8 ms·

Re Smart Bathroom: Every time I hear about all-knowing toilets, I continue to feel it’s putting the cart way ahead of the horse. There’s a rule in medicine: d

Re Smart Bathroom: Every time I hear about all-knowing toilets, I continue to feel it’s putting the cart way ahead of the horse. There’s a rule in medicine: don’t order a test whose outcome doesn’t change your decision. That’s not about cost-savings, it’s about avoiding false positives that make no sense in clinical context but raise flags that must be chased down. This sort of thing is literally promising to just continually run un-merited urinalysis left and right. “More data” is not inherently good. Without a framework of information for interpretation of that data, it will do far more harm than good. Honestly, the reason so little tech disruption keeps happening in the provision of medical services: no one trying to “disrupt” bothers asking what is or is not useful. There are just some ideas completely out of touch with what people need or want or have friction over, and they just refuse to die because they’re the most obvious ideas to have if you’re unfamiliar with the territory.

wonderous 9y ago
Generally speaking the topic falls into the desire to have real-time/always-on data feeds that magically produce value just because they’re always producing data. That said, beyond asking the obvious, why do you need the data real-time and how much value does this produce, I do not know a better filter or means to guide a startup covering this ground.
- arkades 9y ago
  There is no easy guide. Speak to the people doing the work, and target your innovation to the existing revenue streams (that is, if your product benefits an insurer, why are you pitching it to the patients?). As someone in the industry I do of course have a wishlist, but, you know. As to clean: a self cleaning toilet and a roomba living in the corner is a huge step away from treating your toilet as an always-on medical lab.
mynegation 9y ago
There is (pretty horrible) joke: "If violence does not solve the problem, you are not using enough of it". It may be the case with data. Put another way, we may be in the uncanny valley of data. There is definitely an issue of under-diagnosis for many diseases. More data may not help initially but once we are over the critical mass in the amount of data and sophistication of ML algorithms trained on it, it will get over the hump.
- arkades 9y ago
  We have a much bigger problem with overdiagnosis than underdiagnosis, and the latter is not likely to be solved with this sort of scattershot data collection. The former is very likely to be inflamed. The difference is that you actually hear about the Diagnosis X That Was Missed, but you never hear about That Simple Blood Test That Should Never Have Been Drawn but that Showed Positive for a Marker Common In Disease But Also Found in the General Population so They Needed a Biopsy to Rule Out, and Spent Hundreds or Thousands if Dollars and Lost Several Days of Work For Nothing At All. The latter is much, much, more common. The “miss” is usually due to missing something in the modern deluge of data coupled to inadequate appointment time/resources, not lack of data availability. For a real life example: heard about a patient die the other day. Reviewing his records with a student afterwards I saw his potassium had been climbing in his last two panels (though it hadn’t yet gotten high enough to be a red flag), and he didn’t get the blood gas that should have been done as per protocol. Thing is, the data was there, the rules were there, but someone with enough time to meaningfully review it was not. Would more piles of detritus data to sift through made that more likely, or less? I also remain an ML skeptic for the time being. ML analysis of patient data is a big sophisticated version of retrospective analysis, which for purely statistical reasons is highly, highly unreliable.
  - mynegation 9y ago
    Not sure how this proves me wrong. What it does prove is that analysis of data should not be left (entirely) to humans, who are inherently flaky. Dark irony of this situation is that _more_ data from additional test had a chance of saving the patient. The way it should have worked: based on previous labeled examples, computer system should have noticed the uptrend in potassium and flag this client for blood gas, and then make classification based on available and _additional_ data.
    - arkades 9y ago
      It’s not the blood gas that would have saved him; just seeing the potassium trending up would have done it. Thing is, there was a context where that mattered. In others, it wouldn’t have. That’s why you need someone capable of interpretation to -look- at it. EMRs have done more to harm patients than help them, now that everyone constantly copy-pastes old patient hx before adding their notes (so nothing can be said to have been missed), people are constantly shifting through piles of be and missing the pertinent information. To rephrase: algos intelligent enough to be useful in the manner you imagine are a long way off from existing, but data deluge that harms patient care is -already here-. Don’t worsen the deluge until you improve the ability to digest and present it. That EMR “decision aids” aren’t anywhere near sophisticated enough to tell the difference in the myriad of situations we have is why docs fight so hard against those automated “flags.” We get piles of them, all the time. QI people call it alarm fatigue, they know it’s a thing, and yet... they do it anyway, because it sounds (like in your post) like the obvious thing to flag. It’s not that AI is inherently incapable of getting there. It’s that when it does is a long way off. Medicine looks a lot simpler from the outside.
