Heard on CNBC this morning, only slightly paraphrased, after a remark about the security of the new fingerprint feature on Apple's iPhone:
"Supposedly the chances of someone cracking the password on the current iPhone is 1 in 10,000"
It's a four digit password.
:)
A blog on economics, both theory and current events, and world political affairs.
Wednesday, September 18, 2013
Monday, September 16, 2013
Understanding of Affordable Care Act is Overstated
According to a new WSJ/NBC poll,
When will the Independent Payment Advisory Board be appointed and what will it do?
And that leaves out all the quality improvement and reimbursement experiments.
The survey also had findings relating to the likelihood of people signing up for new subsidized insurance:
Overall, nearly 70% of poll respondents said they didn't understand the health-care overhaul passed by Democrats in March 2010 or only understood a part of it.That is incredible. Over 30% understand most or all of ACA?! I have studied the ACA quite thoroughly and am not sure I would say that I understand all or even most of it. How about the taxes on employer based insurance? Where exactly do the hundreds of billions of savings from Medicare come from? How will Medicare Advantage plans be affected? What are the SHOP exchanges? Can I buy insurance anytime during the year or only during enrollment periods? What kind of high deductible plans will be allowed? How will premia be affected for the young and healthy vs. the older?
When will the Independent Payment Advisory Board be appointed and what will it do?
And that leaves out all the quality improvement and reimbursement experiments.
The survey also had findings relating to the likelihood of people signing up for new subsidized insurance:
Only 32% of the uninsured thought they were "fairly" or "very" likely to use the exchanges.If I were a hospital with any reasonable population of uninsured patients, I would set up a desk to help patients sign up for insurance when they show up in a hospital. Think of the return on investment to that.
Saturday, September 07, 2013
Confidence Levels in the IPCC Climate Change Reports
Has anyone ever looked closely at the way the IPCC (Intergovernmental Panel on Climate Change) comes up with its confidence levels in its findings?
For example, just what do these kind of statements mean:
What exactly do these phrases very high confidence and high confidence, and very likely, likely, more likely than not mean exactly?
We all know what a classical confidence interval statement means. These are definitely not classical confidence intervals; there is no explicit null hypothesis and no statistical distribution of a test statistic under the null.
These must be some kind of Bayesian statements of probability. When I took Bayesian econometrics with Ed Leamer at UCLA he characterized Bayesian probabilities as what a bookmaker would use to set terms for bets. But with Bayesian statistics, we still use quantitative distributions, for instance expressing our beliefs over a parameter with something like the lognormal distribution with a specific mean and variance.
Very likely? Likely? More likely than not? Highly confident?
How much do you believe that the Federal Reserve's policies from 2008 to 2012 prevented the world from entering a depression? Very likely? More likely than not? Not at all likely?
Of course, investment banks do issue "highly confident" letters. Those probably don't have an explicit statistical meaning either. I doubt that the IPCC considers their statements to be equivalent in quality to the banks'! (Hmmm...How confident are we that the IPCC statements are more likely to be correct than the banks'?)
Even more problematic, the statements coming out of the IPCC are not for an individual but for a group.
The IPCC does produce a document that describes how the writers should come up with these kind of probability statements. Here are two screen shots of key tables:
I guess my main question would be if the IPCC has invented this kind of group likelihood assessment or if is a well-recognized science. The list of references has only a few non-IPCC or non-climate items; I will see what they are about.
For example, just what do these kind of statements mean:
In terrestrial ecosystems, earlier timing of spring events and poleward and upward shifts in plant and animal ranges are with very high confidence linked to recent warming. In some marine and freshwater systems, shifts in ranges and changes in algal, plankton and fish abundance are with high confidence associated with rising water temperatures, as well as related changes in ice cover, salinity, oxygen levels and circulation. {1.2}
(Source: AR4 Synthesis Report Summary for Policymakers)Human influences have: {2.4}
- very likely contributed to sea level rise during the latter half of the 20th century
- likely contributed to changes in wind patterns, affecting extra-tropical storm tracks and temperature patterns
- likely increased temperatures of extreme hot nights, cold nights and cold days
- more likely than not increased risk of heat waves, area affected by drought since the 1970s and frequency of heavy precipitation events.
What exactly do these phrases very high confidence and high confidence, and very likely, likely, more likely than not mean exactly?
We all know what a classical confidence interval statement means. These are definitely not classical confidence intervals; there is no explicit null hypothesis and no statistical distribution of a test statistic under the null.
