Editors: {T Beale, S Heard}a, {D Kalra, D Lloyd}b | ||
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Revision: 2.1.0 | Pages: 91 | Date of issue: 12 Apr 2007 |
Keywords: EHR, ADL, health records, modelling, constraints
EHR Extract | ||||||
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EHR | Demographic | Integration | Template OM | |||
Composition | openEHR Archetype Profile | |||||
Security | Common | Archetype OM | ADL | |||
Data Structures | ||||||
Data Types | ||||||
Support |
© 2003-2007 The openEHR Foundation.
The openEHR Foundation is an independent, non-profit community, facilitating the sharing of health records by consumers and clinicians via open-source, standards-based implementations.
Founding | David Ingram, Professor of Health Informatics, |
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Chairman | CHIME, University College London |
Founding | Dr P Schloeffel, Dr S Heard, Dr D Kalra, D Lloyd, T Beale |
Members | |
email: info@openEHR.org web: http://www.openEHR.org |
Rev 2.1.0
© Copyright openEHR Foundation 2001 - 2007 All Rights Reserved
Date of Issue: 12 Apr 2007 Page 2 of 91 Editors:{T Beale, S Heard}, {D Kalra, D Lloyd}
© 2003-2007 The openEHR Foundation. email: info@openEHR.org web: http://www.openEHR.org
Rev 2.1.0
Amendment Record
Issue | Details | Raiser | Completed |
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R E L E A S E 1.0.1 | |||
2.1.0 | CR-000144: Add new type: DV_PROPORTION. CR-000198: Change DV_Date/Time/Duration to have value as attribute. CR-000199: Add normal_range attribute to DV_ORDERED. CR-000200. Correct Release 1.0 typographical errors. Correct DV_ENCAPSULATED.size to abstract in definition table. Correct DV_STATE.value in UML of basic package to be DV_CODED_TEXT. Correct DV_ORDINAL.symbol type to DV_CODED_TEXT in UML diagram for QUANTITY package. Add missing inheritance of Ordered to DV_ORDERED. CR-000205: Convert Date/time constants to a class. CR-000211: Add magnitude_status to DV_QUANTIFIED. CR-000215: Merge DV_PARTIAL_XX date/time classes and move ISO 8601 semantics to Support IM. Remove DV_WORLD_TIME class. CR-000216: Allow mixture of W, D etc in ISO8601 Duration (deviation from standard). CR-000219: Use constants instead of literals to refer to terminology in RM. CR-000221. Add normal_status to DV_ORDERED. Adjusted invariants. CR-000227: Remove DV_QUANTITY_RATIO. CR-000230: Change DV_DATE_TIME.to_quantity to seconds CR-000236: Change use of Character to Octet in DV_MULTIMEDIA. CR-000237: Correct semantics of Quantity and Date/Time types. CR-000240: Allow DV_ORDINAL values to be negative. CR-000247: Add DV_TEMPORAL class to Quantity package. | S Heard S Heard S Heard H Frankel S Heard G Grieve D Lloyd R Chen G Grieve D Lloyd S Heard T Beale S Heard R Chen H Frankel S Heard C Ma G Grieve T Beale G Grieve R Chen H Frankel | 12 Apr 2007 |
R E L E A S E 1.0 | |||
2.0.0 | CR-000176. Make DV_QUANTIFIED accuracy optional. CR-000163. Add identifiers to FEEDER_AUDIT for originating and gateway systems. Added assigner attribute to DV_IDENTIFIER. CR-000121. Improve DV_EHR_URI model to support Xpath style paths. CR-000161. Support distributed versioning. Remove functions from DV_EHR_URI. | S Heard H Frankel T Beale T Beale H Frankel | 01 Feb 2006 |
R E L E A S E 0.96 | |||
R E L E A S E 0.95 | |||
1.9.1 | Improve implementation guidance. DV_ORDINAL.limits type corrected to REFERENCE_RANGE<DV_ORDINAL>. | D Lloyd | 22 Feb 2005 |
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Rev 2.1.0
Issue | Details | Raiser | Completed |
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1.9 | CR-000126. Correct details of partial date/time classes. CR-000112. Add DV_PARTIAL_DATE_TIME class CR-000113. Add DATA_VALUE subtype for identifying real-world entities CR-000118. Make package names lower case. CR-000119. Improve Data types documentation. CR-000102. Make DV_TEXT language and charset optional. | T Beale DSTC DSTC T Beale T Beale DSTC | 09 Dec 2004 |
R E L E A S E 0.9 | |||
1.8 | CR-000023. TERM_MAPPING.match should be coded/enumerated. CR-000069. Correct date/time types statistical descriptions. CR-000046. Rename COORDINATED_TERM to CODE_PHRASE and DV_CODED_TEXT.definition to defining_code. CR-000084. Rename DV_COUNTABLE to DV_COUNT. CR-000090. Make TERM_MAPPING.purpose optional. CR-000091. Correct anomalies in use of CODE_PHRASE and DV_CODED_TEXT. CR-000094. Add lifecycle state attribute to VERSION; correct DV_STATE. CR-000095. Remove property attribute from Quantity package. Formally validated using ISE Eiffel 5.4. | G Grieve A Goodchild T Beale DSTC DSTC T Beale DSTC DSTC, S Heard | 09 Mar 2004 |
1.7.9 | CR-000066. Make DV_ORDERED.normal_range a function. Correct UML for DV_QUANTITY. | Z Tun | 10 Nov 2003 |
1.7.8 | CR-000053. Make DV_ORDINAL.limits a function. CR-000054. Move DV_QUANTIFIED.is_normal to DV_ORDERED CR-000055. Redefine DV_ORDERED.less_than as infix function '<'. | T Beale T Beale T Beale | 02 Nov 2003 |
1.7.7 | CR-000041. Visually differentiate primitive types in openEHR documents. CR-000034. State representation of date/time classes to be ISO8601. CR-000052. Change DV_DURATION.sign to prefix "-" operation. CR-000042. Make DV_ORDINAL.rubric a DV_CODED_TEXT; type attribute not needed. | D Lloyd, DSTC, T Beale | 26 Oct 2003 |
1.7.6 | CR-000013. Rename key classes, according to CEN ENV 13606. CR-000026. Rename DV_QUANTITY.value to magnitude. CR-000031. Change abstract NUMERIC to DOUBLE in DV_QUANTITY.value. | S Heard, D Kalra, T Beale, A Goodchild, Z Tun | 01 Oct 2003 |
1.7.5 | CR-000022. Code TERM_MAPPING.purpose. | G Grieve | 20 Jun 2003 |
1.7.4 | CR-000020. Move VERSION.charset to DV_TEXT, territory to TRANSACTION. Remove VERSION.language. | A Goodchild | 10 Jun 2003 |
1.7.3 | DV_INTERVAL now inherits from INTERVAL to avoid duplicating semantics. (Formally validated). | T Beale | 25 Mar 2003 |
Date of Issue: 12 Apr 2007 Page 4 of 91 Editors:{T Beale, S Heard}, {D Kalra, D Lloyd}
Rev 2.1.0
Issue | Details | Raiser | Completed |
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1.7.2 | Minor corrections to diagrams in Text package. Improved heading structure, package naming. Corrected error in TEXT package diagram. Replaced TEXT_FORMAT_PROPERTY class with string attribute of same form. Made MULTIMEDIA.media_type mandatory. (Formally validated). | T Beale, Z Tun | 21 Mar 2003 |
1.7.1 | Moved definitions and assumed types to Support Reference Model. No semantic changes. | T Beale | 25 Feb 2003 |
1.7 | Formally validated using ISE Eiffel 5.2. CR-000001. Review of Data Types specification. Made pluralities of Terminology name definitions (sect 3.2.1) consistent. Corrected types of DV_ENCAPSULATED.language, charset, DV_MULTIMEDIA.integrity_check_algorithm, compression_algorithm, media_type. Corrected pluralities of Terminology name definitions (sect 3.2.1). Corrected invariants of DV_ENCAPSULATED, DV_MULTI_MEDIA, DV_QUANTITY, DV_CODED_TEXT, DV_TEXT, DV_INTERVAL, TERM_MAPPING. Corrected DV_TEXT.formatting; added TERM_MAPPING validity function. Made DV_ORDINAL.limits an attribute. Removed TERM_MAPPING.source; moved COORDINATED_TERM.language to DV_TEXT; changed type to COOORDINATED_TERM. Corrected time specification classes. | Z Tun, T Beale | 17 Feb 2003 |
1.6.1 | Rome CEN TC 251 meeting. Updates to HL7 comparison text. DV_DATE now inherits from DV_CUSTOMARY_QUANTITY. | S Heard, T Beale | 27 Jan 2003 |
1.6 | Sam Heard complete review. Changed constant terminology defs to runtime-evaluated set; removed DV_PHYSICAL_DATA. Added new chapter for generic implementation guidelines, and new section for assumed types. Post-conditions moved to invariants: DV_TEXT.value, DV_ORDERED.is_simple, DV_PARTIAL_DATE.probable_date, possible_dates, DV_PARTIAL_TIME.probable_time, possible_times. Minor updates to HL7 comparison text. Added explanation to HL7 section. | S Heard, T Beale | 13 Dec 2002 |
1.5.9 | Minor corrections: DV_ENCAPSULATED; DV_QUANTITY.units defined to be String; changed COORDINATED_TERM class (but semantically equivalent). | T Beale | 10 Nov 2002 |
1.5.8 | Changed name of LINK package to URI. Major update to Text cluster classes and explanation. Updated HL7 data type comparison. | T Beale, D Kalra, D Lloyd, M Darlison | 1 Nov 2002 |
1.5.7 | DV_TEXT_LIST reverted to TEXT_LIST. DV_LINK no longer a data types; renamed to LINK and moved to Common RM. Link package renamed to “URI”. | S Heard, Z Tun, T Beale, D Kalra, M Darlison | 18 Oct 2002 |
1.5.6 | Rewrite of TIME_SPECIFICATION parse specs. Adjustments to DV_ORDINAL. | T Beale | 16 Sep 2002 |
Editors:{T Beale, S Heard}, {D Kalra, D Lloyd} Page 5 of 91 Date of Issue: 12 Apr 2007
Rev 2.1.0
Issue | Details | Raiser | Completed |
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1.5.5 | Timezone not allowed on pure DV_DATE in ISO8601. | T Beale, S Heard | 2 Sep 2002 |
1.5.4 | Moved DV_QUANTIFIED.units and property attributes to DV_QUANTITY. Introduced DV_WORLD_TIME.to_quantity. Added fractional_second to DV_TIME, DV_DATE_TIME, DV_DURATION. | T Beale, S Heard | 29 Aug 2002 |
1.5.3 | Further corrections - removed derived ‘/’ markers; renamed TERM_MAPPING.granularity to match. Improved explanation of DV_ORDINAL. DV_QUANTIFIED.units is now a DV_PARSABLE. REFERENCE_RANGE.meaning is now a DV_TEXT. DV_ENCAPSULATED.uri is now a DV_URI. DV_LINK.type is now a DV_TEXT. Detailed review by Zar Zar Tun (DSTC). | T Beale, S Heard, P Schloeffel, D Lloyd, Z Tun | 20 Aug 2002 |
1.5.2 | Further corrections - removed derived ‘/’ markers; renamed TERM_MAPPING.granularity to match. | T Beale, D Lloyd, S Heard | 15 Aug 2002 |
1.5.1 | Minor corrections. | T Beale, S Heard | 15 Aug 2002 |
1.5 | Rewrite of section describing text types; addition of new attribute DV_CODED_TEXT.mappings. Removal of TERM_REFERENCE.concept_code. | T Beale, S Heard | 1 Aug 2002 |
1.4.3 | Minor changes to text. Corrections to DV_CODED_TEXT relationships. Made DV_INTERVAL.lower_unbounded and DV_INTERVAL.upper_unbounded functions. | T Beale, Z Tun | 16 Jul 2002 |
1.4.2 | DV_LINK.meaning changed to DV_TEXT (typo in table). Added abstract class DV_WORLD_TIME. | T Beale, D Lloyd | 14 Jul 2002 |
1.4.1 | Changes to DV_ENCAPSULATED, DV_PARSABLE invariants. | T Beale Z Tun | 10 Jul 2002 |
1.4 | DV_ENCAPSULATED. text_equivalent renamed to DV_ENCAPSULATED.alternate_text. Added invariant for QUANTITY.precision. | T Beale, D Lloyd | 1 Jul 2002 |
1.3 | Added timezone to DV_TIME and DV_DATE_TIME and sign to DV_DURATION; added linguistic_order to TERM_RELATION; added as_display_string and as_canonical_string to all types. Added DV_STATE.is_terminal. Renamed TERM_TEXT as CODED_TEXT. | T Beale, D Lloyd | 30 Jun 2002 |
1.2 | Minor corrections to Text package. | T Beale | 15 May 2002 |
1.1 | Numerous small changes, including: term equivalents, relationships and quantity reference ranges. | T Beale, D Lloyd, D Kalra, S Heard | 10 May 2002 |
1.0 | Separated from the openEHR Reference Model. | T Beale | 5 May 2002 |
The work reported in this paper has been funded by a number of organisations, including The University College, London; The Cooperative Research Centres Program through the Department of the
Date of Issue: 12 Apr 2007 Page 6 of 91 Editors:{T Beale, S Heard}, {D Kalra, D Lloyd}
© 2003-2007 The openEHR Foundation. email: info@openEHR.org web: http://www.openEHR.org
Rev 2.1.0
Prime Minister and Cabinet of the Commonwealth Government of Australia; Ocean Informatics, Australia.
Editors:{T Beale, S Heard}, {D Kalra, D Lloyd} Page 7 of 91 Date of Issue: 12 Apr 2007
© 2003-2007 The openEHR Foundation. email: info@openEHR.org web: http://www.openEHR.org
Rev 2.1.0
Date of Issue: 12 Apr 2007 Page 8 of 91 Editors:{T Beale, S Heard}, {D Kalra, D Lloyd}
© 2003-2007 The openEHR Foundation. email: info@openEHR.org web: http://www.openEHR.org
Rev 2.1.0
Table of Contents
Copyright Notice ...................................................................................................2 Amendment Record ................................................................................................3 Acknowledgements .................................................................................................6 Table of Contents ....................................................................................................9
1 Introduction............................................................................ 13
2 Background ............................................................................ 15
3 Introduction............................................................................ 17
4 Basic Package ......................................................................... 18
4.2.1 DATA_VALUE Class ....................................................................20
4.2.2 DV_BOOLEAN Class...................................................................20
4.2.3 DV_STATE Class ..........................................................................21
4.2.4 DV_IDENTIFIER Class................................................................21
5 Text Package........................................................................... 23
5.1.4 Meaning Modification ...................................................................26
5.1.4.4 Representation of Meaning-Modifying Terms ...........................................27
5.1.5.3 More Specific Mappings (Narrower Terms) ...............................................29
5.1.5.4 The Unified Medical Language System (UMLS) .......................................29
5.1.6 Language Translations...................................................................30
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Rev 2.1.0
5.2.1 DV_TEXT Class ........................................................................... 30
5.2.2 TERM_MAPPING Class .............................................................. 32
5.2.3 CODE_PHRASE Class.................................................................33
5.2.4 DV_CODED_TEXT Class ...........................................................34
5.2.5 DV_PARAGRAPH Class.............................................................. 34
6 Quantity Package................................................................... 37
6.2.1 DV_ORDERED Class................................................................... 43
6.2.2 DV_INTERVAL<T : DV_ORDERED> Class.............................. 45
6.2.3 REFERENCE_RANGE<T:DV_ORDERED> Class .................... 45
6.2.4 DV_ORDINAL Class ................................................................... 46
6.2.5 DV_QUANTIFIED Class ............................................................. 47
6.2.6 DV_AMOUNT Class....................................................................48
6.2.7 DV_QUANTITY Class.................................................................49
6.2.9 DV_COUNT Class........................................................................ 51
6.2.10 DV_PROPORTION Class............................................................. 52
6.2.11 PROPORTION_KIND Class ........................................................ 53
6.2.12 DV_ABSOLUTE_QUANTITY Class..........................................54
7 Date Time Package ................................................................ 55
7.2.1 DV_TEMPORAL Class................................................................58
7.2.2 DV_DATE Class ........................................................................... 58
7.2.3 DV_TIME Class............................................................................ 59
7.2.4 DV_DATE_TIME Class ...............................................................60
7.2.5 DV_DURATION Class.................................................................61
8 Time_specification Package .................................................. 63
8.2.1 DV_TIME_SPECIFICATION Class.............................................64
8.2.2 DV_PERIODIC_TIME_SPECIFICATION Class........................65
8.2.2.2 Event-linked Periodic Time Specification Syntax ......................................66
8.2.3 DV_GENERAL_TIME_SPECIFICATION Class........................66
9 Encapsulated Package ........................................................... 69
Date of Issue: 12 Apr 2007 Page 10 of 91 Editors:{T Beale, S Heard}, {D Kalra, D Lloyd}
© 2003-2007 The openEHR Foundation. email: info@openEHR.org web: http://www.openEHR.org
9.2.1 DV_ENCAPSULATED Class.......................................................70
9.2.2 DV_MULTIMEDIA Class ............................................................71
9.2.3 DV_PARSABLE Class..................................................................73
10 Uri Package ............................................................................ 75
10.3.1 DV_URI Class...............................................................................76
10.3.2 DV_EHR_URI Class.....................................................................77
11 Implementation Strategies .................................................... 79
11.2 Quantities and Ordered_numeric .........................................................79
12 Comparison with HL7v3 Types ............................................ 81
12.2.4 Treatment of Inbuilt Types ............................................................82
12.2.5 Use of Null Markers ......................................................................83
12.2.6 Terminology Approach..................................................................86
12.2.7 Date/Time Approach......................................................................86
12.2.8 Time Specification Types ..............................................................86
12.2.9 Type Conversions ..........................................................................87
A References............................................................................... 89
Rev 2.1.0
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Rev 2.1.0
Date of Issue: 12 Apr 2007 Page 12 of 91 Editors:{T Beale, S Heard}, {D Kalra, D Lloyd}
© 2003-2007 The openEHR Foundation. email: info@openEHR.org web: http://www.openEHR.org
Data Types Information Model Introduction Rev 2.1.0
This document defines the openEHR Data Types Information Model, used throughout the openEHR Reference Model. The intended audience includes:
Prerequisite documents for reading this document include:
This document is under development, and is published as a proposal for input to standards processes and implementation works.
