Merken

Django, Python, and Health Care Data

Zitierlink des Filmsegments
Embed Code

Automatisierte Medienanalyse

Beta
Erkannte Entitäten
Sprachtranskript
probably know what it is and to the next so this is just the groups to prove it the things right in my
area and I'm throwing it out and you you a bandit repeated time and you're doing it I will not be an
america nursing you sit and still researchers there's anything at all and the other 1 is the elaboration of the agrarian weights from the law of the yelling on event on and kind of thing that is of the station within each seeing thing that I movement the CC here and there to learn about technology and so in 14 year world of the elite and for those the the optimal error to the I is a kind of organization into low-cost technology platforms for women and men to relieve the learning environment and I learned people and on the other hand girls is the thing and the inside of the world I normally should be carefully to middle-school girls and technology and helped them form a community and the all different careers at all and they have a lot lot of sorts for some of the original data the chapter as many bacteria and other things so that the team I have 1 and a half monitors in it so that the idea that I went to this side of the have and will only get out there today that is made get this in the online and you're acting upon in the audience on you believe in the mid community I there is kind of a little about where a lot of women that are sitting here today and it's usually 1st as well and where having yet person on specially being at least the actual output would be about here the idea that and you major and so you get started so i'm until
there's a folder also 1 of the old and technology especially if you take that in all the tools used technology and representation in the order that you have in the sixties I don't think that's very old but that the operation and actually loads all
the sale of the so there was certainly should be generally about the death of of the ways find it but what we were explicitly related to older adults and how it's used in mentality of the healthy and that in the medium and and this is the outline and
interventional caveat that talk about clinical decisions were in the service the words that have been exploited in health care delivery of be that in and use the of of so
sources of care that I would not have brown and a media in general assessing the health care industry and its there's so much of the use everything the doctor at all times of the year by a quantity and they are right in that they use and where 1 thousand like in more new documents and you know it won't work and then it happened more like and then all them have you been here the hidden to think about that the and this is all the users and people are using the at the hospital decisions on these in themselves can be personal solver now labs and Public Health Reporting here is the researchers and you're handing at and bt period research stating that and also a meeting of the blood of and there's a lot of work on the resulting data the used most recently and so can help record the from right right here they have some of the by the 2 word and what they're interested in finding out because they have been seen as very much vertical and
the differences between the 2 the media and to understand right away and I'll use me as the time goes under the name of the distances in the eye and have recently in the diagnosis codes I have used a lot of work in sharing the coast or medications as competing poses a lot of users I was a little involvement in the hands of free text form used up and the use of more detail in there and the new and made a lot of the insurance is you can easily look at an individual person as well as originally it's very easy to all and 1 these ladies versus what kind of record the efficiency and I you know very detailed reports about what each of you can look at the whole region as well I'm in abstract with the questions about all of the other 1 really think about things that you see everything that each day so 2 main and only a lot of time of the year using the hand to the index of the next week and only after all that many of the things verses the shot that is from 1 house so there and you will see their all information must have many of you here and here position in the in the number of and things did not help guide to the process of going out the charge that is typically more than enough that all I wasn't really experienced pain and used to charter is that if you are those multiple hospitals in the same kind of work and this was not very likely in using different versions of the same software in the heart of the of the you the so the 1st
thing in a way that me that that is at the core of the system works under this is built into a lot of regions and they each had all this data and that is the American system any and all right there's your alerts and all I didn't the rulers and reminders so they you know all medications lesions on any medication and interact with the 2 that were saying this is what we're gonna before we do something the the writers of the time of the of the whole pipeline was the giants and so the data is the creation an then you know that something bad position on city doing and there's not a lot of it is that and they also were assessed so if the hospital and another testing of wasn't in the that I and those who have been here on the only way to do things as well as theirs and diagnostic support or decision support but here's thing about man and test results because you're not near the end of and so and this is where is really the work of writers in lesions and here's the situation I mean better decisions and have already organized me great such and
