Use to record a summary of information about problems or diagnoses found in family members. This information may be used to contribute to the identification of a current health problem, assessment of future risk from familial problems or conditions, or to initiate preventive health activities.
Traditionally the scope of family history has been focused on genetic factors or biomarkers as indicators of risk or potential risk. The scope of this archetype includes both recording of problems or diagnoses that have an inheritable origin as well as those that are not directly inheritable but influenced by the domestic setting, including psychosocial or environmental factors. Examples include exposure to toxins in the family environment, domestic violence, sexual abuse, alcoholism and other addictions.
Non-genetic family members can include adopted or long term fostered children, those related by marriage, or other unrelated individuals who participate in the regular life and influence of the family.
This archetype has been designed to include:
- a narrative overview as free text. This will allow family history details from existing systems to be incorporated as non-structured text; and
- a detailed area focusing on relevant health details about specific family members, including their medical history and biomarkers.
This archetype can be used within many contexts. For example, recording a family history entry within a clinical consultation; populating a Family History List; or to provide a summary statement within a Discharge Summary document.
Additional detail about a family member's specific problem, diagnosis or past procedures can be captured using the EVALUATION.problem_diagnosis or the ACTION.procedure archetype and specifying the 'Subject of Care' as the family member, rather than the subject of the health record.
This archetype can be used as the basis for a Family Pedigree chart of health problems/diagnoses or to support estimations of risk of a condition based on prevalence in the family history or known biomarkers.
It may be necessary to identify each family member specifically and not just by the relationship to the patient. For example, while there will be only one maternal grandmother, there may be many female maternal cousins. This may be required to ensure that a pedigree chart is accurate. It will also enable accurate amendments to the record for each identified family member. If the record is private and will not be shared, for reasons of clarity it may be preferable to record the relative's actual name. If the record, or part of the record, is to be shared, it may be more appropriate for the family member to be identified by a unique label or alias.
Risk of condition based on family history, rejected archetype, openEHR Clinical Knowledge Manager [Internet]. openEHR Foundation. Authored: 2006 04 23. Available at: http://www.openehr.org/ckm/#showArchetype_1013.1.125 (last accessed 2015 03 05).
HL7 Version 3 Standard: Clinical Genomics; Pedigree, Release 1. ANSI/HL7 V3 CGPED, R1-2007. Published 2007 05 07. Available at: http://www.hl7.org/implement/standards/product_brief.cfm?product_id=8 (last accessed 2015 03 05).
Organisation: Ocean Informatics
Email: sam.heard@oceaninformatics.com
Date originally authored: 2010-12-15
Organisation: Ocean Informatics
Email: sam.heard@oceaninformatics.com
Date originally authored: 2010-12-15
- 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: Family History, draft archetype [Internet]. Australia, National eHealth Transition Authority, NEHTA Clinical Knowledge Manager. Authored: 2010 12 15. Available at: http://dcm.nehta.org.au/ckm/#showArchetype_1013.1.927 (last accessed 2015 03 05). Risk of condition based on family history, rejected archetype, openEHR Clinical Knowledge Manager [Internet]. openEHR Foundation. Authored: 2006 04 23. Available at: http://www.openehr.org/ckm/#showArchetype_1013.1.125 (last accessed 2015 03 05). HL7 Version 3 Standard: Clinical Genomics; Pedigree, Release 1. ANSI/HL7 V3 CGPED, R1-2007. Published 2007 05 07. Available at: http://www.hl7.org/implement/standards/product_brief.cfm?product_id=8 (last accessed 2015 03 05).
- Current Contact: Heather Leslie, Ocean Informatics, heather.leslie@oceaninformatics.com
- Original Namespace: org.openehr
- Original Publisher: openEHR Foundation
- Custodian Namespace: org.openehr
- MD5-CAM-1.0.1: E60D3BF80853EA29741A2A0A4C08BD8D
- Build Uid: 83e04805-c355-4bb5-84b4-a0d26666cfa1
- 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 http://www.snomed.org/snomed-ct/get-snomedct or info@snomed.org.
- Revision: 2.0.5-alpha
For example: local information requirements or additional metadata to align with FHIR or CIMI equivalents.
Include:
All not explicitly excluded archetypes
This field can be used to record a summary or the conclusion of all the findings, for unstructured family history information recorded in clinical records, or to import textual data from existing/legacy clinical systems.
If the problem has a genetic predisposition within families, then only genetic relatives should be considered as part of this data. If the problem has psychosocial or environmental effects then non-genetic family members may also be included.
This is the problem for which aggregated data involving all family members will be collected. Coding of the index problem with a terminology is preferred, where possible.
For example: prevalence of the problem/diagnosis in the family.
Include:
openEHR-EHR-CLUSTER.family_
The data elements in this cluster will relate to the individual identified either by name or by alias. Repeat the use of the cluster for other family members.
