Reflecting on my last post: where you store your health data should be a choice, like picking a server on the #Fediverse.
We don't need more national databases or HIEs to act as "landing zones" for unorganized data. HIEs often fail because they are just dumb pipes moving unstandardized noise.
What we need is a shared vocabulary (#OMOP/ #FHIR).
When we have that, the location of our data can be a choice, and we can let the protocol handle the rest. #HealthIT #Interoperability
🚨PhD Opportunity 🚨
This is a great project if you want to:
💡Develop Natural Language Processing models to aid in early diagnosis
💡Analyse echocardiogram and nerve conduction study reports
💡Work collaboratively across the domains of Data Science and Medicine
(This PhD isn't with me, but it's with a fantastic team who are very friendly and supportive!)
PhD Project - Use of natural language processing to aid the identification and treatment of patients with ATTR amyloidosis at Lancaster University, listed on FindAPhD.com
Author summary Reusing routine care data does not come free of charges. Attention must be paid to the entire life cycle of the data to create robust knowledge and develop innovation. Building upon the first overview of CDWs in France, we document key aspects of the collection and organization of routine care data into homogeneous databases: governance, transparency, types of data, data reuse main objectives, technical tools, documentation, and data quality control processes. The landscape of CDWs in France dates from 2011 and accelerated in the late 2020, showing a progressive but still incomplete homogenization. National and European projects are emerging, supporting local initiatives in standardization, methodological work, and tooling. From this sample of CDWs, we draw general recommendations aimed at consolidating the potential of routine care data to improve healthcare. Particular attention must be paid to the sustainability of the warehouse teams and to the multilevel governance. The transparency of the data transformation tools and studies must improve to allow successful multicentric data reuses as well as innovations for the patient.
Réutilisation des données d’anesthésie / réanimation avec #OMOP #OHDSI. Entraidons-nous !
Avec les CHU de #Amiens, #Caen #APHP, #Lille, #Rouen, #Toulouse #HopitalFoch
https://interhop.org/2022/03/22/reunion-interchu-anesth-rea
InterHop est ravie d'avoir présenté le formulaire en ligne de recueil de données de santé opensource et éthique http://goupile.fr au congrès des anesthésites-réanimateur #WeARe https://www.weare-2021.com/
Nous serons ravis de continuer les discussions autour de l'interopérabilité. C'est la mise production des algorithmes qui occupera les 10 prochaines années. Celle ne se fera pas sans l'interopérabilité : #OMOP #FHIR.
Voici nos travaux sur ce sujet en anesthésie : https://pubmed.ncbi.nlm.nih.gov/34714250/
L’utopie Partageons La solidarité, le partage et l’entraide entre les différents acteurs sont les valeurs centrales en santé. Au même titre qu’Internet est un bien commun, le savoir en informatique médicale doit être disponible et accessible à tous. Nous voulons donc promouvoir la dimension éthique particulière qu’engendre l’ouverture de l’innovation dans le domaine médical et nous voulons prendre des mesures actives pour empêcher la privatisation de la médecine.
Ethan Mooney
Nicola Rennie
Pim Volkert
Christos Argyropoulos MD, PhD
the_epidemiologist
interHop