TEDxAustin
Joel Selanikio: The big-data revolution in health care
Džoel Selanikio (Joel Selanikio): Iznenađujuće osnove revolucije velikih podataka u zdravstvu
Filmed:
Readability: 4.1
745,046 views
Skupljanje globalnih podataka o zdravstvu bila je nesavršena nauka - radnici su se vukli kroz sela i kucali po vratima, postavljajući pitanja, zapisivali odgovore na papir i onda unosili podatke - i iz ovih nepotpunih podataka, države su donosile velike odluke. Stručnjak za podatke Džoel Selanikio prolazi kroz more promena u sakupljanju podataka u zdravstvu u protekloj deceniji, počevši s Palm Pajlotom i Hotmejlom i prelazeći na podatke u oblaku. (Snimljeno na TEDxAustin.)
Joel Selanikio - Health and technology activist
Dr. Joel Selanikio combines technology and data to help solve global health challenges. Full bio
Dr. Joel Selanikio combines technology and data to help solve global health challenges. Full bio
Double-click the English transcript below to play the video.
00:12
There's an old joke about a cop who's walking his beat
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Postoji jedna stara šala
o policajcu koji šeta u patroli
o policajcu koji šeta u patroli
00:15
in the middle of the night,
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tokom noći
00:16
and he comes across a guy under a street lamp
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i susreće lika ispod ulične lampe
00:18
who's looking at the ground and moving from side to side,
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koji gleda na zemlju
i pomera se levo-desno
i pomera se levo-desno
00:21
and the cop asks him what he's doing.
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i policajac ga pita
šta radi.
šta radi.
00:23
The guys says he's looking for his keys.
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Čovek kaže
da traži svoje ključeve.
da traži svoje ključeve.
00:25
So the cop takes his time and looks over
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Policajac ostaje s njim
i odmerava teren,
i odmerava teren,
00:27
and kind of makes a little matrix and looks
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obilazi krug i traži
00:29
for about two, three minutes. No keys.
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neka dva, tri minuta.
Nema ključeva.
Nema ključeva.
00:32
The cop says, "Are you sure? Hey buddy,
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Policajac pita:
"Jesi li siguran? Hej, druže,
"Jesi li siguran? Hej, druže,
00:35
are you sure you lost your keys here?"
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jesi li siguran da si
ovde izgubio ključeve?"
ovde izgubio ključeve?"
00:37
And the guy says, "No, no, actually I lost them
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I lik odgovara: "Ne, ne, u stvari
izgubio sam ih
izgubio sam ih
00:38
down at the other end of the street,
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tamo na drugom kraju ulice,
00:40
but the light is better here."
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ali je svetlo ovde bolje."
00:46
There's a concept that people talk about nowadays
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Postoji jedan koncept o kome
ljudi danas govore,
ljudi danas govore,
00:47
called big data, and what they're talking about
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"veliki podaci",
a ono o čemu govore
a ono o čemu govore
00:50
is all of the information that we're generating
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jeste skup podataka
koji stvaramo
koji stvaramo
00:52
through our interaction with and over the Internet,
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putem naše interakcije
sa i preko interneta,
sa i preko interneta,
00:55
everything from Facebook and Twitter
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sve od Fejsbuka i Tvitera
00:56
to music downloads, movies, streaming, all this kind of stuff,
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do skidanja muzike, filmova,
prenosa i tih stvari,
prenosa i tih stvari,
01:01
the live streaming of TED.
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živi prenos TED govora.
01:02
And the folks who work with big data, for them,
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Ljudi koji rade sa "velikim podacima"
01:05
they talk about that their biggest problem is
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kažu da je njihov najveći problem to
01:07
we have so much information,
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što postoji toliko informacija,
01:09
the biggest problem is, how do we organize all that information?
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najveći problem je,
kako organizovati sve te informacije?
kako organizovati sve te informacije?
01:12
I can tell you that working in global health,
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Radeći u sferi globalnog zdravlja,
mogu vam reći
mogu vam reći
01:15
that is not our biggest problem.
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da to nije naš najveći problem.
01:18
Because for us, even though the light
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Jer nama,
iako je svetlo
iako je svetlo
01:19
is better on the Internet,
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bolje na internetu,
01:22
the data that would help us solve the problems
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podaci koji bi nam pomogli
da rešimo probleme
da rešimo probleme
01:25
we're trying to solve is not actually present on the Internet.
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koje pokušavamo da rešimo,
nisu u stvari prisutni na internetu.
nisu u stvari prisutni na internetu.
01:28
So we don't know, for example, how many people
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I zato ne znamo, na primer,
koliko ljudi
koliko ljudi
01:30
right now are being affected by disasters
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se upravo sada
suočava sa nekom katastrofom
suočava sa nekom katastrofom
01:32
or by conflict situations.
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ili se nalazi u konfliktnoj situaciji.
01:35
We don't know for really basically any of the clinics
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Ne znamo, u suštini,
ni za jednu od klinika
ni za jednu od klinika
01:39
in the developing world, which ones have medicines
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u svetu u razvoju,
koje od njih imaju lekove,
koje od njih imaju lekove,
01:41
and which ones don't.
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a koje ih nemaju.
01:42
We have no idea of what the supply chain is for those clinics.
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Nemamo predstavu kakav
lanac nabavki imaju te klinike.
lanac nabavki imaju te klinike.
01:45
We don't know -- and this is really amazing to me --
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Ne znamo - i ovo mi je zaista
zapanjujuće -
zapanjujuće -
01:48
we don't know how many children were born,
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ne znamo koliko dece je rođeno
01:51
or how many children there are in Bolivia
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ili koliko dece ima u Boliviji
01:54
or Botswana or Bhutan.
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ili Bocvani ili u Butanu.
01:57
We don't know how many kids died last week
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Ne znamo koliko dece
je umrlo prošle nedelje
je umrlo prošle nedelje
01:59
in any of those countries.
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u bilo kojoj od tih država.
02:01
We don't know the needs of the elderly, the mentally ill.
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Ne znamo potrebe starijih,
mentalno obolelih.
mentalno obolelih.