This document is available at http://svn.openehr.org/specification/TAGS/Release 1.0.1/publishing/architecture/rm/data_types_im.pdf .
The latest version of this document can be found at http://svn.openehr.org/specifica tion/TRUNK/publishing/architecture/rm/data_types_im.pdf .
Blue text indicates sections under active development.
Areas where more analysis or explanation is required are indicated with “to be continued” paragraphs like the following:
To Be Continued: more work required
Reviewers are encouraged to comment on and/or advise on these paragraphs as well as the main content. Please send requests for information to info@openEHR.org. Feedback should preferably be provided on the mailing list openehr-technical@openehr.org, or by private email.
Conformance of a data or software artifact to an openEHR Reference Model specification is determined by a formal test of that artifact against the relevant openEHR Implementation Technology
Editors:{T Beale, S Heard}, {D Kalra, D Lloyd} Page 13 of 91 Date of Issue: 12 Apr 2007
© 2003-2007 The openEHR Foundation. email: info@openEHR.org web: http://www.openEHR.org
Introduction Data Types Information Model Rev 2.1.0
Specification(s) (ITSs), such as an IDL interface or an XML-schema. Since ITSs are formal, automated derivations from the Reference Model, ITS conformance indicates RM conformance.
Date of Issue: 12 Apr 2007 Page 14 of 91 Editors:{T Beale, S Heard}, {D Kalra, D Lloyd}
© 2003-2007 The openEHR Foundation. email: info@openEHR.org web: http://www.openEHR.org
Data Types Information Model Background Rev 2.1.0
The data type specification presented here defines the clinical/scientific data types which are used in other openEHR models. Harmonisation of data types between information models used by related services in a health information infrastructure is essential to reducing the conversion work and potential for errors between these services. Accordingly, the openEHR data type specification is intended to work not only for the EHR, but also for other models defined by openEHR, such as the openEHR demographic and terminological models.
The types described here have been derived from data types used in the GEHR [14], Synapses and SynEx [10], CEN 13606 [11] , [13] and the HL7v3 [15] reference models.
Over and above the need to satisfy the functional requirements of clinical data, three concerns have driven the design of the openEHR data types:
The first of these has led to models which try to clearly convey the semantics of types required by the clinical domain. The use of constraints (pre- and post-conditions and class invariants) and a comprehensible class structure ensures formal self-consistency, correct type-substitutability and implementability in object-oriented formalisms. Types have been designed so as not to clash with norms of object-oriented languages and libraries, in particular, class names and the inbuilt types. Accordingly, all types presented here have a logical name commencing with ‘DV_’, ensuring that there is no clash with a type in the implementation formalism, hence the type DV_DATEpresented here will not be confused with the type DATE which appears in many programming languages or libraries.
Object-oriented languages which have been considered include IDL, C++, Java, C#, Eiffel, Delphi and Python. Each of these languages obeys some variant of the well-known semantics of classes, encapsulation, typing and inheritance. The data types described here follow the tenets of object-orientation defined in UML most closely, while being careful not to invalidate their implementation in any language. The models have all been validated by implementation in the Eiffel language, the closest available semantic fit for UML, and currently the most powerful of mainstream object-oriented formalisms.
Implementability in XML-schema has also been an important design criterion, and the current data types remove many of the problems which the GEHR and CEN data types presented for XML-schema. There has been no attempt to support XML-DTD, since it has no type system, and cannot reliably be reasoned about in an object-oriented way.
To simplify implementation in all object-oriented formalisms, including IDL, programming languages and XML-schema, multiple inheritance has generally been avoided (where it is used, only onr branch corresponds to substitutability). Generic classes have been used, since they significantly clarify the model. Type genericity is available in Java, C#, Eiffel, C++, and some othre languages. For languages not having it, there is a well-known transformation from models containing generic classes to classes for non-generic types systems (see for example [3]).
Editors:{T Beale, S Heard}, {D Kalra, D Lloyd} Page 15 of 91 Date of Issue: 12 Apr 2007
© 2003-2007 The openEHR Foundation. email: info@openEHR.org web: http://www.openEHR.org
Background Data Types Information Model Rev 2.1.0
Implementability in relational databases has also been considered, and appears relatively straightforward, since only the data view of the types needs to be represented. Many implementations are likely to use only a single String or XML string to represent each entire data instance, which significantly simplifies things.
Four other type systems for clinical data, namely the GEHR data types, the HL7 v3 data types, the CEN 13606 data item types, and the Corbamed data types were carefully scrutinised in order to ensure a) that all needed types were covered in the openEHR specification, and b) that data conversion will be possible. Concepts from all three are cross-referenced throughout this specification where possible.
Because the HL7v3 data type specification is a widely available and comprehensive specification for clinican data types, particular attention has been paid to incorporating its semantics, as well as fixing errors or shortcomings. While there are differences both in design approach and in detail, a significant debt must be recognised to the authors of this work, from which many ideas in the present specification were drawn. A detailed discussion is found under Comparison with HL7v3 Types on page 81 .
Date of Issue: 12 Apr 2007 Page 16 of 91 Editors:{T Beale, S Heard}, {D Kalra, D Lloyd}
© 2003-2007 The openEHR Foundation. email: info@openEHR.org web: http://www.openEHR.org
Data Types Information Model Introduction Rev 2.1.0
This specification describes a set of types suitable for use in scientific, clinical and related information structures. In order for such types to exist, a set of primitive types is assumed, namely Integer, Real, Boolean, Character, Octet, String, List<T>, Set<T>, and Array<T>. These have standard definitions in the OMG object model used in UML, OCL, and are available in almost all type systems. The exact assumptions are described in the openEHR Support Information Model. A number of symbolic definitions (similar to constants in programming) are also described in the Support IM.
The data types described here are named with the class prefix “DV_”, and inherit from the class DATA_VALUE. They have two distinct uses in reference models. Firstly, they may be used as ‘data values’ in reference model structures wherever the DATA_VALUE class appears, for example, in the EHR Reference Model via the ELEMENT.value attribute. Additionally, specific subtypes of the data types described here can also be used as attribute types in other classes in reference models, such as date/times, coded terms and so on. The difference is that in the former case, only subtypes of DATA_VALUE may be used, whilst in the latter case, other types may be used as well, from the assumed set of basic types.
The package structure of the openEHR data types is illustrated in FIGURE 1.
DATA_VALUE
data_types basic
text time_specification uri
encapsulated
date_time
FIGURE 1 openehr.rm.data_types Package
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Basic Package Data Types Information Model Rev 2.1.0
The data_types.basic package, illustrated in FIGURE 2, contains types for the concepts of bi state, state (in a state machine) and real-world entity identifiers (see the openEHR Common IM for a discussion on identifier types).
OPENEHR_DEFINITIONS (support.definition)
basic | ||
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DATA_VALUE | ||
DV_BOOLEAN value[1]: Boolean | DV_STATE value[1]: DV_CODED_TEXT is_terminal[1]: Boolean | DV_IDENTIFIER issuer[1]: String assigner[1]: String id[1]: String type[1]: String |
FIGURE 2 rm.data_types.basic Package
One of the most basic types of data is boolean or bi-state data. The need here is for a type which both includes a boolean value, and which inherits from the type DATA_VALUE, enabling it to be used as an ELEMENT.value.
A type is required to represent state values of a state machine. In a simple system of data types, a simple integer would appear sufficient to perform this job. However, in an archetyped framework, a distinct type is required, so that it can be archetyped not by the constraints used for integers, but by a state machine definition instead. The type DV_STATE is provided for this purpose. An example of a state machine which models the lifecycle of a medication order is illustrated in FIGURE 3 . This definition would appear in an archetype; the values of a DV_STATE object are then restricted to the values of the states in the definition.
Real world entities (RWEs) such as people, car engines, invoices, and appointments may all be assigned identifiers. Although many of these are designed to be unique within a jurisdiction or issuing space, they are often not, due to data entry errors, bad design (ids which are too small or incorporate some non-unique characteristic of the identified entities), bad process (e.g. non-synchronised id issuing points); identity theft (e.g. via theft of documents of proof or hacking). In general, while some real world identifiers (RWIs) are “nearly unique”, none can be guaranteed so. Therefore, from a strict computatoinal point of view, RWIs are not treated as reliable identifiers, but as attributes of their owning objects, in the same ways as names and addresses for example.
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Data Types Information Model Basic Package Rev 2.1.0
start
FIGURE 3 Example State Machine for Medication Orders
Examples of RWE identifiers which are intended to be unique within the space of the issuing authority or organisation include:
The defining logical characteristic of RWE ids is that they continue to identify the entities in question, regardless of how they change in time; for example a social security number does not change when someone changes their hair colour or even their gender (both of which attributes may be recorded in the database). In general it should be the case that if two RWE ids are equal, they refer to the same RWE.
At a practical level, RWE identifiers differ from information entity (IE) identifiers in that the former are generally not assigned by the computing infrastructure that uses them - that is to say, in the production computing system, such identifiers are no different from other characteristics of the entity, such as names or addresses.
The model defined here in the DV_IDENTIFIER class allows the recording of three things as part of identifying an item of interest:
In addition, the type of item being identified can also be recorded.
See the Support IM specification for a further discussion of RWEs and IEs, and the definition of IEs in openEHR.
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Basic Package Data Types Information Model Rev 2.1.0
4.2.1 DATA_VALUE Class
CLASS | DATA_VALUE (abstract) |
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Purpose | Serves as a common ancestor of all data value types in openEHR models. |
ISO 18308 | STR 3.1 - 3.13 |
CEN | The Data_Item class in CEN is a mixture of DATA_VALUE and ELEMENT in openEHR. |
OMG HDTF | COAS::ObservationValue |
HL7 | DataValue (ANY) |
Invariants |
4.2.2 DV_BOOLEAN Class
CLASS | DV_BOOLEAN | |
---|---|---|
Purpose | Items which are truly boolean data, such as true/false or yes/no answers. | |
Use | For such data, it is important to devise the meanings (usually questions in subjective data) carefully, so that the only allowed results are in fact true or false. | |
MisUse | The DV_BOOLEAN class should not be used as a replacement for naively modelled enumerated types such as male/female etc. Such values should be coded, and in any case the enumeration often has more than two values. | |
ISO 18308 | (none) | |
CEN | Not provided as a subtype of Data Item | |
Synapses | A special use of the Numeric class is defined to represent the Boolean data type, limiting the permitted values to zero or one. | |
HL7 | Boolean (BL) type. HL7 also allows NULL values. See section 12.2.5 on page 83. | |
Inherit | DATA_VALUE | |
Attributes | Signature | Meaning |
1..1 | value: Boolean | Boolean value of this item. |
Invariants | Value_exists: value /= Void |
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Data Types Information Model Basic Package Rev 2.1.0
4.2.3 DV_STATE Class
CLASS | DV_STATE | |
---|---|---|
Purpose | For representing state values which obey a defined state machine, such as a variable representing the states of an instruction or care process. | |
Use | DV_STATE is expressed as a String but its values are driven by archetype-defined state machines. This provides a powerful way of capturing stateful complex processes in simple data. | |
ISO 18308 | (none) | |
CEN | The Component Annotation Life Cycle was intended to permit architectural components to include a reference to this aspect of state. | |
Synapses | The Element class includes an attribute LifeCycle to indicate the lifecycle of an instruction or action, with permitted values taken from the ENV13606-2 Domain Termlist Component Annotation of the same name. | |
Inherit | DATA_VALUE | |
Attributes | Signature | Meaning |
1..1 | value: DV_CODED_TEXT | The state name. State names are determined by a state/event table defined in archetypes, and coded using openEHR Terminology or local archetype terms, as specified by the archetype. |
1..1 | is_terminal: Boolean | Indicates whether this state is a terminal state, such as “aborted”, “completed” etc from which no further transitions are possible. |
Invariants | value_exists: value /= Void Is_terminal_exists: is_terminal /= Void |
4.2.4 DV_IDENTIFIER Class
CLASS | DV_IDENTIFIER |
Purpose | Type for representing identifiers of real-world entities. Typical identifiers include drivers licence number, social security number, vertans affairs number, prescription id, order id, and so on. |
Use | DV_IDENTIFIER is used to represent any identifier of a real thing, issued by some authority or agency. |
Misuse | DV_IDENTIFIER is not used to express identifiers generated by the infrastructure to refer to information items; the types OBJECT_ID and OBJECT_REF and subtypes are defined for this purpose. |
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CLASS | DV_IDENTIFIER | |
---|---|---|
ISO 18308 | (none) | |
GEHR | GEHR had a type PHYSICAL_DATA for the purpose of recording locations of items, such as specimen bottles. | |
Inherit | DATA_VALUE | |
Attributes | Signature | Meaning |
1..1 | issuer: String | Authority which issues the kind of id used in the id field of this object. |
1..1 | assigner: String | Organisation that assigned the id to the item being identified. |
1..1 | id: String | The identifier value. Often structured, according to the definition of the issuing authority’s rules. |
1..1 | type: String | The identifier type, such as “prescription”, or “SSN”. One day a controlled vocabulary might be possible for this. |
Invariants | issuer_valid: issuer /= Void and then not issuer.is_empty assigner_valid: assigner /= Void and then not assigner.is_empty id_valid: id /= Void and then not id.is_empty type_valid: type /= Void and then not type.is_empty |
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Data Types Information Model Text Package Rev 2.1.0
The data_types.text package contains classes for representing all textual values in the health record, including plain text, coded terms, and narrative text. It is illustrated in FIGURE 4.
DATA_VALUE
coded by openEHRcoded by openEHR
(rm.data_types.basic)
codeset “languages”
codeset “character sets”
DV_PARAGRAPH
coded by openEHR Terminology, group
“term mapping purpose”
FIGURE 4 rm.data_types.text Package
The sections below describe the requirements of text data types. Two overriding principles should be noted at the outset with regard to text.
Terminology Ids are likely to be of various types.
1. Terminology_Id = “local”: this constant value means that the origin of allowable values is described within the archetype. This is coded to allow translation. The local archetype then only needs the set of codes and the local translation. The archetype may contain a translation table if required.