was_boring 9y ago
> “More data” is not inherently good. Without a framework of information for interpretation of that data, it will do far more harm than good. I'm glad people are saying this. I'm in a constant fight at work with people who want "more data." What ends up happening most of the time is it's ignored or people do not interpret it correctly because they don't have the ability or context to do it (doing stats wrong for instance).
- davemel37 9y ago
  Have them read Chapter 5 of this book. https://www.cia.gov/library/center-for-the-study-of-intelligence/csi-publications/books-and-monographs/psychology-of-intelligence-analysis/PsychofIntelNew.pdf https://www.cia.gov/library/center-for-the-study-of-intellig... "Using experts in a variety of fields as test subjects, experimental psychologists have examined the relationship between the amount of information available to the experts, the accuracy of judgments they make based on this information, and the experts’ confidence in the accuracy of these judgments." "Key findings from this research are: • Once an experienced analyst has the minimum information necessary to make an informed judgment, obtaining additional information generally does not improve the accuracy of his or her estimates. Additional information does, however, lead the analyst to become more confident in the judgment, to the point of overconfidence. • Experienced analysts have an imperfect understanding of what information they actually use in making judgments. They are unaware of the extent to which their judgments are determined by a few dominant factors, rather than by the systematic integration of all available information. Analysts actually use much less of the available information than they think they do."
  - 0xCMP 9y ago
    But, the main issue is "once an experienced analyst has the minimum information necessary to make an informed judgement" is followed by "they are unaware of the extent to which their judgements are determined by a few dominant factors." Which implies they do not know which part of the data is most important. No? disclaimer: didn't click link/read chapter
    - 9y ago
traviswingo 9y ago
This reminded me of the urinal in "Benchwarmers"
username223 9y ago
> That’s not about cost-savings, it’s about avoiding false positives that make no sense in clinical context but raise flags that must be chased down. Unfortunately the rule doesn't apply in this case. Your "smart" toilet is not trying to diagnose problems. It is trying to infer which ads you will click on the most, to make money for a surveillance company. A toilet that has a handful of true positives, a huge number of false ones, and doesn't kill too many people is pure win: surveillance and pharma both make money, and it's very hard for a consumer to tell if he never had X disease, or if buying the medicine prevented his X disease.
WmyEE0UsWAwC2i 9y ago
Why would the data only be used for patology? * Diet balancig? (Hey, eat more cucumbers) * Calories? (IANAD) * Also more serendipiteous opportunities we can't foresee now Or: (at the doctor's) t = 0 - Doc - I would need a urine analysis t = 60s - User - Here you are. Cons: * Huge privacy concerns (Hey, you are fired! btw, you also have cancer)
- underwoodley 9y ago
  It's possible that a) diet isn't that hard to figure out and b) gamifying, quantifying, testing, and over-extrapolation from isolated scientific results make people confused and much less effective at making the right decisions consistently, which is the part they really need help with.
alphonsegaston 9y ago
It's also literally an Onion article: https://www.theonion.com/new-e-toilet-to-revolutionize-online-shitting-1819565332 https://www.theonion.com/new-e-toilet-to-revolutionize-onlin...
LambdaComplex 9y ago
>“More data” is not inherently good. Without a framework of information for interpretation of that data, it will do far more harm than good. There's an episode of Star Trek: Voyager about this[1]. Seven of Nine absorbs months worth of data (way more than a human could actually process) from the ship's computer, and "discovers" that both half of the ship plans on mutinying and that the Captain wasn't actually trying to get them home. Both of which were false. 1. http://memory-alpha.wikia.com/wiki/The_Voyager_Conspiracy_(episode) http://memory-alpha.wikia.com/wiki/The_Voyager_Conspiracy_(e...
- ams6110 9y ago
  However she does also make the useful and correct deduction that photonic fleas have infested the plasma conduits.
subdane 9y ago
Garbage in, garbage out.
outworlder 9y ago
> There’s a rule in medicine: don’t order a test whose outcome doesn’t change your decision. That’s not about cost-savings, it’s about avoiding false positives that make no sense in clinical context but raise flags that must be chased down. There is also a rule in (system) operations: don't page unless immediate action (from humans) is required. This doesn't stop us from collecting data. If there is an anomaly, then we can look back at the data if necessary. Alternatively, there ARE things you can alert on. My brother has type 1 diabetes. He got a free urinalysis in the form of ants crawling in the toilet. I expect – but since I don't have time series data from this toilet, I can't prove – that sensors would detect and increasing amount of glucose in the urine over time. If anonymized, this sort of data would be useful for research as well. I agree that giving any joe schmuck access to the raw data would result in unnecessary procedures.