02:04
For all of these different critically important problems
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O svim ovim različitim
problemima od ključnog značaja
problemima od ključnog značaja
02:07
or critically important areas that we want to solve problems in,
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ili oblastima ključnog značaja
u kojima želimo da rešimo probleme,
u kojima želimo da rešimo probleme,
02:10
we basically know nothing at all.
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mi ne znamo skoro ništa.
02:15
And part of the reason why we don't know anything at all
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Deo razloga zašto ne znamo ništa
02:18
is that the information technology systems
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jeste to da su
sistemi informacionih tehnologija
sistemi informacionih tehnologija
02:20
that we use in global health to find the data
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koje koristimo u globalnom zdravlju
za prikupljanje podataka
za prikupljanje podataka
02:24
to solve these problems is what you see here.
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za rešavanje ovih problema
ono što vidite ovde.
ono što vidite ovde.
02:27
And this is about a 5,000-year-old technology.
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Ovo je tehnologija
stara 5.000 godina.
stara 5.000 godina.
02:29
Some of you may have used it before.
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Neki od vas su
je možda već koristili ranije.
je možda već koristili ranije.
02:30
It's kind of on its way out now, but we still use it
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Polako je napuštamo,
ali se ona i dalje koristi
ali se ona i dalje koristi
02:32
for 99 percent of our stuff.
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za 99 odsto
stvari koje radimo.
stvari koje radimo.
02:34
This is a paper form, and what you're looking at
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Ovo je papirni formular,
a ono što vidite
a ono što vidite
02:38
is a paper form in the hand of a Ministry of Health nurse
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jeste formular u rukama
sestre Ministarstva zdravlja
sestre Ministarstva zdravlja
02:42
in Indonesia who is tramping out across the countryside
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u Indoneziji koja
peške obilazi sela
peške obilazi sela
02:45
in Indonesia on, I'm sure, a very hot and humid day,
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u Indoneziji po, verujem,
veoma toplom i vlažnom danu
veoma toplom i vlažnom danu
02:49
and she is going to be knocking on thousands of doors
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i ona će kucati
na hiljade vrata
na hiljade vrata
02:51
over a period of weeks or months,
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tokom nedelja i meseci,
02:53
knocking on the doors and saying, "Excuse me,
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kucaće na vrata
i govoriti: "Izvinite,
i govoriti: "Izvinite,
02:56
we'd like to ask you some questions.
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voleli bismo da vam
postavimo neka pitanja.
postavimo neka pitanja.
02:58
Do you have any children? Were your children vaccinated?"
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Imate li dece?
Da li su vaša deca vakcinisana?"
Da li su vaša deca vakcinisana?"
03:02
Because the only way we can actually find out
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Zato što je jedini način
na koji možemo da saznamo
na koji možemo da saznamo
03:03
how many children were vaccinated in the country of Indonesia,
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koliko dece je vakcinisano
u Indoneziji,
u Indoneziji,
03:06
what percentage were vaccinated, is actually not
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koji procenat je vakcinisan,
u stvari nije
u stvari nije
03:09
on the Internet but by going out and knocking on doors,
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internet, nego
obilaženje i kucanje na vrata,
obilaženje i kucanje na vrata,
03:12
sometimes tens of thousands of doors.
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ponekad na desetine hiljada vrata.
03:15
Sometimes it takes months to even years
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Ponekad su potrebni
meseci pa čak i godine
meseci pa čak i godine
03:17
to do something like this.
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da bi se ovako nešto uradilo.
03:19
You know, a census of Indonesia
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Znate, popis u Indoneziji
03:21
would probably take two years to accomplish.
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bi najverovatnije
trajao dve godine.
trajao dve godine.
03:23
And the problem, of course, with all of this is that
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Problem sa svime ovime
je, naravno,
je, naravno,
03:25
with all those paper forms — and I'm telling you
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da sa svim tim papirnim formularima -
i kažem vam
i kažem vam
03:27
we have paper forms for every possible thing.
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imamo formulare za svaku moguću stvar.
03:29
We have paper forms for vaccination surveys.
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Imamo upitnike za vakcinaciju.
03:32
We have paper forms to track people who come into clinics.
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Imamo formulare za praćenje ljudi
koji posete klinike.
koji posete klinike.
03:36
We have paper forms to track drug supplies,
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Imamo formulare za praćenje
snabdevanja lekovima,
snabdevanja lekovima,
03:38
blood supplies, all these different paper forms
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krvlju, a sve ovo su
različiti formulari
različiti formulari
03:41
for many different topics,
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za mnogo različitih oblasti
03:43
they all have a single common endpoint,
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i svi oni završavaju na istom mestu,
03:45
and the common endpoint looks something like this.
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a to mesto izgleda otprilike ovako.
03:48
And what we're looking at here is a truckful o' data.
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Ono što vidimo ovde je
kombi pun podataka.
kombi pun podataka.
03:52
This is the data from a single vaccination coverage survey
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Ovo su upitnici sa jednog
ispitivanja dometa vakcinacije
ispitivanja dometa vakcinacije
03:57
in a single district in the country of Zambia
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u jednom jedinom okrugu
u Zambiji
u Zambiji
03:59
from a few years ago that I participated in.
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od pre nekoliko godina
gde sam i ja učestvovao.
gde sam i ja učestvovao.
04:01
The only thing anyone was trying to find out
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Jedina stvar koju
je neko pokušavao da otkrije
je neko pokušavao da otkrije
04:04
is what percentage of Zambian children are vaccinated,
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jeste koji procenat dece u Zambiji
je vakcinisan
je vakcinisan
04:07
and this is the data, collected on paper over weeks
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i ovo su podaci
skupljeni na papiru tokom nedelja
skupljeni na papiru tokom nedelja
04:10
from a single district, which is something like a county
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iz jednog jedinog okruga,
što je nešto poput rejona
što je nešto poput rejona
04:13
in the United States.
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u SAD.
04:14
You can imagine that, for the entire country of Zambia,
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Možete da zamislite,
da bi odgovori čitave Zambije
da bi odgovori čitave Zambije
04:16
answering just that single question
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na samo to jedno pitanje
04:20
looks something like this.
