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we expect people to keep on walking in just since we start so if I wait then somebody else will come in and so woods get going welcome to the terminology track not always necessarily the most exciting
track in a fire dev days but actually terminology is pretty important so something I want to do today is hopefully yeah I'm a bit too enthusiastic about it which is a little bit worrying but hopefully you'll see
why and over here so today I'm going to be talking giving an overview sno-med first of all how many how many of you are well obviously knows thing with but know how to use sno-med and have
experience with it spattering use that they ask you that's cute that's the starting point all that well now we're going to hope to explain what it is so the point of today really
is to kind of open up what's no words about and try and display it just given us some of the myths that we hear about my name is Roy Davidson I'm from snowboard international so it is our
fault if there is issues but hopefully we're here to answer any questions you have the point they is really coming out to a group of software developers like this I'm a software developer by
backgrounds I'm not a terminal gist I'm not a clinician I just like playing with code and so the reasons why we wanted to be here was to kind of explain how sno-med fits very nicely into software
development and as we go through you'll see the benefit of using it and and why we should be and how to use it and also really to see how do we use it easily we have two sessions this one which is the overview and we have a hands-on
afterwards so if you do want to hang out in snow where there's an hour and 20 of snowed living the dream okay so a quick introduction it's the most like a bit of context and everybody here would
understand this you know we've we've had electronic healthcare records from really the last 30 to 40 years and that was a great start and we moved away from surgeries and hospitals that had reams and reams of documents and papers and
the first set was we put them into PDF form and now we've electric electronic records that's kind of a good start but obviously we can't redo much with it we can't make that meaningful how does a
machine understand free text how does a machine understand the abbreviations that a clinician puts into a notes field and a patient record in a hospital there's a lot of these they out there so how do we make sure that we can use the
data that we record and so this is where sno-med comes in your sno-med allows us to record that clinical information against patient encounters and it's part of most EHRs today now talk about coding
systems and really what we're trying to do is is almost evangelize why sno-med spits this box and why you should be looking to use it so big benefit of sno-med and why we why we keep on saying
this this just saying this message is yes no it's a very logical thing it's a very this is why it's interesting talking to this audience it's a it actually makes a lot of sense it's a very simple logical model it allows us
to have a common framework it's very standards and framework oriented it has post-coordination which we're not gonna go in today because that starts to open up a bit of complexity that we don't really have to do time to do in 40
minutes but it does mean that you can extend the terminology infinitely if you put if you wish to wish to there's a very strict update and versioning process there's a full audit trail so
something that was no longer used from 10 years ago you can still find out why and what it's been replaced by so it's a very nice trail from machines to be able to keep track of what code you're working with and you can see the full
historical view of sno-med back to 2002 and so this is the marketing line that you always hear it's the biggest most comprehensive coding system there are 350,000 clinical codes with sno-med CT
there's still more to add but it's that covers a extremely large scope of some sometimes unexpected concepts so we're going to be of an introduction to sno-med what the
components are just to give a bit of context before we get on to the fire terminology services so you hear about sno-med and people always talk about really concepts
and I think of concepts as the unit of work so everything hangs around a concept a concept has descriptions and a concept has relationships other parts of logical design to be aware of
you can localize sno-med we obviously work at some international we work with many countries and so it's localized is translated but some of the benefits you'll see is that the identifier for
concept never changes so we're really ticking the interoperability checkbox people can extend it you'll be we're aware there's a u.s. addition there are other extensions in other countries from the International
and that's used for translations for local concepts administrative concepts in the US in particular it has a concept model that's very well defined snow made
is self referential it describes itself it's it's it's an ontology that allows you to really find out how does the model exist the model itself is within sno-med and it has an expression model
so you can express more than just a single concept you can post coordinate and express more than that there's a lot of things in there but actually today we're going to talk on these bits and a little bit on that bit so reference sets
which link to value sets but really what is the concept how descriptions hang together and what our relationships so concepts as I said the concepts are the central component they're the unit of
work every single concept has an identifier but identifier is made up of a number of aspects it's a sequence something called a namespace which means you can tell roughly where that concepts
come from it has a type which allows you to identify whether it's a concept or another type of component and has a check digit but ultimately it's just a number and it's unique within sno-med
across the globe every concept has what is called a fully specified name this is essentially the the single unique way of clinically describing that particular concept and these are both linked so
they're immutable they do not change you cannot change a fully specified name if you change that you need to inactivate it and this is back to the history mechanism around sno-med in that nothing ever gets deleted everything is a
logical remove so you inactivate it but you can still find it and you get told what it's been replaced by so when you see a concept with a fully specified name and identifier that is pretty much fixed for all time and again but really
helps the interoperability message descriptions and this is one of the nice things that sno-med does compare to some some terminologies in that you have multiple descriptions every concept must
have a fully specified name as it talks about and at least one synonym and that synonym tends to be something called the preferred term and the preferred term is generally based on the language so here presump Alesi appendectomies is the
procedure with a procedure which is the FSN it has a semantic tag back to you know sno-med is an ontology it sits and semantic technologies and so the FSN has
a semantic tag it contains there's a hierarchy tag so you know that in this scenario and pen I always have an issue saying and ped appendectomies is a procedure the synonym as I said
it's you can have multiple synonyms it gets a concept here we have a preferred term which is unpinned ex--my in the US but we also have other ways of describing this clinical terms clinical
meaning append victim e and excision of appendix these all mean the same things so you'll see some concepts that have up to ten or even more synonyms to basically explain what is the language
used locally to explain that particular clinical meaning and this is what we mean by a concept represents a clinical meaning that model is the clinical meaning of that concept but the synonyms
can be multiple things will you jump in a gun but yes almost wait yes that will get them in the next slide description types is one more description type is
called a definition it's not used very frequently this is really used for at the moment mostly rare diseases for references to see where this coming from but you wouldn't expect these to appear in EHR
or with the clinicians this translations so this is where it comes into it so a translation in in our world is just another synonym it just happens to be in language so when you look down here the
benefit is you can see we have appendectomies in us we have a pen dick to me because we spell it a bit different in the UK you also have appendectomies in Danish
and Swedish and also in Spanish but the ID stays the same so when that patient record has the identifier and you go across countries then it always is the saintly people can understand it in the
European context where there's a lot of countries and with very closed borders this it's invaluable so you can go with your record and wherever you go the local Commission's wheel to understand the clinical concept has been recorded
against your patient record yes the FSM never changes generally most languages don't translate the FSM and this is down to an experience thing that we found when we were translating between English to
French for example that French has a smaller vocabulary than English and so we started to find that we didn't have unique FS ends because we couldn't translate exactly so we defaulted to saying the FS n is a clinical meaning
and that's not what you would display to your clinicians generally you would display their preferred term and so here we would say the clinician will be looking to record and pend ectomy and so
it what's makes sense locally basically sorry yes so every syndrome has a language ISO code but the way that languages work is they they link to something that's called a language
reference set in that you can say here's a description and here's its prayer its acceptability in a language so for example here we would say that appendix imme is not acceptable in US English but
it is in GB English and similarly the Spanish version is not acceptable in any of the English is but it's preferred in Spanish so yes it's very well defined one thing it is a bit uninteresting
whilst I said that FS ends are unique yes so there was a decision made a long time ago because Newman International does translate to the Spanish edition and at the time it was decided to translate the Spanish FSN but it's the
only language that does that translation it's very much a local country decision so Sweden for example have translated the hull of sno-med they've only translated their preferred terms so you
can choose but generally as a minister so the benefit of speaking English that everybody kind of understands a little bit so if you understand the clinical meaning then people are happy to check with MSN in English and quite frankly
save a bit of money to not translate them every word has a cost so the one thing that is interesting as I said terms synonyms actually I'm not unique and it's an example here is the fundus
which clinicians are there well understand this I didn't it's the I won't you explain it because the the bit opposite the opening of bits in the body and essentially but this actually is
more than one thing it's a synonym across multiple concepts in the body structure another example is cysts sis can be a morphological abnormality it can be a disorder as well so you can have that
term coming across and this is where you use the FSN in in coordination to identify actually okay we're looking at different things it's on to relationships and this is where you start to get the real power of sno-med
and this really starts to play out with brick when we start talking about analytics and well it depends the synonyms synonyms are made for the local
environment so if sis is multiple things and the fundus is multiple things yeah I blame thing called vocabulary so wanting
relationships every concept has a set of relationships and these relationships essentially define the concept and this is back to the machinable expression of a concept so here we say every concept
