Peter van Manen: How can Formula 1 racing help ... babies?

Translator: Joachim Mangilima Reviewer: Nelson Simfukwe

Motor racing is a funny old business.

Mbio za magari ni biashara ya zamani ya kufurahisha

We make a new car every year,

Tunatengeneza gari jipya kila mwaka,

and then we spend the rest of the season

halafu tunatumia msimu wote

trying to understand what it is we've built

kujaribu kuelewa ni nini ambacho tumekijenga

to make it better, to make it faster.

kuifanya iwe bora zaidi, na kuifanya iende kasi zaidi.

And then the next year, we start again.

halafu mwaka unaofuata, tunaanza upya.

Now, the car you see in front of you is quite complicated.

Gari lililo mbele yako

The chassis is made up of about 11,000 components,

chesisi inaundwa na vifaa mbalimbali takribani 11,000

the engine another 6,000,

Injini vingine 6000,

the electronics about eight and a half thousand.

vya elektroniki takriban 8500

So there's about 25,000 things there that can go wrong.

kwa hiyo kuna vitu kama 25,000 hivi vinavyoweza kuharibika.

So motor racing is very much about attention to detail.

kwa umakini wa hali ya juu ni muhimu sana katika mbio za magari

The other thing about Formula 1 in particular

Kitu kingine kuhusu mbio za magari hasa ya langa langa

is we're always changing the car.

ni kwamba kila wakati tunabadilisha gari.

We're always trying to make it faster.

Kila wakati tunajaribu kulifanya bora zaidi.

So every two weeks, we will be making

Kila baada ya wiki mbili, tunakuwa tunatengeneza

about 5,000 new components to fit to the car.

vifaa vipya 5000 kwa ajili ya kuweka katika gari.

Five to 10 percent of the race car

asilimia 5 mpaka 10 ya gari la mbio.

will be different every two weeks of the year.

linabadilishwa kila baada ya wiki mbili.

So how do we do that?

Kwa hiyo tunafanyaje haya yote?

Well, we start our life with the racing car.

Tunaanza na gari la mashindano,

We have a lot of sensors on the car to measure things.

Tuna vifaa vya kupima mambo mbalimbali vingi sana.

On the race car in front of you here

katika gari la mashindano mbele

there are about 120 sensors when it goes into a race.

kuna vifaa vya kupima mambo mbalimbali kama 120 linapoenda mashindanoni.

It's measuring all sorts of things around the car.

vinapima vitu mbalimbali katika gari

That data is logged. We're logging about

Taarifa zinawekwa katika kumbukumbu. tunatunza kumbukumbu

500 different parameters within the data systems,

500 mbalimbali za vitu mbalimbali,

about 13,000 health parameters and events

vitu mbalimbali kuhusu afya ya gari na matukio

to say when things are not working the way they should do,

kuelezea mambo yanapoenda vibaya,

and we're sending that data back to the garage

tunatuma taarifa hizi kwenda kitengo cha matengenezo

using telemetry at a rate of two to four megabits per second.

Kwa kutumia kifaa cha kupima taarifa mbalimbali

So during a two-hour race, each car will be sending

kila masaa mawili ya mbio,kila gari linatuma

750 million numbers.

namba 750 millioni

That's twice as many numbers as words that each of us

hiyo ni mara mbili ya maneno ambayo

speaks in a lifetime.

tunazungumza katika maisha yetu

It's a huge amount of data.

ni kiasi kikubwa cha taarifa.

But it's not enough just to have data and measure it.

lakini haitoshi tu, kuwa na taarifa na vipimo.

You need to be able to do something with it.

unahitaji kuwa na uwezo wa kuzifanyia kazi.

So we've spent a lot of time and effort

Kwa hiyo tumetumia muda mwingi na juhudi

in turning the data into stories

kubadilisha taarifa kuwa hadithi

to be able to tell, what's the state of the engine,

ili kuweza kueleza, hali ya injini,

how are the tires degrading,

Matairi yanachoka vipi,

what's the situation with fuel consumption?

mafuta yanatumikaje?

So all of this is taking data

hiyo yote inachukua taarifa

and turning it into knowledge that we can act upon.

na kuzibadilisha kuwa maarifa tunayoweza kujifunza.

Okay, so let's have a look at a little bit of data.

Sawa,kwa hiyo tuangalie kidogo kuhusu taarifa.

Let's pick a bit of data from

tuangalie kiasi kidogo cha taarifa kutoka

another three-month-old patient.

kwa mgonjwa wa miezi mitatu.