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izgledali nekako ovako.
04:22
Truck after truck after truck
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Kamioni i kamioni
04:24
filled with stack after stack after stack of data.
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ispunjeni gomilama podataka.
04:28
And what makes it even worse is that
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Ono što ovo čini još gorim
04:29
that's just the beginning,
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jeste da je ovo tek početak,
04:31
because once you've collected all that data,
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jer kad jednom skupite
sve te podatke,
sve te podatke,
04:33
of course someone's going to have to --
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naravno, neko će morati -
04:35
some unfortunate person is going to have to type that into a computer.
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neka nesrećna osoba
će morati da unese sve to u računar.
će morati da unese sve to u računar.
04:38
When I was a graduate student, I actually was
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Tokom postdiplomskih studija,
ja sam u stvari
ja sam u stvari
04:40
that unfortunate person sometimes.
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ponekad bio ta nesrećna osoba.
04:42
I can tell you, I often wasn't really paying attention.
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Mogu vam reći
da često nisam zaista obraćao pažnju.
da često nisam zaista obraćao pažnju.
04:45
I probably made a lot of mistakes when I did it
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I verovatno sam u procesu
načinio mnog grešaka
načinio mnog grešaka
04:47
that no one ever discovered, so data quality goes down.
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koje niko nikada nije otkrio
i s time se kvalitet podataka smanjuje.
i s time se kvalitet podataka smanjuje.
04:50
But eventually that data hopefully gets typed into a computer,
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Ali se na kraju, idealno,
ti podaci unose u računar
ti podaci unose u računar
04:53
and someone can begin to analyze it,
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i neko započinje analizu
04:55
and once they have an analysis and a report,
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i kada su analiza i izveštaj gotovi
04:57
hopefully then you can take the results of that data collection
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nadamo se da možemo da
te podatke
te podatke
05:01
and use it to vaccinate children better.
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iskoristimo da unapredimo
vakcinaciju dece.
vakcinaciju dece.
05:03
Because if there's anything worse
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Jer ako je nešto gore
05:06
in the field of global public health,
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u sferi globalnog javnog zdravlja,
05:08
I don't know what's worse than allowing children on this planet
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ne znam šta bi bilo gore,
nego dozvoliti da deca na ovoj planeti
nego dozvoliti da deca na ovoj planeti
05:11
to die of vaccine-preventable diseases,
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umru od bolesti
koje se mogu sprečiti vakcinacijom,
koje se mogu sprečiti vakcinacijom,
05:14
diseases for which the vaccine costs a dollar.
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bolesti za koje vakcina
košta jedan dolar.
košta jedan dolar.
05:17
And millions of children die of these diseases every year.
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A milioni dece umiru
od ovih bolesti svake godine.
od ovih bolesti svake godine.
05:20
And the fact is, millions is a gross estimate because
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Činjenica je da su ti milioni
gruba procena,
gruba procena,
05:24
we don't really know how many kids die each year of this.
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jer ne znamo zaista koliko dece
umire zbog ovoga svake godine.
umire zbog ovoga svake godine.
05:27
What makes it even more frustrating is that
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Ono što je još više frustrirajuće jeste
05:29
the data entry part, the part that I used to do as a grad student,
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što deo unosa podataka,
deo koji sam ja radio kao diplomac,
deo koji sam ja radio kao diplomac,
05:32
can take sometimes six months.
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može ponekad da traje
šest meseci.
šest meseci.
05:34
Sometimes it can take two years to type that information
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Ponekad unos informacija
u računar
u računar
05:37
into a computer, and sometimes, actually not infrequently,
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traje dve godine i, ponekad,
ne retko, u stvari,
ne retko, u stvari,
05:40
it actually never happens.
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on se ni ne desi.
05:42
Now try and wrap your head around that for a second.
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Pokušajte da sagledate to sada.
05:44
You just had teams of hundreds of people.
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Timovi od stotina ljudi su
05:47
They went out into the field to answer a particular question.
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izašli na teren da bi
pronašli odgovor na jedno pitanje.
pronašli odgovor na jedno pitanje.
05:49
You probably spent hundreds of thousands of dollars
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Potrošili ste najverovatnije
stotine hiljada dolara
stotine hiljada dolara
05:51
on fuel and photocopying and per diem,
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na benzin i fotokopije
dnevno
dnevno
05:55
and then for some reason, momentum is lost
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i onda iz nekog razloga
trenutak je prošao
trenutak je prošao
05:58
or there's no money left,
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ili nema više novca
05:59
and all of that comes to nothing
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i sve to se svodi na ništa,
06:01
because no one actually types it into the computer at all.
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jer niko u stvari neće
uneti te podatke u računar.
uneti te podatke u računar.
06:04
The process just stops. Happens all the time.
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I proces naprosto stane.
To se stalno dešava.
To se stalno dešava.
06:07
This is what we base our decisions on in global health:
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Ovo je ono na čemu baziramo
odluke u globalnom zdravlju:
odluke u globalnom zdravlju:
06:10
little data, old data, no data.
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na malo podataka, starim podacima
ili nikakvim podacima.
ili nikakvim podacima.
06:15
So back in 1995, I began to think about ways
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1995. počeo sam
da razmišljam o načinima
da razmišljam o načinima
06:18
in which we could improve this process.
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na koje bismo mogli
da poboljšamo ovaj proces.
da poboljšamo ovaj proces.
06:20
Now 1995, obviously that was quite a long time ago.
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1995. je očigledno bila davno.
06:23
It kind of frightens me to think of how long ago that was.
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Pomalo me plaši da pomislim
koliko davno.
koliko davno.
06:25
The top movie of the year was
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2194
Film godine je bio
06:27
"Die Hard with a Vengeance."
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1182
"Umri muški 3".
06:28
As you can see, Bruce Willis had a lot more hair back then.
145
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2783
Kao što vidite, Brus Vilis je tada
imao mnogo više kose.
imao mnogo više kose.
06:31
I was working in the Centers for Disease Control,
146
379704
2384
Radio sam u Centrima za kontrolu bolesti
06:34
and I had a lot more hair back then as well.