For example: 'Aunt Susan' or 'Susan Smith'. However, for privacy reasons this may not be appropriate for recording, sharing or public display and in this situation the 'Alias' should be used.
To be used to assist in distinguishing one individual from multiple family members with identical relationships. For example, the label to distinguish one specific sister from three known sisters might be 'eldest sister' 'sister with the red hair' or 'sister #1'.
May include structured detail that identifies the family member more specifically or other details relevant to the family history of the family member.
Include:
openEHR-EHR-CLUSTER.person.v1
Coding of the sex with a terminology is preferred, where possible.
For example: mother, step-father, maternal grandmother, or paternal uncle. Coding of the relationship with a terminology is preferred, where possible and including specification of maternal and paternal as required.
If the 'Relationship' data element uses pre-coordinated terms that include the degree of relationship, then this data element is redundant.
- First degree relative [50% genetic share with the subject - for example, parent, sibling or child.]
- Second degree relative [25% genetic share with the subject - for example, grandparent, aunt, uncle, niece, nephew, grandchildren and half siblings.]
- Third degree relative [12.5% genetic share with the subject - for example, great grandparent, great aunt, great uncle, first cousin, children of nieces and nephews, and great grandchildren.]
If the 'Relationship' data element uses pre-coordinated terms that include the family line, then this data element is redundant.
- Maternal line [Related through the subject's mother.]
- Paternal line [Related through the subject's father.]
Record as 'True' if family member is deceased.
Allowed values: {true}
Age of death can be useful if the problem/diagnosis which caused their death is being considered as a risk factor for the subject of the health record. For example: death of mother from breast cancer at young age significally increases the risk of breast cancer in a daughter.
Date of death may be useful in some situations in which the month of death may trigger decision support or identify groupings of disease. For example: environmental allergens triggering respiratory exaccerbations; or events such as Christmas.
If more detail is required, suggest using EVALUATION.problem_diagnosis or the ACTION.procedure archetype and specifying the 'Subject of Care' as the family member, rather than the subject of the health record.
Coding of the family member's problem or diagnosis with a terminology is preferred, where possible. May link from this data element to a detailed record of a Problem/Diagnosis using the EVALUATION.problem_diagnosis archetype with the Subject of Care set to the family member, not to the patient.
For health problems with multiple occurrences, this describes the first nown occurrence.
Choice of:
Coded Text- Direct cause or closely related [The problem or diagnosis was a direct cause or closely related to the direct cause of death.]
- Unrelated [The problem or diagnosis was unrelated to the cause of death.]
- Indeterminate [It is impossible to determine whether the problem or diagnosis was closely related to the direct cause of death.]
Text
For example: detailed information on BRCA mutations in family members. Note: More data elements will be needed in future to record detailed genetic marker information.
Include:
All not explicitly excluded archetypes
For example: a pedigree chart.
Include:
openEHR-EHR-CLUSTER.media_
Ole Andreas Bjordal, Webmed, Norway
Gunn Anita Skjulhaug, Helse-Bergen HF, Norway
Rita Apelt, Department of Health,NT, Australia
Vebjørn Arntzen, Oslo universitetssykehus HF, Norway (Nasjonal IKT redaktør)
Koray Atalag, University of Auckland, New Zealand
Silje Ljosland Bakke, Helse Vest IKT AS, Norway (openEHR Editor)
John Bennett, NEHTA, Australia
Kristian Berg, Universitetssykehuset Nord Norge, Norway
Lars Bitsch-Larsen, Haukeland University Hospital, Bergen, Norway
Anita Bjørnnes, Helse Bergen, Norway
Terje Bless, Helse Nord FIKS, Norway
Diego Bosca, IBIME group, Spain
Mauricio Botero, Universidad de Caldas, Colombia
Rong Chen, Cambio Healthcare Systems, Sweden
Bjørn Christensen, HUS, Norway
