the major causes of the healthcare.com fiasco of the last two months is the Obama administration’s decision to require site visitors to fully enroll in Obamacare before they could receive a price quotation for health insurance.

Sometimes, the numbers are not the numbers: they may be correct, and they may be understandable, but they don’t really address the question being asked. A good example of this dissonance is Obamacare and the frequent assertion that it is absolutely budget-neutral.

The Washington Post recently ran a front-page story headlined “106,000 have signed up for health coverage,” with a sub-heading of “Enrollment less than predicted.”

Much has been said about how tight-lipped the Obama administration has been about the enrollment numbers since October 1 for the private exchanges mandated by Obamacare. There is a lesson here about communicating, that applies just as powerfully to quantation (the act of presenting numbers) as it applies to all other types of communication.

Kudos goes to Mark Whitehouse for his April 9 “Number of the Week” piece in the online Wall Street Journal. The topic is an important one – how much we spend on healthcare – and he presents some very important numbers in a clear and concise way. Here’s the chart he included in his post.

Let’s talk about a gritty, real-life issue: What should your car’s collision insurance deductible be? The decision is based on pure math, but every one of you can figure this out. And you might save a few bucks! Here’s how: