Use to create a framework for recording answers to pre-defined screening questions about the use of any specified medication or grouping (including classes) of medications.
Examples of medications, groupings and classes of medications are 'alendronic acid', 'anti osteoporosis medications' and 'bisphosphonates', respectively.
Common use cases include, but are not limited to:
- Systematic questioning in any consultation related to patterns of medication usage, for example:
--- Do you use paracetamol? Yes, No, Unknown.
--- Have you been using any anticoagulants the last four weeks? Yes, No, Unknown.
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. In a template, each data element would usually be renamed to the specific question asked. Where value sets have been proposed for common use cases, these can be adapted for local use by using the DV_TEXT or the DV_BOOLEAN datatypes choice to match each specific use case.
The EVENT structure from the reference model can be used to specify whether the questions relate to point in time or over a period of time. Use a separate instance of this archetype to distinguish between a questionnaire recording information about a medication that has been used at any time in the past and information about a medication used within a specified time interval - for example the difference between "Do you use paracetamol?" compared to "Have you been using any anticoagulants 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 the presence of a medication it is recommended that clinical system record and persist the specific details about the medication using a relevant medication archetype, for example the OBSERVATION.medication_statement to record a detailed snapshot view about the actual use of a single specified medication.
Organisation: Nasjonal IKT HF
Email: silje.ljosland.bakke@nasjonalikt.no
Date originally authored: 2018-11-07
Organisation: Nasjonal IKT HF
Email: silje.ljosland.bakke@nasjonalikt.no
Date originally authored: 2018-11-07
- 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: Avgrenet fra: Medication screening questionnaire, Published archetype [Internet]. openEHR Foundation, openEHR Clinical Knowledge Manager [cited: 2023-07-12]. Available from: https://ckm.openehr.org/ckm/archetypes/1013.1.4677
- Original Namespace: org.openehr
- Original Publisher: openEHR Foundation
- Custodian Namespace: org.openehr
- MD5-CAM-1.0.1: 189016652B796FD2552171C762A5602E
- Build Uid: e71a497f-3cff-4a20-ae9d-e7fbd7d2dcc9
- 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: 1.0.3
For example: local information requirements; or additional metadata to align with FHIR.
Include:
All not explicitly excluded archetypes
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 previous use of a class of medications, such as bisphosphonates.
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 using the DV_TEXT or the DV_BOOLEAN datatypes choice to match each specific use case.
Choice of:
Coded Text
Text
Boolean
Use separate instances of this CLUSTER to differentiate between specific medications or groupings of medication.
For example: 'alendronic acid', 'anti osteoporosis medications' or 'bisphosphonates'. Coding of the 'Medication name' with a terminology is preferred, where possible.
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 using the DV_TEXT or the DV_BOOLEAN datatypes choice to match each specific use case. For example an alternative valueset using the DV_TEXT datatype can be: Currently using [The individual currently uses the specific medication either on a regular basis or as required.] Never used [The individual has never used the specific medication.] Used in the past [The individual has used the specific medication in the past, but isn't currently using it.] Unknown [It is not known whether the individual uses or has used the specific medication.]
Choice of:
- Coded Text
- Text
- Boolean
Can be a partial date, for example, only a year.
Choice of:
Date/Time- Text
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 the medication or grouping of medications were used. The specific and intended semantics can be further clarified in a template. For example: the actual date and/or time; the start and stop time for the use of the medication or grouping of medications; the interval of time during which the medication or grouping of medications were used; the duration of the medication or grouping of medications were used; the age of the individual at the time the medication or grouping of medications were used; or the duration of time since it were used. A partial date is valid, using the DV_DATE_TIME data type, to record only a year.
Choice of:
Duration
Interval of Duration
- Text
- Date/Time
Interval of Date/Time
Include:
openEHR-EHR-CLUSTER.dosage.v2 and specialisations
Include:
All not explicitly excluded archetypes
Astrid Askeland, Dips AS, Norway
Silje Ljosland Bakke, Helse Vest IKT AS, Norway (openEHR Editor)
SB Bhattacharyya, Bhattacharyyas Clinical Records Research & Informatics LLP, India
Randi Brendberg, Helse Nord RHF, Norway
Yexuan Cheng, 浙江大学, China
Are Edvardsen, SKDE, Helse Nord RHF, Norway
Alexander Eikrem-Lüthi, Lovisenberg Diakonale Sykehus, Norway
Kåre Flø, DIPS ASA, Norway
Grant Forrest, Lunaria Ltd, United Kingdom
Anca Heyd, DIPS ASA, Norway
Joost Holslag, Nedap, Netherlands
Evelyn Hovenga, EJSH Consulting, Australia
Mikkel Johan Gaup Grønmo, Regional forvaltning EPJ, Helse Nord, Norway
Gunnar Jårvik, Helse Vest IKT AS, Norway
Anjali Kulkarni, Karkinos, India
Kanika Kuwelker, Helse Vest IKT, Norway
Jörgen Kuylenstierna, eWeave AB, Sweden
Liv Laugen, Oslo University Hospital, Norway, Norway
Øygunn Leite Kallevik, Helse Bergen, Norway
Heather Leslie, Atomica Informatics, Australia (openEHR Editor)
Mikael Nyström, Cambio Healthcare Systems AB, Sweden
Jussara Rotzsch, Hospital Alemão Oswaldo Cruz, Brazil
Andre Smitt-Ingebretsen, Sørlandet sykehus HF, Norway
Natalia Strauch, Medizinische Hochschule Hannover, Germany
Norwegian Review Summary, Norwegian Public Hospitals, Norway
John Tore Valand, Helse Bergen, Norway (openEHR Editor)
Marit Alice Venheim, Helse Vest IKT, Norway (openEHR Editor)
Ina Wille, Helse-Vest RHF, Norway
- German: Kim Sommer, Natalia Strauch, Alina Rehberg, Medizinische Hochschule Hannover, sommer.kimkatrin@mh-hannover.de, Strauch.Natalia@mh-hannover.de, rehberg.alina@mh-hannover.de
- Norwegian Bokmål: Silje Ljosland Bakke, John Tore Valand, Helse Vest IKT AS, Helse Bergen, silje.ljosland.bakke@helse-vest-ikt.no, john.tore.valand@helse-bergen.no, john.tore.valand@helse-vest-ikt.no
- Dutch: Martijn van Eenennaam, Nedap Healthcare, martijn.vaneenennaam@nedap.com, PhD
- Catalan: Laura Moral Lopez, Sistema de Salut de Catalunya, lmorallopez@gmail.com
- Spanish (Spain): Laura Moral Lopez, Sistema de Salut de Catalunya, lmorallopez@gmail.com