has there is a is a it's a type of something everything has one parent but it also has relationships which you call attributes and a simple example carrying on with our pair penned ectomy is that an appendectomy is
a type of procedure that make sense but it has a procedure site on the appendix so from a machine point of view it now knows that this happens on the appendix and it's a procedure and I haven't got
to describe it it's a very simple model but what you also have in sno-med is as an ontology you can have multiple parents so here for example appendectomies is an operation on appendix but it's also a partial
excision of the large intestine these are both correct so depending on your data and how you're slicing your data that concept will appear in essentially the queries and analysis you can pull together well that starts to
look like from a hierarchical point of view is here we have appendectomies an operational an appendix and a post excision they then have their own parents they have their own parents and
then their own parents and it basically grows to the point of the top of the tree which is the single sno-med CT concept now the interesting thing is there that anything in there is a true statement so appendectomies a procedure
by sight appendectomies is it's a removal these are all valid questions and so you can see the analysis you start to be able to come down on what you're doing with the concept yes
yes and I'll be able to show that and and and this is where we get to in the fire services you can see this information so so attribute relationships we call them relationships but they're just almost side relationships attributes appendectomies
ample is it has a procedure site on the appendix structure like we just show but it is an excision so we now start to see that this concealed concept has an attribute of Appendix structure
procedure site and the method is excision again I start to be able to machine this and understand what I'm looking at and then that starts look at the the defining relationships of appendectomies here you know it's an operation on the appendix it's a partial
excision of large intestine it happens on your painting structure and it's an excision and this is a fully defined concept all of those must be true and you have that very specific clinical disorder that you've record procedure
rather than you've recorded against a patient record and it comes back down to this machinable there's no ambiguity in here there's no okay it's it might be a type of appendectomies if that code is there and it's been entered correctly by
the user or the clinician then you know very specifically that that patient has had an excision on the appendix structure as a starting point and you can build out that information from that particular model the next slide is the
one I really like doing with technical audiences in that you know good old data model picture but this is what sno-med is it's a very simple standard data structure everything is a sno-med
component a concept has multiple descriptions and a concept has multiple relationships and that itself defines the whole model of snowed and how it hangs together the other thing before we
start to get into the fire terminology services is to talk through sets you've heard me mention reference sets we have value sets we have subsets so it's
always quite useful to say what are they and what are the differences so reference sets is a very particular sno-med artifact it's essentially a set of references to sno-med CT components
so that can be a list of let's say for example allergies it could be a general practice reference sets of these the concepts we used general practice it can be a little more it can be used for maps as well so these
are very specific sno-med things and I'm explaining this because you won't hear about reference sets within the context of fire but we equate them between the two so value sets is a fire resource
it's uniquely identifiable sets of valid concept representations the difference being it's not just sno-med and that has a very useful context in many of your environments I'm sure obviously I'm
coming from the sno-med viewpoint and we'll give you some demos on how this works in sno-med but value sets can be used for many different things and then we have subsets which people talk about
as well but these are just really the definition the mathematical definition of a set it's a subset of a larger set you know there are no unique identifiers like he's going to be in an Excel
spreadsheet and I passed it around by email yeah then they're not something that sits in an intra bility playing area with sno-med CT the way we work with value sets and subsets is that we
represent these as reference sets and then one thing that a reference set is and just to kind of clarify is it's it's something that's published and versioned so every reference set has a unique
identifier in its own right and it then gets published in version so you'll get this out of the US Edition and another editions now what that means are the benefits so I put a table together to see what's the differences in where you
use them so reference sets are where we really see them being used the most is from point of your reporting and the best and what best example is national reporting we have countries who presume
Pilar reporting on smoking related diseases so what you do is so that you ensure that all your organizations in your country or territory are reporting the same things you create and publish this version reference sets so
everybody's using the same set of codes and there's no people aren't just adding things when you feel like it so you'll report at a national level or a regional level is is standardized reference sets also get used for other
things like maps so we map between multiple terminologies and coding systems and we do that in reference sets they are an extensible structure that allows us to say is a source concept and here's the source