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Narrative text items are used in the EHR in a number of cases, including:
While narrative text items themselves are not themselves coded, they may have code phrases associ ated with them, as described below under Mappings, and may be mixed within a paragraph with coded items.
Textual entities available in a terminology service are used in the health record to enable processing, from simple queries to decision support. Reasons for using terminology include the following.
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A basic requirement for interoperability of text items, coded using terms (i.e. where the text is the official rubric for the code), is that both the rubric and the code (or ‘code-phrase’) must be recorded, to ensure the originally intended text is retained for receivers of EHR information who do not have access to the terminologies used at the origin. However, where a terminology service is available, the key can be used to unambiguously locate the string value of the term, and can also be used to find translations in other languages. (Note that these comments do not apply to mappings, which are described below).
In some terminologies, there are semantic networks of links emanating from most coded terms, which classify them or relate them to other terms. Such links provide a means for decision support to make inferences about specific things found in the record. For instance if the term “leukaemia” is found, queries to the terminology service can be made in order to deduce that the patient has both a “cancer” and a “disease of the immune system” (assuming leukaemia is classified under these more general terms in the terminology).
This specification assumes the existence of a terminology service which is responsible for interrogating actual terminologies and performing validated coordination of terms, i.e. creating combinations deemed valid by the underlying source terminology, potentially without even assigning a new code to the result. All validated coordination is carried out inside the terminology service, and any “term” made available by the service is already ‘coordinated’. The difference between ‘pre-coordinated’ and ‘post-coordinated’ terms is that the former have a single code, whereas the latter have a code phrase, or expression that is interpretable by the terminology. For example, the coordination “foot, left” (a shorthand way of writing the relationship “foot has-laterality left”) could be created by the terminology service from the source terms “foot”, “left” and “has-laterality” from a terminology such as SNOMED. Any such coordination must be valid within the source terminology, i.e. correspond to valid relationships defined therein.
The class DV_CODED_TEXTdescribed here captures the association of two things:
The class CODE_PHRASE.code_string records a key, in the form of arguments to some retrieval function in the terminology service interface.
The semantics attached to coordinations of terms may differ. Two categories of coordination described in the literature are ‘qualification’ and ‘modification’. A common definition of the first is that “qualification narrows meaning” - i.e. creates a new term whose possible real world instances are within the set denoted by the original root term. Modification on the other hand changes the meaning of a root term. Various cases are described below under Meaning Modification. Both coordination types are assumed to be managed by the terminology service.
Coded terms may also be mapped to terms from other terminologies, which may be intended as equivalents, classifiers, or something in between. The section below on Mappings deals with these.
All atomic text items are either instances of the type DV_TEXT or of DV_CODED_TEXT. The former allows the expression of text with optional formatting and hyperlinking. The latter additionally connects the text value to a key in the terminology service, with the implication that the key refers to a terminological entity lexically and semantically identical to the text value.
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The model of DV_CODED_TEXT is designed to capture the actual coded term chosen by the user or software at runtime; it is implicitly assumed that this includes whichever synonym (term of equivalent meaning from the same terminology) was chosen, for terminologies supporting synonyms, and any coordination of underlying distinct terms. A DV_CODED_TEXT instance can only be used if the final textual value chosen by the user is lexically identical to the rubric returned by the terminology service for the key; if the user makes even the slightest change, the identity of rubric / key is lost, and a mapping (see Mappings on page 28 ) should be used instead.
The type DV_TEXT should be used wherever a coded or non-coded text item is allowed, while the type DV_CODED_TEXT should be used wherever a text item must be coded.
The type DV_PARAGRAPH allows larger tracts of text to be built up from lists of DV_TEXT instances,
i.e. instances of DV_TEXT and DV_CODED_TEXT, as illustrated in FIGURE 5.
terminology_id = snomed-ct
CODE_PHRASE
code_string = nnnnnnn
FIGURE 5 A DV_PARAGRAPH
Qualification is the process of making a term more specific through the post-coordination of additional terms. It occurs when a terminology defines relationships between a primary term and other terms that qualify the primary. For example a coordination using the term “bronchitis” which creates a qualified term might be “acute bronchitis”; all real world instances of the latter are also instances of the former.
Terms that change the meaning of other terms are often known as “modifiers”. The difference between modification and qualification is that modifiers change the meaning so that the modifed term as a whole does not refer to instances of the unmodified term. We describe below the particular types of modifiers and how they are represented using the text data types.
One class of modifers is exemplified by the addition of words like “risk of”, “fear of”, “history of” and so on. These are sometimes called mode-changing terms, since they change the “mode” of the root term from the present to the past (“history of”), a potential future (“risk of”) or some other alternate reality. Terms which are modified in this way should never be matched in queries searching for the root term; for example, a query for “coronary diease” (of the patient) should not match “family history of coronary disease”.
There are many terms whose meaning is changed by the context in which they are stated, such as within a certain kind of note or test result. Consider the following:
• a blood sugar level after a 75gm oral loading has a different meaning than a fasting blood sugar;
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Data Types Information Model Text Package Rev 2.1.0
Negation is a special kind of mode change and has been a serious design challenge in the past, because modifiers like “not” or “no” only make sense when attached to some terms, and create nonsensical values or ambiguities by arbitrarily association with other terms.
Rather than provide explicit features for representing modifier terms within DV_CODED_TEXT, the general principle underlying representation of all post-coordinations other than qualifications, is that a higher-level, archetyped structure such as an ENTRY(defined in the EHR RM), is a minimal indivisible unit of information. Such higher-level entities can have internal structure, and it is possible (and desirable) to achieve the effect of combinations of terms through this structure. In the case of ENTRY, it will be via structuring of CLUSTER/ELEMENT objects. The general rule is: to obtain the full meaning of any terms found in the record, all of the node names in any ENTRY (coded or not) must be considered from the root to the relevant leaf. Conversely, the “final” meaning of any term in the record cannot be known in isolation from the rest of the terms in the structure.
Accordingly, the concept “family history of coronary disease” is represented as an ENTRY whose root is named (for example) “subject family history”, and which includes further structure, which may be in greater of lesser detail; the coded term “coronary disease” would appear somewhere in this structure. The actual structure is completely defined by appropriate archetypes. Contrary to some perceptions, there is no general way to represent concepts such as “family history of coronary disease”, since it will vary depending on how much detail is recorded. Where some GPs routinely record just the simplest form, others may record the details of which family members had heart problems and exactly what they were.
The same approach is used for context-dependent terms. Archetypes defining contexts such as “planned procedures” or “differential diagnosis” will use these terms as their root nodes; as a result, the meaning of any term appearing below the root can only be understood by including the root. Once again, the exact structures are completely dependent upon archetyping, and may be simple or quite sophisticated.
Negations are more complex than might first be apparent and are best handled by good archetype design. Terminologies might provide a term such as “No known allergies” which is helpful. But if someone has an allergy of some sort, the medicolegal requirement might be to record that the person has no known allergies to penicillin or another class of medication that is being prescribed. The often-proposed approach of using a generic negation ‘modifier’ to deal with such issues results in further problems. Consider the use of negation with liver - “no liver”, “no palpable liver”, “no liver disease”, “no history of liver disease”, “no liver function”, “no liver function tests”. The meaning of negated terms may be non-sensical and difficult to interpret.
A basic principle of dealing with negatives is to realise that most naïve suggested use cases are quite ambiguous as stated. Does “no allergies” mean “no reported episode of allergy”, “no allergic reactions ever”, “no known allergies to medication” or something else? Does it mean that these statements are taken as given by the patient, or determined by tests? Like all medical phenomena, allergies must be described in some detail for the EHR to be of any real use. Almost inevitably, this precludes the use of negated terms. Since the actual information structure will be determined in advance by arche
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type designers, clinicians will almost never be in the situation of having to negate a term. However, if the need does arise, it should be dealt with by a negative or quantitative answer, i.e. a value rather than a name. For example, in any ENTRY describing current problems, the clinician may record the name/value pair “allergies: NONE”. Here, “allergies” will be a DV_CODED_TEXT, and “NONE” will be either a DV_CODED_TEXTor a DV_TEXT; the two will be associated by a containing object, such as an instance of the ELEMENT class from the EHR RM. There is no explicit model of negation in openEHR.
In a number of circumstances, both plain text and coded text items are mapped to terms from other terminologies. In theory, this should never occur, since it means that relationships between terms which should only be knowable in the knowledge base (in the form of the terminology service, or something else) are being created and transmitted as part of EHR information, potentially invalidating or overriding the knowledge base. Where mappings are required, the proper approach is to create thesauri within the knowledge environment, and map through them. Unfortunately, in some cases, activities in the real world do not respect the information/knowledge boundary, hence the model described here includes an explicit mapping concept, which itself includes a “purpose” and a “match” indicator. Matching corresponds to the categories described below.
Any text item, whether coded or not, may be classified with a coded term, for research, reporting and decision support purposes. For example, a GP working in tropical Australia may wish to write “Ross River infection”, and be working with ICD9, which does not contain this term (although ICD9-CM does). He or she will use a plain text item, but will still be able to map it to an ICD9 classifier, such as the code for “arbovirus infection NOS”. The same approach can be used for adding a classifying term to a coded text item. The utility of classifier terms is various: they allow decision support to make more powerful inferences; in situations where the available terminologies do not provide the classification inbuilt, and where it is known that not all users of EHR data will have terminologies available. In data terms, classification mapping can be visualised as illustrated in FIGURE 6.
visible text (“what the clinician said”)
terminology_id = | icd9 | CODE_ |
code_string = 480 | PHRASE | |
(rubric = viral pneumonia) |
FIGURE 6 Plain Text and Coded Text with Classifier(s)
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Classifying mappings are represented by adding a term to the mappings list of the original term. Each mapping is explicitly represented with an instance of TERM_MAPPING, which indicates both the term being associated with the original text item, and a value of ‘>’ for the match attribute, which indicates that the mapping is “broader”. The possible values of the match attribute are ‘>’ (broader), ‘<‘ (narrower), and ‘=’ (equivalent); they are taken from the ISO standards 2788 (“Guide to Establishment and development of monolingual thesauri”) and 5964 (“Guide to Establishment and development of multilingual thesauri”).
Data from pathology laboratories has often been coded using a terminology local to the laboratory, due to lack of or economic unfeasibility of using existing widespread terminologies for the job. However, some laboratories also supply a nearest equivalent code from a well-known terminology such as LOINC, to enable the receiver of the data to process it in a more standard fashion. Here, “equivalence” is taken to mean a term of the same meaning but from a different vocabulary.
Another instance where equivalent terms might be supplied is to effect the translation of terms across specialist vocabularies such as nursing vocabularies when sharing EHRs across jurisdictions.
In theory, the cleanest way for senders and receivers of data coded with both a local and a more standard equivalent to deal with the mapping problem is for the originator of the local terminology to provide a complete thesaurus of translations into one or more recognised terminologies. However, in practice, laboratories using the HL7 v2.x messaging standard usually encode a primary term and equivalents with the HL7 CE data type, meaning that equivalents are included only with the term they are used with. A similar pragmatic approach to mapping equivalent terms in the EHR is likely to be used with the data types described here, and can be effected with the same mapping approach as for classification.
A further situation in which text values - this time plain text - is mapped to equivalent terms is when natural language processing is used to generate coded terms for existing free-text prose. The aim of such processing is to detect word phrases and associate them with a coded term of the same meaning, without obliterating the original text. In this case, an instance of DV_CODED_TEXT is associated with an instance of DV_TEXT via the mappings attribute.
In all cases with equivalents, the value of the match attribute is ‘=’, indicating that the mapping is a synonym.
Occasionally, there is a need to create a mapping to a term of narrower meaning than the original text item. Circumstances in which this occurs include when a clinician wants to record a syndrome such as “croup” or “influenza”, but the terminology does not contain these general terms, although it does contain more specific terms, e.g. “viral laryngo-tracheitis” or “influenza type A”. Clearly the clinician should be allowed to record what he/she wants (as plain text if necessary), but it should also be possible to add a mapping to the more precise term. For mappings to narrower terms, the value of the match attribute is ‘<’.
It has been argued in GEHR [14] that UMLS reference terms should also be supplied with occur rences of coded terms, in the form of the UMLS concept unique identifier, or “CUI”. UMLS is a way of encoding terms developed at the National Library of Medicine in the United States, and consists of a meta-thesaurus, in which terms from any extant term set (such as ICD, SNOMED, READ) can be cross-referenced. UMLS CUIs could turn out to be extremely useful for decision support and reporting.
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The proper use of UMLS is that terms from particular terminologies are passed to a UMLS interface and a CUI + rubric received in response. However, the mapping approach described above could also be used to map UMLS CUIs to existing text or terms in an EHR; in this case, a DV_CODED_TEXT is constructed for each UMLS “term”, where the code is the CUI and the rubric is the text rendering of the CUI (guaranteed unique in UMLS). The same approach can be used for any other thesaurus which becomes available in the future.
In cases where legacy data has to be converted to openEHR-compliant data, and only codes are available, e.g. ICD or ICPC codes, the following approach is recommended:
correspond to the available code in the legacy data.
This expresses the reality that no text was ever recorded in the legacy system; rather a code was recorded directly in the data field. In the converted data, this code is more correctly considered a mapping.
In most cases the natural language of a text object is known from the enclosing Entry (i.e. Observation) or other enclosing context. Where it is different (e.g. a german sentence within an English language diagnosis), or there is no enclosing context, the DV_TEXT.language attribute can be set to indicate the language of the text item.