- arkades 9y ago
  There’s a legal context here. Once the data is available, physicians are obligated to chasenit down even if they think it’s unimportsnt. Ignoring data loses malpractice suits; unnecessary and ultimately harmful diagnostics prompted by data does not.
  - gerdesj 9y ago
    Not all medicine is practised within the legal framework that you labour under. If you are a doctor then you should be able to publish your real opinions here, within reason (prefaced with a short disclaimer if you deem it necessary, I would, along the lines of "I'm a MD, practising in <country> and this my personal opinion") and I, for one, would love to hear them.
    - doctoring 9y ago
      I'm an MD, practicing in the US. I don't know the actual legality. But here's what I do know from attempting to implement multiple projects within the US for clinical care and for clinical research: most providers, hospitals, and pharmaceutical companies we have worked with have balked at the ability to have high resolution data fed into their medical record or research data systems. In most cases, they are worried that if they had the data, they would have to act on it were something to be concerning. And they do not want that responsibility. Example: we were in talks to feed in near-realtime blood glucose, activity, and blood pressure measurements from patients on a clinical trial. Surely that would be useful for better sussing out the effects of a research drug than the current process (patient comes in every few months to get measured or have their log data entered or meter data downloaded)? Nope, multiple top 5 pharma companies didn't want the responsibility and liability of seeing their data that often, because what if a patient had super low or super high glucose and they later died? You had the ability to act on it but didn't. They'd rather just not have it at all. It sounds ridiculous. And again, I don't know the actual legal/liability issues, but based on my experience with malpractice cases, I could see a viable case to be made. And there are certainly institutions out there who believe the benefit is worth the cost of that responsibility for certain use cases. But my experiences have definitely made me reconsider some of these things. All that said, I am definitely in favor of collecting more health data (somehow), because until we have more data we won't know its utility. So far, in general it has been shown that more testing and more information often doesn't lead to better outcomes, but the cost of data is getting lower -- aside from aforementioned liability cost/fear.
firethief 9y ago
The applicability of that rule is a symptom of healthcare's overreliance on human judgement. To a rational decision-maker, more data is better. When the problem calls for an expert system, it's a problem well within the domain where algorithms outperform humans.
gricardo99 9y ago
I'm guessing the big innovation here would be developing useful diagnostics that skew towards high specificity at the expense of lower sensitivity. Additionally, If you're collecting a bunch of datapoints much more frequently than current screening/testing regimes, You would need some smarter averaging to find trends and weed out many, if not all false positives. I think Reliable, cheap, user friendly medical diagnostics would be a game changer, but of course the data analytics to make good use would be different than how current, one-off, medical testing is treated.
throwawaylalala 9y ago
What if ypu use that data to train AI? How many lives saved or serious health issues avoided by early detection?
blackkettle 9y ago
Moreover, the whole 'smart bathroom' thing has already been pretty much solved in Japan - and more or less keeping in mind the principle that you describe. You can get your temperature, get a warm seat, turn on some ambient music to mask your own, more personal music, flush, bidet, whatever all in most toilets in your average department store. You can get more complex offerings that do perform some more complicated tests if you really want to. The 'bath room' itself is also typically a single, self contained unit, often in some kind of mold, and including the shower, accoutrements, and bath in a full space designed to get wet and save/share the clean water in the bath. The 'bath room' usually has a waterproof, electronic control panel which allows you to set timers for filling the bath, set an ambient temperature to keep it at, set the preferred level of water, set different default temperatures for the shower and bath, and typically also access all these features from other places like the kitchen where a companion panel is installed. This is typical of your average house - I just described my wife's parents' place, which was built 10 years ago. The whole design thing is completely solved there, and why that approach has not been adopted across the U.S. and Europe by now is completely beyond me. But the killer thing there would be to bring the Japanese approach to the US and Europe and plug in some better smart access features. Or go to Japan and plug them in there, where the infrastructure and demand is already in place [well, Google is probably on it already but...]
Chris2048 9y ago
> don’t order a test whose outcome doesn’t change your decision > raise flags that must be chased down If a red flag must be chased down, doesn't that mean it changes your decision?

