About Frank de Libero

I aim to make the complex understandable, for myself as well as others. A numbers guy, my approach is to question often and use graphs, models and narrative to understand and communicate. Hopefully the result is a take away for each project, some unifying data driven concept you can put in your pocket. That's the goal. As an independent analyst, a majority of my work is related to health and public policy. I have 30 years experience, a PhD in applied statistics from the U. of Washington, Seattle, and a BA and MS in mathematics from Adelphi U., New York. For relaxation I cook and occasionally woodwork.

The Right Path but the Wrong Direction

Get a good education, work hard, and good things will happen, that’s the American Dream. But it may be fading as we let stagnant earnings continue as they have. This post, which is about work, earnings, higher education, and inflation, also portends an American Dream for some, but not for the majority who find themselves going backwards.

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On Ending a Health Care Fallacy

Here it’s argued that we need to retire the health care fallacy, “We spend more on health care than other rich countries but have worse outcomes.” The fallacy implies U.S. health care is deficient in spite of being costly. Indeed our health care costs too much, but there is little evidence that our care is less effective than care in other countries. On the other hand, there’s plenty of evidence that our social determinants of health are worse.

The argument segues off a recent article by Victor Fuchs. The case is presented by using a simple linear model to explore how life expectancy might change when we substitute the numbers of other countries’ determinants of health for U.S. numbers. After making these substitutions and holding health care spending constant the model predicts U.S. life expectancy is right there with the other OECD countries, 81.6 years compared to their average 81.4 years. This what-if modelling makes clear what should be obvious but the fallacy hides, that health care is only one part of population health.
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Senior Health Care Costs Connected to Loneliness

For more than 20 years organizations and policy makers looked for cost estimates associated with loneliness and social isolation. This summer a client wanted a sense of those costs. Using recent literature I derived a rough estimate of health care expenditures linked to loneliness: about 2.5% of market-based medical costs for seniors. The background and methods are given below the fold. Continue reading

Estimating County Health Care Costs in Washington State

Besides state and higher-level health care expenditures, county level HCE are useful, integral really. For example, to promote the Triple Aim (the best care for the whole population at the lowest cost) you need per capita HCE. And knowing those costs at the county level would help a lot. However, county estimates generally don’t exist. They didn’t in Washington State until a client needed cost estimates for our 39 counties. To supply those estimates I used a regression approach resulting in this model:

percaphce = +0.1*percapinc + 247*pctage65 + 0.71*percapmedaid + 10.5*pctrural – 1349 Continue reading

Risk Pushed Down onto Us

Within a day I was twice alerted to Bruce Schneier’s recent essay, “Our Newfound Fear of Risk.” Schneier meaningfully and regularly contributes on security issues. He deserves our appreciation. However, I disagree with his connotation that “Our Newfound Fear of Risk” is our fault, for that’s how the essay reads: “We’re afraid of risk”, “We’re bad at accurately assessing risk”, “We need to relearn how to accept risk.” The examples given about our implied overreaction to risk are policing, control and, terrorism. Continue reading

On Refusing to Expand Medicaid

Robert Pear wrote in the Times that the refusal by “states to expand Medicaid will leave millions of poor people ineligible for government-subsidized health insurance…” 1 Indeed, the refusals will do that, as well as worsen what instead should be remedied. In the following I present a graph of two chronic diseases over the 50 states. Those states which have opted out of the Medicaid expansion are identified. Additionally each state’s poverty rate is indicated. The take-away is that populations in greater need are being further disadvantaged. A conjecture is presented as to why. Continue reading

  1. http://www.nytimes.com/2013/05/25/us/states-policies-on-health-care-exclude-poorest.html?hp&pagewanted=print