5.2.1 DV_TEXT Class
CLASS | DV_TEXT |
Purpose | A text item, which may contain any amount of legal characters arranged as e.g. words, sentences etc (i.e. one DV_TEXT may be more than one word). Visual formatting and hyperlinks may be included. A DV_TEXT can be “coded” by adding mappings to it. |
Use | Fragments of text, whether coded or not are used on their own as values, or to make up larger tracts of text which may be marked up in some way, eventually going to make up paragraphs. |
ISO 18308 | STR 2.6, 2.9 |
Synapses | The Text data value class can contain either plain text or a term taken from a terminology system (coding scheme). |
HL7 | Roughly equivalent to CWE (coded with extensions) - i.e. a text value which may optionally be coded. |
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CLASS | DV_TEXT | |
---|---|---|
Inherit | DATA_VALUE | |
Attributes | Signature | Meaning |
1..1 | value: String | Displayable rendition of the item, regardless of its underlying structure. For DV_CODED_TEXT, this is the rubric of the complete term as provided by the terminology service. No carriage returns, line feeds, or other non-printing characters permitted. |
0..1 | mappings: List <TERM_MAPPING> | terms from other terminologies most closely matching this term, typically used where the originator (e.g. pathology lab) of information uses a local terminology but also supplies one or more equivalents from well-known terminologies (e.g. LOINC). |
0..1 | formatting: String | A format string of the form “name:value; name:value...”, e.g. "font-weight : bold; font-family : Arial; font-size : 12pt;". Values taken from W3C CSS2 properties lists “background” and “font”. |
0..1 | hyperlink: DV_URI | Optional link sitting behind a section of plain text or coded term item. |
0..1 | language: CODE_PHRASE | Optional indicator of the localised language in which the value is written. Coded from openEHR Code Set “languages”. Only used when either the text object is in a different language from the enclosing ENTRY, or else the text object is being used outside of an ENTRY or other enclosing structure which indicates the language. |
0..1 | encoding: CODE_PHRASE | Name of character encoding scheme in which this value is encoded. Coded from openEHR Code Set “character sets”. Unicode is the default assumption in openEHR, with UTF-8 being the assumed encoding. This attribute allows for variations from these assumptions. |
Invariants | Value_valid: value /= void and then not value.is_empty and then not (value.has(CR) or value.has(LF)) Language_valid: language /= Void implies code_set(Code_set_id_languages).has_code(language) Encoding_valid: encoding /= Void implies code_set(Code_set_id_character_sets).has_code(encoding) Mappings_valid: mappings /= void implies not mappings.is_empty Formatting_valid: formatting /= void implies not formatting.is_empty |
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5.2.2 TERM_MAPPING Class
CLASS | TERM_MAPPING | |
---|---|---|
Purpose | Represents a coded term mapped to a DV_TEXT, and the relative match of the target term with respect to the mapped item. Plain or coded text items may appear in the EHR for which one or mappings in alternative terminologies are required. Mappings are only used to enable computer processing, so they can only be instances of DV_CODED_TEXT. | |
Use | Used for adding classification terms (e.g. adding ICD classifiers to SNOMED descriptive terms), or mapping into equivalents in other terminologies (e.g. across nursing vocabularies). | |
ISO 18308 | STR 4.5 | |
Attributes | Signature | Meaning |
1..1 | target: CODE_PHRASE | The target term of the mapping. |
1..1 | match: Character | The relative match of the target term with respect to the mapped text item. Result meanings: • ‘>’: the mapping is to a broader term e.g. orginal text = “arbovirus infection”, target = “viral infection” • ‘=’: the mapping is to a (supposedly) equivalent to the original item • ‘<’: the mapping is to a narrower term. e.g. original text = “diabetes”, mapping = “diabetes mellitus”. • ‘?’: the kind of mapping is unknown. The first three values are taken from the ISO standards 2788 (“Guide to Establishment and development of monolingual thesauri”) and 5964 (“Guide to Establishment and development of multilingual thesauri”). |
1..1 | purpose: DV_CODED_TEXT | Purpose of the mapping e.g. “automated data mining”, “billing”, “interoperability” |
Functions | Signature | Meaning |
narrower:Boolean ensure match = ‘<’ implies Result | The mapping is to a narrower term. |
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CLASS | TERM_MAPPING | |
---|---|---|
equivalent:Boolean ensure match = ‘=’ implies Result | The mapping is to an equivalent term. | |
broader:Boolean ensure match = ‘>’ implies Result | The mapping is to a broader term. | |
unknown:Boolean ensure match = ‘?’ implies Result | The kind of mapping is unknown. | |
is_valid_match_code(c: Character):Boolean ensure Result := c = ‘>’ or c = ‘=’ or c = ‘<’ or c = ‘?’ | True if match valid. | |
Invariants | Target_exists: target /= Void Purpose_valid: purpose /= Void implies terminology(Terminology_id_openehr). has_code_for_group_id(Group_id_term_mapping_purpose, pur-pose.defining_code) Match_valid: is_valid_match_code(match) |
5.2.3 CODE_PHRASE Class
CLASS | CODE_PHRASE | |
---|---|---|
Purpose | A fully coordinated (i.e. all “coordination” has been performed) term from a terminology service (as distinct from a particular terminology). | |
ISO 18308 | STR 4.2 | |
Attributes | Signature | Meaning |
1..1 | terminology_id: TERMINOLOGY_ID | Identifier of the distinct terminology from which the code_string (or its elements) was extracted. |
1..1 | code_string: String | The key used by the terminology service to identify a concept or coordination of concepts. This string is most likely parsable inside the terminology service, but nothing can be assumed about its syntax outside that context. |
Invariants | Terminology_id_exists: terminology_id /= Void Code_string_exists: code_string /= Void and then not code_string.is_empty |
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5.2.4 DV_CODED_TEXT Class
CLASS | DV_CODED_TEXT | |
---|---|---|
Purpose | A text item whose value must be the rubric from a controlled terminology, the key (i.e. the ‘code’) of which is the defining_code attribute. In other words: a DV_CODED_TEXT is a combination of a CODE_PHRASE (effectively a code) and the rubric of that term, from a terminology service, in the language in which the data was authored. | |
Use | Since DV_CODED_TEXT is a subtype of DV_TEXT, it can be used in place of it, effectively allowing the type DV_TEXT to mean “a text item, which may optionally be coded”. | |
Misuse | If the intention is to represent a term code attached in some way to a fragment of plain text, DV_CODED_TEXT should not be used; instead use a DV_TEXT and a TERM_MAPPING to a CODE_PHRASE. | |
ISO 18308 | STR 4.1, 4.2, 4.3 | |
CEN | Text | |
OMG HDTF | COAS::CodedElement, LooselyCodedElement. | |
Synapses | Text | |
GEHR | G1_TERM_TEXT | |
HL7 | ConceptDescriptor (CD), CodedValue (CV) and CodedSimple (CS) | |
Inherit | DV_TEXT | |
Attributes | Signature | Meaning |
1..1 | defining_code:CODE_PHRASE | The term which the ‘value’ attribute is the textual rendition (i.e. rubric) of. |
Invariants | Definition_exists: defining_code /= Void |
5.2.5 DV_PARAGRAPH Class
CLASS | DV_PARAGRAPH |
Purpose | A logical composite text value consisting of a series of DV_TEXTs, i.e. plain text (optionally coded) potentially with simple formatting, to form a larger tract of prose, which may be interpreted for display purposes as a paragraph. |
Use | DV_PARAGRAPH is the standard way for constructing longer text items in summaries, reports and so on. |
ISO 18308 | STR 2.6 |
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CLASS | DV_PARAGRAPH | |
---|---|---|
GEHR | G1_PARAGRAPH | |
Inherit | DATA_VALUE | |
Attributes | Signature | Meaning |
1..1 | items: List<DV_TEXT> | Items making up the paragraph, each of which is a text item (which may have its own formatting, and/or have hyperlinks). |
Invariants | items_exists: items /= void and then not items.is_empty |
FIGURE 7 illustrates the visual appearance of a typical DV_PARAGRAPH.
xxxxx xxxx xxx xxxxxxx xx xx xxxxxxx xxx xxxxxxxxx xxxx xxxxxxxxxxxx xxxx xxx xxxxxx xxxxxxxxx xxxxxx xxxxx xxxxx xxxx xxxxxx a xxxxxxx xxxx xxxxx xxxxx xxxxxxx xxxxxx x xxx
FIGURE 7 PARAGRAPH visual structure
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The data_types.quantity package is illustrated in FIGURE 8. Dates and Times are found in the next section.
Ordered
INTERVAL<T> (rm.support.assumed)
DATA_VALUE
(rm.support.assumed)
(rm.data_types.basic)
FIGURE 8 rm.data_types.quantity Package
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Medicine is one domain in which symbols representing relative magnitudes are commonly used, without exact values being known. The main purpose is usually to classify patients into groups for which different decisions might be made. Thus, while approximate ranges (technically speaking “fuzzy intervals”) might be stated (such as for a urinalysis), concrete values are not of interest, only categories are. Take for example the characterisation of pain as being “mild”, “medium”, “severe”, or the reflex response to tendon percussion as “-”, “+/-”, “+”, “++”, ”+++”, “++++”. There may be no way to scientifically precisely quantify such values because they reflect a subjective experience of the patient or informal judgement by clinician. However, they are understood as being ordered, e.g. “++” is ‘greater than’ “+”.
Similarly, even though the symbolic values for haemolysed blood in a urinalysis have approximate ranges stated for them, as shown below, these ‘values’ are not usable in the same way as true quantities.
A second requirement for ordinal values is that in many cases there is a need to associate integer values with the symbols, in order to facilitate ordered comparison, and also to enable longitudinal comparison across results of the same kind (e.g. pain, protein). Integer values may be negative, 0 and positive, typically to allow the 0 value to correspond to a neutral value in a range.
[Note: an argument sometimes put forward for recording all ordinals in a more precise way is that comparisons might want to be made between the values quoted by two laboratories for the same symbol (e.g. “moderate”). There are a number of counter-arguments. Firstly, such comparisons are a poor attempt at normalisation, an activity which is the business of pathologists, not EHR users. Secondly, the symbolic values are often arrived at by the tester making a judgement of colour on a strip, which while an adequate (and cost-effective) approach for classifying, is not a valid means of quantifying a value. Lastly, in most cases, if a quantified point value or range is desired, or available, then it will be used - meaning that the appropriate quantitative data type can be used, rather than an the ordinal type.]
An common kind of data value in medicine is the dimensionless countable quantity, e.g. “number of doses: 2”, “number of previous pregnancies: 1”, “number of tablets: 3”. Values of this type are always integral. Countable values need to be convertible to real numbers for statistical purposes, for example for a study of average number of pregnancies per couple.
Some countable entities such as tablets are divisible into major fractions, typically halves and occasionally quarters.
The most common kind of quantity is a measured, dimensioned quantity. Anything which is measurable (rather than countable) involves a number of data aspects, namely:
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Examples of dimensioned quantities include:
A common quantitative type in science and medicine is the proportion, or ratio, which is used in situations like the following:
In general ratios have real number values, even if many examples appear to be integer ratios. Proportions with unitary denominator and % (denominator = 100) are common.
A concept superficially similar to proportions and ratios is formulations of materials, such as a solid in a liquid e.g.:
• 250 mg / 500 ml (solute/solvent)
Although a single solute/single solvent formulation appears to have the same form as a ratio, the general form is for any number of substances to be mixed together, usually according to a particular procedure. Formulations are therefore not candidates for direct modelling as fine-grained quantities, but instead are constructed by archetyping a higher-level structure, each leaf element of which contains the required kind of Quantity.
Quantity ranges are ubiquitous in science and medicine, and may be defined for any kind of measured phenomenon. Examples include:
A reference range is a quantity range attached to a measured value, and is common for laboratory result values. The typical form of a reference range found in a pathology result indicates what is considered the ‘normal’ range for a measured value. Examples of reference ranges:
Ranges can also be quoted for drug administrations, in which case they are usually thought of as the ‘therapeutic’ range. For example, the anticonvulsant drug Carbamazepine has a therapeutic range of
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20 - 40 µMol/L. In some cases, there are multiple ranges associated with a drug, for example, Salicylate has a therapeutic range of 1.0 - 2.5 mmol/L and a toxic range > 3.6 mmol/L
Various examples occur in which multiple ranges may be stated, including the following.
Where there are multiple ranges, the important question is: which range information is relevant to the actual data being recorded for the patient? In theory, only the range corresponding to the particular patient situation should be used, i.e. the range which applies after taking into account sex, age, smoking status, “professional athlete”, organ transplanted, etc. In most cases, this is a single “normal” range, or a pair of ranges, typically “therapeutic” and “critical”. However, practical factors complicate things. Firstly, data is sometimes supplied from pathology labs along with some or all of the applicable reference ranges, even though only some could possibly apply. This is particularly the case if the laboratory has no other data on the patient, and cannot evaluate which range applies. The requirement for faithfulness of recording might be extended to reference data supplied by laboratories, regardless of how irrelevant or arbitrarily chosen the reference data is, meaning that such data has to be stored in the record anyway. Secondly, there may be circumstances in which physicians want a number of reference ranges, even while knowing that only one range is applicable to the datum. Ranges above and below the relevant one might be useful to a physician wishing to determine how far out of range the datum is.
It is quite common for laboratories to include a normal range with each measured value, and/or a normal ‘status’, which indicates where the value lies with respect to the normal range. The latter will commonly take the form of markers like “HHH” (critically high), HH (abnormally high), H (borderline high), L, LL, LLL in HL7v2 messaging, although other schemes are undoubtedly used.
In order to make sense of the requirements in a systematic way, a proper typology for quantities is needed. The most basic characteristic of all values typically called ‘quantities’ is that they are ordered, meaning that the operator “<” (less-than) is defined between any two values in the domain. An ancestor class for all quantities called DV_ORDERED is accordingly defined. This type is subtyped into ordinals and true quantities, represented by the classes DV_ORDINAL and DV_QUANTIFIED respectively. DV_ORDINAL represents data values whose exact numeric values are not known, and which use symbolic renderings instead, such as “+”, “++”, “+++”, or “mild”, “medium”, “severe”. Each symbol can be assigned any integer value, providing a basis for computable comparison. In contrast, instances of DV_QUANTIFIED and all its subtypes have precise numeric magnitudes.
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DV_QUANTIFIED itself introduces the concepts of magnitude and magnitude_status. The magnitude attribute is guaranteed to be available on any DV_QUANTIFIED, carrying the effective value, regardless of the particular subtype. The optional magnitude_status attribute can be used to provide a non-quantified indication of accuracy, and takes the following values:
If not present, meaning is “=”.
Logically, an accuracy attribute should also be included in DV_QUANTIFIED, but as its modelling is different in the subtypes in a way that does not easily lend itself to a common ancestor, it is only included in the subtypes.
The DV_QUANTIFIED class has two subtypes: DV_AMOUNT and DV_ABSOLUTE_QUANTITY. The former corresponds to relative ‘amounts’ of something, either a physical property(such as mass) or items (e.g. cigarettes). Mathematically, the ‘+’ and ‘-’ operators (as well as ‘*’ and ‘/’) are defined in the same way as for the real numbers (or any other mathematical ‘field’), with the semantics that adding two relative quantities measuring the same thing (i.e. with the same units) produces another relative quantity of the same kind; while the semantics of subtraction are that one relative quantity subtracted from another generates a third.
The second subtype of DV_QUANTIFIED, DV_ABSOLUTE_QUANTITY, models quantities whose values are absolute along a line having a defined origin. The main example of absolute quantities are the temporal concepts date, time and date/time. These are distinguished from relative quantities in that the normal addition and subtraction operations don’t apply. Instead, the semantics of such operators are based on the idea of the difference between absolute values being a relative amount. For example, two dates can be subtracted, but the result is a duration, not another date. For this reason, the operations add, subtract and diff are defined rather than ‘+’ or ‘-’. Date/time types, as well as the relative concept duration, are defined in the Date Time Package on page 55.
Subtypes of DV_AMOUNT are DV_PROPORTION, DV_QUANTITY, DV_COUNT, and DV_DURATION (see date_time package). The type DV_COUNT has an integer magnitude and is used to record naturally countable things such as number of previous pregnancies, number of steps taken by a recovering stroke victim and so on. There are no units or precision in a DV_COUNT. Countable quantities can be used to create instances of DV_QUANTITY, such as during a statistical study which average tobacco consumption over a time period. Such a computation might cause the creation of DV_QUANTITY objects representing values like {magnitude = 5.85, units = ‘/ week’}
DV_QUANTITY is used to represent amounts of measurable things, and has a real number magnitude, precision, units and accuracy. The units attribute contains the scientific unit in a parsable form defined by the Unified Code for Units of Measure (UCUM) [8] . A valid units string always implies a measured property, such as “force” or “pressure”. The property of a Quantity can conveniently constrained in archetypes, e.g. to “pressure”, which would allow any pressure unit. Unit strings can be compared to determine if they measure the same property (e.g. “bar” and “kPa” are both units corresponding to the property “pressure”), which enables the is_strictly_comparable_to function defined on DV_ORDERED to be properly specified on DV_QUANTITY.
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It is important to note that while these semantics will allow comparison of e.g. two pressures recorded in mbar and mmHg, or even two accelerations whose units are “m.s^-2” and “m/s^2”, they provide no guarantee that this is a sensible thing to do in terms of domain semantics: comparing a blood pressure to an atmospheric pressure for example may or may not make any sense. It is not within the scope of the quantity package to express such semantics: this is up to application software which uses Quantities found in specific places in the data.
Theoretically it might be argued that ‘accuracy’ should not be included in a model for quantified values, because it is an artifact of a measuring process and/or device, not of a quantity itself. For example, a weight of “82 kg +/-5%” can be represented in two parts. The “82 kg” is represented as a DV_QUANTITY, while the “+/-5%” may be included in the protocol description of the weighing instrument, since this is where the error comes from. For practical purposes however, (in)accuracy in a measured quantity corresponds to a range of possible values. In realistic computing in health, it is quite likely that the accuracy will be required in computations on the quantity, especially for statistical population queries in which measurement error must be disambiguated from true correlation. Accuracy is therefore included as an attribute of DV_AMOUNT, where it is of type Real (if no accuracy recorded its value is 0), and DV_ABSOLUTE_QUANTITY, where it is of a differential type defined by subtypes (no accuracy recorded corresponds to a Void accuracy attribute).
The related notion of “uncertainty” is understood as a subjective judgement made by the clinician, indicating that he/she is not certain of a particular statement. It is not the same as accuracy: uncertainty may apply to non-quantified values, such as subjective statements, and it is not an aspect of objective measurement processes, but of human confidence. Where the uncertainty is due to subjective memory e.g. “I think my grandfather was 56 when he died”, the uncertainty is simply recorded as another value, along with the main data item being recorded. Uncertainty is therefore not directly modelled in the openEHR data types, but appears instead in particular archetypes.
Ranges are modelled by the generic type DV_INTERVAL<T:DV_ORDERED> which enables a range of any of the other quantity types (except ratio) to be constructed. This allows any subtype of DV_ORDERED to occur as a range as well.