wonderous 9y ago

Generally speaking the topic falls into the desire to have real-time/always-on data feeds that magically produce value just because they’re always producing data. That said, beyond asking the obvious, why do you need the data real-time and how much value does this produce, I do not know a better filter or means to guide a startup covering this ground.

arkades 9y ago
There is no easy guide. Speak to the people doing the work, and target your innovation to the existing revenue streams (that is, if your product benefits an insurer, why are you pitching it to the patients?). As someone in the industry I do of course have a wishlist, but, you know. As to clean: a self cleaning toilet and a roomba living in the corner is a huge step away from treating your toilet as an always-on medical lab.

mynegation 9y ago

There is (pretty horrible) joke: "If violence does not solve the problem, you are not using enough of it". It may be the case with data. Put another way, we may be in the uncanny valley of data. There is definitely an issue of under-diagnosis for many diseases. More data may not help initially but once we are over the critical mass in the amount of data and sophistication of ML algorithms trained on it, it will get over the hump.

arkades 9y ago
We have a much bigger problem with overdiagnosis than underdiagnosis, and the latter is not likely to be solved with this sort of scattershot data collection. The former is very likely to be inflamed. The difference is that you actually hear about the Diagnosis X That Was Missed, but you never hear about That Simple Blood Test That Should Never Have Been Drawn but that Showed Positive for a Marker Common In Disease But Also Found in the General Population so They Needed a Biopsy to Rule Out, and Spent Hundreds or Thousands if Dollars and Lost Several Days of Work For Nothing At All. The latter is much, much, more common. The “miss” is usually due to missing something in the modern deluge of data coupled to inadequate appointment time/resources, not lack of data availability. For a real life example: heard about a patient die the other day. Reviewing his records with a student afterwards I saw his potassium had been climbing in his last two panels (though it hadn’t yet gotten high enough to be a red flag), and he didn’t get the blood gas that should have been done as per protocol. Thing is, the data was there, the rules were there, but someone with enough time to meaningfully review it was not. Would more piles of detritus data to sift through made that more likely, or less? I also remain an ML skeptic for the time being. ML analysis of patient data is a big sophisticated version of retrospective analysis, which for purely statistical reasons is highly, highly unreliable.
- mynegation 9y ago
  Not sure how this proves me wrong. What it does prove is that analysis of data should not be left (entirely) to humans, who are inherently flaky. Dark irony of this situation is that _more_ data from additional test had a chance of saving the patient. The way it should have worked: based on previous labeled examples, computer system should have noticed the uptrend in potassium and flag this client for blood gas, and then make classification based on available and _additional_ data.
  - arkades 9y ago
    It’s not the blood gas that would have saved him; just seeing the potassium trending up would have done it. Thing is, there was a context where that mattered. In others, it wouldn’t have. That’s why you need someone capable of interpretation to -look- at it. EMRs have done more to harm patients than help them, now that everyone constantly copy-pastes old patient hx before adding their notes (so nothing can be said to have been missed), people are constantly shifting through piles of be and missing the pertinent information. To rephrase: algos intelligent enough to be useful in the manner you imagine are a long way off from existing, but data deluge that harms patient care is -already here-. Don’t worsen the deluge until you improve the ability to digest and present it. That EMR “decision aids” aren’t anywhere near sophisticated enough to tell the difference in the myriad of situations we have is why docs fight so hard against those automated “flags.” We get piles of them, all the time. QI people call it alarm fatigue, they know it’s a thing, and yet... they do it anyway, because it sounds (like in your post) like the obvious thing to flag. It’s not that AI is inherently incapable of getting there. It’s that when it does is a long way off. Medicine looks a lot simpler from the outside.