147
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3043
i takođe sam tada imao
mnogo više kose.
mnogo više kose.
06:37
But to me, the most significant thing that I saw in 1995
148
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3342
Za mene, najbitnija stvar
koju sam video 1995.
koju sam video 1995.
06:40
was this.
149
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1454
je bila ovo.
06:41
Hard for us to imagine, but in 1995,
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2641
Pomalo je teško zamisliti,
ali 1995.
ali 1995.
06:44
this was the ultimate elite mobile device.
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3598
ovo je bio vrhunski
elitni mobilni uređaj.
elitni mobilni uređaj.
06:48
Right? It wasn't an iPhone. It wasn't a Galaxy phone.
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Nije bio Ajfon.
Nije bio Galaksi.
Nije bio Galaksi.
06:50
It was a Palm Pilot.
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1478
Bio je to Palm Pajlot.
06:52
And when I saw the Palm Pilot for the first time, I thought,
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3564
Kada sam video Palm Pajlot
po prvi put, pomislio sam,
po prvi put, pomislio sam,
06:55
why can't we put the forms on these Palm Pilots
155
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2527
zašto ne možemo da stavimo
formulare na ove uređaje
formulare na ove uređaje
06:58
and go out into the field just carrying one Palm Pilot,
156
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2872
i izađemo na teren
noseći samo njih
noseći samo njih
07:00
which can hold the capacity of tens of thousands
157
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3117
i oni imaju kapacitet
desetina hiljada
desetina hiljada
07:04
of paper forms? Why don't we try to do that?
158
412096
2181
papirnih formulara?
Zašto ne pokušamo da uradimo to?
Zašto ne pokušamo da uradimo to?
07:06
Because if we can do that, if we can actually just
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2748
Jer ako možemo da uradimo to,
ako možemo
ako možemo
07:09
collect the data electronically, digitally,
160
417025
2514
da podatke prikupimo
elektronski, digitalno
elektronski, digitalno
07:11
from the very beginning,
161
419539
1903
od samog početka
07:13
we can just put a shortcut right through that whole process
162
421442
3017
to bi bila prečica
kroz čitav proces
kroz čitav proces
07:16
of typing,
163
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3222
kucanja
07:19
of having somebody type that stuff into the computer.
164
427681
1983
zapošljavanja nekog
da ukucava te stvari u računar.
da ukucava te stvari u računar.
07:21
We can skip straight to the analysis
165
429664
1959
Možemo odmah
da krenemo sa analizom
da krenemo sa analizom
07:23
and then straight to the use of the data to actually save lives.
166
431623
3075
i onda na upotrebu podataka
kako bismo u stvari spasili živote.
kako bismo u stvari spasili živote.
07:26
So that's actually what I began to do.
167
434698
2515
To je ono što sam ja
i počeo da radim.
i počeo da radim.
07:29
Working at CDC, I began to travel to different programs
168
437213
3334
Radeći u Centrima,
počeo sam da putujem
počeo sam da putujem
07:32
around the world and to train them in using Palm Pilots
169
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4069
širom sveta i obučavam ljude
da koriste Palm Pajlote
da koriste Palm Pajlote
07:36
to do data collection instead of using paper.
170
444616
2525
za prikupljanje podataka
umesto papira.
umesto papira.
07:39
And it actually worked great.
171
447141
2109
I to je u stvari
fenomenalno radilo.
fenomenalno radilo.
07:41
It worked exactly as well as anybody would have predicted.
172
449250
2665
Radilo je upravo onako
kako bi bilo ko predvideo.
kako bi bilo ko predvideo.
07:43
What do you know? Digital data collection
173
451915
2233
Ko bi rekao?
Digitalno prikupljanje podataka
Digitalno prikupljanje podataka
07:46
is actually more efficient than collecting on paper.
174
454148
2271
je u stvari efikasnije
od prikupljanja na papiru.
od prikupljanja na papiru.
07:48
While I was doing it, my business partner, Rose,
175
456419
2364
Dok sam to radio,
moj poslovni partner, Rouz,
moj poslovni partner, Rouz,
07:50
who's here with her husband, Matthew, here in the audience,
176
458783
2817
koja je tu sa mužem, Metjuom,
u publici,
u publici,
07:53
Rose was out doing similar stuff for the American Red Cross.
177
461600
3177
Rouz je radila sličnu stvar
za američki Crveni krst.
za američki Crveni krst.
07:56
The problem was, after a few years of doing that,
178
464777
2065
Problem nakon
nekoliko godina je bio
nekoliko godina je bio
07:58
I realized I had done -- I had been to maybe
179
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2740
što sam uvideo da sam -
bio sam na možda
bio sam na možda
08:01
six or seven programs, and I thought,
180
469582
2718
šest ili sedam programa
i mislio sam
i mislio sam
08:04
you know, if I keep this up at this pace,
181
472300
2310
ako nastavim ovim tempom
08:06
over my whole career, maybe I'm going to go
182
474610
1654
tokom moje čitave karijere,
otići ću
otići ću
08:08
to maybe 20 or 30 programs.
183
476264
2277
na možda 20 ili 30 programa.
08:10
But the problem is, 20 or 30 programs,
184
478541
3229
Problem je što je
20 ili 30 programa,
20 ili 30 programa,
08:13
like, training 20 or 30 programs to use this technology,
185
481770
2973
obuka na 20 ili 30 programa
za korišćenje ove tehnologije
za korišćenje ove tehnologije
08:16
that is a tiny drop in the bucket.
186
484743
2206
mala kap u okeanu.
08:18
The demand for this, the need for data to run better programs,
187
486949
4039
Potražnja, potreba za
boljim programima
boljim programima
08:22
just within health, not to mention all of the other fields
188
490988
2736
samo unutar zdravlja,
da ne spominjem sve ostale oblasti
da ne spominjem sve ostale oblasti
08:25
in developing countries, is enormous.
189
493724
2166
u zemljama u razvoju,
je ogromna.
je ogromna.
08:27
There are millions and millions and millions of programs,
190
495890
4010
Postoje milioni i milioni programa,
08:31
millions of clinics that need to track drugs,
191
499900
2535
milioni klinika kojima
je potrebno da pronađu lekove,
je potrebno da pronađu lekove,
08:34
millions of vaccine programs.