The DV_PROPORTION type is provided for representing true ratios, i.e. relative values, and consists of numerator and denominator Real values, and a magnitude function which is computed as the result of the numerator/denominator division. The type attribute is used to indicate the logical type of the proportion. Supported types include:
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Lastly, the is_integral function indicates that the numerator and denominator are both integer values; this is used for fractions (the fraction and integer_fraction types above) and other commonly occurring ratios where both parts are always integer values.
Normal range for any of the quantity types (i.e. any instance of a subtype of DV_ORDERED) can be included via the attribute DV_ORDERED.normal_range, of type REFERENCE_RANGE. Other reference ranges (e.g. subcritical, critical etc) can be included via the attribute DV_ORDERED.other_reference_ranges. The separation of normal and other reference range attributes is used because the former constitute the vast majority of ranges quoted for quantitative data.
Normal status can be included via the attribute DV_ORDERED.normal_status, which takes the form of a DV_ORDINAL, whose symbol atttribute is coded according to the openEHR terminology group “normal status”, and takes values “HHH” (critically high), “HH” (abnormally high), “H” (borderline high)”, “N” (normal), “L” ... “LLL”.
Time can be recorded in two ways. Absolute times in the social time domain, such as dates and time of day are recorded using the types in the date_time package. Fine-grained ‘time’, which is a duration rather than a time, is recorded using a DV_QUANTITY with units = ‘s’ or another temporal unit (‘h’, ‘ms’, ‘ns’ etc).
6.2.1 DV_ORDERED Class
CLASS | DV_ORDERED (abstract) | |
---|---|---|
Purpose | Abstract class defining the concept of ordered values, which includes ordinals as well as true quantities. It defines the functions ‘<’ and is_strictly_comparable_to, the latter of which must evaluate to True for instances being compared with the ‘<’ function, or used as limits in the DV_INTERVAL<T> class. | |
Use | Data value types which are to be used as limits in the DV_INTERVAL<T> class must inherit from this class, and implement the function is_strictly_comparable_to to ensure that instances compare meaningfully. For example, instances of DV_QUANTITY can only be compared if they measure the same kind of physical quantity. | |
Inherit | DATA_VALUE, Ordered | |
Abstract | Signature | Meaning |
infix ‘<’ (other: like Current): Boolean require is_strictly_comparable_to(other) | Tests if this item is less than other, which must be of the same concrete type. | |
is_strictly_comparable_to (other: like Current): Boolean | Test if two instances are strictly comparable. |
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CLASS | DV_ORDERED (abstract) | |
---|---|---|
Attributes | Signature | Meaning |
0..1 | normal_range: DV_INTERVAL<like Current> | Optional normal range. |
0..1 | other_reference_ranges: List <REFERENCE_RANGE<like Current>> | Optional tagged other reference ranges for this value in its particular measurement context |
0..1 | normal_status: CODE_PHRASE | Optional normal status indicator of value with respect to normal range for this value. Often included by lab, even if the normal range itself is not included. Coded by ordinals in series HHH, HH, H, (nothing), L, LL, LLL; see openEHR terminology group “normal status”. |
Functions | Signature | Meaning |
is_normal: Boolean require normal_range /= Void or normal_status /= Void ensure normal_range /= Void implies Result = normal_range.has(Current) normal_status /= Void implies normal_status.code_string.is_equal(“ N”) | Value is in the normal range, determined by comparison of the value to the normal_range if present, or by the normal_status marker if present. | |
is_simple: Boolean | True if this quantity has no reference ranges. | |
Invariants | Other_reference_ranges_validity: other_reference_ranges /= Void implies not other_reference_ranges.is_empty Is_simple_validity: (normal_range = Void and other_reference_ranges = Void) implies is_simple Normal_status_validity: normal_status /= Void implies code_set(Code_set_id_normal_statuses).has_code(normal_status) Normal_range_and_status_consistency: (normal_range /= Void and normal_status /= Void) implies (normal_status.code_string.is_equal(“N”) xor not normal_range.has(Current)) |
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6.2.2 DV_INTERVAL<T : DV_ORDERED> Class
CLASS | DV_INTERVAL<T : DV_ORDERED> |
Purpose | Generic class defining an interval (i.e. range) of a comparable type. An interval is a contiguous subrange of a comparable base type. |
Use | Used to define intervals of dates, times, quantities (whose units match) and so on. The type parameter, T, must be a descendant of the type DV_ORDERED, which is necessary (but not sufficient) for instances to be compared (strictly_comparable is also needed). Without the DV_INTERVAL class, quite a few more DV_ classes would be needed to express logical intervals, namely interval versions of all the date/time classes, and of quantity classes. Further, it allows the semantics of intervals to be stated in one place unequivocally, including the conditions for strict comparison. The basic semantics are derived from the class INTERVAL<T>, described in the support RM. |
ISO 18308 | STR 3.13 |
CEN | Time Interval; also includes a measurement range data type but not the ability to specify if minimum or maximum values are inclusive. |
Synapses | QuantityRange + ability to specify if the range is inclusive or exclusive separately of the maximum and minimum values. |
GEHR | G1_QUANTITY_RANGE |
HL7 | IVL<T:QTY> |
Inherit | DATA_VALUE, INTERVAL<T> |
Invariants | Limits_consistent: (not upper_unbounded and not lower_unbounded) implies (lower.is_strictly_comparable_to(upper) and lower <= upper) |
6.2.3 REFERENCE_RANGE<T:DV_ORDERED> Class
CLASS | REFERENCE_RANGE<T:DV_ORDERED> | |
---|---|---|
Purpose | Defines a named range to be associated with any ORDERED datum. Each such range is particular to the patient and context, e.g. sex, age, and any other factor which affects ranges. | |
Use | May be used to represent normal, therapeutic, dangerous, critical etc ranges. | |
ISO 18308 | STR 3.13 | |
Attributes | Signature | Meaning |
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CLASS | REFERENCE_RANGE<T:DV_ORDERED> | |
---|---|---|
1..1 | meaning: DV_TEXT | Term whose value indicates the meaning of this range, e.g. “normal”, “critical”, “therapeutic” etc. |
1..1 | range: DV_INTERVAL<T> | The data range for this meaning, e.g. “critical” etc. |
Functions | Signature | Meaning |
is_in_range (val: T): Boolean | Indicates if the value ‘val’ is inside the range | |
Invariants | Meaning_exists: meaning /= Void Range_exists: range /= Void Range_is_simple: (range.lower_unbounded or else range.lower.is_simple) and (range.upper_unbounded or else range.upper.is_simple) |
6.2.4 DV_ORDINAL Class
CLASS | DV_ORDINAL | |
---|---|---|
Purpose | Models rankings and scores, e.g. pain, Apgar values, etc, where there is a) implied ordering, b) no implication that the distance between each value is constant, and c) the total number of values is finite. Note that although the term ‘ordinal’ in mathematics means natural numbers only, here any integer is allowed, since negative and zero values are often used by medical professionals for values around a neutral point. Examples of sets of ordinal values: -3, -2, -1, 0, 1, 2, 3 -- reflex response values 0, 1, 2 -- Apgar values | |
Use | Used for recording any clinical datum which is customarily recorded using symbolic values. Example: the results on a urinalysis strip, e.g. {neg, trace, +, ++, +++} are used for leucocytes, protein, nitrites etc; for non-haemolysed blood {neg, trace, moderate}; for haemolysed blood {neg, trace, small, moderate, large}. | |
ISO 18308 | STR 3.2 | |
HL7 | Quantity (QTY) | |
Inherit | DV_ORDERED | |
Attributes | Signature | Meaning |
1..1 | value: Integer | Value in ordered enumeration of values. Any integer value can be used. |
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CLASS | DV_ORDINAL | |
---|---|---|
1..1 | symbol: DV_CODED_TEXT | Coded textual representation of this value in the enumeration, which may be strings made from “+” symbols, or other enumerations of terms such as “mild”, “moderate”, “severe”, or even the same number series as the values, e.g. “1”, “2”, “3”. Codes come from archetype. |
Functions | Signature | Meaning |
limits: REFERENCE_RANGE <DV_ORDINAL> | limits of the ordinal enumeration, to allow comparison of an ordinal value to its limits. | |
infix ‘<’ (other: like Current): Boolean ensure value < other.value implies Result | True if types are the same and values compare | |
is_strictly_comparable_to (other: like Current): Boolean ensure symbol.is_comparable (other.symbol) implies Result | True if symbols come from same vocabulary, assuming the vocabulary is a subset or value range, e.g. “urine:protein”. | |
Invariants | Symbol_exists: symbol /= Void Limits_valid: limits /= Void and then limits.meaning.is_equal(“limits”) Reference_range_valid: other_reference_ranges /= Void and then other_reference_ranges.has(limits) |
6.2.5 DV_QUANTIFIED Class
CLASS | DV_QUANTIFIED (abstract) | |
---|---|---|
Purpose | Abstract class defining the concept of true quantified values, i.e. values which are not only ordered, but which have a precise magnitude. | |
OMG HDTF | COAS::Measurement. | |
Synapses | Attributes in the Quantity class for unit and accuracy (double plus units) | |
HL7 | Quantity (QTY) | |
Inherit | DV_ORDERED | |
Abstract | Signature | Meaning |
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CLASS | DV_QUANTIFIED (abstract) | |
---|---|---|
magnitude: Ordered_Numeric | Numeric value of the quantity in canonical (i.e. single value) form. Implemented as constant, function or attribute in subtypes as appropriate. The type Ordered_numeric is mapped to the available appropriate type in each implementation technology. | |
Attributes | Signature | Meaning |
0..1 | magnitude_status: String | Optional status of magnitude with values: • “=” : magnitude is a point value • “<“ : value is < magnitude • “>” : value is > magnitude • “<=” : value is <= magnitude • “>=” : value is >= magnitude • “~” : value is approximately magnitude If not present, meaning is “=”. |
Functions | Signature | Meaning |
valid_magnitude_status (s: String): Boolean ensure Result = s.is_equal(“=”) or s.is_equal(“<”) or s.is_equal(“>”) or s.is_equal(“<=”) or s.is_equal(“>=”) or s.is_equal(“~”) | Test whether a string value is one of the valid values for the magnitude_status attribute. | |
Invariants | Magnitude_exists: magnitude /= Void Magnitude_status_valid: magnitude_status /= Void implies valid_magnitude_status(magnitude_status) |
6.2.6 DV_AMOUNT Class
CLASS | DV_AMOUNT (abstract) | |
---|---|---|
Purpose | Abstract class defining the concept of relative quantified ‘amounts’. For relative quantities, the ‘+’ and ‘-’ operators are defined (unlike descendants of DV_ABSOLUTE_QUANTITY, such as the date/time types). | |
Inherit | DV_QUANTIFIED | |
Abstract | Signature | Meaning |
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CLASS | DV_AMOUNT (abstract) | |
---|---|---|
prefix ‘-’: like Current | Negated version of current object, such as used for representing a difference, e.g. a weight loss. | |
infix ‘+’ (other: like Current): like Current | Sum of this quantity and another whose formal type must be the difference type of this quantity. | |
infix ‘-’ (other: like Current): like Current | Difference of this quantity and another whose formal type must be the difference type of this quantity type. | |
Attributes | Signature | Meaning |
0..1 | accuracy: Real | Accuracy of measurement, expressed either as a half-range percent value (accuracy_is_percent = True) or a half-range quantity. A value of 0 means that accuracy was not recorded. |
0..1 | accuracy_is_percent: Boolean | If True, indicates that when this object was created, accuracy was recorded as a percent value; if False, as an absolute quantity value. |
Functions | Signature | Meaning |
valid_percentage (val: Numeric): Boolean ensure Result implies val >= 0.0 and val <= 100.0 | Test whether a number is a valid percentage, i.e. between 0 and 100. | |
Invariants | Accuracy_is_percent_validity: accuracy = 0 implies not accuracy_is_percent Accuracy_validity: accuracy_is_percent implies valid_percentage(accuracy) |
6.2.7 DV_QUANTITY Class
CLASS | DV_QUANTITY |
Purpose | Quantitified type representing “scientific” quantities, i.e. quantities expressed as a magnitude and units. Units were inspired by the Unified Code for Units of Measure (UCUM), developed by Gunther Schadow and Clement J. McDonald of The Regenstrief Institute [8]. |
Use | Can also be used for time durations, where it is more convenient to treat these as simply a number of seconds rather than days, months, years. |
ISO 18308 | STR 3.2 - 3.4 |
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CLASS | DV_QUANTITY | |
---|---|---|
CEN | Quantifiable Data Item; Measurement data value class. | |
OMG HDTF | COAS::Numeric. | |
Synapses | Quantity | |
GEHR | G1_QUANTITY | |
HL7 | PhysicalQuantity (PQ) | |
Inherit | DV_AMOUNT | |
Attributes | Signature | Meaning |
1..1 | magnitude: Double | numeric magnitude of the quantity. |
1..1 | units: String | Stringified units, expressed in UCUM unit syntax, e.g. "kg/m2", “mm[Hg]", "ms-1", "km/h". Implemented accordingly in subtypes. |
0..1 | precision: Integer | Precision to which the value of the quantity is expressed, in terms of number of decimal places. The value 0 implies an integral quantity. The value -1 implies no limit, i.e. any number of decimal places. |
Functions | Signature | Meaning |
is_integral: Boolean is_strictly_comparable_to (other: like Current): Boolean require units_equivalent(units, other.units) | True if precision = 0; quantity represents an integral number. Test if two instances are strictly comparable by ensuring that the measured property is the same, achieved using the Measurement service function units_equivalent. | |
(effected) | ||
Invariants | Precision_valid: precision >= -1 Units_valid: units /= void |
The BNF syntax specification of the units string, adapted from [8] is as follows:
units ::= ‘/’ exp_units | units ‘.’ exp_units | units ‘/’ exp_units | exp_units
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Data Types Information Model Quantity Package Rev 2.1.0
exp_units ::= unit_group exponent | unit_group
unit_group ::= PREFIX annot_unit | annot_unit | ‘(’ exp_units ‘)’ | factor
annot_unit ::= unit_name | unit_name ‘{’ ANNOTATION ‘}’ | ‘{’ ANNOTATION ‘}’
factor ::= Integer
exponent ::= SIGN Integer | Integer
PREFIX ::= ‘Y’ |‘Z’ | ‘E’ | ‘P’ | ‘T’ | ‘G’ | ‘M’ | ‘k’ | ‘h’ | ‘da’
| ‘d’ | ‘c’ | ‘m’ | ‘µ’ | ‘n’ | ‘p’ | ‘f’ | ‘a’ | ‘z’ | ‘y’ UNIT_NAME ::= [a-zA-Z_%]+ ; from unit tables ANNOTATION ::= [a-zA-Z’.]+ ; from unit tables SUFFIX ::= [a-zA-Z0-9’_]+ ; from unit tables
SIGN ::= ‘+’ | ‘-’ Integer ::= [0-9]+
This proposal is comprehensive, covering all useful unit systems, including SI, various imperial, customary mesaures, and some obscure measures, as well as clinically specific additions. Metric prefixes, meaning-changing textual suffixes (e.g. “[Hg]” in “mm[Hg]”) and non-meaning-changing annotations (e.g. “kg {total}”) are recognised. With this syntax, units can be simply expressed in strings such as:
“kg/m^2”, “m.s^-1”, “km/h”, “mm[Hg]”
and so on.
