1 1 anatomy of an app

Here are the steps to complete the tasks in the template designer walkthrough: 1. Open the template in the designer 2. Find the Problem/Diagnosis archetype and rename it to Main Diagnosis 3. Constrain the Main Diagnosis archetype to keep only the Problem/Diagnosis name node, removing all other nodes 4. Pull in the Adverse Reaction archetype 5. Constrain the Adverse Reaction archetype to keep only the Substance and Manifestation nodes, removing all other nodes 6. Rename the Manifestation node to Reaction Details and set it to mandatory (single occurrence required) 7. Find the Medication Order archetype 8. Clone the Specific

1 7 open_ehr in context

1 4 intro to archetypes and templates

2 4 open_ehr archetypes cluster

2 7 open_ehr rm reference model overview

The document provides an introduction to key concepts in the openEHR Reference Model (RM) including: 1) It describes several core RM classes - EHR, Composition, Section, and Entry - that define the structure of a patient health record in openEHR. Compositions contain patient data organized into Sections and Entries. 2) It explains key attributes for different types of Entries defined in the RM like Observations, Evaluations, Instructions, and Actions that support the "clinical investigator cycle". 3) It outlines important datatypes in the RM like Quantity, Text, and CodedText and their relevant attributes for modeling clinical data values and coded items. 4) It describes how archetypes are

What is openEHR?

openEHR is an open specification for a health information model that supports an open platform ecosystem in a vendor-neutral and technology-neutral manner. It uses open source clinical archetypes and content definitions to allow for substantially faster app development with lower barriers to market entry and no vendor/technology lock-in. openEHR utilizes a common information model with archetypes, a vendor-neutral querying language, and open-source content libraries to provide interoperable clinical data repositories for storing and querying health records.

2 2 open_ehr archetypes classes

This document provides an overview of openEHR archetypes and their classes. It describes the main generic classes used in openEHR such as COMPOSITION, SECTION, ENTRY and ELEMENT. It then explains how archetypes act as recipes for defining clinical content using these classes. Key parts of archetypes like COMPOSITION, SECTION, ENTRY and their subclasses are defined. The roles of different ENTRY types like OBSERVATION, EVALUATION and INSTRUCTION are outlined. Examples of common archetypes are also referenced.

This document discusses clinical information modeling and interoperability. It introduces openEHR, a two-level modeling approach using archetypes and templates to define clinical information. OpenEHR aims to support app development through a shared information model and democratize healthcare standards development. The document also discusses challenges with mismatched clinical models, the need for a shared platform and information standard, and an evolutionary approach to standards development involving clinical stakeholders.

2 3 open_ehr archetypes observation

openEHR Clinical Workshop - Implementer perspective

openEHR China Localization working group

xudong_lu

The document discusses openEHR China localization efforts. It proposes establishing a sharable archetype repository in China to accelerate archetype publication through an implementation-driven process. This involves modelers developing archetypes, implementers testing them in projects, and experts reviewing. The goal is to localize openEHR for Chinese needs faster while collaborating with the international community and standards bodies in China. A working group and timeline are proposed to publish the first localized archetypes by early 2018.

The openEHR Revolution Heidelberg 2018

This document provides an overview of Ian McNicoll's background and roles related to openEHR, as well as the current state and future potential of openEHR in the UK. It discusses openEHR adoption by various NHS organizations, the Genomics England project, and efforts to establish an open platform architecture and bridge openEHR to FHIR through the INTEROpen and Apperta groups. The vision is for openEHR to expand commercially and help enable an interoperable health system through open standards and APIs.

Introduction to openEHR Clinical Workshop MIE2016

The document discusses the complexity of healthcare data and the challenges of capturing requirements from clinicians. It introduces openEHR as an open specification for a health information model that supports an open platform ecosystem in a vendor and technology neutral manner. The specification includes an open information model, REST API, and query language to allow multiple applications to access the shared openEHR clinical record in an open platform architecture. The workshop aims to provide perspectives on openEHR from international, national, and implementation views.

