ABOUT THE SPEAKER
Peter van Manen - Electronic systems expert
Peter van Manen is the Managing Director of McLaren Electronics, which provides data systems to major motorsports series.

Why you should listen

To say that Peter van Manen has a high-speed job would be an understatement. As Managing Director of McLaren Electronics, which provides electronics and data collection software to motorsports events, he and his team work in real time during a race to improve cars on about 500 different parameters. That's about 750 million data points in two hours.

But recently van Manen and his team have been wondering: Why can't the extremely precise and subtle data-collection and analysis systems used in motorsports be applied elsewhere, for the benefit of all? They have applied their systems to ICU units at Birmingham Children's Hospital with real-time analysis that allows them to proactively prevent cardiac arrests. The unit has seen a 25 percent decrease in life-threatening events. And it's just the beginning.

More profile about the speaker
Peter van Manen | Speaker | TED.com
TEDxNijmegen

Peter van Manen: Better baby care -- thanks to Formula 1

Si munden garat e Formula 1 te ndihmojne...foshnjet?

Filmed:
845,406 views

Gjate nje gare te Formula 1, nje makine dergon qindra milione te dhena numerike ne garazh per analize ne kohe reale dhe reagim. Pra pse mos te perdorim kete sistem te detajuar dhe rigoroz diku tjeter si... ne nje spital femijesh? Peter van Manen na tregon me shume.
- Electronic systems expert
Peter van Manen is the Managing Director of McLaren Electronics, which provides data systems to major motorsports series. Full bio

Double-click the English transcript below to play the video.