6.2.9 DV_COUNT Class
CLASS | DV_COUNT | |
---|---|---|
Purpose | Countable quantities. | |
Use | Used for countable types such as pregnancies and steps (taken by a physiotherapy patient), number of cigarettes smoked in a day. | |
Misuse | Not used for amounts of physical entities (which all have units) | |
ISO 18308 | STR 3.2 - 3.4 | |
HL7 | INT | |
Inherit | DV_AMOUNT | |
Attributes | Signature | Meaning |
1..1 | magnitude: Integer | numeric magnitude of the quantity |
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Quantity Package Data Types Information Model Rev 2.1.0
6.2.10 DV_PROPORTION Class
CLASS | DV_PROPORTION | |
---|---|---|
Purpose | Models a ratio of values, i.e. where the numerator and denominator are both pure numbers. | |
Use | Used for recording titers (e.g. 1:128), concentration ratios, e.g. Na:K (unitary denominator), albumin:creatinine ratio, and percentages, e.g. red cell distirbution width (RDW). | |
MisUse | Should not be used to represent things like blood pressure which are often written using a ‘/’ character, giving the misleading impression that the item is a ratio, when in fact it is a structured value. E.g. visual acuity “6/24” is not a ratio. Should not be used for formulations. | |
ISO 18308 | STR 3.6 | |
OMG HDTF | COAS::Ratio. | |
HL7 | Ratio (RTO). | |
Inherit | DV_AMOUNT, PROPORTION_KIND | |
Attributes | Signature | Meaning |
1..1 | numerator: Real | numerator of ratio |
1..1 | denominator: Real | denominator of ratio |
1..1 | type: Integer | Indicates semantic type of proportion, including percent, unitary etc. |
0..1 | precision: Integer | Precision to which the numerator and denominator values of the proportion are expressed, in terms of number of decimal places. The value 0 implies an integral quantity. The value -1 implies no limit, i.e. any number of decimal places. |
Functions | Signature | Meaning |
is_integral: Boolean | True if the numerator and denominator values are integers, i.e. if the precision is 0. |
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CLASS | DV_PROPORTION | |
---|---|---|
magnitude: Real ensure Result = numerator / denominator | Effective magnitude represented by ratio. | |
(effected) | is_strictly_comparable_to (other: like Current): Boolean ensure type = other.type implies Result | True if type is the same. |
Invariants | Type_validity: valid_proportion_kind(type) Precision_validity: precision = 0 implies is_integral Is_integral_validity: is_integral implies (numerator.floor = numerator and denominator.floor = denominator) Fraction_validity: (type = pk_fraction or type = pk_integer_fraction) implies is_integral Unitary_validity: type = pk_unitary implies denominator = 1 Percent_validity: type = pk_percent implies denominator = 100 |
6.2.11 PROPORTION_KIND Class
CLASS | PROPORTION_KIND | |
---|---|---|
Purpose | Class of enumeration constants defining types of proportion for the DV_PROPORTION class. | |
Attributes | Signature | Meaning |
const | pk_ratio: Integer = 0 | Ratio type. Numerator and denominator may be any value |
const | pk_unitary: Integer = 1 | Denominator must be 1 |
const | pk_percent: Integer = 2 | Denominator is 100, numerator is understood as a percentage value. |
const | pk_fraction: Integer = 3 | Numerator and denominator are integral, and the presentation method uses a slash, e.g. “1/2”. |
const | pk_integer_fraction: Integer = 4 | Numerator and denominator are integral, and the presentation method uses a slash, e.g. “1/2”; if the numerator is greater than the denominator, e.g. n=3, d=2, the presentation is “1 1/2”. |
Functions | Signature | Meaning |
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CLASS | PROPORTION_KIND | |
---|---|---|
valid_proportion_kind (n: Integer): Boolean | True if n is one of the defined types. | |
Invariants |
6.2.12 DV_ABSOLUTE_QUANTITY Class
CLASS | DV_ABSOLUTE_QUANTITY (abstract) | |
---|---|---|
Purpose | Abstract class defining the concept of quantified entities whose values are absolute with respect to an origin. Dates and Times are the main example. | |
Inherit | DV_QUANTIFIED | |
Abstract | Signature | Meaning |
add (a_diff: like diff): like Current | Addition of a differential amount to this quantity. | |
subtract (a_diff: like diff): like Current | Result of subtracting a differential amount from this quantity. | |
diff (other: like Current): DV_AMOUNT | Difference of two quantities. | |
Attributes | Signature | Meaning |
0..1 | accuracy: like diff | Accuracy of measurement, expressed as a half-range value of the diff type for this quantity (i.e. an accuracy of x means +/−x). |
Invariants |
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© 2003-2007 The openEHR Foundation. email: info@openEHR.org web: http://www.openEHR.org
Data Types Information Model Date Time Package Rev 2.1.0
The data_types.quantity.date_time package includes three absolute date/time concepts: DV_DATE, DV_TIME, DV_DATE_TIME, and a relative concept: DV_DURATION. The representations of all of these are ISO8601:2004-compatible date/time strings. They also include the ISO8601 semantics for partial dates and times. The date_time package is illustrated in FIGURE 9.
DV_ABSOLUTE_QUANTITY
DV_AMOUNT
(rm.data_types.quantity)
(rm.data_types.quantity)
FIGURE 9 rm.data_types.quantity.date_time Package
The basic requirement is for types which represent the following concepts:
Partial or uncertain date/times have to be supported in clinical medicine. It is common for patients to be unsure about dates and durations. Requirements for partial date/times include the following.
• For dates, one of the following rules applies to any instance:
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Date Time Package Data Types Information Model Rev 2.1.0
- only the year is known
- only the year and month are known
If not even the year is known, then the date is obviously extremely approximate and it would
probably be unsafe to represent it computationally. However, if computatable representation
was needed in this case, a date interval can be used. A pedantic example which breaks these
rules is someone who claims to be born on “a Monday at the start of May in 1934” (i.e. day
but not date unknown). Either the clinician determines what date the first Monday in May
1934 actually was and record that (assuming the patient’s way of accurately remembering
just happens to be via day rather than date), or else records a partial date of the form “May
1934” (in ISO 8601 form, “1934-05”) if they determine that the patient really is unsure.
To satisfy the faithfulness requirement for health record recording it should always be possible to record the narrative form of the datum provided by the patient as well as the formal form.
Date/time values are somewhat special in the realm of data types in that they are expressed in their “customary” form, in which the standard structure of {value, unit} and metric relationships between orders of magnitude do not hold. The customary form is what we are used to using in the social time domain, such as births, deaths, ages, and times and durations of events which we remember. In all these cases it is expressed using the familiar year/month/date/hour/minute/second system, in which the relationships between each successive unit of time is non-metric. The customary form can be converted to a magnitude since an origin point, and many date/time libraries do this in order to implement various operations, particularly comparison.
The date/time types fall into two categories: absolute and relative. The absolute category comprises the Date, Date_time and Time concepts, each of which measure time from a known origin. Date and Date_time measure calendrical time from the date 0001-01-01, while Time measures clock time from midnight. Both Date_time and Time can include timezone information, ensuring that their instances are correctly situated on the same timeline. All absolute time types inherit from the DV_TEMPORAL type, which provides the appropriate signature for the diff() function.
The relative category contains only the Duration concept, which expresses elapsed time between two time points. The DV_DURATION class is used for expressing durations of clinical phenomena and differences between absolute times.
All four concepts are defined in the ISO 8601:2004 standard, which is accordingly used as the definitional basis of the openEHR date/time types.
The types defined in this specification support the notion of partially specified dates and times. The modelling approach used here takes into account the known needs for representing partial date/time
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Data Types Information Model Date Time Package Rev 2.1.0
data, while balancing that with the need to avoid incomprehensibly complex types whose generality would only apply to a tiny percent of difficult cases. Thus, the basis for modelling incomplete date/times is as follows.
Based on the above considerations, the requirements for partial types are satisfied by the semantics of ISO8601:2004 for “reduced accuracy” date/times, in which parts of a date, time or date/time can be missing from the right hand end of the string. This models the reasonable situation where e.g. day may be unknown in a date, but a date cannot have month unknown and day known.
A comment on calendars is in order. In this specification, all date/time types currently modelled are Gregorian calendar based. This is the same assumption made by by ISO 8601, and most technical computing systems today in many parts of the world. At first glance this may seem like a culturally insensitive approach, but in fact it makes sense in computational terms, for both users of the Gregorian and other calendars, e.g. Julian, Islamic, Baha’i, etc. Arguments against trying to use the date/time classes defined here to represent date/times from any calendar include the following:
For users requiring non-Gregorian dates in EHR and other health systems there are two approaches. One is to treat non-Gregorian dates as a localisation issue, to be handled inside the application and GUI evnvironment. The other is to actually add further sibling packages to the openEHR date/time package, for each new calendar or calendar group required. Conversion algorithms would most likely be needed in and out of the Gregorian types to enable interoperability of information drawn from different applications or sources. This approach may require a substantial modelling effort.
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Date Time Package Data Types Information Model Rev 2.1.0
Algorithms for conversion between the Egyptian, Armenian, Khwarizmian, Persian, Ethiopian, Coptic, Republican, Macedonian, Syrian, Julian Roman, Gregorian, Islamic A, Islamic B, Baha’i and Saka calendars are described by Richards [7] and are based on the work of D. A. Hatcher (1986).
All of the date/time classes described here are defined so as to have an attribute called value of type String, in the form of an ISO 8601:2004 string. ISO 8601 is convenient for this purpose, as it is a simple syntax, and covers not only all four variants of fully-specified date/time described here, but also the partial varieties. Using a single string attribute significantly simplifies persistence as well as mapping to XML-based formalisms, which use a mostly ISO 8601 compliant date/time representation. The ISO 8601 semantics assumed by EHR are defined in classes found in the classes ISO8601_DATE, ISO8601_TIME, ISO8601_DATE_TIME, ISO8601_DURATION, from the rm.support.assumed_types package. These classes are inherited into the corresponding classes defined below.
7.2.1 DV_TEMPORAL Class
CLASS | DV_TEMPORAL (abstract) | |
---|---|---|
Purpose | Specialised temporal variant of DV_ABSOLUTE_QUANTITY whose diff type is DV_DURATION. | |
Inherit | DV_ABSOLUTE_QUANTITY | |
Abstract | Signature | Meaning |
(redefined) | diff (other: like Current): DV_DURATION | Difference of two temporal quantities. |
Invariants |
7.2.2 DV_DATE Class
CLASS | DV_DATE |
Purpose | Represents an absolute point in time, as measured on the Gregorian calendar, and specified only to the day. Semantics defined by ISO 8601. |
Use | Used for recording dates in real world time. The partial form is used for approximate birth dates, dates of death, etc. |
ISO 18308 | STR 3.7 |
CEN | TOCD choice Quantifiable Observation Data Item |
Synapses | DTValue attribute of DateTime class (this does not distinguish the representation of dates and of times) |
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Data Types Information Model Date Time Package Rev 2.1.0
CLASS | DV_DATE | |
---|---|---|
GEHR | G1_DATE | |
HL7 | PointInTime (TS). Note that this type simply measures a number of seconds since an epoch, with a timezone. These values are convertable to y/m/d form via the calendar attribute of TS. | |
Inherit | DV_TEMPORAL, ISO8601_DATE | |
Functions | Signature | Meaning |
(effected) | diff (other: like Current): DV_DURATION | Difference of two dates. |
Attributes | Signature | Meaning |
value: String | ISO8601 date string | |
Functions | Signature | Meaning |
(effected) | magnitude: Integer ensure Result >= 0 | Numeric value of the date as days since the calendar origin point 1/1/0000 |
Invariants | Value_valid: valid_iso8601_date(value) |
7.2.3 DV_TIME Class
CLASS | DV_TIME |
Purpose | Represents an absolute point in time from an origin usually interpreted as meaning the start of the current day, specified to the second. Semantics defined by ISO 8601. |
Use | Used for recording real world times, rather than scientifically measured fine amounts of time. The partial form is used for approximate times of events and substance administrations. |
ISO 18308 | STR 3.7, 3.10 |
CEN | TOCD choice Quantifiable Observation Data Item |
Synapses | DTValue attribute of DateTime class (this does not distinguish the representation of dates and of times) |
GEHR | G1_TIME |
HL7 | PointInTime (TS). Note that this type simply measures a number of seconds since an epoch. These values are convertable to ymd form via the calendar attribute of TS. |
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Date Time Package Data Types Information Model Rev 2.1.0
CLASS | DV_TIME | |
---|---|---|
Inherit | DV_TEMPORAL, ISO8601_TIME | |
Functions | Signature | Meaning |
(effected) | diff (other: like Current): DV_DURATION | Difference of two times. |
Attributes | Signature | Meaning |
value: String | ISO8601 time string | |
Functions | Signature | Meaning |
(effected) | magnitude: Double ensure Result >= 0.0 | Numeric value of the time as seconds since the start of day. |
Invariants | Value_valid: valid_iso8601_time(value) |
7.2.4 DV_DATE_TIME Class
CLASS | DV_DATE_TIME | |
---|---|---|
Purpose | Represents an absolute point in time, specified to the second. Semantics defined by ISO 8601. | |
Use | Used for recording a precise point in real world time, and for approximate time stamps, e.g. the origin of a HISTORY in an OBSERVATION which is only partially known. | |
ISO 18308 | STR 3.7, 3.10 | |
CEN | TOCD choice Quantifiable Observation Data Item | |
OMG HDTF | COAS::DateTime | |
Synapses | DTValue attribute of DateTime class (this does not distinguish the representation of dates and of times) | |
GEHR | G1_DATE_TIME | |
HL7 | PointInTime (TS). Note that this type simply measures a number of seconds since an epoch, with a timezone. These values are convertable to y/m/d form via the calendar attribute of TS. | |
Inherit | DV_TEMPORAL, ISO8601_DATE_TIME | |
Functions | Signature | Meaning |
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CLASS | DV_DATE_TIME | |
---|---|---|
(effected) | diff (other: like Current): DV_DURATION | Difference of two date/times. |
Attributes | Signature | Meaning |
value: String | ISO8601 date/time string | |
Functions | Signature | Meaning |
(effected) | magnitude: Double ensure Result >= 0.0 | numeric value of the date/time as seconds since the calendar origin point. |
Invariants | Value_valid: valid_iso8601_date_time(value) |
7.2.5 DV_DURATION Class
CLASS | DV_DURATION | |
---|---|---|
Purpose | Represents a period of time with respect to a notional point in time, which is not specified. A sign may be used to indicate the duration is “backwards” in time rather than forwards. Note that a deviation from ISO8601 is supported, allowing the ‘W’ designator to be mixed with other designators. See assumed types section in the Support IM. | |
Use | Used for recording the duration of something in the real world, particularly when there is a need a) to represent the duration in customary format, i.e. days, hours, minutes etc, and b) if it will be used in computational operations with date/time quantities, i.e. additions, subtractions etc. | |
MisUse | Durations cannot be used to represent points in time, or intervals of time. | |
ISO 18308 | STR 3.10 | |
CEN | Time Interval or Date Range or text description (pt 4) | |
GEHR | G1_DATE_TIME_DURATION | |
HL7 | Interval of Point in Time, IVL<TS>. The width attribute provides the duration. IVL<TS> thus models an anchored duration. | |
Inherit | DV_AMOUNT, ISO8601_DURATION | |
Attributes | Signature | Meaning |
value: String | ISO8601 duration | |
Functions | Signature | Meaning |
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CLASS | DV_DURATION | |
---|---|---|
prefix ‘-’: like Current | Negated copy of current object. | |
(effected) | magnitude: Double | Numeric value of the duration in seconds. |
Invariants | Value_valid: valid_iso8601_duration(value) |
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© 2003-2007 The openEHR Foundation. email: info@openEHR.org web: http://www.openEHR.org
Data Types Information Model Time_specification Package Rev 2.1.0
Time specification is about potentiality rather than actuality, and needs its own types. The openEHR data_types.time_specification package provides such types, based on the HL7 types of the same names, and is illustrated in FIGURE 10 .
DATA_VALUE
(rm.data_types.basic)
DV_TIME_SPECIFICATION
value[1]: DV_PARSABLE calendar_alignment: String event_alignment: String institution_specified: Boolean
DV_GENERAL_TIME_ SPECIFICATION DV_PERIODIC_TIME_ SPECIFICATION
calendar_alignment: String calendar_alignment: String period: DV_DURATION
event_alignment: String event_alignment: String
institution_specified: Boolean institution_specified: Boolean
FIGURE 10 rm.data_types.time_specification Package
One of the difficulties with time is expressing future times, since potential occurrences, durations, repetitions cannot be expressed in the same way as actual time. Complicating the problem is the fact that humans tend to use very customary (i.e. calandar-anchored) ways of specifying time, such as “every second Tuesday”, or “ the first Sunday of the month”. In clinical medicine, future time is most commonly used to express when medications or other therapies are intended to take place. They are often anchored to the calendar, and can easily include repetitions.