code in another terminology value sets are a little bit more free and that's the nature of value sets they're useful for local users they're useful to create them locally they're not necessarily published or released but they have a
very different use case and your subsets just a subset I couldn't think of anything the rapidly but it's just a subset so I'm going to the five terminology services before I jump in there I thought I just so you break any
questions or any or questions about the sno-med stuff that's not quite clear yet normally I thought we have we have lots of online e-learning courses and they take normally about ten hours so I've
just pressed that into 15 minutes so there might be some bits missing but if you have any questions just come and speak to me or Peter or go to Jim's talk and tomorrow the lots more information you can get from people around so five
terminology services five from my plump user developer has really come at the perfect time for my sins I was involved in hl7 version 3 in the UK and I try to wash it off and move on from that but
fires really started to bring healthcare IT into the world of other industries if you working if you ever worked in finance or tourism or other areas you know this type of approach REST API is
not new and healthcare is always taking a bit longer to get into that world and so it's really refreshing that now you know we have this community six hundred people just blows my mind it's excellent that we're getting there finally and so
we really see the benefit of having terminology services to allow people to access sno-med in a more simplistic way without the complication that people often throw at terminologies like sno-med
so things going to talk about I was gonna draw pictures and I realized that the picture on the hl7 fire a website was better than I could do so I'll just copy and paste of it but the things that
we were going to talk about our code system the concept map and value sets the other ones on the pictures so element definitions and elements are very much within the profiles that many
people are speaking about over the next couple of days but from a terminology point of view we're really focusing on these three areas and so the code system allows you to find the code system there are particular operations that will show
concept map is useful translation now we use that from a pointee of mapping that's how we've translated that from a sno-med point of view and value sets how do we use value sets how do we crave
value sets and how do we retrieve them so code system will start with code system code system has a number operations validate code subsumes and
look up there's somewhat self-explanatory so validate code is provide a code validate that exists true or false from a single code code point
of view and this is very much a personal opinion that you know do you do a lookup for a code do you get a validate if you get one back is that valid there's a different thing about that but where we see validate code being used is when we
start thinking about post-coordination and post call nation's expressions validate that is it a valid expression that's where that was really going to come into play subsumes is a relationship a type of X so we think
back to that picture were the appendectomies up to there was a removal as one of the concepts you know is that pink depth is appendectomies sub soon some soon by removal hulls get the wrong way around
then you can ask that question and find it is it a type of essentially and then lookup which is a bit more split straightforward here's a code what does it come back at so as we're all
developers here obviously we have to give some examples and so I'll show you some examples so here's example of how do we look up the sno-med CT code four
to seven deliver now that's right correct yeah and one of the things we'll talk about in the hands-on session after this one is so one thing that was no
wait if national does whilst no matt has a licensing model at a country level we produce a lot of open-source software so we have an open-source terminology server that's fully fire fire enabled for sno-med CT so this is using that
particular software so and I'll walk through that a bit in the next session but for now if we look at the the URL here so what are we looking at simplistically we're going to code system we're looking at the lookup operation system that we're using is
this particular URI so sno-med dot info SCT you'll always see that when we're using sno-med that's the specific you are a the code is the code we're looking at and the jason we've we returned jason
just because it's easier to look at on the screen if I click this through it should show so do that so this is the response from that lookup
so the initial display it's an absurd check obstetric I really should choose ones I can say umbilical artery Doppler and it's that's the FSM so you can see we responded with the FSM and that to a
certain extent is a choice around the terminology server because that where we see this the ones that some of these national works with they come in at from different countries in different contexts the FSM is very specific so we
don't have that issue around duplication the system for example we can say this is the particular concept we're getting back and then we start to see the designations or essentially the descriptions coming back here we see
obstetric umbilical artery Doppler it's a synonym and it's your question about language en now if I go down and say okay here's the procedure here's the FSM
fully specified name again in English it has another synonym it's a third synonym Doppler ultrasound scan and local artery one of the things that we're still working through with terminology
services working group is how do we then explain which is the preferred term there isn't currently a mechanism for that yet in in the terminology services API but and there's complexes around languages and
contexts as well but eventually expect that to appear at some point yep No so this banner coding is saying that again it's a machinable thing a synonym
