On Ending a Health Care Fallacy

Introduction
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