was_boring 9y ago

> “More data” is not inherently good. Without a framework of information for interpretation of that data, it will do far more harm than good. I'm glad people are saying this. I'm in a constant fight at work with people who want "more data." What ends up happening most of the time is it's ignored or people do not interpret it correctly because they don't have the ability or context to do it (doing stats wrong for instance).

davemel37 9y ago
Have them read Chapter 5 of this book. https://www.cia.gov/library/center-for-the-study-of-intelligence/csi-publications/books-and-monographs/psychology-of-intelligence-analysis/PsychofIntelNew.pdf https://www.cia.gov/library/center-for-the-study-of-intellig... "Using experts in a variety of fields as test subjects, experimental psychologists have examined the relationship between the amount of information available to the experts, the accuracy of judgments they make based on this information, and the experts’ confidence in the accuracy of these judgments." "Key findings from this research are: • Once an experienced analyst has the minimum information necessary to make an informed judgment, obtaining additional information generally does not improve the accuracy of his or her estimates. Additional information does, however, lead the analyst to become more confident in the judgment, to the point of overconfidence. • Experienced analysts have an imperfect understanding of what information they actually use in making judgments. They are unaware of the extent to which their judgments are determined by a few dominant factors, rather than by the systematic integration of all available information. Analysts actually use much less of the available information than they think they do."
- 0xCMP 9y ago
  But, the main issue is "once an experienced analyst has the minimum information necessary to make an informed judgement" is followed by "they are unaware of the extent to which their judgements are determined by a few dominant factors." Which implies they do not know which part of the data is most important. No? disclaimer: didn't click link/read chapter
  - 9y ago

traviswingo 9y ago

This reminded me of the urinal in "Benchwarmers"

username223 9y ago

> That’s not about cost-savings, it’s about avoiding false positives that make no sense in clinical context but raise flags that must be chased down. Unfortunately the rule doesn't apply in this case. Your "smart" toilet is not trying to diagnose problems. It is trying to infer which ads you will click on the most, to make money for a surveillance company. A toilet that has a handful of true positives, a huge number of false ones, and doesn't kill too many people is pure win: surveillance and pharma both make money, and it's very hard for a consumer to tell if he never had X disease, or if buying the medicine prevented his X disease.

WmyEE0UsWAwC2i 9y ago

Why would the data only be used for patology? * Diet balancig? (Hey, eat more cucumbers) * Calories? (IANAD) * Also more serendipiteous opportunities we can't foresee now Or: (at the doctor's) t = 0 - Doc - I would need a urine analysis t = 60s - User - Here you are. Cons: * Huge privacy concerns (Hey, you are fired! btw, you also have cancer)

underwoodley 9y ago
It's possible that a) diet isn't that hard to figure out and b) gamifying, quantifying, testing, and over-extrapolation from isolated scientific results make people confused and much less effective at making the right decisions consistently, which is the part they really need help with.

alphonsegaston 9y ago

It's also literally an Onion article: https://www.theonion.com/new-e-toilet-to-revolutionize-online-shitting-1819565332 https://www.theonion.com/new-e-toilet-to-revolutionize-onlin...

LambdaComplex 9y ago

>“More data” is not inherently good. Without a framework of information for interpretation of that data, it will do far more harm than good. There's an episode of Star Trek: Voyager about this[1]. Seven of Nine absorbs months worth of data (way more than a human could actually process) from the ship's computer, and "discovers" that both half of the ship plans on mutinying and that the Captain wasn't actually trying to get them home. Both of which were false. 1. http://memory-alpha.wikia.com/wiki/The_Voyager_Conspiracy_(episode) http://memory-alpha.wikia.com/wiki/The_Voyager_Conspiracy_(e...

ams6110 9y ago
However she does also make the useful and correct deduction that photonic fleas have infested the plasma conduits.

subdane 9y ago

Garbage in, garbage out.

outworlder 9y ago

> There’s a rule in medicine: don’t order a test whose outcome doesn’t change your decision. That’s not about cost-savings, it’s about avoiding false positives that make no sense in clinical context but raise flags that must be chased down. There is also a rule in (system) operations: don't page unless immediate action (from humans) is required. This doesn't stop us from collecting data. If there is an anomaly, then we can look back at the data if necessary. Alternatively, there ARE things you can alert on. My brother has type 1 diabetes. He got a free urinalysis in the form of ants crawling in the toilet. I expect – but since I don't have time series data from this toilet, I can't prove – that sensors would detect and increasing amount of glucose in the urine over time. If anonymized, this sort of data would be useful for research as well. I agree that giving any joe schmuck access to the raw data would result in unnecessary procedures.