192
502435
1299
milioni programa vakcinacije.
08:35
There are schools that need to track attendance.
193
503734
2057
Školama je potrebno
da prate prisustvo.
da prate prisustvo.
08:37
There are all these different things
194
505791
2005
Sve ove razne stvari
08:39
for us to get the data that we need to do.
195
507796
2095
su nam potrebne
da prikupimo podatke.
da prikupimo podatke.
08:41
And I realized, if I kept up the way that I was doing,
196
509891
4526
I shvatio sam, da ako
nastavim onako kako sam radio,
nastavim onako kako sam radio,
08:46
I was basically hardly going to make any impact
197
514417
3243
neću ostvariti skoro nikakav
uticaj
uticaj
08:49
by the end of my career.
198
517660
1832
do kraja moje karijere.
08:51
And so I began to wrack my brain
199
519492
2155
Počeo sam da razbijam glavu
08:53
trying to think about, you know,
200
521647
1143
pokušavajući da shvatim
08:54
what was the process that I was doing,
201
522790
1518
koji je bio proces
kojim sam prolazio,
kojim sam prolazio,
08:56
how was I training folks, and what were the bottlenecks
202
524308
2856
kako sam obučavao ljude
i gde su uska grla
i gde su uska grla
08:59
and what were the obstacles to doing it faster
203
527164
2813
i šta su prepreke
da bi sve išlo brže
da bi sve išlo brže
09:01
and to doing it more efficiently?
204
529977
1520
i da bi bilo efikasnije?
09:03
And unfortunately, after thinking about this for some time,
205
531497
3143
Nesrećom, nakon što
sam razmišljao o ovome neko vreme
sam razmišljao o ovome neko vreme
09:06
I realized -- I identified the main obstacle.
206
534640
3452
ustanovio sam glavnu prepreku.
09:10
And the main obstacle, it turned out,
207
538092
1977
I glavna prepreka,
kako se ispostavilo,
kako se ispostavilo,
09:12
and this is a sad realization,
208
540069
1835
i ovo je tužno uviđanje,
09:13
the main obstacle was me.
209
541904
2268
glavna prepreka
sam bio ja.
sam bio ja.
09:16
So what do I mean by that?
210
544172
2196
Šta mislim pod tim?
09:18
I had developed a process whereby
211
546368
2488
Razvio sam proces u kome
09:20
I was the center of the universe of this technology.
212
548856
5045
sam ja bio centar univerzuma
ove tehnologije.
ove tehnologije.
09:25
If you wanted to use this technology, you had to get in touch with me.
213
553901
2989
Ako ste želeli da koristite ovu tehnologiju,
morali ste mene da kontaktirate.
morali ste mene da kontaktirate.
09:28
That means you had to know I existed.
214
556890
2106
To znači da ste morali da znate
da ja postojim.
da ja postojim.
09:30
Then you had to find the money to pay for me
215
558996
1474
Onda ste morali da skupite novac
kako biste mi platili
kako biste mi platili
09:32
to fly out to your country
216
560470
1486
let do vaše države
09:33
and the money to pay for my hotel
217
561956
1548
i novac za hotel
09:35
and my per diem and my daily rate.
218
563504
2760
i moje dnevne troškove
i dnevnice.
i dnevnice.
09:38
So you could be talking about 10,000 or 20,000 or 30,000 dollars
219
566264
2949
To je moglo biti
oko 10 ili 20 ili 30 hiljada dolara
oko 10 ili 20 ili 30 hiljada dolara
09:41
if I actually had the time or it fit my schedule
220
569213
2582
ako sam imao vremena
u rasporedu
u rasporedu
09:43
and I wasn't on vacation.
221
571795
1947
ili nisam bio na odmoru.
09:45
The point is that anything, any system that depends
222
573742
2897
Poenta je da bilo šta,
bilo koji sistem koji zavisi
bilo koji sistem koji zavisi
09:48
on a single human being or two or three or five human beings,
223
576639
2870
od jednog jedinog čoveka
ili dva ili tri ili petoro ljudi
ili dva ili tri ili petoro ljudi
09:51
it just doesn't scale.
224
579509
1736
ne može da se proširi.
09:53
And this is a problem for which we need to scale
225
581245
2021
A ovo je problem za koji
nam je potrebno proširenje
nam je potrebno proširenje
09:55
this technology and we need to scale it now.
226
583266
2997
ove tehnologije
i moramo da je proširimo sada.
i moramo da je proširimo sada.
09:58
And so I began to think of ways in which I could basically
227
586263
2222
Počeo sam da razmišljam
o načinima na koje bih
o načinima na koje bih
10:00
take myself out of the picture.
228
588485
2384
mogao sebe da izdvojim iz slike.
10:02
And, you know, I was thinking,
229
590869
4496
Znate, mislio sam
10:07
how could I take myself out of the picture
230
595365
2096
kako bih mogao sebe
da izdvojim
da izdvojim
10:09
for quite some time.
231
597461
1809
poprilično dugo.
10:11
You know, I'd been trained that the way that
232
599270
2157
Znate, bio sam naučen
da je način
da je način
10:13
you distribute technology within international development
233
601427
2722
distribuiranja tehnologije
u internacionalnom razvoju
u internacionalnom razvoju
10:16
is always consultant-based.
234
604149
2027
uvek zasnovan na konsultantima.
10:18
It's always guys that look pretty much like me
235
606176
2977
To su uvek momci
koji izgledaju kao ja
koji izgledaju kao ja
10:21
flying from countries that look pretty much like this
236
609153
2301
i lete od država koje izgledaju ovako
10:23
to other countries with people with darker skin.
237
611454
3106
do drugih država
sa ljudima tamnije kože.
sa ljudima tamnije kože.
10:26
And you go out there, and you spend money on airfare
238
614560
2445
I vi idete tamo
i trošite novac na letove
i trošite novac na letove
10:29
and you spend time and you spend per diem
239
617005
3510
i trošite vreme
i imate dnevne troškove
i imate dnevne troškove
10:32
and you spend [on a] hotel and you spend all that stuff.