00:12
Motor racing is a funny old business.
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Garat me makina jane nje biznes i vjeter dhe i kendshem.
00:14
We make a new car every year,
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Ne krijojme nje makine te re cdo vit,
00:16
and then we spend the rest of the season
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dhe pastaj e kalojme pjesen tjeter te sezonit
00:19
trying to understand what it is we've built
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duke u perpjekur te kuptojme se c'kemi ndertuar
00:21
to make it better, to make it faster.
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per ta bere me te mire, per ta bere me te shpejte.
00:25
And then the next year, we start again.
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Dhe pastaj vitin tjeter, rifillojme perseri.
00:28
Now, the car you see in front of you is quite complicated.
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Kjo makine qe shikoni eshte disi e komplikuar.
00:32
The chassis is made up of about 11,000 components,
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Shasia eshte krijuar me rreth 11.000 komponenente,
00:36
the engine another 6,000,
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motorri me 6.000 te tjera,
00:38
the electronics about eight and a half thousand.
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pjesa elektronike me rreth tete mije e 500.
00:41
So there's about 25,000 things there that can go wrong.
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Pra, ka rreth 25.000 gjera aty qe mund te shkojne keq.
00:46
So motor racing is very much about attention to detail.
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Pra garat me makina jane pak a shume kujdesi ndaj detajeve.
00:51
The other thing about Formula 1 in particular
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Pjesa tjeter e Formula 1 ne vecanti
00:54
is we're always changing the car.
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eshte se perhere e ndryshojme makinen.
00:56
We're always trying to make it faster.
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Perhere perpiqemi ta bejme me te shpejte.
00:58
So every two weeks, we will be making
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Pra cdo dy jave, ne do jemi duke krijuar
01:01
about 5,000 new components to fit to the car.
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rreth 5.000 komponente te rinj qe ti pershtaten makines.
01:05
Five to 10 percent of the race car
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Pese ne 10 perqind te makines garuese
01:08
will be different every two weeks of the year.
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do jete ndryshe cdo dy jave te vitit.
01:11
So how do we do that?
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Pra si e bejme kete?
01:14
Well, we start our life with the racing car.
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Ne e fillojme jeten tone me makinen garuese.
01:17
We have a lot of sensors on the car to measure things.
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Kemi shume sensore ne makine per te matur gjerat.
01:21
On the race car in front of you here
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Ne kete makine garuese para jush
01:23
there are about 120 sensors when it goes into a race.
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ka rreth 120 sensor kur ajo shkon per nje gare.
01:26
It's measuring all sorts of things around the car.
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Masin gjithcka rreth makines.
01:30
That data is logged. We're logging about
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Te dhenat jane te regjistruara. Regjistrojme rreth
01:32
500 different parameters within the data systems,
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500 parametra te ndryshme ne sistemin e te dhenave,
01:36
about 13,000 health parameters and events
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rreth 13.000 parametra shendetesore dhe ngjarje
01:39
to say when things are not working the way they should do,
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per te treguar kur gjerat nuk shkojne ashtu sic duhet,
01:44
and we're sending that data back to the garage
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dhe i dergojme te dhenat pas ne garazh
01:47
using telemetry at a rate of two to four megabits per second.
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duke perdorur telemetrine ne shkallen dy deri kater megabit per sekond.
01:52
So during a two-hour race, each car will be sending
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Pra cdo gare dy oreshe, cdo makine do dergoje
01:55
750 million numbers.
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750 milion numra.
01:57
That's twice as many numbers as words that each of us
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Kjo eshte dyfishi i numrave te fjaleve qe secili nga ne perdor
02:00
speaks in a lifetime.
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per te folur gjate gjithe jetes se tij.
02:02
It's a huge amount of data.
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Eshte nje sasi e madhe te dhenash.
02:05
But it's not enough just to have data and measure it.
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Por te pasurit vec te dhena dhe matje nuk mjafton.
02:07
You need to be able to do something with it.
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Duhet te jesh i afte te besh dicka me te.
02:09
So we've spent a lot of time and effort
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Pra kemi shpenzuar shume kohe dhe mund
02:12
in turning the data into stories
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per ti kthyer te dhenat ne histori
02:14
to be able to tell, what's the state of the engine,
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per te qene te afte te tregojme se cila eshte situata e motorit,
02:17
how are the tires degrading,
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si po degradojne gomat,
02:19
what's the situation with fuel consumption?
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cila eshte situata me konsumin e karburantit?
02:23
So all of this is taking data
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Keto jane te dhena te marra
02:26
and turning it into knowledge that we can act upon.
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dhe te kthyera ne njohuri per te vepruar me pas.
02:29
Okay, so let's have a look at a little bit of data.
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Ne rregull, le ti hedhim nje sy disa te dhenave.
02:32
Let's pick a bit of data from
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Le te marim disa te dhena nga
02:34
another three-month-old patient.
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nje pacient tre-muajsh.
02:37
This is a child, and what you're seeing here is real data,
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Ky eshte nje femije, dhe ajo cka shikoni ketu jane te dhena te verteta,
02:41
and on the far right-hand side,
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dhe ne fundin e anes se krahut te djathte,
02:43
where everything starts getting a little bit catastrophic,
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aty ku gjithcka fillon te behet disi katastrofike,
02:46
that is the patient going into cardiac arrest.
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e cila eshte qe ky pacient eshte nen arrest kardiak.
02:49
It was deemed to be an unpredictable event.
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Mendohet se ishte nje ngjarje e paparishikueshme.
02:53
This was a heart attack that no one could see coming.
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Ky ishte nje infarkt i zemres ku asnje nuk e priti.