These must be some kind of Bayesian statements of probability. When I took Bayesian econometrics with Ed Leamer at UCLA he characterized Bayesian probabilities as what a bookmaker would use to set terms for bets. But with Bayesian statistics, we still use quantitative distributions, for instance expressing our beliefs over a parameter with something like the lognormal distribution with a specific mean and variance.
Very likely? Likely? More likely than not? Highly confident?
How much do you believe that the Federal Reserve's policies from 2008 to 2012 prevented the world from entering a depression? Very likely? More likely than not? Not at all likely?
Of course, investment banks do issue "highly confident" letters. Those probably don't have an explicit statistical meaning either. I doubt that the IPCC considers their statements to be equivalent in quality to the banks'! (Hmmm...How confident are we that the IPCC statements are more likely to be correct than the banks'?)
Even more problematic, the statements coming out of the IPCC are not for an individual but for a group.
The IPCC does produce a document that describes how the writers should come up with these kind of probability statements. Here are two screen shots of key tables:
I guess my main question would be if the IPCC has invented this kind of group likelihood assessment or if is a well-recognized science. The list of references has only a few non-IPCC or non-climate items; I will see what they are about.
Friday, September 06, 2013
Health Insurance Plans on the Exchanges
With the advent of the new health care insurance exchanges, there will be lots of interesting developments over the next few months. How many plans get offered, what do they look like in terms of coverage and networks, how are they priced, how many uninsured pick up a plan?
In my state of New Hampshire, Anthem just announced some aspects of the statewide health plan they will offer on the NH exchange (run by the Feds since NH declined to develop its own).
See this story for some of the details; I apologize if the Valley News requires you to sign up first but I think you might get one free look at an article. If not, here is the gist of it: Anthem is offering a health plan that excludes certain hospitals across the state, with what seems to be a focus on excluding the smaller hospitals in certain area. Alice Peck Day hospital in Lebanon is excluded in my local area while the much-larger Dartmouth Hitchcock is included. Anthem is the only insurer offering a plan on the exchange for this year.
I have said all along that I expected exchange-based plans to embrace tight, closed networks. I think this is a good way to both control costs and possibly improve care.
Cost control occurs in at least two ways. One, high price suppliers can be excluded. Second, by directing more volume to a smaller number of suppliers, those favored in-network suppliers might offer the plan better prices. Care can improve if the limited suppliers can keep patients within one set of suppliers who agree on care protocols and avoid patients bouncing around from doctor to doctor.
Of course, these savings and improvements come at the cost of limiting patient choice (ex post choice, that is, after they have chosen the plan!)
I am curious on which of the two factors are the main reason for excluding some of the small hospitals in NH. Are the small places really the high cost suppliers? I might have thought that they would be able to offer lower prices. If so, then I am left relying on the second reason, that the other hospitals want to direct the patient volume to them.
At any rate, there could be dynamic effects of this kind of policy that should be considered. If losing access to these patients causes any of these hospitals to disappear, that will be a loss of competition.
In my state of New Hampshire, Anthem just announced some aspects of the statewide health plan they will offer on the NH exchange (run by the Feds since NH declined to develop its own).
See this story for some of the details; I apologize if the Valley News requires you to sign up first but I think you might get one free look at an article. If not, here is the gist of it: Anthem is offering a health plan that excludes certain hospitals across the state, with what seems to be a focus on excluding the smaller hospitals in certain area. Alice Peck Day hospital in Lebanon is excluded in my local area while the much-larger Dartmouth Hitchcock is included. Anthem is the only insurer offering a plan on the exchange for this year.
I have said all along that I expected exchange-based plans to embrace tight, closed networks. I think this is a good way to both control costs and possibly improve care.
Cost control occurs in at least two ways. One, high price suppliers can be excluded. Second, by directing more volume to a smaller number of suppliers, those favored in-network suppliers might offer the plan better prices. Care can improve if the limited suppliers can keep patients within one set of suppliers who agree on care protocols and avoid patients bouncing around from doctor to doctor.
Of course, these savings and improvements come at the cost of limiting patient choice (ex post choice, that is, after they have chosen the plan!)
I am curious on which of the two factors are the main reason for excluding some of the small hospitals in NH. Are the small places really the high cost suppliers? I might have thought that they would be able to offer lower prices. If so, then I am left relying on the second reason, that the other hospitals want to direct the patient volume to them.
At any rate, there could be dynamic effects of this kind of policy that should be considered. If losing access to these patients causes any of these hospitals to disappear, that will be a loss of competition.
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