This is a child, and what you're seeing here is real data,

Huyu ni mtoto, na unachokiona hapa ni taarifa halisi,

and on the far right-hand side,

na upande huu wa kulia,

where everything starts getting a little bit catastrophic,

mahali ambapo kila kitu kiaanza kuwa cha hatari,

that is the patient going into cardiac arrest.

ambapo mgonjwa anapata mshituko wa moyo.

It was deemed to be an unpredictable event.

inaonekana kuwa ni tukio lisilotabirika..

This was a heart attack that no one could see coming.

Hili lilikuwa ni shambulio la moyo ambalo hakuna mtu aliyeliona.

But when we look at the information there,

Lakini tunapoangalia taarifa pale,

we can see that things are starting to become

tunaona vitu vinaanza kuwa

a little fuzzy about five minutes or so before the cardiac arrest.

havieleweki kama dakika tano hivi kabla ya shambulio la la moyo.

We can see small changes

Tunaona mabadiliko madogo

in things like the heart rate moving.

katika vitu kama mapigo ya moyo

These were all undetected by normal thresholds

hivi vilikuwa haviwezekani kugundulika na vipimo vya kawaida

which would be applied to data.

ambazo zitatumika na taarifa

So the question is, why couldn't we see it?

kwa hiyo swali, lilikuwa ni kwa nini hatukuweza kuona?

Was this a predictable event?

Je hili lilikuwa ni tukio la kutabirika?

Can we look more at the patterns in the data

je tunaweza kuangalia tabia za taarifa

to be able to do things better?

ili kuweza kufanya vitu upya?

So this is a child,

Kwa hiyo huyu ni mtoto,

about the same age as the racing car on stage,

umri sawa na gari la mbio jukwaani,

three months old.

miezi mitatu.

It's a patient with a heart problem.

Ni mgonjwa mwenye tatizo la moyo

Now, when you look at some of the data on the screen above,

Ukiangalia baadhi ya taarifa hapo juu,

things like heart rate, pulse, oxygen, respiration rates,

mapigo ya moyo,oksijeni,upumuaji,

they're all unusual for a normal child,

vyote sio sawa kwa mtoto wa kawaida,

but they're quite normal for the child there,

lakini ni sawa kwa mtoto yule,

and so one of the challenges you have in health care is,

kwa hiyo moja kati ya changamoto tuliyo nayo katika huduma za afya,

how can I look at the patient in front of me,

Nawezaje kumwangalia mgonjwa mbele yangu

have something which is specific for her,

na kuwa na kitu maalum kwake

and be able to detect when things start to change,

na kugundua mambo yanapoanza kubadilika,

when things start to deteriorate?

mambo yanapoharibika?

Because like a racing car, any patient,

Kwa sababu kama vile gari la mashindano,mgonjwa yeyote,

when things start to go bad, you have a short time

mambo yanapoharibika,unakuwa na muda mfupi

to make a difference.

kuleta mabadiliko.

So what we did is we took a data system

tulichofanya ni kuchukua mfumo wa taarifa

which we run every two weeks of the year in Formula 1

ambao unafanya kazi kila baada ya wiki mbili za mwaka

and we installed it on the hospital computers

na kuufunga katika kompyuta za hospitali

at Birmingham Children's Hospital.

katika hospitali ya watoto ya Birmingham.

We streamed data from the bedside instruments

Tulisafirisha taarifa kutoka katika vifaa vya vitandani

in their pediatric intensive care

katika wodi ya watoto mahututi

so that we could both look at the data in real time

ili tuweze kuona taarifa kwa wakati huo huo

and, more importantly, to store the data

na muhimu zaidi,kutunza taarifa

so that we could start to learn from it.

ili tuweze kujifunza

And then, we applied an application on top

na baadae tukatumia mfumo

which would allow us to tease out the patterns in the data

ambao uliruhusu kufanya majaribio na taarifa

in real time so we could see what was happening,

kw awakati huo huo ili kuona kilichokuwa kinatokea,

so we could determine when things started to change.

ili tuweze kujua wakati mambo yanapobadilika.

Now, in motor racing, we're all a little bit ambitious,

katika mbio za magari, tuna kuwa tumejaa matumaini

audacious, a little bit arrogant sometimes,

na wakati mwingine kujivuna kiasi,

so we decided we would also look at the children

kwa hiyo tukaamua kuangalia watoto

as they were being transported to intensive care.

walipokuwa wanapelekwa katika wodi ya watu mahututi.

Why should we wait until they arrived in the hospital

Kwa nini tusubiri mpaka wanapowasili katika hospitali

before we started to look?

kabla ya kuanza kuangalia?