02:56
But when we look at the information there,
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Por kur shohim informacionin ketu,
02:59
we can see that things are starting to become
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mund te shohim se gjerat po fillojne te behen
03:01
a little fuzzy about five minutes or so before the cardiac arrest.
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disi te turbulla per rreth pese minuta para arrestit kardiak.
03:05
We can see small changes
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Mund te shohim ndryshime te vogla
03:07
in things like the heart rate moving.
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ne gjera si levizja e rrahjes se zemres.
03:10
These were all undetected by normal thresholds
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Keto ishin te padallueshme nga pragjet normale
03:12
which would be applied to data.
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te cilat mund te aplikoheshin ne te dhena.
03:15
So the question is, why couldn't we see it?
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Pra pyetja eshte, pse nuk mund ta shikonim?
03:18
Was this a predictable event?
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Ishte kjo nje ngjarje e parashikueshme?
03:20
Can we look more at the patterns in the data
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Mund te shohim me shume ne strukturen e te dhenave
03:23
to be able to do things better?
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per te mundur ti bejme gjerat me mire?
03:27
So this is a child,
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Pra ky eshte nje femije,
03:29
about the same age as the racing car on stage,
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ne te njejten moshe sa nje makine garuese ne skene
03:33
three months old.
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tre muajsh.
03:34
It's a patient with a heart problem.
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Eshte nje pacient me nje problem kardiak.
03:37
Now, when you look at some of the data on the screen above,
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Nese mund te shikoni disa te dhena ne monitorin e mesiperm,
03:40
things like heart rate, pulse, oxygen, respiration rates,
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gjera si ritmi kardiak, pulsi, oksigjeni, ritmi i frymemarrjes,
03:45
they're all unusual for a normal child,
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jane te gjitha te pazakonte per nje femije normal,
03:48
but they're quite normal for the child there,
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por jane shume normale per kete femije ketu,
03:51
and so one of the challenges you have in health care is,
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dhe nje nga sfidat qe keni ne kujdesin ndaj shendetit eshte,
03:55
how can I look at the patient in front of me,
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si mund ta shoh pacientin para meje,
03:58
have something which is specific for her,
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te kete dicka qe eshte specifike per ate,
04:01
and be able to detect when things start to change,
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dhe te mundem te zbuloj kur gjerat fillojne te ndryshojne,
04:04
when things start to deteriorate?
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kur gjerat fillojne te perkeqesohen?
04:06
Because like a racing car, any patient,
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Sepse ashtu si nje makine garuese, cdo pacient,
04:09
when things start to go bad, you have a short time
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kur gjerat fillojne te shkojne keq, ke nje kohe te shkurter
04:12
to make a difference.
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per te bere ndryshimin.
04:14
So what we did is we took a data system
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Pra ajo cka beme ishte, morem nje sistem te dhenash
04:17
which we run every two weeks of the year in Formula 1
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te cilen e perdorim cdo dy jave te vitit ne Formula 1
04:20
and we installed it on the hospital computers
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dhe e instaluam ne kompjuterat e spitalit
04:23
at Birmingham Children's Hospital.
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ne Spitalin e Femijeve te Birmingham.
04:25
We streamed data from the bedside instruments
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I morem te dhenat nga aparatet ne ane te krevatit
04:27
in their pediatric intensive care
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ne pavionin e kujdesit intensiv pediatrik
04:30
so that we could both look at the data in real time
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ne menyre qe te shikonim te dhenat ne kohe reale
04:33
and, more importantly, to store the data
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dhe, me e rendesishmja, te ruanim te dhenat
04:36
so that we could start to learn from it.
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ne menyre qe te fillonim te mesonim nga ato.
04:39
And then, we applied an application on top
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Me pas, aplikuam nje aplikacion mbi to
04:44
which would allow us to tease out the patterns in the data
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i cili do na lejonte te nxirrnim strukturat ne te dhenat
04:47
in real time so we could see what was happening,
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ne kohe reale ne menyre qe te shikonim cka po ndodhte,
04:50
so we could determine when things started to change.
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qe te percaktonim nisjen e ndryshimit te gjerave.
04:54
Now, in motor racing, we're all a little bit ambitious,
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Ne garat me makina, ne jemi disi ambicioz,
04:58
audacious, a little bit arrogant sometimes,
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guximtar, pak arrogant disa here,
05:00
so we decided we would also look at the children
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dhe keshtu vendosem qe te shikonim dhe tek femijet
05:04
as they were being transported to intensive care.
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ndersa po transportoheshin ne kujdesin intesiv.
05:06
Why should we wait until they arrived in the hospital
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Pse te prisnim deri sa ata te mberrinin ne spital
05:09
before we started to look?
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para se te fillonim shikimin?
05:11
And so we installed a real-time link
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Dhe per kete instaluam nje lidhje ne kohe reale
05:14
between the ambulance and the hospital,
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mes ambulances dhe spitalit,
05:16
just using normal 3G telephony to send that data
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duke perdorur thjesht telefoni 3G per te derguar te dhenat
05:20
so that the ambulance became an extra bed
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ne menyre qe ambulanca te behej nje krevat shtese
05:23
in intensive care.
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ne kujdesin intesiv.
05:26
And then we started looking at the data.
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Dhe me pas filluam te shikonim te dhenat.
05:30
So the wiggly lines at the top, all the colors,
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Linjat e dredhuar ketu lart, te gjitha ngjyrat,
05:32
this is the normal sort of data you would see on a monitor --
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keto jane tipi i te dhenave normale qe do shikonin ne nje monitor--