is also a concept so the description of synonym as a reference data is that particular ID so we're saying that this is a synonym which has that ID as in the
type has the ID basically that's a code for synonym so this is this is the the self referential part of it so and it
comes down to the reason why we provide the code is it a machine level the Machine needs to understand that this is synonym it knows through that it has that information yep sorry that's very good question there's a lot
of codes sorry no not a lot and lookup not for a single concept yep so we have the destination then we have
properties so we have the effective time which is the versioning aspect so this concept was created in 2007 July 31 it has a module ID now module ID every
concept has a module ID and that is generally linked to the organization it's it's who has created it so this particular module ID is the International module ID if you find a concept that's been created in the US and used in the US Edition that will
have a us identify where that comes into use that's use if you are working in a system that's in multiple you know multiple territories then you would use the module to see what you would display and not necessarily what you wouldn't but then we have parents so we talked
about the parents before this particular concept has two parents that particular Act one and that one very simplest thingy and also the child so here we can
see that's the child so a single child it hasn't got descent it we don't list the descendents only the direct child so that's a very simple lookup on that concept I go back here but if I want to
get more information so I talked about the attributes then one thing you can do on the lookup operation is requested the normal form and the normal form is a way of explaining in an expression what does the clinical what
is the representation of that that concept so if we run that particular one again yeah so what we have here they're things we've seen before the display the
designations again the descriptions the properties but also then we have another property now called normal form and portly doesn't get out very well but
here we can see we have it's an it's an investigation and a Doppler and this is the expression explains the procedure sight is the gravid uterus structure the method is ultrasound imaging and so you
use describe the the I mean means that you need to be able to obviously interpret that expression yes though this this is defeating that picture we had appendectomies apparent cine
attributes this is explaining that picture not further off the tree so it's saying the direct parents and the attributes and how that's was the how that's how that con that concept is made up basically
so expressions in sno-med which is what the normal form is have a very particular syntax and so by implementing that expression being able to interpret the expressions you will be able to actual interpret where there's
attributes it yeah yeah yes so if you go to the fire Docs it lists all those properties you can request obviously not everything is implemented by every
single terminology server yes correct yes that's defined by fire yeah hmm yeah so I'll move on a bit because I'm
talking to you slowly so here we go so that's cone system we then have concept map which is back - how do we find map targets how do we map between sno-med and say icd-10-cm so the way
that we do this is an example and running this through again you can see now we have concept map is the resource and the operation is translate the code that we're looking up is this one an
assistant that we going from is we're going from snow McQueen sno-med CT is where the code comes from the source is a sno-med CT code and the target is an icd-10 code so we want to find what is
the icd-10 code that's related to that particular sno-med code and this thing here in sno-med saying this is the map record is part of so if I click on this
it just gives me back so for that code the map target icd-10 is j14 at five
point nine yep yes yep since no minutes national so we already mapped to icd-10
the NLM in the US map to IT 10cm we mapped to I CPC I see NP a load of other ones I see do and so on so we provide this maps and those are released as part of the standard editions so when you
load these into a terminology server then you would get these maps in if the terminology server is important those correctly that the thing that we don't do it at least with snow maidens national point of view is we don't store the full other terminologies we just
store them as map targets there are other ontology there other terminology servers out there that still multiple terminologies so you can actually get the information from other terminologies so okay
another example is same as I talked about the history how do we find out that a concept here this particular one was inactivated so this is no longer useful to me I have this in my record I've told you till it's inactivated but
I can find out what hasn't been replaced by it and if I click this one through it says comes through and it shows me that it's been replaced by this newer concept so again from a machining point
of view I can trace that order built that traceability all the way through come back there begin to balance s and I think this is really where you get into the power of fire and snow met together
the one operation that we really really look into is expanding so how do we expand what isn't value set how do we find out what's in it how do we query what what's in the value set and there are a number of parameters that are
useful for sno-med CT if you look on the fire Doc's online every terminology has slightly different parameters these ones are very specific to sno-med and I'll walk through these what they mean so the
first one is just give me all the concepts in that particular version on the terminology server one then is a it's it's you getting the wrong word wrong but essentially this is saying
what is give me the descendants all the concepts that are a type of that so if I say back sorry so if I had a code there for asthma and I put there is a the asthma code then I would receive all the
