Comment by boxspam | Hacker News Reader

Comment by boxspam | Hacker News Reader

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> is likely just overfitting the existing data.

I would be more careful with your assessment. Or you are overfitting to your limited 5-minute-understanding of what this does. Telling mathematicians and statisticians they have overfitted is akin to a grave professional insult (you are basically accusing them of foolish behavior at best, fraud/unethical behavior at worst. As a bioinformatician, you may be interested in these articles, which go a little deeper on the technology: https://www.nature.com/articles/srep01236 https://www.sciencedirect.com/science/article/pii/S240547121... http://journals.plos.org/plosone/article?id=10.1371/journal....

> probably doesn't have the data to really build a robust model

It is both possible to build robust models on small datasets (and that data is shared, or more abundant than you expect).

> Even major academic centers have relatively limited data for the number of permutations of health possibilities.

This is one of the problems they (the IT supplier) solved. They are able to build regulatory-proof models from 100.000's of permutations. Another, more recent, advance is in counterfactual analysis (what would have happened if this pneumonia patient also had COPD?).

Listen I'll be thrilled if I'm wrong, but the article says they 'expect to save' $xxxx.xx. Not that they are saving that much. Come back to me when they actually have reduced average length of stay for pneumonia patients by two days over a long time period. Just because they can find a most efficient pathway for patients, doesn't mean it will be followed, or that it is even possible to be followed clinically.

My hospital currently uses Allscripts, we have care pathways, and when I want to order something for a patient of mine (because I think the patient needs it) that isn't in the care pathway, I just order it. It seems that what they are trying to do is 'Nudge', in the Thaler sense, providers to do what they suggest is the most efficient pathway. Would love to see a randomized trial of giving some providers this nudge and others the current pathway to see which is most effective. But what I often see is that providers have learned behaviors from years of training where they 'need' tests X, Y, and Z for disease Q, so without extensive education, they still tend to order those things.

edit: just saw that ballenf beat me to this punchline already.

They actually reduced the average length of stay for knee replacement from 3.3 to 2.4 days. They verifiably saved costs of a middle-sized hospital of 10m$ a year. If we assume professional integrity, then they won't intentionally inflate projected savings, so we have no reason to doubt their expectations. (Just like I don't have any reason to doubt that you don't give inflated life expectancy projections to your patients, or receive kickbacks from needless prescriptions). It is, on a professional level, like telling an engineer who projects a bridge to be safe, that they likely build an unsafe bridge, and you'll only believe it when at least a 1000 people have crossed it (trust me, I am a lorry driver who loves driving over bridges).

The hospital in the article also used Allscripts.

> The next step for Flagler was to review the findings with the Physician IT Group (called the PIT Crew) and to make the necessary changes to AllScripts. Physician buy-in is critical...

> There are two interesting anecdotes from this process that bear repeating. The first is that once doctors became aware of the work that was being done, requests for membership in the PIT Crew skyrocketed and attendance at the bi-weekly meetings doubled. Doctors want access to data.

> The second is that one of the more accomplished physicians remarked that the care process model for pneumonia was far lighter than what he would have used, but upon looking at the outcomes, readily agreed that it delivered the same or better care in almost every case – and that what he was doing was essentially unnecessary, or wasteful. Presented with the evidence, he committed himself to rethinking his approach.

Edit:

> but decreasing length of stay by 2 days would be a shocking advance.

If you look at the industry average, maybe. But these 2 days were for this specific hospital (being a community hospital they get many different patients, and you can't have experts for every area). Perhaps removing those 2 days brought them closer to industry average, which seems like a very reasonable advance.

Sorry for the shameless plug but check out what we're doing at Emerge. (Savinghealthcare.net)

We are offering better, cleaner amd aggregated patient data at the point of care. We use ML not to predict patient outcome or progress but to make sense of the data.

For the record, I'm working on a topological data analysis project that is in some ways quite similar to this, and I'd be astonished if a single community hospital has the depth needed. We're working with thirty-some.

The key here is that TDA is packaged into an application that is designed explicitly for use by practitioners. All of the underlying math (and you know there is lots of it in TDA) is abstracted. What is shown is the groups and the atomic level explains (this group is here for these reasons e.g. they received albuterol upon admittance). Your instinct is correct, but that is what is interesting about this case - the hospital, without a single data scientist, was able to to achieve this with only slick SQL skills and engaged doctors.

Screenshots for the app and videos can be found here: https://www.ayasdi.com/solutions/clinical-variation-manageme...

you are basically accusing them of foolish behavior at best, fraud/unethical behavior at worst

Given the conflict of interest in this article, I'd say that's the least of what the authors should be accused of.

Why? Just because you have active PR, your methods are now also flawed?

What is the conflict of interest for a company doing or hiring a PR? Is it fraud or unethical to promote your company?

Your logic/conclusion makes no sense to me at all.

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