Stephen Chu, Queensland Health, Australia
Lisbeth Dahlhaug, Helse Midt - Norge IT, Norway
Eva Dybvik, Nasjonal kompetansetjeneste for leddproteser og hoftebrudd, Haukeland Universitetssjukehus, Norway
David Evans, Queensland Health, Australia
Shahla Foozonkhah, Ocean Informatics, Australia
Einar Fosse, UNN HF, Norwegian Centre for Integrated Care and Telemedicine, Norway
Samuel Frade, Marand, Portugal
Hildegard Franke, freshEHR Clinical Informatics Ltd., United Kingdom
Tim Garden, NTG Department of Health, Australia
Sebastian Garde, Ocean Informatics, Germany
Jacquie Garton-Smith, Royal Perth Hospital and DoHWA, Australia
Andrew Goodchild, NEHTA, Australia
Gyri Gradek, Senter for medisinsk genetikk og molekylærmedisin, Haukeland Universitetssykehus, Norway
Heather Grain, Llewelyn Grain Informatics, Australia
Elisabeth Gudmestad, Helse Bergen HF, Haukeland Universitetssykehus, Dokumentasjonsavdelingen, Norway
Daniel Habashi, PasientSky AS, Norway
Dag Hanoa, Oslo universitetssykehus, Norway
Sam Heard, Ocean Informatics, Australia (Editor)
Kristian Heldal, Telemark Hospital Trust, Norway
Anca Heyd, DIPS ASA, Norway
Nils-Harald Holsen, Nasjonal IKT HF, Norway
Evelyn Hovenga, EJSH Consulting, Australia
Ann Iren Tellnes Moe, Helse Vest IKT, Norway
Leif Ivar Havelin, Helse Bergen, Norway
Lars Ivar Mehlum, Helse Bergen HF, Norway
Hans Johan Breidablik, Helse Førde HF, Norway
Lars Karlsen, DIPS ASA, Norway
Goran Karlstrom, County Of Värmland, Sweden
Mary Kelaher, NEHTA, Australia
Shinji Kobayashi, Kyoto University, Japan
Nils Kolstrup, Skansen Legekontor og Nasjonalt Senter for samhandling og telemedisin, Norway
Robert L'egan, NEHTA, Australia
Sabine Leh, Helse-Bergen, Norway
Heather Leslie, Atomica Informatics, Australia (openEHR Editor)
Hugh Leslie, Ocean Informatics, Australia
Hallvard Lærum, Oslo Universitetssykehus HF, Norway
Mike Martyn, The Hobart Anaesthetic Group, Australia
Shane McKee, Belfast Health & Social Care Trust, United Kingdom
Ian McNicoll, freshEHR Clinical Informatics, United Kingdom (openEHR Editor)
Chris Mitchell, RACGP, Australia
Lars Morgan Karlsen, DIPS ASA, Norway
Stewart Morrison, NEHTA, Australia
Bengt Nilssen, Sykehuset Innlandet HFq, Norway
Bjørn Næss, DIPS ASA, Norway
Jeremy Oats, NT Health, Australia
Andrej Orel, Marand d.o.o., Slovenia
Lynne Parsons, Primary and Community Health Services, Australia
Anne Pauline Anderssen, Helse Nord RHF, Norway
Vladimir Pizzo, Hospital Sírio Libanês, Brazil
Jodie Pycroft, Adelaide Northern Division of General Practice Ltd, Australia
Norwegian Review Summary, National ICT Norway, Norway
Robyn Richards, NEHTA - Clinical Terminology, Australia
Tanja Riise, Nasjonal IKT HF, Norway
Jussara Rotzsch, UNB, Brazil
Anoop Shah, University College London, United Kingdom
Elizabeth Stanick, Hobart Anaesthetic Group, Australia
Kirsten Steen Kyrkjebø, Helse Vest IKT AS, Norway
Møyfrid Stokke, Helse Vest IKT, Norway
Line Sæle, Nasjonal IKT HF, Norway
John Taylor, NEHTA, Australia
Micaela Thierley, Helse Bergen, Norway
Gordon Tomes, Australian Institute of Health and Welfare, Australia
John Tore Valand, Haukeland Universitetssjukehus, Norway (Nasjonal IKT redaktør, Nasjonal IKT oversettelsesredaktør)
Richard Townley-O'Neill, NEHTA, Australia
Donna Truran, ACCTI-UoW, Australia
Jon Tysdahl, Furst medlab AS, Norway
Ørjan Vermeer, Haukeland Universitetssjukehus, Kvinneklinikken, Norway
Jo Wright, NT Dept of Health, Australia (Editor)
Natalia Strauch, Medizinische Hochschule Hannover, Germany
- German: Sarah Ballout, Natalia Strauch, Medizinische Hochschule Hannover, ballout.sarah@mh-hannover.de, Strauch.Natalia@mh-hannover.de
- Swedish: Emma Malm, sofia Lång Janstad, Karolinska Universitetssjukhuset, Karolinska University Hospital, emma.malm@cambio.se, sofia.lang-janstad@regionstockholm.se
- Norwegian Bokmål: Micaela Thierley, Einar Fosse, John Tore Valand, Silje Ljosland Bakke, Liv Laugen, Oslo University Hospital, Norway, liv.laugen@ous-hf.no
- Portuguese (Brazil): Vladimir Pizzo, Hospital Sirio Libanes - Brazil, vladimir.pizzo@hsl.org.br
- Greek: Erasmia Partafylla, Sigmasoft, c.partafylla@sigmasoft.gr
- French: Vanessa Pereira, Better - Pathfinder, vanessapereira@protonmail.com
- Chinese (PRC): Lin Zhang, Taikang Insurance Group, linforest@163.com, TBD