concepts that are type of asthma reference set this gives me a list of all the reference sets on the sno-med terminology server then if I provide the identifier for a reference set this will give me all the content of that
reference set a filter is another parameter which I can then add to it's a term like a put heart attack or asthma and I'll do a search to search through that particular that particular term and then I can display the language so I can
choose a display Spanish or Swedish instead of English we have some examples on these so it's a simple one I want to get all the descendants of the code two seven six two four zero zero three now
if I click through then you'll see now I start to get a long list of codes coming back so this is just limited to ten we have a count on there just allows us to eliminate how much comes back and but
you can see this is a very simple here's a list of all those concepts that are a descendant of that particular concept if I look back but then I could do the same thing in Spanish so I odd to
display language in Spanish you notice the other thing that changed here is the URL and the URL now includes the module ID which display which describes it as the Spanish edition so every Edition has a module ID and this is the idea the
Spanish so I click through on this one the same result comes back with Spanish descriptions and we can do that for all the descriptions that exist again the concept IDs are exactly the same it's a
different display language then I could do something a bit more we will loose like I want to find every description or every act concept that has a description containing the words heart attacking so here I've just gone for fire underscore
vs so give me all the concepts filter on heart attack and just give me ten back to start with and here you see there are nine of these apparently and you can see that these whilst you don't necessarily
see that in the display so look at this one here myocardial infarction there are synonyms that say heart attack on there so this is where we come back to we always display the FSN in these lists because it makes more sense from a
clinical safety point of view but if you go through and look at that particular concept you will see that one of the synonyms is hostile [Music] yes so once it's a concept could have multiple synonyms and so what we're
saying is a heart attack is not necessarily a clinical term it's a localized term to how people describe myocardial infarction so this is returns you back the concept and not
the description these are all concepts yeah so let's say that the way work is all what your back to the unit work is always a concept and so we move away
from picking out the descriptions it's always linked to that concept so this is yeah that's what we go in the patient record would be two to nine eight zero zero six because wherever they look at that record it'll mean the same clinical
thing and finally if I want to get all the concepts in a reference set so this is a reference set for general practice it's just got the rep set link label and
then the ID and this gives me back a list of there are four thousand two hundred eighty nine concepts in this particular reference set and here's just that list of what's in there some
reference sets are created by countries by governments some are created by local regions in their own editions as in reference sets are things that are published based on so we have some internationally each country has their
own ones built in sorry yeah that's how you do within the context of fire so everything else back it's a value set that happens to be a value set defined with the clinical the
correctness limit model so what this means is I haven't had to go and create manually create a value set with all those entries I'm just using the sno-med expression and model to get the
information back I'll move on sort of thing I've gone well over time but I'll be doing quite quickly so we call and create a value set this is very simplistically it's an HTP put with a
JSON but here you can see we have a resource type of value set the URL for it a timestamp but also what's in it and this one is just an example of we have a fire code and we have sno-med code you
can have multiple codes in manually created value sets you can update that by just using a put with the same JSON that will just update that value set and also delete it's just an HTTP delete
request quickly going through so that's a very simplistic thing but going on to some of the advanced know mode retrieval where how do you find out attributes of a concept how do you do the more
powerful analysis and just moving on quite quickly so one of the things to show this is how sno-med differentiates from ICD so icd-9 and icd-10 I always like to think of it as very powerful for
statisticians and sno-med is very powerful for clinicians because their clinical meaning and other one which is used for mortality reporting for example which is where it started with WH o we
maps these classifications as I just showed but the reason for just bringing this up is it shows you the difference of how what you can do with sno-med once you start to implement the advanced query so the icd-10 if we were looking
for viral pneumonia we would say does the patient have a respiratory disorder and we would type in J and we'd get J 12 back but we wouldn't be able to know does they have an infection does a patient that does this disorder affect a
lung and is this caused by virus because that information is not within the model of ICD quite correctly that's not supposed to be there with sno-med though we know that viral pneumonia is a type of respiratory disorder it's a type of infectious
disease it is fining site on the lung structure and the course of agent is virus so means that I can do a search across any of those particular attributes on that concept and always come back to the same concept so we have