so this is where the character and that it means that happened balls and you and the services and support and for this reason we patients in the hospital in each and every district out of thing and and doesn't right most of the research on the internet and so on I don't have all list so many articles that altogether this presentation that if you're interested in this research and application of a little while thanks to the regions of the hospital was very complex and they have a situation in which the war it happened in the hospital International at the old articles that have multiple of the this is island is really complex you and so the decision of whether the need to go somewhere in the world were home or not carefully and you become decision and so on and all of a lot of pupils recent research is all around building work around the resources and I'm so current research on talking about me questions that we're using proper so that with the work of monopoly on hospital well here's the Shiseido population my of using the hospital can now using the term post-acute care about the presentation and you have a character anything right afterward and the home here in this realization fillers for these there's home how I mean this condition at the hospital i is really important notable at the hospital and amenities and the radar among all the different departments and the loose functions such as walking the of the themselves and so this isn't transition the so the 1st
question who is at risk of world so animals instrumentation has low res and there's stations and 1 that she goes what effexor with the use of some kind of you care services and so this model was built using expert opinions and then regression modeling so where where it has learned President 2 of the frame of the 2 each RDF and the hospital here in the studies of real speech of the and include all the information on what happened in the past that all medications clinical history lattice and is that a full what support that the international only the devastating to these case studies I'm a neurocrine experts but actually mostly on from a number of different disciplines and use it people there this position social workers this certainly the unknown will have these values around here and all that really in the area of I'm so the routines in the in the article that he studies and then then whether they want to discharge of patients home or whether is your 1st 1st and why so I the that of the head of the 1st round there was an agreement again and do that around and to it and discuss it I heard of you the lack of timely help for a number of patients in reasons why and he did regression modeling and he say if there is a lot there were made that were out of localization unused where each walking abilities like his name the number of morae conditions read this they have depression and self-rated health assessment so we are and how the whole the where it's were very good points that the reader the and so on all the things the things that have gotten fully into the charges and the other at moment the are in dealing with so this has created while actually got into the of of the year all this stuff on the Earth the tree throughout the text of the of here solutions and the new research and win the algorithm was implemented on the show that it's an abbreviated 82 asked him over the surface and work studied the 2 after you does decreased variance std relations and it is better to each so I want you without and was a neural net net question was where the university and so well here's here's the answer this process with again very similar I'm hold knew each are records of together all these case studies under out 1200 variables in the nursing emission they not only documentation and and and and changes in the socio-demographic cognitive status this whole mental health coming back social work I think about character lesions medical history depression part and the teams very very interdisciplinary doctors nurses social workers and the school there understand the only thing that really I'm in all the history with the online so going to be the I have yet to know whether the Earth where they wanted to prevent you know that he got the check boxes that set of variable energy back in fact all variables that help them make that decision and this 1 we were using these characters were hospitals unsnapping mentioned earlier in the process to merge that you know they're all using the same pair of customized their tolerance for reducing the burden of the accident all the same I'm through this study will last 1 question to what was found was that were patients and were actually refusing him so there has to been made in the recommended it was used in the world things and you actually defined as it is on the next
question was you know wired the thing services are those are the land because happened then any so that happens is being recruited in the model and this is the word I'm working on right now on the article that are estimable once again I was looking at conditions are leading hospital information you want to know I this I think almost 30 and older adults in the hospital at home the questions about what the knew about different is the faces and what they were concerned about being offered and the no and so we have the 2 questions in analyzing the top of the work that when the first one was when discussing options available to you as possible services would you like to know parents services to help me informed decision and he's on the shipment you wife and that was and the whole thing is if I'm no to the model in which the whole care is the radius known for approaching the shape and the age-old are comparable so mean it's the only way to better conditions the onset and they really are Celestina and we should have something in to me as well as I did in this section of the to study the notes the help and that's the we presented here just passed the nonsense about of projects