240
620515
2112
i trošite na hotel
i trošite sve te stvari.
i trošite sve te stvari.
10:34
As far as I knew, that was the only way
241
622627
1851
Koliko sam ja znao,
to je bio jedini način
to je bio jedini način
10:36
you could distribute technology, and I couldn't figure out a way around it.
242
624478
3269
za distribuiranje tehnologije
i nisam mogao da pronađem zaobilaznicu.
i nisam mogao da pronađem zaobilaznicu.
10:39
But the miracle that happened,
243
627747
2671
Ali se onda desilo čudo,
10:42
I'm going to call it Hotmail for short.
244
630418
2750
zvaću ga Hotmejl skraćeno.
10:45
Now you may not think of Hotmail as being miraculous,
245
633168
2181
Možda ne mislite da je
Hotmejl čudesan,
Hotmejl čudesan,
10:47
but for me it was miraculous, because I noticed,
246
635349
2913
ali za mene je bio,
jer sam primetio
jer sam primetio
10:50
just as I was wrestling with this problem,
247
638262
2566
dok sam se borio
s ovim problemom,
s ovim problemom,
10:52
I was working in sub-Saharan Africa mostly at the time.
248
640828
3414
radio sam u delu Afrike
južno od Sahare.
južno od Sahare.
10:56
I noticed that every sub-Saharan African health worker
249
644242
2589
Primetio sam da svaki
radnik južno od Sahare
radnik južno od Sahare
10:58
that I was working with had a Hotmail account.
250
646831
4108
sa kojim sam radio
ima nalog na Hotmejlu.
ima nalog na Hotmejlu.
11:02
And I thought, it struck me,
251
650939
2144
I pomislio sam,
shvatio sam,
shvatio sam,
11:05
wait a minute, I know that the Hotmail people
252
653083
2615
čekaj samo malo,
znam da ljudi iz Hotmejla
znam da ljudi iz Hotmejla
11:07
surely didn't fly to the Ministry of Health of Kenya
253
655698
2716
sigurno nisu doleteli
do Ministartstva zdravlja u Keniji
do Ministartstva zdravlja u Keniji
11:10
to train people in how to use Hotmail.
254
658414
2711
da obuče ljude
kako da koriste Hotmejl.
kako da koriste Hotmejl.
11:13
So these guys are distributing technology.
255
661125
2487
Ovi ljudi dakle
distribuiraju tehnologiju.
distribuiraju tehnologiju.
11:15
They're getting software capacity out there
256
663612
2004
Dopremaju softver,
11:17
but they're not actually flying around the world.
257
665616
2009
ali ne lete širom sveta.
11:19
I need to think about this some more.
258
667625
1560
Moram da porazmislim
o ovome.
o ovome.
11:21
While I was thinking about it, people started using
259
669185
2173
Dok sam razmišljao o tome,
ljudi su počeli da koriste
ljudi su počeli da koriste
11:23
even more things just like this, just as we were.
260
671358
3200
još stvari nalik ovoj,
baš kao i mi.
baš kao i mi.
11:26
They started using LinkedIn and Flickr
261
674558
1210
Počeli su da koriste
Linkedin i Flikr
Linkedin i Flikr
11:27
and Gmail and Google Maps, all these things.
262
675768
2761
i Džimejl i Gugl mape,
sve ove stvari.
sve ove stvari.
11:30
Of course, all of these things are cloud-based
263
678529
2726
Naravno, sve ove stvari
su zasnovane na "oblaku"
su zasnovane na "oblaku"
11:33
and don't require any training.
264
681255
2206
i ne zahtevaju obuku.
11:35
They don't require any programmers.
265
683461
1600
Ne zahtevaju programere.
11:37
They don't require any consultants, because
266
685061
1709
Ne zahtevaju konsultante,
11:38
the business model for all these businesses
267
686770
2394
jer poslovni model
svih ovih kompanija
svih ovih kompanija
11:41
requires that something be so simple we can use it ourselves
268
689164
2997
zahteva da stvari budu toliko
jednostavne da možemo sami da ih koristimo
jednostavne da možemo sami da ih koristimo
11:44
with little or no training.
269
692161
1185
sa malo ili bez obuke.
11:45
You just have to hear about it and go to the website.
270
693346
2614
Samo morate da čujete za njih
i odete na njihov sajt.
i odete na njihov sajt.
11:47
And so I thought, what would happen if we built software
271
695960
4365
Pomislio sam, šta bi se desilo
da napravimo softver
da napravimo softver
11:52
to do what I'd been consulting in?
272
700325
2011
koji će raditi ono
za šta sam ja bio konsultant?
za šta sam ja bio konsultant?
11:54
Instead of training people how
273
702336
1434
Umesto da obučavamo ljude
11:55
to put forms onto mobile devices,
274
703770
2850
kako da postave formulare
na mobilne uređaje,
na mobilne uređaje,
11:58
let's create software that lets them do it themselves
275
706620
2284
hajde da stvorimo softver
koji im dozvoljava da to rade sami
koji im dozvoljava da to rade sami
12:00
with no training and without me being involved?
276
708904
1890
bez obuke
i bez mog uplitanja?
i bez mog uplitanja?
12:02
And that's exactly what we did.
277
710794
1804
I to je upravo ono
što smo uradili.
što smo uradili.
12:04
So we created software called Magpi,
278
712598
3684
Stvorili smo softver
Megpaj (Magpi)
Megpaj (Magpi)
12:08
which has an online form creator.
279
716282
1877
koji služi za pravljenje
onlajn formulara.
onlajn formulara.
12:10
No one has to speak to me.
280
718159
1151
Niko ne mora
da priča sa mnom.
da priča sa mnom.
12:11
You just have to hear about it and go to the website.
281
719310
2694
Morate samo da čujete za njega
i odete na sajt.
i odete na sajt.
12:14
You can create forms, and once you've created the forms,
282
722004
2747
Možete da pravite formulare
i kada ste ih napravili
i kada ste ih napravili
12:16
you push them to a variety of common mobile phones.