some way to do that in Sonoma call ECL which is expression constraint language which means we can say for example here's a good example the best ways I would like to select a disorder or procedure use the location of where they
occur in the body so give me all the patients who have had a procedure on the airway structure and I can find that by just by the concepts they've got in their patient records we have a full syntax on that and we'll talk about in
the next session where we get this see we see that's getting news is things like data input that's one of the key starting points especially with type-ahead how do I make sure that I'm working in the same area when the issues
I hear a lot is snow it's too big how do you work with sno-med and sometimes that's down to I see the implementation tends to be a big drop down with all the codes of sno-med well yeah that's unwieldly for anybody so you can use ECL
as a constraint language to only display what's relevant in the context of you working with it so if we were working in the cardiology department you could query you could restrict what they're querying based on this ECL this query
language here for example we can use a four type-ahead for asthma we're working in matching assessment scales so I'm only I'm going to query within the assessment scale hierarchy so it just returns you back and that's defined by
this query syntax what it looks like is these I'll give you some examples how do we find patients with any types of diabetes we have a little to less than
here that show give me the patient's any concept that has is a type of diabetes then we say how to find patients with an infectious sort of the lung here's a it's I want all the concepts that are
sorry a type of infection disease where the finding site is the lung and so again this comes down to a machinable query that you can use to find the information so when your patient data is coded with this
you can do the analysis across the data to find the information if I wanted to find any patients who had a behavior finding in the nursing health referencing health issues reference set then here I can say give me a concepts
that are a member of that reference set and our type of behavior finding and it's a very simple thing that the query language is very powerful in these are some simple examples but you can see how you would provide reports based on
patient coded data using this there's a load of syntax in here I've talked about some of these a descendant of or descendant or self of parents of you can do conjunction disjunction the exclusion
so you can build up quite powerful queries to to really produce analysis but also to restrict what your users work with and there's a full guide on snow medaka mentation that gives you a
lot of information about this I recommend that yes next slide yes that could be a good question
so where this comes into is value sets so value sets in sno-med there is a parameter which allows us to provide an ECL so you can get that value set back with the results of that particular
query so an example here is we want to get all the concepts that are type of chronic disease the ECL is this less than sign in the concept and then the fire looks like the same things before
but with ECL for slash the idea is they're always URL encoded but that's the idea so if I pass that in we basically get the result of that query there's a very simplistic way you can create these queries and just query them
that way and they come back as a value set through the fire Technology Services API correct exactly so you put you pull back the information if you're working in an analysis scenario then and general you
don't you can do these on the fly but you'll be saying we want to find all the patients that are have a type of diabetes give me all the codes and now find me all the patient records that have those codes yeah it depends on
implementation but exactly go to Jim spear doctor tomorrow but one thing quickly to get onto because I've gone well over is basically you can create
value set as an ECL so instead of having to always rewrite the ECL you can put this in as a type of value set so here I've created one they're going to call chronic disease a value set and the URL includes the ECL so now I can actually
just call that particular value set that's calling disease and expand it without having to always write the ECL yes it stores that the value set is stored as that particular format there so it just brings back the query it
depends on how some terminology servers might cache some just run with the query so and we can then expand it and we can filter on it so here using the filter parameter I'm searching for heart on
that so if I did that it looks like there for example everything in my particular value set that has heart and it's essentially using that ECL query
and to close just quickly we have a session after this a hands-on will go things in a bit more detail but this week as Jim's thing back here has a great session tomorrow Whisperer more detail how to use the terminology services API
with a handled session I'd strongly recommend going to that Daniel Riemann from link will be showing how link works with fire you know all these terminology systems don't sit in isolation they all need to work together so I'd recommend
going to see that and then Rob Heusen does a bit more advanced around terminology services further steps on Wednesday so I'd recommend if you're interested in using the different terminologies to go to those sessions there's a load of information I think
these slides that will be available I believe to everybody there's a snow mode on fire working group where we have got a lot of quite a growing community between Chael seven fire community and snow
international you're welcome to join that if you'd like to be part of that group but have lots of links here and the next session we'll be talking about how do we do this on our open-source terminology server platform with fire
technology services so there we go if you have questions come up after's will please stay for the next session thank you [Applause]
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