Developing openEHR EHRs - core functionalities

Pablo Pazos Gutiérrez gave a talk on developing openEHR systems. He discussed storing openEHR data using different database types, openEHR system architectures that have evolved to be more distributed and service-oriented, generating user interfaces from archetypes and templates, performing archetype-based validation on entered data, querying and visualizing openEHR data, and implementing openEHR over the past 8 years in Latin America.

openEHR Technical Workshop Intro MIE 2016

openEHR is an open specification for a health information model that supports an open platform ecosystem. It uses two-level modeling with reference models representing health data and archetypes representing clinical concepts separately. Archetypes capture clinical concepts in an open source and computable format. Templates aggregate archetypes to deliver clinical datasets. AQL allows querying of the information model independent of the database. Building a high-quality openEHR system is challenging as it requires understanding and supporting archetypes, templates, information modeling querying, and being fast and flexible.

2 6 open_ehr archetypes instructions_actions

The document discusses openEHR Archetypes for clinical instructions and actions. It describes archetypes for orders that arise from clinical assessment, such as lab test requests, medication orders, and referrals to specialists. It also describes action archetypes that record activities resulting from instructions, like lab tests being performed or medications being prescribed and administered. Additionally, it outlines features of entry subtypes like observations, evaluations, instructions, and actions, including whether they include fields for provider, subject, data, history, and workflow pathways.

openEHR Medinfo2015 Brazil Sponsor Session

openEHR: NHS Code4Health RippleOSI and EtherCis

Christian Chevalley has over 30 years of experience in software development and has been developing platforms based on openEHR since 2010. He has delivered a first release of EtherCIS, an open source openEHR server. EtherCIS takes advantage of PostgreSQL's mixed support for relational and JSON datatypes in a single table structure. It uses the jOOQ library extensively for SQL coding in Java and allows easy migration between database backends like Oracle or DB2. EtherCIS is fully compliant with the Ehrscape API and its development includes adding validation handling and common provisioning tools.

Design and implementation of Clinical Databases using openEHR

This document provides an overview of designing and implementing clinical databases using openEHR. It discusses clinical information requirements, organization, and database technologies. OpenEHR's goals are to create flexible, interoperable EHRs through archetypes and templates that define clinical concepts. For database design, archetype IDs, paths, and node IDs are important for querying openEHR data. Relational databases can be used through object-relational mapping, mapping classes to tables, relationships, and inheritance.

openEHR sll-2015final

Enabling Clinical Data Reuse with openEHR Data Warehouse Environments

Luis Marco Ruiz

Modern medicine needs methods to enable access to data, captured during health care, for research, surveillance, decision support and other reuse purposes. Initiatives like the National Patient Centered Clinical Research Network in the US and the Electronic Health Records for Clinical Research in the EU are facilitating the reuse of Electronic Health Record (EHR) data for clinical research. One of the barriers for data reuse is the integration and interoperability of different Healthcare Information Systems (HIS). The reason is the differences among the HIS information and terminology models. The use of EHR standards like openEHR can alleviate these barriers providing a standard, unambiguous, semantically enriched representation of clinical data to enable semantic interoperability and data integration. Few works have been published describing how to drive proprietary data stored in EHRs into standard openEHR repositories. This tutorial provides an overview of the key concepts, tools and techniques necessary to implement an openEHR-based Data Warehouse (DW) environment to reuse clinical data. We aim to provide insights into data extraction from proprietary sources, transformation into openEHR compliant instances to populate a standard repository and enable access to it using standard query languages and services

Bringing Things Together and Linking to Health Information using openEHR

Koray Atalag

openEHR and DIPS Arena: the 'Best of Breed 3.0' revolution

Dr. Ian McNicoll introduces openEHR and discusses health information systems. OpenEHR aims to create an open platform where clinical data can be exchanged between any system regardless of programming language, human language, or database technology. OpenEHR uses archetypes, which are computable models of clinical concepts, to define clinical content in a standard way that is not locked into any one application. This "Best of Breed 3.0" open platform architecture allows different applications to access a shared set of clinical models and data, offering more flexibility and clinician control over clinical content.

openEHR in China 2019-06

- Early research on openEHR in China began in 2009 and included PhD theses and papers on openEHR frameworks and models. - In 2016, the openEHR Technical Committee (TC) was established under the China Medical Software Association to promote openEHR modeling and implementation. It organizes workshops, tutorials and conferences. - Notable openEHR implementations in China include the CLEVER clinical data registry developed by Zhejiang University and the PHIP population health information platform developed by ZTE-ICT. Both use openEHR archetypes and reference models. - Over 20 companies and 47 institutions in China have adopted openEHR in their systems and projects, mainly focusing on electronic medical record,

EHRbase, open source openEHR CDR

This document provides an overview of the openEHR CDR open source project called EHRbase. EHRbase aims to provide an open standard-compliant backend platform for electronic health records and clinical applications using the openEHR specification. It has a team of developers across multiple continents and uses modern development practices like Scrum and BDD. EHRbase provides a REST API and SDK for creating, querying, and managing openEHR objects in a clinical data repository, and also integrates with FHIR through a FHIR bridge. It is being used as the backend platform for a national COVID-19 system in Germany.