and lead to greater being elected to the DCs to it as an expert opinions and rationally as taking all the data in each are all the time running statistics from that and see the improvement in that there probably worked on in the past year will get under insurance company I work specifically in hearing aids which is the whole plants after all articles and by the way that we work in informatics for prosecution populations and what is really saying about the disaster for us about the prediction that outcomes I have nurses and other health professionals in the world so the the know that have problems lately I we you something and it is the same for that's New so the 1st one of the likelihood of
population model and it's is the form of the local and the oxygen needed an interview about the model an activity of many of its ease of predicting the sector personal styles of data and the likelihood constellation of in internet they're testing is nurse call coaching so that focused on the factors that have older adults and non durable Ministère looking at the type of I had the just a part failure of coronary diseases reaction of her own I the in the of the so managers and so they're creating kind of relation of testing whether they're kind of doing the action through region and and the 2nd 1 being
working models predict I used as the article is looking at me created a model the reserve at the end of the day that the test set so that the the article I don't respect announces the once they have a lot of new words there can be predicted with a that's how 18 months from the queen and so it's a hell of a models doing me as the as the and the the the ROC curve receiver-operating parents on word the related to data model a million carrying out and to 85 personal knowledge is just like in that you know the value of the city and be to those without it they were and they can make the model more than I so here we have the model and now I'm looking at outcomes respectively so that's not
a reason to out his 1 of the unlucky in philly over the delay which is that the city is a of the but this is not really an immediate 26 how it affects the overall 300 that they're all available see the 20th but you know I cannot reason filling actually DT just
as the help services I friends with that help the initiative to open up the and make it more publicly available on the the background is all the way to the others to companies in the sense as this morning and the interest in playing around with anyhow pretty at the competing models of a a lot of data that are easily available on the planet and the the house was learning more about it and initialization I'm using the data available announcement
managing and using patenting of specifically talking on the the phone ladies is as the software architecture for the program and the product of that is cooperation between electrical engineering at the Italy to the media group here in philly I think over the and this is started in the last 2 weeks of training workers together to work on it I'm usually Ogino as well as machine learning and kind of not the I going this to other companies in the late I have the property data I did well how people can think the all hold interest themselves in predicting what the amendment very high mass familiar with that they also have to do is find where each year and using think I need to know the condition in both the health care within their own not the program which is a type of records the new was built with the energy of the young man who was on the
and it is would it
means at the end
Flächeninhalt
Gruppenkeim
Computeranimation
Nichtlinearer Operator
Gewicht <Mathematik>
Selbst organisierendes System
Selbstrepräsentation
Gesetz <Physik>
Systemplattform
Ereignishorizont
Quick-Sort
Computeranimation
Last
Arbeitsplatzcomputer
Ordnung <Mathematik>
Programmierumgebung
Fehlermeldung
Funktion <Mathematik>
Dienst <Informatik>
Entscheidungsunterstützungssystem
Wort <Informatik>
Computeranimation
Subtraktion
Prozess <Physik>
Ortsoperator
Freeware
Abstraktionsebene
Versionsverwaltung
Zahlenbereich
Quellcode
Frequenz
Computeranimation
Datensatz
Bildschirmmaske
Verbandstheorie
Automatische Indexierung
Rechter Winkel
Software
Hypermedia
Codierung
Entscheidungsunterstützungssystem
Wort <Informatik>
Information
Abstand
Verkehrsinformation
Softwaretest
Resultante
Amenable Gruppe
Ortsoperator
Gebäude <Mathematik>
Gruppenoperation
Interaktives Fernsehen
Schlussregel
Kartesische Koordinaten
Mailing-Liste
Physikalisches System
Kombinatorische Gruppentheorie
Term
Dialekt
Computeranimation
Internetworking
Dienst <Informatik>
Konditionszahl
Entscheidungsunterstützungssystem
Speicherabzug
Metropolitan area network
Subtraktion
Punkt
Gewicht <Mathematik>
Prozess <Physik>
Ortsoperator
Momentenproblem
Quader
Rahmenproblem
Mathematisierung
Zahlenbereich
Sprachsynthese
Unrundheit
Computeranimation
Netzwerktopologie
Datensatz
Variable
Informationsmodellierung
Algorithmus
Reelle Zahl
Flächentheorie
Koroutine
Arbeitsplatzcomputer
Vererbungshierarchie
Grundraum
Hilfesystem
Varianz
Schreib-Lese-Kopf
Regressionsanalyse
Beobachtungsstudie
Radius
Expertensystem
Shape <Informatik>
Relativitätstheorie
Stellenring
Ähnlichkeitsgeometrie
Konfiguration <Informatik>
Energiedichte
Dienst <Informatik>
Verbandstheorie
Flächeninhalt
Rechter Winkel
Konditionszahl
Mereologie
Entscheidungsunterstützungssystem
Wort <Informatik>
Projektive Ebene
Garbentheorie
Information
Statechart
Softwaretest
Statistik
Benutzerfreundlichkeit
Likelihood-Funktion
Gruppenoperation
Relativitätstheorie
Systemaufruf
Teilbarkeit
Computeranimation
Internetworking
Umweltinformatik
Informationsmodellierung
Bildschirmmaske
Prognoseverfahren
Datenmanagement
Datentyp
Mereologie
Softwaretest
Informationsmodellierung
Vererbungshierarchie
Datenmodell
Wort <Informatik>
Kurvenanpassung
Computeranimation
Wellenpaket
Kategorie <Mathematik>
Gruppenkeim
Biprodukt
Computeranimation
Energiedichte
Informationsmodellierung
Dienst <Informatik>
Datensatz
Konditionszahl
Softwarearchitektur
Datentyp
Hypermedia
Algorithmische Lerntheorie
Optimierung
Hilfesystem
Metropolitan area network
Arithmetisches Mittel
Computeranimation