As with other time types, there are both simple and complex cases to consider. One of the most common examples of time in the future is the timing for drug administrations, e.g. “once every four hours”. This could be represented as a simple periodic specification, consisting of a start point in time, a period, and a number of repetitions. The specification for taking blood sugar levels during a glucose test could be represented as a simple aperiodic series, e.g. “.5hr, 1hr, 2hr”. However, even common specifications for prescriptions e.g. “three times a day for seven days” start to become quite complex, for example, because “three times a day” might not mean literally 8 hours apart.
Some of the factors to consider in timing specifications are:
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Time_specification Package Data Types Information Model Rev 2.1.0
Because time is inherently “messy” (months do not all have the same number of days, leap years change the number of days in some years etc), and because the relationship we have with time can also be arbitrary (e.g. anchored to mealtimes etc), specifying linguistically obvious specifications formally is quite challenging.
The HL7 version 3 data types for time specification appear to allow for all of the required possibilities. The syntax is based on the ISO 8601 standard [9]. It provides types which express:
The HL7 syntax for time specification is encapsulated in equivalent openEHR types described here.
8.2.1 DV_TIME_SPECIFICATION Class
CLASS | DV_TIME_SPECIFICATION (abstract) | |
---|---|---|
Purpose | This is an abstract class of which all timing specifications are specialisations. Specifies points in time, possibly linked to the calendar, or a real world repeating event, such as “breakfast”. | |
ISO 18308 | STR 3.9 | |
Inherit | DATA_VALUE | |
Attributes | Signature | Meaning |
1..1 | value: DV_PARSABLE | the specification, in the HL7v3 syntax for PIVL or EIVL types. See below. |
Abstract | Signature | Meaning |
calendar_alignment: String | Indicates what prototypical point in the calendar the specification is aligned to, e.g. “5th of the month”. Empty if not aligned. Extracted from the ‘value’ attribute. |
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Data Types Information Model Time_specification Package Rev 2.1.0
CLASS | DV_TIME_SPECIFICATION (abstract) | |
---|---|---|
event_alignment: String | Indicates what real-world event the specification is aligned to if any. Extracted from the ‘value’ attribute. | |
institution_specified: Boolean | Indicates if the specification is aligned with institution schedules, e.g. a hospital nursing changeover or meal serving times. Extracted from the ‘value’ attribute. | |
Invariant | Value_valid: value /= Void |
8.2.2 DV_PERIODIC_TIME_SPECIFICATION Class
CLASS | DV_PERIODIC_TIME_SPECIFICATION | |
---|---|---|
Purpose | Specifies periodic points in time, linked to the calendar (phase-linked), or a real world repeating event, such as “breakfast” (event-linked). Based on the HL7v3 data types PIVL<T>and EIVL<T>. | |
Use | Used in therapeutic prescriptions, expressed as INSTRUCTIONs in the openEHR model. | |
ISO 18308 | STR 3.9 | |
CEN | The Duration data value class provides for the specification of time intervals, and also for a simple string description of the periodicity. | |
HL7 | PIVL<T>, EIVL<T> | |
Inherit | DV_TIME_SPECIFICATION | |
Functions | Signature | Meaning |
period: DV_DURATION ensure Result /= Void | The period of the repetition, computationally derived from the syntax representation. Extracted from the ‘value’ attribute. | |
calendar_alignment: String | Calendar alignment extracted from value. | |
event_alignment: String | Event alignment extracted from value. | |
institution_specified: Boolean | Extracted from value. | |
Invariant | Value_valid: value.formalism.is_equal(“HL7:PIVL”) or value.formal-ism.is_equal(“HL7:EIVL”) |
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Time_specification Package Data Types Information Model Rev 2.1.0
The syntactic form of phase-linked periodic time specifications (derived from the PIVL<T> spec HL7v3 ballot) is as follows.
“[” interval “]” “/” “(” difference “)” [ “@” alignment ] [ “IST” ]
Examples include:
11:10 AM. A parse specification is as follows:
phase_linked_time_spec: pure_phase_linked_time_spec | pure_phase_linked_time_spec “IST”
pure_phase_linked_time_spec: phase | phase “@” alignment
phase: interval “/” “(” difference “)”
alignment: “DW” | etc /* terms from “HL7::CalendarCycle” domain */
difference: /* ISO 8601 for time difference */
interval: “[” interval_spec “]”
interval_spec: “;” | “;” date_time | date_time “;” date_time | date_time “;”
date_time: /* ISO 8601 for date/time string yyyymmdd[hh[mm[ss]]] */
Examples of event-linked periodic time specifications include:
• "PC+[1h;1h]"= one hour after meal
• "HS-[50min;1h]" = one hour before bedtime for 10 minutes The following parse specification defines the syntax for event-related periodic time specifications.
event_linked_time_spec: event | event offset
event: “AC” | “ACD” | etc /* HL7 domain “HL7::TimingEvent” */
offset: "+" dur_interval | "-" dur_interval
dur_interval: /* ISO 8601 for duration interval */
Specifies points in time in a general syntax. Based on the HL7v3 GTS data type.
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Data Types Information Model Time_specification Package Rev 2.1.0
CLASS | DV_GENERAL_TIME_SPECIFICATION | |
---|---|---|
Use | ||
ISO 18308 | STR 3.9 | |
CEN | The Duration data value class provides for the specification of time intervals, and also for a simple string description of the periodicity. | |
HL7 | GTS | |
Inherit | DV_TIME_SPECIFICATION | |
Functions | Signature | Meaning |
calendar_alignment: String | Calendar alignment extracted from value. | |
event_alignment: String | Event alignment extracted from value. | |
institution_specified: Boolean | Extracted from value. | |
Invariant | Value_valid: value.formalism.is_equal(“HL7:GTS”) |
The class is the same structurally as the DV_TIME_SPECIFICATION parent. The syntax is the HL7 GTS syntax, defined by the following parse specification:
general_time_spec: symbol | union | exclusion
union: intersection ";" union | intersection
exclusion: exclusion "\" intersection
intersection: factor intersection | factor
hull: factor ".." hull | factor
factor: interval | phase_linked_time_spec | event_linked_time_spec | "(" general_time_spec ")"
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Time_specification Package Data Types Information Model Rev 2.1.0
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Data Types Information Model Encapsulated Package Rev 2.1.0
The data_types.encapsulated package contains classes representing data values whose internal structure is defined outside the EHR model, such as multimedia and parsable data. It is illustrated in FIGURE 11.
DATA_VALUE
(rm.data_types.basic)
There is a need to be able to include content in the EHR whose interior structure is not modelled in the EHR reference model, but instead documented by sufficient meta-data attributes for specific tools to process the data. Types of content in this category are as follows.
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Encapsulated Package Data Types Information Model Rev 2.1.0
be represented in syntax form - such as the unit strings used in quantities. The name of the formalism should be stored as meta-data.
Sufficient meta-data must be included with all of these types to enable a way for the content to be processed, typically by indicating either its type (e.g. “jpeg”, “word document”) or the name of a tool which can be used to process it. Important meta-data include:
Any encapsulated data item may be a summary, “thumbnail” or otherwise reduced form of an original content item found outside the EHR, in some other system or file-system.
Checksums must be expressible for those items for which a checksum is available, or for which the system generates checksums to improve the quality of its internal data transmissions.
The design approach used here is based on the following analysis.
These observations lead naturally to an abstract DV_ENCAPSULATED class, with two subtypes, DV_PARSABLE, for all content which is syntactic in nature, and DV_MULTIMEDIAfor everything else. Note that it is possible to imagine parsable content items which are large, stored in compressed form, and are themselves a summary of another item elsewhere on the web; such items can for practical purposes be represented as instances of DV_MULTIMEDIA, rather than DV_PARSABLE. The vast majority of parsable encapsulated data are expected to be short and stored in native textual form, e.g. fragments of XML or HTML.
The formal model of the classes DV_ENCAPSULATED and DV_MULTIMEDIA are closely based on the ED type from the HL7v3 data types specification.
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Data Types Information Model Encapsulated Package Rev 2.1.0
CLASS | DV_ENCAPSULATED (abstract) | |
---|---|---|
Purpose | Abstract class defining the common meta-data of all types of encapsulated data. | |
ISO 18308 | STR 2.6 | |
CEN | TBD | |
OMG HDTF | COAS::MultiMedia | |
HL7 | Encapsulated_data (ED) | |
Inherit | DATA_VALUE | |
Abstract | Signature | Meaning |
1..1 | size: Integer | Original size in bytes of unencoded encapsulated data. I.e. encodings such as base64, hexadecimal etc do not change the value of this attribute. |
Attributes | Signature | Meaning |
0..1 | charset: CODE_PHRASE | Name of character encoding scheme in which this value is encoded. Coded from openEHR Code Set “character sets”. Unicode is the default assumption in openEHR, with UTF-8 being the assumed encoding. This attribute allows for variations from these assumptions. |
0..1 | language: CODE_PHRASE | Optional indicator of the localised language in which the data is written, if relevant. Coded from openEHR Code Set “languages”. |
Functions | Signature | Meaning |
as_string: String | Result = alternate_text [(uri)] | |
Invariant | Size_positive: size >= 0 Language_valid: language /= Void implies code_set(Code_set_id_languages).has_code(language) Charset_valid: charset /= Void implies code_set(Code_set_id_character_sets).has_code(charset) |
A specialisation of DV_ENCAPSULATED for audiovisual and biosignal types. Includes further metadata relating to multimedia types which are not applicable to other subtypes of DV_ENCAPSULATED.
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Encapsulated Package Data Types Information Model Rev 2.1.0
CLASS | DV_MULTIMEDIA | |
---|---|---|
Use | ||
ISO 18308 | STR 3.1 | |
Synapses | The Bulky Data class provides for the representation and storage of all binary data classified by its MIME type. | |
GEHR | G1_MULTIMEDIA_DATA | |
HL7 | Encapsulated_data (ED) | |
Inherit | DV_ENCAPSULATED | |
Attributes | Signature | Meaning |
0..1 | alternate_text: String | Text to display in lieu of multimedia display/replay |
1..1 | media_type: CODE_PHRASE | Data media type coded from openEHR code set “media types” (interface for the IANA MIME types code set). |
0..1 | compression_algorithm: CODE_PHRASE | Compression type, a coded value from the openEHR “Integrity check” code set. Void means no compression. |
0..1 | integrity_check: Array <Octet> | Binary cryptographic integrity checksum |
0..1 (cond) | integrity_check_algorithm: CODE_PHRASE | Type of integrity check, a coded value from the openEHR “Integrity check” code set. |
0..1 | thumbnail: DV_MULTIMEDIA | The thumbnail for this item, if one exists; mainly for graphics formats. |
0..1 (cond) | uri: DV_URI | URI reference to electronic information stored outside the record as a file, database entry etc, if supplied as a reference. |
0..1 (cond) | data: Array <Octet> | The actual data found at uri, if supplied inline |
1..1 (effected) | size: Integer | Size in bytes of data, if present, or else of the object referred to by uri. |
Functions | Signature | Meaning |
is_external: Boolean ensure uri /= Void implies Result | Computed from the value of the uri attribute: True if the data is stored externally to the record, as indicated by `uri'. A copy may also be stored internally, in which case `is_expanded' is also true. |
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CLASS | DV_MULTIMEDIA | |
---|---|---|
is_inline: Boolean ensure data /= Void implies Result | Computed from the value of the data attribute: True if the data is stored in expanded form, ie within the EHR itself. | |
is_compressed: Boolean ensure compression_algorithm /= Void implies Result | Computed from the value of the compression_algorithm attribute: True if the data is stored in compressed form. | |
has_integrity_check: Boolean ensure integrity_check_algorithm /= Void implies Result | Computed from the value of the integrity_check_algorithm attribute: True if an integrity check has been computed. | |
Invariant | Not_empty: is_inline or is_external Media_type_validity: media_type /= Void and then code_set(Code_set_id_media_types).has_code(media_type) Compression_algorithm_validity: compression_algorithm /= Void implies code_set(Code_set_id_compression_algorithms). has_code(compression_algorithm) Integrity_check_validity: integrity_check /= Void implies integrity_check_algorithm /= Void Integrity_check_algorithm_validity: integrity_check_algorithm /= Void implies code_set(Code_set_id_integrity_check_algorithms). has_code(integrity_check_algorithm) |
9.2.3 DV_PARSABLE Class
CLASS | DV_PARSABLE | |
---|---|---|
Purpose | Encapsulated data expressed as a parsable String. The internal model of the data item is not described in the openEHR model in common with other encapsulated types, but in this case, the form of the data is assumed to be plaintext, rather than compressed or other types of large binary data. | |
Use | Used for representing values which are formal textual representations, e.g. guidelines. | |
ISO 18308 | (none) | |
Inherit | DV_ENCAPSULATED | |
Functions | Signature | Meaning |
1..1 (effected) | size: Integer | Size in bytes of value. |
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Encapsulated Package Data Types Information Model Rev 2.1.0
CLASS | DV_PARSABLE | |
---|---|---|
Attributes | Signature | Meaning |
1..1 | value: String | The string, which may validly be empty in some syntaxes |
1..1 | formalism: String | name of the formalism, e.g. “GLIF 1.0”, “proforma” etc. |
Invariant | value_valid: value /= Void formalism_validity: formalism /= Void and then not formalism.is_empty |
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© 2003-2007 The openEHR Foundation. email: info@openEHR.org web: http://www.openEHR.org
Data Types Information Model Uri Package Rev 2.1.0
The data_types.uri package includes two types used for referring to information resources. The DV_URI type allows data values which are references to objects on the world wide web to be created. Its specialisation, DV_EHR_URI, enables any element in an openEHR record to be identified in the same way as other objects on the web. The DV_EHR_URI type is convenient, because it is a string, like any other URI, and is therefore easily transportable and processable. Because it has its own scheme space, “ehr”, instances can be globally unique, as long as EHR identification is globally unique. DV_EHR_URIs are used to express all runtime paths in the EHR. The uri Package is illustrated in FIGURE 12.
DATA_VALUE
(rm.data_types.basic)
uri
DV_URI
value[1]: String scheme: String path: String fragment_id: String query: String
DV_EHR_URI
FIGURE 12 rm.data_types.uri Package
This package meets the requirement for a DATA_VALUE subtype which represents a W3C Uniform Resource Identifier (URI). A common example of where this might be used is to represent a reference to a clinical guideline or other justifying document associated with an intervention or treatment plan recorded in the EHR.
URIs are a superset of Uniform Resource Locators (URLs) (although the two are often confused, even within the W3C), and can be used to specify the location of any information item, regardless of its type, location or storage method, as long as a URI “scheme” exists for that type of information.
There is an additional requirement for a kind of URI that can point at an EHR data item, either inside the same EHR containing the link, or in another EHR. This is the basis of implementing the LINK type.
A simple design approach is used whereby a URI is represented as a String, and appropriate functions are defined to extract the various parts according to the syntax of URIs defined by Tim Berners-Lee at http://www.ietf.org/rfc/rfc2396.txt. An EHR specific subtype is defined, whose scheme is “ehr”, and which contains further attributes enabling the instances of the type to record what kind of object they are referring to.
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Uri Package Data Types Information Model Rev 2.1.0
The following symbolic definitions are used in the classes below.