283
724751
2340
prosledite ih na razne
uobičajene telefone.
uobičajene telefone.
12:19
Obviously nowadays, we've moved past Palm Pilots
284
727091
2475
Danas smo očigledno
otišli dalje od Palm Pajlota
otišli dalje od Palm Pajlota
12:21
to mobile phones.
285
729566
1328
na mobilne telefone.
12:22
And it doesn't have to be a smartphone.
286
730894
1132
To ne mora biti
"pametni" telefon.
"pametni" telefon.
12:24
It can be a basic phone like the phone on the right there,
287
732026
2707
To može biti najobičniji telefon,
ovaj s desne strane,
ovaj s desne strane,
12:26
you know, the basic kind of Symbian phone
288
734733
1336
znate, osnovni Simbijan
telefon
telefon
12:28
that's very common in developing countries.
289
736069
2466
koji je veoma uobičajen
u zemljama u razvoju.
u zemljama u razvoju.
12:30
And the great part about this is, it's just like Hotmail.
290
738535
3999
Odlična strana ovoga je
što je baš kao Hotmejl.
što je baš kao Hotmejl.
12:34
It's cloud-based, and it doesn't require any training,
291
742534
2334
Zasnovan je na oblaku
i ne zahteva nikakvu obuku,
i ne zahteva nikakvu obuku,
12:36
programming, consultants.
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programiranje,
konsultante.
konsultante.
12:38
But there are some additional benefits as well.
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1936
Ali ima i dodatnih prednosti.
12:40
Now we knew, when we built this system,
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1955
Kada smo gradili ovaj sistem,
znali smo
znali smo
12:42
the whole point of it, just like with the Palm Pilots,
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zašto to radimo,
baš kao i sa Palm Pajlotima,
baš kao i sa Palm Pajlotima,
12:45
was that you'd have to, you'd be able to
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2604
to je bilo kako biste morali,
mogli
mogli
12:47
collect the data and immediately upload the data and get your data set.
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3191
da sakupljate podatke i
odmah ih postavite i dobijete skup podataka.
odmah ih postavite i dobijete skup podataka.
12:50
But what we found, of course, since it's already on a computer,
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758887
2437
Ali ono što smo otkrili je,
naravno, pošto je već na računaru,
naravno, pošto je već na računaru,
12:53
we can deliver instant maps and analysis and graphing.
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da možemo da oformimo trenutačne mape
i analizu i grafove.
i analizu i grafove.
12:56
We can take a process that took two years
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Proces od dve godine
12:58
and compress that down to the space of five minutes.
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možemo da sabijemo
u nekoliko minuta.
u nekoliko minuta.
13:01
Unbelievable improvements in efficiency.
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Neverovatan napredak
u efikasnosti.
u efikasnosti.
13:04
Cloud-based, no training, no consultants, no me.
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Zasnovan na oblaku, bez obuke,
bez konsultanata, bez mene.
bez konsultanata, bez mene.
13:09
And I told you that in the first few years
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Rekao sam vam da je
u prvih nekoliko godina
u prvih nekoliko godina
13:11
of trying to do this the old-fashioned way,
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1827
pokušaja da se ovo uradi
na tradicionalan način,
na tradicionalan način,
13:13
going out to each country,
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odlaženjem u svaku državu
13:14
we reached about, I don't know,
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domet bio oko, ne znam,
13:17
probably trained about 1,000 people.
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verovatno smo obučili
oko 1.000 ljudi.
oko 1.000 ljudi.
13:19
What happened after we did this?
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Šta se desilo nakon što
smo uradili ovo?
smo uradili ovo?
13:21
In the second three years, we had 14,000 people
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2506
U sledeće tri godine,
14.000 ljudi
14.000 ljudi
13:24
find the website, sign up, and start using it to collect data,
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3193
je pronašlo vebsajt, prijavilo se
i počelo da ga koristi za skupljanje podataka,
i počelo da ga koristi za skupljanje podataka,
13:27
data for disaster response,
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1502
podataka za katastrofe,
13:28
Canadian pig farmers tracking pig disease and pig herds,
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kanadski stočari su ga koristili
za praćenje oboljevanja i odumiranja krda,
za praćenje oboljevanja i odumiranja krda,
13:33
people tracking drug supplies.
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ljudi su pratili nabavku lekova.
13:36
One of my favorite examples, the IRC,
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1942
Jedan od mojih omiljenih primera, MSS,
13:37
International Rescue Committee,
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1629
Međunarodna služba za spasavanje
13:39
they have a program where semi-literate midwives
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ima program u kome
polu-pismene babice
polu-pismene babice
13:42
using $10 mobile phones
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koristeći telefone od
deset dolara
deset dolara
13:45
send a text message using our software
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šalju poruke, putem našeg softvera,
13:47
once a week with the number of births
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2209
jednom nedeljno
o broju rađanja
o broju rađanja
13:49
and the number of deaths, which gives IRC
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i smrti,
koji službi daje
koji službi daje
13:52
something that no one in global health has ever had:
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nešto što niko u globalnom zdravlju
do sada nije imao:
do sada nije imao:
13:54
a near real-time system of counting babies,
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3637
sistem za brojanje novorođenčadi
skoro u stvarnom vremenu,
skoro u stvarnom vremenu,
13:58
of knowing how many kids are born,
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informaciju o tome
koliko dece je rođeno,
koliko dece je rođeno,
13:59
of knowing how many children there are
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1676
koliko dece postoji
14:01
in Sierra Leone, which is the country where this is happening,
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2782
u Sijera Leoneu, koja je država
u kojoj se ovo dešava
u kojoj se ovo dešava
14:04
and knowing how many children die.
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i informaciju o tome koliko dece umire.
14:07
Physicians for Human Rights --
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Lekari za ljudska prava -
14:08
this is moving a little bit outside the health field —
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ovo je malo van polja zdravstva -
14:11
they are gathering, they're basically training people
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skupljaju se, u suštini
obučavaju ljude
obučavaju ljude
14:14
to do rape exams in Congo, where this is an epidemic,
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da rade na slučajevima silovanja u Kongu,
gde je ovo postala epidemija,
gde je ovo postala epidemija,
14:17
a horrible epidemic,
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užasna epidemija,
14:19
and they're using our software to document
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i koriste naš softver da zabeleže
14:21
the evidence they find, including photographically,
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dokaze koje pronađu,
uključujući fotografije,
uključujući fotografije,
14:24
so that they can bring the perpetrators to justice.