Metadaten

Formale Metadaten

Titel Django, Python, and Health Care Data
Serientitel DjangoCon US 2016
Teil 29
Anzahl der Teile 52
Autor Nock, Becca
Lizenz CC-Namensnennung - Weitergabe unter gleichen Bedingungen 3.0 Unported:
Sie dürfen das Werk bzw. den Inhalt zu jedem legalen und nicht-kommerziellen Zweck nutzen, verändern und in unveränderter oder veränderter Form vervielfältigen, verbreiten und öffentlich zugänglich machen, sofern Sie den Namen des Autors/Rechteinhabers in der von ihm festgelegten Weise nennen und das Werk bzw. diesen Inhalt auch in veränderter Form nur unter den Bedingungen dieser Lizenz weitergeben.
DOI 10.5446/32689
Herausgeber DjangoCon US
Erscheinungsjahr 2016
Sprache Englisch

Inhaltliche Metadaten

Fachgebiet Informatik
Abstract Data and technology can be used to improve the health of older adults and to help them to continue to live at home and in the community as they age. Predictive analytics and modeling can predict who will get sick, be hospitalized, or have adverse outcomes in the future. Once we know who is at risk, we can design interventions to decrease the likelihood of negative health outcomes. This talk will introduce you to health care data sources, such as electronic medical records and insurance claims; predictive modeling and how it can be used to improve the care we provide; and publicly available and open health data. We will talk about the D2S2 (discharge decision support system), which helps health care providers make decisions when older adults are getting ready to be discharged from the hospital; and how Django and Python can be used to visualize open health-related data. Intro: Who I am (2 min) Health care data and where it comes from (5 min) Electronic health records Dr. Chrono is actually built with Django! Claims data Predictive modeling and decision support (10 min) Predicting readmissions & the discharge decision support system (D2S2) Predict whether older adults are at high risk or low risk of being readmitted to the hospital after discharge. Building decision support to improve hospital discharge decision-making Once we know a patient is at high risk of being readmitted, how do we decide what care they should receive after they leave the hospital? Use expert knowledge to develop decision support into the electronic medical record that will recommend a site for post acute care (care once the patient leaves the hospital). Building patient preferences into the recommendations made to health care providers about what care the patient should receive after their hospitalization. Brief overview of: Predicting diabetes Likelihood of hospitalization modeling and nurse health coaching Django and health care data (8 min) Overview of open and publically available health care data Open Data Philly HealthData.gov Visualizing open health data with Python and Django

Ähnliche Filme

Loading...