arkades 9y ago
There’s a legal context here. Once the data is available, physicians are obligated to chasenit down even if they think it’s unimportsnt. Ignoring data loses malpractice suits; unnecessary and ultimately harmful diagnostics prompted by data does not.
- gerdesj 9y ago
  Not all medicine is practised within the legal framework that you labour under. If you are a doctor then you should be able to publish your real opinions here, within reason (prefaced with a short disclaimer if you deem it necessary, I would, along the lines of "I'm a MD, practising in <country> and this my personal opinion") and I, for one, would love to hear them.
  - doctoring 9y ago
    I'm an MD, practicing in the US. I don't know the actual legality. But here's what I do know from attempting to implement multiple projects within the US for clinical care and for clinical research: most providers, hospitals, and pharmaceutical companies we have worked with have balked at the ability to have high resolution data fed into their medical record or research data systems. In most cases, they are worried that if they had the data, they would have to act on it were something to be concerning. And they do not want that responsibility. Example: we were in talks to feed in near-realtime blood glucose, activity, and blood pressure measurements from patients on a clinical trial. Surely that would be useful for better sussing out the effects of a research drug than the current process (patient comes in every few months to get measured or have their log data entered or meter data downloaded)? Nope, multiple top 5 pharma companies didn't want the responsibility and liability of seeing their data that often, because what if a patient had super low or super high glucose and they later died? You had the ability to act on it but didn't. They'd rather just not have it at all. It sounds ridiculous. And again, I don't know the actual legal/liability issues, but based on my experience with malpractice cases, I could see a viable case to be made. And there are certainly institutions out there who believe the benefit is worth the cost of that responsibility for certain use cases. But my experiences have definitely made me reconsider some of these things. All that said, I am definitely in favor of collecting more health data (somehow), because until we have more data we won't know its utility. So far, in general it has been shown that more testing and more information often doesn't lead to better outcomes, but the cost of data is getting lower -- aside from aforementioned liability cost/fear.

firethief 9y ago

The applicability of that rule is a symptom of healthcare's overreliance on human judgement. To a rational decision-maker, more data is better. When the problem calls for an expert system, it's a problem well within the domain where algorithms outperform humans.

gricardo99 9y ago

I'm guessing the big innovation here would be developing useful diagnostics that skew towards high specificity at the expense of lower sensitivity. Additionally, If you're collecting a bunch of datapoints much more frequently than current screening/testing regimes, You would need some smarter averaging to find trends and weed out many, if not all false positives. I think Reliable, cheap, user friendly medical diagnostics would be a game changer, but of course the data analytics to make good use would be different than how current, one-off, medical testing is treated.

throwawaylalala 9y ago

What if ypu use that data to train AI? How many lives saved or serious health issues avoided by early detection?

blackkettle 9y ago

Moreover, the whole 'smart bathroom' thing has already been pretty much solved in Japan - and more or less keeping in mind the principle that you describe. You can get your temperature, get a warm seat, turn on some ambient music to mask your own, more personal music, flush, bidet, whatever all in most toilets in your average department store. You can get more complex offerings that do perform some more complicated tests if you really want to. The 'bath room' itself is also typically a single, self contained unit, often in some kind of mold, and including the shower, accoutrements, and bath in a full space designed to get wet and save/share the clean water in the bath. The 'bath room' usually has a waterproof, electronic control panel which allows you to set timers for filling the bath, set an ambient temperature to keep it at, set the preferred level of water, set different default temperatures for the shower and bath, and typically also access all these features from other places like the kitchen where a companion panel is installed. This is typical of your average house - I just described my wife's parents' place, which was built 10 years ago. The whole design thing is completely solved there, and why that approach has not been adopted across the U.S. and Europe by now is completely beyond me. But the killer thing there would be to bring the Japanese approach to the US and Europe and plug in some better smart access features. Or go to Japan and plug them in there, where the infrastructure and demand is already in place [well, Google is probably on it already but...]

Chris2048 9y ago

> don’t order a test whose outcome doesn’t change your decision > raise flags that must be chased down If a red flag must be chased down, doesn't that mean it changes your decision?