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tako da mogu
da privedu zločince pravdi.
da privedu zločince pravdi.
14:28
Camfed, another charity based out of the U.K.,
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Kamfed, još jedna dobrotvorna
organizacija iz Ujedinjenog Kraljevstva,
organizacija iz Ujedinjenog Kraljevstva,
14:32
Camfed pays girls' families to keep them in school.
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Kamfed plaća porodicama devojčica
kako bi one ostale u školi.
kako bi one ostale u školi.
14:36
They understand this is the most significant intervention
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Oni razumeju da je ovo
najbitnija intervencija
najbitnija intervencija
14:38
they can make. They used to track the dispersements,
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3284
koju mogu da učine.
Pre su pratili premeštanja,
Pre su pratili premeštanja,
14:41
the attendance, the grades, on paper.
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869330
1986
prisustvo, ocene, i to na papiru.
14:43
The turnaround time between a teacher
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Vreme obrta između nastavnika
14:44
writing down grades or attendance
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koji zapisuje ocene ili prisustvo
14:46
and getting that into a report was about two to three years.
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do stavljanja toga u izveštaj
bilo je od dve do tri godine.
bilo je od dve do tri godine.
14:49
Now it's real time, and because this is such
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Sada je to u realnom vremenu,
i zbog toga što je ovo tako
i zbog toga što je ovo tako
14:51
a low-cost system and based in the cloud, it costs,
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2940
jeftin sistem i zasnovan na oblaku,
on košta
on košta
14:54
for the entire five countries that Camfed runs this in
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za svih pet zemalja
gde Kamfed ovo vodi,
gde Kamfed ovo vodi,
14:57
with tens of thousands of girls,
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1932
sa desetinama hiljada devojaka,
14:59
the whole cost combined is 10,000 dollars a year.
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887796
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ukupan trošak je
10 000 dolara godišnje.
10 000 dolara godišnje.
15:03
That's less than I used to get
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To je manje od onoga
što bih ja dobio
što bih ja dobio
15:04
just traveling out for two weeks to do a consultation.
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da samo otputujem na dve nedelje
da uradim konsultaciju.
da uradim konsultaciju.
15:10
So I told you before that
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Pre toga sam vam rekao
15:12
when we were doing it the old-fashioned way, I realized
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da kada smo ovo radili
na starinski način, shvatio sam
na starinski način, shvatio sam
15:14
all of our work was really adding up to just a drop in the bucket --
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902354
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da je sav naš rad samo dodavao
na kap u moru -
na kap u moru -
15:17
10, 20, 30 different programs.
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905252
2226
10, 20, 30 različitih programa.
15:19
We've made a lot of progress, but I recognize
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907478
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Napravili smo dosta napretka,
ali shvatam da sada,
ali shvatam da sada,
15:21
that right now, even the work that we've done
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909753
2157
čak i posao koji smo uradili
15:23
with 14,000 people using this,
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kada 14 000 ljudi ovo koristi,
15:26
is still a drop in the bucket. But something's changed.
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914314
2946
to je još uvek kap u moru.
Ali nešto se promenilo.
Ali nešto se promenilo.
15:29
And I think it should be obvious.
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1216
Mislim da to treba da bude očigledno.
15:30
What's changed now is,
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918476
2091
Promenjeno je to da,
15:32
instead of having a program in which we're scaling at such a slow rate
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920567
3578
umesto da imamo program
gde se raste tako malim koracima,
gde se raste tako malim koracima,
15:36
that we can never reach all the people who need us,
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924145
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da nikada ne možemo da dođemo
do svih ljudi kojima smo potrebni,
do svih ljudi kojima smo potrebni,
15:39
we've made it unnecessary for people to get reached by us.
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učinili smo da nije potrebno
da mi dopremo do ljudi.
da mi dopremo do ljudi.
15:43
We've created a tool that lets programs
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3076
Napravili smo alat koji
programima dozvoljava
programima dozvoljava
15:46
keep kids in school, track the number of babies
365
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3155
da decu drže u školama,
da prate broj beba
da prate broj beba
15:49
that are born and the number of babies that die,
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koje su rođene i onih koje umru,
15:52
to catch criminals and successfully prosecute them,
367
940037
3623
da hvataju kriminalce
i uspešno ih gone,
i uspešno ih gone,
15:55
to do all these different things to learn more
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da rade sve ove različite stvari
kako bi naučili više
kako bi naučili više
15:58
about what's going on, to understand more, to see more,
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o tome šta se dešava,
da razumeju više, da vide više,
da razumeju više, da vide više,
16:03
and to save lives and improve lives.
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i da sačuvaju i poboljšaju živote.
16:07
Thank you.
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Hvala vam.
16:09
(Applause)
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(Aplauz)
ABOUT THE SPEAKER
Joel Selanikio - Health and technology activistDr. Joel Selanikio combines technology and data to help solve global health challenges.
Why you should listen
A practicing pediatrician, former Wall Street computer consultant, and former epidemiologist at the Centers for Disease Control, Dr. Joel Selanikio is the CEO of DataDyne, a social business working in fields such as international development and global health.
Selanikio started to experiment with electronic data capture back when the Palm Pilot was cutting edge technology. In the years since then, he has helped to experiment with the growing potential and availability of technology--and the growing ubiquity of the cloud. Combining the two has led to systems such as Magpi mobile data collection software. Previously known as "EpiSurveyor," the service now has over 20,000 users in more than 170 countries.
Selanikio holds a bachelor's degree from Haverford College, a medical degree from Brown University, and he is a graduate of the Epidemic Intelligence Service fellowship of the CDC. He continues to practice clinical pediatrics as an Assistant Professor at Georgetown University and on the Emergency Response Team of the International Rescue Committee.
Joel Selanikio | Speaker | TED.com