05:36
heart rate, pulse, oxygen within the blood,
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ritmi kardiak, pulsi, oksigjen ne gjak
05:39
and respiration.
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dhe frymemarrja.
05:42
The lines on the bottom, the blue and the red,
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Linjat ne fund, blu-ja dhe e kuq-ja,
05:45
these are the interesting ones.
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jane ato interesantet.
05:46
The red line is showing an automated version
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Linja e kuqe tregon nje version automatizes
05:49
of the early warning score
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te pikave fillestare paralajmeruese
05:51
that Birmingham Children's Hospital were already running.
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te cilat Spitali i Femijeve Birmingham po perdorte fillimisht.
05:53
They'd been running that since 2008,
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Po e perdornin qe prej 2008,
05:56
and already have stopped cardiac arrests
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dhe kishin ndaluar arreste kardiake
05:58
and distress within the hospital.
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dhe shqetesime brenda spitalit.
06:01
The blue line is an indication
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Linja blu eshte nje tregues
06:03
of when patterns start to change,
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se kur struktura fillon te ndryshoje
06:06
and immediately, before we even started
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dhe menjehere, para se ne te fillonim
06:08
putting in clinical interpretation,
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duke i vendosur ne interpretim klinik,
06:10
we can see that the data is speaking to us.
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mund te shohim se te dhenat po flasin me ne.
06:13
It's telling us that something is going wrong.
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Na tregojne se dicka po shkon gabim.
06:16
The plot with the red and the green blobs,
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Subjekti me pikat e kuqe dhe jeshile,
06:20
this is plotting different components
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kjo tregon komponente te ndryshem
06:23
of the data against each other.
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nga te dhenat kundrejt njera tjetres.
06:25
The green is us learning what is normal for that child.
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Jeshilja jemi ne duke mesuar cka eshte normale per ate femije.
06:29
We call it the cloud of normality.
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Ne e quajme reja e normalitetit.
06:32
And when things start to change,
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Dhe kur gjerat fillojne te ndryshojne,
06:34
when conditions start to deteriorate,
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kur kushtet fillojne te perkeqesohen,
06:37
we move into the red line.
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ne kalojme ne linjen e kuqe.
06:39
There's no rocket science here.
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Nuk ka shkence raketash ketu.
06:41
It is displaying data that exists already in a different way,
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Tregon te dhena qe ekzistojne ne nje menyre ndryshe,
06:45
to amplify it, to provide cues to the doctors,
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per ta plotesuar ate, per te ti dhene sugjerime mjekeve,
06:48
to the nurses, so they can see what's happening.
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infermiereve, qe te shohin cka po ndodh.
06:51
In the same way that a good racing driver
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Ne te njejten menyre qe nje shofer i mire garash
06:54
relies on cues to decide when to apply the brakes,
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mbeshtetet ne te dhenat per te percaktuar se kur duhet te perdori frenat,
06:58
when to turn into a corner,
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kur te marre kthesen,
06:59
we need to help our physicians and our nurses
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duhet te ndihmojne mjeket dhe infermieret tane
07:02
to see when things are starting to go wrong.
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per te pare gjerat kur fillojne te shkojne keq.
07:06
So we have a very ambitious program.
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Pra kemi nje program shume ambicioz.
07:09
We think that the race is on to do something differently.
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Mendojme se gara eshte per te bere dicka ndryshe.
07:14
We are thinking big. It's the right thing to do.
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Ne mendojme ne shkalle te gjere. Eshte gjeja e duhur per te bere.
07:17
We have an approach which, if it's successful,
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Kemi nje rruge e cila, nese eshte e sukseshme,
07:20
there's no reason why it should stay within a hospital.
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nuk ka arsye pse duhet te qendroje brenda spitalit.
07:22
It can go beyond the walls.
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Mund te dali jashte mureve.
07:24
With wireless connectivity these days,
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Me lidhjen jo kabllor te ketyre diteve,
07:26
there is no reason why patients, doctors and nurses
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nuk ka arsye pse pacientet, mjeket dhe infermieret
07:30
always have to be in the same place
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duhet gjithmone te jene ne te njejtin vend
07:32
at the same time.
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ne te njejten kohe.
07:34
And meanwhile, we'll take our little three-month-old baby,
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Dhe nderkohe, ne do marrim foshnjen tone tre muajshe
07:38
keep taking it to the track, keeping it safe,
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duke e mbajtur ne gjurme, duke e mbajtur te sigurte
07:42
and making it faster and better.
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dhe ta bejme me te shpejte dhe me te mire.
07:44
Thank you very much.
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Ju faleminderit shume.
07:45
(Applause)
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(Duartrokitje)
Translated by Alisa Xholi
Reviewed by Iris Xholi

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ABOUT THE SPEAKER
Peter van Manen - Electronic systems expert
Peter van Manen is the Managing Director of McLaren Electronics, which provides data systems to major motorsports series.

Why you should listen

To say that Peter van Manen has a high-speed job would be an understatement. As Managing Director of McLaren Electronics, which provides electronics and data collection software to motorsports events, he and his team work in real time during a race to improve cars on about 500 different parameters. That's about 750 million data points in two hours.

But recently van Manen and his team have been wondering: Why can't the extremely precise and subtle data-collection and analysis systems used in motorsports be applied elsewhere, for the benefit of all? They have applied their systems to ICU units at Birmingham Children's Hospital with real-time analysis that allows them to proactively prevent cardiac arrests. The unit has seen a 25 percent decrease in life-threatening events. And it's just the beginning.

More profile about the speaker
Peter van Manen | Speaker | TED.com