Use to create a framework for recording answers to pre-defined screening questions about movement to or from one or more geographic
locations outside of the individual’s usual place of residence, for example to survey for possible stay within a disaster area or for possible
exposure to an infectious agent.
Common use cases include, but are not limited to:
- Infectious disease surveillance
- Creating a patient profile in a disease registry
- Systematic questioning in any consultation related to patterns of disease.
The semantics of this archetype are intentionally loose, and querying this archetype would normally only be useful or safe within the context of each specific template. Each data element would usually be renamed in a template to represent the specific question asked. Where value sets have been proposed for common use cases, these can be adapted to align with local requirements by using the DV_TEXT or the DV_BOOLEAN datatypes choice to match each specific use case.
Utilising this framework within a template can enable documentation of a broad range of question/answer pairs such as:
- Have you been overseas in the past 6 weeks? Yes, No, Unsure.
- Have you travelled to Africa in the past 1 year? Yes, No, Unsure.
- Has the patient travelled to an area where malaria is endemic in the past 2 weeks? Yes, No, Unknown.
- Has the patient ever travelled to an active war zone? Yes, No, Unknown.
The EVENT structure from the reference model can be used to specify whether the questions relate to a specific point in time or a period of time. Use a separate instance of this archetype to distinguish between a questionnaire recording information about an investigation or test that has been done at any time in the past and information about an investigation or test done within a specified time interval - for example, the difference between "Have you ever travelled to an area with high radiation activity?" and "Have you travelled to an area with high radiation activity during the last four weeks?".
The source of the information in a questionnaire response may vary in different contexts but can be specifically identified using the 'Information provider' element in the Reference Model.
This archetype has been designed to be used as a screening tool or to record simple questionnaire-format data for use in situations such as a disease registry. If the screening questionnaire identifies a travel activity tha has been carried out, additional details required for persistence as part of a clinical record can be captured using relevant archetypes.
Organisation: Atomica Informatics
Email: heather.leslie@atomicainformatics.com
Date originally authored: 2022-10-21
Organisation: Atomica Informatics
Email: heather.leslie@atomicainformatics.com
Date originally authored: 2022-10-21
- Licence: This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-sa/4.0/.
- Custodian Organisation: openEHR Foundation
- References: Fragebogen zum Reise-Screening, Archetypen-Entwurf [Internet]. openEHR Foundation, OpenEHR International Clinical Knowledge Manager [zitiert am: 28.01.2025]. Abgerufen von: https://ckm.openehr.org/ckm/archetypes/1013.1.4431
- Original Namespace: org.openehr
- Original Publisher: openEHR Foundation
- Custodian Namespace: org.openehr
- MD5-CAM-1.0.1: 61C7497C638C0C808F55166F2059C97E
- Build Uid: 1884ff0b-8cfc-48a8-b850-706f0b732b8a
- Ip Acknowledgements: This artefact includes content from SNOMED Clinical Terms® (SNOMED CT®) which is copyrighted material of the International Health Terminology Standards Development Organisation (IHTSDO). Where an implementation of this artefact makes use of SNOMED CT content, the implementer must have the appropriate SNOMED CT Affiliate license - for more information contact https://www.snomed.org/snomed-ct/get-snomed or info@snomed.org.
- Revision: 1.0.0
For example: local information requirements; or additional metadata to align with FHIR.
Include:
All not explicitly excluded archetypes
In a template, the data element would usually be renamed to the specific question asked. The proposed value set can be adapted for local use by choosing between the DV_TEXT or the DV_BOOLEAN datatypes to match each specific use case.
Choice of:
Coded Text
Text
Boolean
This data element is intended to provide collection context for the question/answer groups when queried at a later date. It is not expected that this data element will be exposed to the individual, but only stored in data. For example: pre-admission screening, the name of the actual questionnaire or screening for potential exposures.
For example: 'Local', 'National', 'International', 'Cruise ship'; or 'War zone'. Coding of the 'Travel activity' with a terminology is preferred, where possible.
Choice of:
- Text
- Coded Text
- National travel [Travel occurred to places or regions within the usual country of residence.]
- International travel [Travel occurred to places or regions within countries other than the usual country of residence.]
In a template, the data element would usually be renamed to the specific question asked. The proposed value set can be adapted for local use by choosing between the DV_TEXT or the DV_BOOLEAN datatypes to match each specific use case.
Choice of:
- Coded Text
- Text
- Boolean
The 'Timing' data element has deliberately been loosely modelled to support the myriad of ways that it can be used in questionnaires to capture when an investigation was carried out. The specific and intended semantics can be further clarified in a template. For example: the actual date and/or time of travel; the departure and return time for the trip; the interval of time during which the individual was travelling; the duration of the trip; the age of the individual at the time of the trip; or the duration of time since the trip occurred. A partial date is valid, using the DV_DATE_TIME data type, to record only a year.
Choice of:
Date/Time- Text
Interval of Date/Time
Interval of Duration
Duration
Include:
All not explicitly excluded archetypes
Include:
All not explicitly excluded archetypes
Silje Ljosland Bakke, Helse Vest IKT AS, Norway (openEHR Editor)
Ivar Berge, Oslo University Hospital, Norway (openEHR Editor)
SB Bhattacharyya, Bhattacharyyas Clinical Records Research & Informatics LLP, India
Hanne Marte Bårholm, Helse Vest IKT, Norway (openEHR Editor)
Gunn Elin Blakkisrud, DIPS ASA, Norway
Aleksander Furnes, Helse Nord IKT, Norway
Ciprian Gerstenberger, Helse Nord IKT, Norway (openEHR Editor)
Heather Grain, Llewelyn Grain Informatics, Australia
Evelyn Hovenga, EJSH Consulting, Australia
Anne K Fossum, OUS, Norway
June Marie Nepstad Knappskog, Helse Nord IKT AS, Norway (openEHR Editor)
Kanika Kuwelker, Helse Vest IKT, Norway (openEHR Editor)
Jörgen Kuylenstierna, eWeave AB, Sweden
Eli Larsen, UNN, Norway (openEHR Editor)
Liv Laugen, Oslo University Hospital, Norway, Norway (openEHR Editor)
Heather Leslie, Atomica Informatics, Australia (openEHR Editor)
Jonas Lyshaug, FSE/ HN IKT, Norway
Olha Nikolaieva, University Hospital Basel, Switzerland
Mikael Nyström, Cambio Healthcare Systems AB, Sweden
Marlene Pérez Colman, Digital Health and Care Wales, United Kingdom
Terje Sagmyr, Helse Vest IKT, Norway (openEHR Editor)
Lena Schell-Majoor, University of Oldenburg, Germany
Norwegian Review Summary, Norwegian Public Hospitals, Norway
Nyree Taylor, CSIRo, Australia
John Tore Valand, Helse Vest IKT, Norway (openEHR Editor)
Karsten Øvretveit, Helse Vest IKT, Norway (openEHR Editor)
- German: Darin Leonhardt, PLRI, PLRI für medizinische Informatik/ Medizinische Hochschule, leonhardt.darin@mh-hannover.de
- Norwegian Bokmål: Silja Mikkola Jensen, Helse Nord, silja.mikkola.jensen@helse-nord.no