• Ehr_scheme: String is “ehr”
10.3.1 DV_URI Class
CLASS | DV_URI | |
---|---|---|
Purpose | A reference to an object which conforms to the Universal Resource Identifier (URI) standard, as defined by W3C RFC 2936. See "Universal Resource Identifiers in WWW" by Tim Berners-Lee at http://www.ietf.org/rfc/rfc2396.txt. This is a World-Wide Web RFC for global identification of resources. See http://www.w3.org/Addressing for a starting point on URIs. See http://www.ietf.org/rfc/rfc2806.txt for new URI types like telephone, fax and modem numbers. | |
Use | Enables external resources to be referenced from within the content of the EHR. A number of functions return the logical subparts of the URI string. | |
MisUse | ||
CEN | TBD | |
OMG HDTF | COAS::TechnologyInstanceLocator | |
HL7 | TBD | |
Inherit | DATA_VALUE | |
Attributes | Signature | Meaning |
1..1 | value: String | Value of URI as a String. |
Functions | Signature | Meaning |
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Data Types Information Model Uri Package Rev 2.1.0
CLASS | DV_URI | |
---|---|---|
scheme: String | A distributed information "space" in which information objects exist. The scheme simultaneously specifies an information space and a mechanism for accessing objects in that space. For example if scheme = "ftp", it identifies the information space in which all ftpable objects exist, and also the application - ftp - which can be used to access them. Values may include: "ftp", "telnet", "mailto", "gopher" and many others. Refer to WWW URI RFC for a full list. New information spaces can be accommodated within the URI specification. | |
path: String | A string whose format is a function of the scheme. Identifies the location in <scheme>space of an information entity. Typical values include hierarchical directory paths for any machine. For example, with scheme = "ftp", path might be /pub/images/image_01. The strings "." and ".." are reserved for use in the path. Paths may include internet/intranet location identifiers of the form: sub_domain...domain, e.g. "info.cern.ch" | |
fragment_id: String | A part of, a fragment or a sub-function within an object. Allows references to sub-parts of objects, such as a certain line and character position in a text object. The syntax and semantics are defined by the application responsible for the object. | |
query: String | Query string to send to application implied by scheme and path Enables queries to applications, including databases to be included in the URI Any query meaningful to the server, including SQL. | |
Invariant | value_exists: value /= Void and then not value.is_empty |
10.3.2 DV_EHR_URI Class
CLASS | DV_EHR_URI |
Purpose | A DV_EHR_URI is a DV_URI which has the scheme name “ehr”, and which can only reference elements in EHRs. The syntax is described below. |
Use | Used to reference elements in an EHR, which may be the current one, or another. |
Inherit | DV_EHR_URI |
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CLASS | DV_EHR_URI | ||
---|---|---|---|
Functions | Signature | Meaning | |
Invariant | Scheme_is_ehr: scheme.is_equal(Ehr_scheme) |
The syntax of a DV_EHR_URI is an openEHR path, inside the “ehr” URI scheme-space, and is of the form:
“ehr://” ehr_path
The syntax of ehr_path is described in the section on Paths in The openEHR Architecture Overview document. DV_EHR_URIs are used as a mechanism for referencing in the EHR, ensuring readability by humans, as well as validity when extracts are transmitted elsewhere: even if the target of a path is not present, the path can be used to locate the missing item on demand.
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Data Types Information Model Implementation Strategies Rev 2.1.0
This section notes a few of the general challenges for mapping the openEHR data types to implementation technologies such as programming languages and XML. For specific guidelines, Implementation Technology Specification (ITS) document for each target formalism should be consulted.
In the quantity package, the type DV_QUANTIFIED is shown having an abstract property of type Ordered_numeric. This is intended to indicate that the type DV_QUANTIFIED is distinguished by the magnitude property (compared to say DV_ORDERED, which describes ordered things without having magnitudes). The type Ordered_numeric be mapped to various types in implementation technologies as follows:
• Eiffel: NUMERIC
All of these type systems currently suffer from not having a single type whose meaning is both “ordered” (having the function ‘<‘) and “numeric” (having the functions ‘+’, ‘-’, ‘*’, ‘/’) but in practice it does not matter much. For type systems with no convenient supertype of the numeric concrete types Real, Integer, Double, the magnitude property can safely be left out of DV_QUANTIFIED; the only drawback is that code cannot call DV_QUANTIFIED.magnitude polymmorphically, e.g. in a statistical application processing DV_QUANTITY and DV_COUNT objects.
Unicode is supported in various ways in different languages. In Java, since JDK 1.1, unicode support is implicit in the base classes. From the documentation:
the classes java.io.InputStreamReader, java.io.OutputStreamWriter, and
java.lang.String can convert between Unicode and a number of other character
encodings. More information is available at:
http://java.sun.com/j2se/1.3/docs/guide/intl/encoding.doc.html. In the C# language, conversion can be done between Unicode and other codepages using the System.Text.UnicodeEncoding (for UTF-16) and System.Text.UTF8Encoding (for UTF-8) classes.
In XML unicode is handled by specifying the encoding of the document in the XML declaration, e.g. <?xml version="1.0" encoding="UTF-16"?>.
In the Eiffel language, unicode is available in the Gobo public domain library (see http://www.gobosoft.com), in the UC_STRING class, which inherits from the String class.
The support in other languages varies, and may require a special type like the UC_STRING used in Eiffel.
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Implementation Strategies Data Types Information Model Rev 2.1.0
In some formalisms, dates and times are represented using a single calendar-like class. This is not considered to be good practice from the point of specification, since it is more difficult to state proper invariants for such a class used to represent a particular logical type such as a DATE or TIME, however, its utility in implementation is recognised.
Where implementors want to use such a class (call it CALENDAR here for the sake of discussion) the recommended approach is to wrap the class CALENDAR with classes representing the types described in this specification, i.e. DATE etc. This enables the addition of any necessary functionality in the wrapper for example, for serialising and deserialising in and out of XML.
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Data Types Information Model Comparison with HL7v3 Types Rev 2.1.0
Some HL7v3 types are not modelled in openEHR. HL7v3 V3DT types which are assumed by openEHR to exist in the underlying type system of any implementation technology include:
HL7v3 types which are not modelled here because they are almost always too volatile for concrete modelling, and can be created with archetyped generic information structures are as follows (even in HL7 they are really data structures rather than data types):
These types are all modelled by archetyped spatial data structures in openEHR (equivalent to subtypes of Structure in the CDA specification). HL7v3 types which may need to be modelled in the future include:
There are some significant differences in design approach between the openEHR data types and the HL7v3 data types, described in the following sections.
All types in the HL7 specification have two names, one short and one long. For example the type representing physical quantities is known both as “PhysicalQuantity” and “PQ”. While short names may be reasonable for often-used types, someshort names are not obvious, e.g. “EN”, “ON”, “TN”, “NPPD” etc. Short names certainly have benefits for drawing tools such as Rational Rose or other
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UML tools, however, it is questionable whether a formal model should include concept names chosen on the basis of visual appearance in such tools (one might argue that such tools should provide aliases for visual purposes, without changing the actual model). Another problem is that UML does not include the concept of class name aliases, nor do most programming languages.
The openEHR model uses one name only for each class.
The HL7 V3DT includes the types II, UID, OID and UUID. The II type is claimed to be for identifying all kinds of entities, which we here classify as real-world entities (“RWEs”) (such as people, vehicle registrations, invoices) and informational entities (“IEs”) - which in general are snapshots of data representing an RWE in a computer system. One problem with RWE identification schemes is that some are known (e.g. social security number) to produce fallible identifiers or situations where multiple RWEs have the same identifier, or no identifier at all. Conversely, with well-controlled and internationally agreed ways of issuing/generating information system identifiers (e.g. GUID, ISO OID) it is thought that such identifiers can be made reliable, and indeed correspond 1:1 with their intended IEs. However, a problem with IEs is that there are often duplicates and also multiple versions in time, each intended to represent the same RWE (such as a particular person, observation or composition).
As far as can be ascertained currently, there is no standard analysis taking into account the existence of IEs and RWEs, and recognising the fact that multiple versions and/or duplicates may refer to the same RWE.
The approach taken in openEHR with respect to identifiers is currently as follows.
The openEHR data types are defined on the assumption of archetype-based systems. While they will work perfectly well in systems which know nothing about archetyping, some types are not defined because archetypable structures built from more basic entities are assumed instead, rather than concretely modelled data types. These include “types” for address and person name which are found in HL7v3 and CEN 13606.
The HL7v3 data types do not make any assumptions about the existence of types typically built-in to most object and relational formalisms, such as the basic types String, Integer, Boolean, Real, Double, and the generic types Set<T>, Bag<T> and Array<T>. Hence, the types ST, INT, REAL, BL, SET<T>, BAG<T> and so on are redefined by HL7. The supposed advantage of this approach is that the semantics of all types in the HL7 system, right down to atomic data items are self-contained
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Data Types Information Model Comparison with HL7v3 Types Rev 2.1.0
in the definition, and do not rely on external semantics. Possible problems with this approach include the following.
In general, where differences exist between same-named types in HL7 and an underlying formalism such as a programming language, there is likely to be some confusion in implementation. Further, there is likely to be confusion in how to process instances of basic types which contain numerous (and sometimes recursive) fields which are not used in the standard specifications of basic types.
The openEHR approach with respect to inbuilt types is to assume only those types found in the mainstream object-oriented programming languages, and in particular, definitive formalisms like OMG IDL and XML. While this means there there is in theory less control over these types than in the HL7 approach, the number of types involved is quite small, and the problem of bindings to the basic types of object formalisms is well understood. Additionally, since it is recognised that some data types defined by openEHR could clash with types found in some languages and libraries, all data type class names are prefaced with “DV_” to avoid naming confusion, and to allow implementations of openEHR types to co-exist with existing types in implementation formalisms.
All HL7 data types inherit from the ANY class (equivalent to the DATA_VALUE class in openEHR) which contains the attributes:
BL nonNull;
CS nullFlavor;
BL isNull;
The purpose of these attributes is to indicate whether a datum is Null, and for what reason. Since some data type classes also appear as the attributes of other data types, the Null markers also indicate
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Comparison with HL7v3 Types Data Types Information Model Rev 2.1.0
whether any part of a datum is null. Thus, in the class Interval<T> shown below, all attributes have the possibility of containing a Null marker.
type Interval<T> alias IVL<T> extends Set<T>
{ T low;
BL lowClosed;
T high;
BL highClosed;
T.diff width;
T center;
IVL<T> hull(IVL<T> x); literal ST;
promotion IVL<T> (T x);
demotion T;
};
For example, this allows an interval with missing ends and width to exist as a structured type. The consequence of the approach is that the entire model is essentially a model of “partial” data types; any attribute and any function call may return a Null value, as well as the true values of its type (in fact, in the specification, Null values are defined to be valid values of all data types). This design decision was taken in HL7 so that any datum, no matter how unknown, would be structurally representable in the same way as completely known data, enabling it to be processed in the same way as all other instances of the same type.
However, an important object-oriented design principle has been ignored in this approach. In the proper design of classes, properties and class invariants are stated. Invariants are statements which describe the correctness conditions of instances of the class; the general rule is that the post-condition of a creation routine (constructor) of a class must be that the invariants are satisfied. For example, an invariant of the HL7 IVL<T> class could be:
(exists(low) and exists(high)) or else
(exists(low) and exists(width)) or else
(exists(width) and exists(high))
When an instance of this class is created, this condition should be satisfied, and remain satisfied for the life of the instance. To do otherwise is to create instances of data which other software can make no assumptions about, and is forced to check every single field, and then determine what to do in an ad hoc way. (See [6] p366, [4] p43, [5] p29 for detailed explanations of the invariant concept).
Possible consequences of the built-in Null marker design approach include:
The HL7 data type model is in contrast with simpler approaches such as used in CEN, GEHR, and openEHR, where data types are formal models of types such as Coded_term, Quantity and so on.
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Data Types Information Model Comparison with HL7v3 Types Rev 2.1.0
Rather than build the possibility of null markers into every attribute and class in the data types, a single null marker is defined in relevant containing classes. This decision is based on the principle that data types should be defined independently of their context of use. Hence, where data types are used as data values, such as in the value attribute of the class ELEMENT from the openEHR EHR reference model, the parallel features is_null and null_flavour are also defined. However, where data types appear as attributes elsewhere in the model and there is no possibility of them being null, no null markers are used. FIGURE 13 shows visually the difference between the two approaches.
Data Data Data Value #1 Value #2 Value #3
HL7 approach
Typical approach
The consequences of the standard software-engineering approach include:
In order to deal with the last possibility, various approaches are used in openEHR:
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A consequence of the HL7 model is that data instances represented in XML or another structured text format will be structurally the same regardless of whether there are Null values or not. A structured form for partially known data (which would normally break the invariants of its class) may well be useful for representing the data as part of a text field, making it easier to use for whatever processing is possible later on.
The approach in openEHR is to assume the existence of a Terminology Server which is the sole authoritative interface with terminologies of any kind, and is the only entity which can assume responsibility for querying, post-coordination or other manipulations of terms. No allowance is made for coordination of “modifiers”, “qualifiers” or any other terms outside the service. As a consequence, there are no coordination facilities in the type DV_CODED_TEXT, a departure from earlier versions of the specification - any term provided from the terminology service must already be “coordinated”, either by the terminology service, or by one of the terminologies it accesses. This places the responsibility of combining terms firmly in the knowledge part of the system, and prevents unsanctioned, unvalidated combinations being created elsewhere.
The HL7 specification uses a single TS type to represent all logical dates, times, date/times, and partial versions thereof. The openEHR specification defines distinct types for each, since these are the types which occur in the real world, and it is easier to specify correctness constraints with this approach. It is recognised that a single type may be used by some implementors (depending on what is available in the language being used), however, the recommended practice is to wrap any such types with the logical types described in this specification. This approach reduces the possibility for any errors in transmitted data (since no strange combinations of year, ... , second can occur not explicitly described in the type definitions).
The HL7 approach for time specification appears to cover all reasonable requirements, but has some minor problems, including:
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Data Types Information Model Comparison with HL7v3 Types Rev 2.1.0
peutic prescriptions have the form "do X every Y time", where the X describes what to do, and how long to do it for (e.g. 40 mins massage, administer a drug slowly over 10 mins). In fact, what we are really interested in with a timing specification is the specification of the starting points in time of some activity, not a time-based graph of on/off points, whch is effectively what the PIVL type is now.
The HL7v3 data types specification allows various type conversions, as follows:
Three kinds of type conversions are defined: promotion, demotion, and character string literals. Type conversions can be implicit or explicit. Implicit type conversion occurs when a certain type is expected (e.g. as an argument to a statement) but a different type is actually provided.
One notable kind of conversion possible in HL7 is of a value of any type T into an instance of Set<T>, List<T>, Bag<T> or IVL<T> containing the value.
The openEHR model does not provide for any type conversions other than those automatically available between inbuilt basic numeric types such as Integer, Float and Double, and between types related by inheritance, as supported by all object-oriented languages.
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Data Types Information Model References Rev 2.1.0
1 Berners-Lee T. "Universal Resource Identifiers in WWW". Available at ht tp://www.ietf.org/rfc/rfc2396.txt . This is a World-Wide Web RFC for global identification of resources. In current use on the web, e.g. by Mosaic, Netscape and similar tools. See http://www.w3.org/Addressing for a starting point on URIs.
2 Beale T. Archetypes: Constraint-based Domain Models for Future-proof Information Systems. See http://www.deepthought.com.au/it/archetypes.html .
3 Beale T et al. Design Principles for the EHR. See http://www.deepthought.com.au/openEHR .
4 Booch G. Object-Oriented Analysis and Design with applications. 2nd ed. Benjamin/Cummings 1994.
5 Kilov H. Information Modelling - an object-oriented approach. Prentice Hall 1994.
6 Meyer B. Object-oriented Software Construction, 2nd Ed. Prentice Hall 1997.
7 Richards E G. Mapping Time - The Calendar and its History. Oxford University Press 1998.
8 Schadow G, McDonald C J. The Unified Code for Units of Measure, Version 1.4, April 27, 2000. Regenstrief Institute for Health Care, Indianapolis. See http://aurora.rg.iu- pui.edu/UCUM
9 ISO 8601 standard describing formats for representing times, dates, and durations. See e.g. http://www.mcs.vuw.ac.nz/technical/software/SGML/doc/iso8601/ISO8601.html and ht tp://www.cl.cam.ac.uk/~mgk25/iso-time.html .
10 Dixon R, Grubb P, Lloyd D. EHCR Support Action Deliverable 3.5: "Final Recommendations to CEN for future work". Oct 2000. Available at http://www.chime.ucl.ac.uk/HealthI/EHCR SupA/documents.htm .
11 ENV 13606-1 - Electronic healthcare record communication - Part 1: Extended architecture. CEN/ TC 251 Health Informatics Technical Committee.
12 ENV 13606-2 -Electronic healthcare record communication - Part 2: Domain term list. CEN/ TC 251 Health Informatics Technical Committee.
13 ENV 13606-3 -Electronic healthcare record communication - Part 3: Distribution rules. CEN/ TC 251 Health Informatics Technical Committee.
14 Beale T, Heard S. GEHR Technical Requirements. See http://www.gehr.org/technical/require ments/gehr_requirements.html .
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References Data Types Information Model Rev 2.1.0
15 Schadow G, Biron P. HL7 version 3 deliverable: Version 3 Data Types. (2nd ballot 2002 version).
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