And so we installed a real-time link

Kwa hiyo tukaweka kiunganishi cha wakati huo huo

between the ambulance and the hospital,

kati ya gari ya wagonjwa na hospitali,

just using normal 3G telephony to send that data

na kwa kutumia mfumo wa simu wa 3G kutuma taarifa

so that the ambulance became an extra bed

Kwa hiyo gari ya wagonjwa likawa ni kitanda cha ziada

in intensive care.

katika wodi ya wagonjwa mahututi.

And then we started looking at the data.

Na baadae tukaanza kuangalia taarifa.

So the wiggly lines at the top, all the colors,

Mistari yote hii juu,rangi zote,

this is the normal sort of data you would see on a monitor --

Ni taarifa za kawaida kuziona katika kirusha picha

heart rate, pulse, oxygen within the blood,

mapigo ya moyo,oksijeni katika damu,

and respiration.

na kupumua.

The lines on the bottom, the blue and the red,

Mistari hapo chini, ya bluu na myekundu

these are the interesting ones.

hii ni ya kustaajabisha.

The red line is showing an automated version

Mstari mwekundu unaonyesha mfumo wa moja kwa moja

of the early warning score

wa maonyo ya mapema

that Birmingham Children's Hospital were already running.

ambayo yalikuwa yanaendeshwa na hospitali ya watoto ya birmingham

Walikuwa wanaiendesha toka 2008,

They'd been running that since 2008,

and already have stopped cardiac arrests

na tayari imesimamamisha mistuko ya moyo

and distress within the hospital.

na msongo wa mawazo hospitalini

The blue line is an indication

Mstari wa bluu ni kiashiria

of when patterns start to change,

cha mwenendo unapoanza kubadilika,

and immediately, before we even started

na haraka,kabla hata ya kuanza

putting in clinical interpretation,

na kuweka utafsiri wa kitabibu

we can see that the data is speaking to us.

tunaweza kuona taarifa zikuzungumza nasi.

It's telling us that something is going wrong.

zinatuambia kuwa kitu si sawa.

The plot with the red and the green blobs,

mistari ya rangi nyekundu na kijani

this is plotting different components

hii inaonyesha kitu kingine

of the data against each other.

kuhusu taarifa.

The green is us learning what is normal for that child.

Kijani inaonyesha kilicho sawa kwa mtoto

We call it the cloud of normality.

tunaiita kuwa ni wingu la kawaida.

And when things start to change,

na mambo yanapobadilika,

when conditions start to deteriorate,

na hali kuwa mbaya

we move into the red line.

tunaenda katika mstari mwekundu.

There's no rocket science here.

Hakuna kitu cha ajabu hapa.

It is displaying data that exists already in a different way,

inaonyesha taarifa ambazo zipo katika njia nyingine,

to amplify it, to provide cues to the doctors,

kuwaonyesha madaktari

to the nurses, so they can see what's happening.

na manesi, ili wajue kinachoendelea.

In the same way that a good racing driver

sawa sawa na jinsi dereva wa mbio za magari

relies on cues to decide when to apply the brakes,

anavyotegemea kama kuna foleni ili ajue wakati wa kupiga breki,

when to turn into a corner,

wakati wa kukata kona,

we need to help our physicians and our nurses

tunahitaji kuwasaidia madaktari na manesi wetu

to see when things are starting to go wrong.

kuona ni wakati gani mambo yanapoanza kuharibika,

So we have a very ambitious program.

kwa hiyo tuna mpango wa kutia matumaini.

We think that the race is on to do something differently.

Tunaamini mbio zinaenda kufanya kitu tofauti.

We are thinking big. It's the right thing to do.

Tunawaza mbali, ni kitu sahihi kabisa kufanyika,

We have an approach which, if it's successful,

tuna njia ambayo kama itafanikiwa,

there's no reason why it should stay within a hospital.

hakuna sababu ibaki hospitalini tu.

inaweza kwenda zaidi ya hapo.

It can go beyond the walls.

With wireless connectivity these days,

na mawasiliano ya bila waya ya siku hizi,

there is no reason why patients, doctors and nurses

hakuna sababu wagonjwa,daktari na nesi

always have to be in the same place

ya kuwafanya wawe sehemu moja

at the same time.

kwa wakati mmoja

And meanwhile, we'll take our little three-month-old baby,

na wakati huo huo,tutachukua mtoto wetu wa miezi mitatu,

keep taking it to the track, keeping it safe,

tutaendelea kumpeleka uwanjani salama,

and making it faster and better.

na kuifanya kuwa ya haraka na nzuri zaidi.

Thank you very much.

Asante Sana.

(Applause)

(Makofi)