Introduction of BJU-BMR-RG and use case study of Applying openEHR archetypes ...

The document discusses applying openEHR archetypes to implement a clinical data repository (CDR) in China. It analyzes existing EMR data schemas, identifies 892 relevant data items, and maps them to 62 clinical concepts guided by openEHR. Most concepts were mapped directly to existing archetypes, while some required extension or specialization to fully represent Chinese CDR requirements. Implementing a CDR based on openEHR archetypes allows clinical experts to define, retrieve, and query necessary data flexibly.

E health dublin sept 2016

This document discusses the challenge of interoperability between health systems and the role open source can play in addressing this challenge. It notes that open source software and specifications allow systems to avoid vendor lock-in, but that open source applications alone do not ensure interoperability unless everyone uses the same system. It argues that the strength of open source lies in open infrastructure components, not just applications. An open platform based on common open standards and information models could substantially accelerate app development and lower barriers to the market while avoiding lock-in.

Personium - Open Source PDS envisioning the Web of MyData

暁生下野

How can we citizens maximize the benefits of the new right to data portability, which is now rapidly being recognized globally? Personal Data Store is a technology that will receive all “My Data” from hundreds of services. It aggregates and integrates them, and at times discloses a portion of them to others under user’s control for creating new values. This talk will introduce an open-source Personal Data Store (PDS) server “Personium”, providing details on its technical implementation, the underpinning business models, and the actual implemented and future use cases.

Tag.bio: Self Service Data Mesh Platform

Sanjay Padhi, Ph.D

The global need to securely derive (instant) insights, have motivated data architectures from distributed storage, to data lakes, data warehouses and lake-houses. In this talk we describe Tag.bio, a next generation data mesh platform that embeds vital elements such as domain centricity/ownership, Data as Products, Self-serve architecture, with a federated computational layer. Tag.bio data products combine data sets, smart APIs, statistical and machine learning algorithms into decentralized data products for users to discover insights using FAIR Principles. Researchers can use its point and click (no-code) system to instantly perform analysis and share versioned, reproducible results. The platform combines a dynamic cohort builder with analysis protocols and applications (low-code) to drive complex analysis workflows. Applications within data products are fully customizable via R and Python plugins (pro-code), and the platform supports notebook based developer environments with individual workspaces. Join us for a talk/demo session on Tag.bio data mesh platform and learn how major pharma industries and university health systems are using this technology to promote value based healthcare, precision healthcare, find cures for disease, and promote collaboration (without explicitly moving data around). The talk also outlines Tag.bio secure data exchange features for real world evidence datasets, privacy centric data products (confidential computing) as well as integration with cloud services

What's hot

Openehr clinical modelling

2 3 open_ehr archetypes observation

openEHR Clinical Workshop - Implementer perspective

openEHR China Localization working group

xudong_lu

The openEHR Revolution Heidelberg 2018

Introduction to openEHR Clinical Workshop MIE2016

Developing openEHR EHRs - core functionalities

openEHR Technical Workshop Intro MIE 2016

2 6 open_ehr archetypes instructions_actions

openEHR Medinfo2015 Brazil Sponsor Session

openEHR: NHS Code4Health RippleOSI and EtherCis

Design and implementation of Clinical Databases using openEHR

openEHR sll-2015final

Enabling Clinical Data Reuse with openEHR Data Warehouse Environments

Luis Marco Ruiz

Bringing Things Together and Linking to Health Information using openEHR

Koray Atalag

openEHR and DIPS Arena: the 'Best of Breed 3.0' revolution

openEHR in China 2019-06

EHRbase, open source openEHR CDR

Introduction of BJU-BMR-RG and use case study of Applying openEHR archetypes ...

E health dublin sept 2016