. 2023 Jul 27;18(7):e0280106. doi: 10.1371/journal.pone.0280106
Vincenzo Della Mea
1,2,#, Ann-Helene Almborg
3,4,#, Michela Martinuzzi
5,#, Samson W Tu
6,7,#, Andrea Martinuzzi
8,2,*,#
Editor: Ernesto Iadanza9
PMCID: PMC10374130PMID: 37498874
Abstract
The Family of International Classifications of the World Health Organization (WHO-FIC) currently includes three reference classifications, namely International Classification of Diseases (ICD), International Classification of Functioning, Disability, and Health (ICF), and International Classification of Health Interventions (ICHI). Recently, the three classifications have been incorporated into a single WHO-FIC Foundation that serves as the repository of all concepts in the classifications. Each classification serves a specific classification need. However, they share some common concepts that are present, in different forms, in two or all of them. For the WHO-FIC Foundation to be a logically consistent repository without duplicates, these common concepts must be reconciled. One important set of shared concepts is the representation of human anatomy entities, which are not always modeled in the same way and with the same level of detail. To understand the relationships among the three anatomical representations, an effort is needed to compare them, identifying common areas, gaps, and compatible and incompatible modeling. The work presented here contributes to this effort, focusing on the anatomy representations in ICF and ICD-11. For this aim, three experts were asked to identify, for each entity in the ICF Body Structures, one or more entities in the ICD-11 Anatomic Detail that could be considered identical, broader or narrower. To do this, they used a specifically developed web application, which also automatically identified the most obvious equivalences. A total of 631 maps were independently identified by the three mappers for 218 ICF Body Structures, with an interobserver agreement of 93.5%. Together with 113 maps identified by the software, they were then consolidated into 434 relations. The results highlight some differences between the two classifications: in general, ICF is less detailed than ICD-11; ICF favors lumping of structures; in very few cases, the two classifications follow different anatomic models. For these issues, solutions have to be found that are compliant with the WHO approach to classification modeling and maintenance.
Introduction
The Family of International Classifications of the World Health Organization (WHO-FIC) currently includes three reference classifications, namely:
ICD: the International Classification of Diseases
ICF: the International Classification of Functioning, Disabilities and Health
ICHI: the International Classification of Health Interventions
Each of the classifications covers a specific need that may arise when classifying the content of health documentation. Furthermore, while they share common principles, their structures depend in part on choices made at their initial design and development phases, which were done at different times and which in turn depend on knowledge and constraints defined at the times. In particular, the 11th revision of ICD [1] marks a departure from the paper-based model that led the development of the previous revisions, with a specific attention to information technology aspects, including proper formalization of the represented concepts, and a double-layered structure composed of an ICD-11 Foundation that includes all possible ICD-related information and one or more linearizations that represents different versions of the classification designed to satisfy specific use cases [2]. The ICD-11 experience informs the development of ICHI, which is the youngest classification of the family; on the other side, ICF might be considered the oldest one, as it is still oriented towards traditional paper-based usage, although recently it is subjected to some enhancement in the computerized direction [3, 4].
The most notable recent enhancement to the three classifications is that, following the development of a new architecture for ICD-11 [5], all of them have been incorporated into a single WHO-FIC Foundation [6] which is an integrated semantic network consisting of all of the knowledge related to the concepts in the three classifications. Formalized in the Web Ontology Language (OWL), the Foundation organizes concepts in polyhierarchies that have no residual terms. The concepts are structured according to a WHO-FIC Content Model [7] that specifies the necessary attributes, such as titles and definitions, of a concept; its lexical properties, such as synonyms and inclusions; and the logical organization of the hierarchies, such as the allowed and required post-coordination axes. Different classifications, such as ICF, ICHI, and versions of ICD-11 designed for different use cases, can be generated automatically as different linearizations according to their specifications in the Foundation. The WHO-FIC Foundation promises to be a modern terminology system that is both backward compatible with the traditional requirements of statistical classifications and also prepared for linking and mapping to other terminologies and ontologies. Currently, in this combined representation, ICD-11 and ICF concepts are represented separately, while ICHI, because of its recent provenance, references some ICD-11 and ICF concepts.
For the WHO-FIC Foundation to realize its promise, it needs to reorganize the ICD-11, ICHI, and ICF concepts so that they form a logically consistent and semantically integrated and linked whole. Even though they cover different needs, the classifications share common concepts that are currently present in different forms in the Foundation. ICF, for example, includes body functions such as “Sensation of pain” (b280) that are closely related to ICD-11’s pain symptoms. Furthermore, with the introduction of post-coordination [8], ICD-11 includes extension codes, such as anatomical entities and health devices, equipment and supplies, that are not in past versions of ICD and that increase the possibility of overlaps among the classifications. Identifying, characterizing, and harmonizing all the possible shared concepts is a huge and complex task. It is the aim of a current WHO effort to harmonize the shared concepts among the reference classifications of the family so that duplicates are removed and related concepts are organized in consistent hierarchies. Such harmonized concepts across classifications will facilitate the joint use of the classifications, for example in documenting disability characteristics of children in early intervention [9] or determining functioning and disability profiles of chronic stroke patients [10]. ICD-11 codes post-coordinated with anatomical details and ICF-coded data on body structure impairments can be made interoperable just as ICHI health intervention codes already use ICF body functions and activities and participation codes as targets. Such consistent coding practices will facilitate coordinated care and enhance data integration and analysis. These benefits to users of the classifications and of the Foundation cannot be realized until this harmonization is completed.
Identifying, characterizing, and harmonizing all the possible shared concepts is a huge and complex task. Groups in the WHO-FIC community are embarking on projects to identify areas of overlap among the classifications, to understand the use cases for different types of harmonization, to investigate methods for mapping the related concepts, and to organize the necessary workflow and governance to propose, consider, and approve necessary changes to the Foundation and to the classifications. However there is one set of concepts that is obviously shared and easy to recognize, i.e., human anatomy. In fact, an anatomical entity may define the site of a disease in ICD-11, the body structure subject to impairment in ICF, and also the target of some health interventions defined in ICHI. Thus, the harmonization of the anatomical entities in the three classifications presents a useful case study that will inform the larger harmonization work.
While they are present everywhere, it is not obvious that all the anatomical entities are modeled the same way and with the same level of detail in the three reference classifications. To understand the relationships among the three anatomical representations, an effort is needed to compare them, identifying common areas, gaps, and compatible and incompatible models. The work presented here contributes to this effort, focusing on the anatomy representations in ICF and ICD-11 at first.
The aims of the present paper are thus:
To identify anatomical detail as represented in ICF and ICD-11;
To compare the representations by setting relationships among specific entities;
To characterize the level of detail in each classification;
To characterize areas where the underlying modeling is different or even incompatible;
Finally, to suggest measures to be taken to harmonize and consolidate the representations.
While there exists a deeply formalized representation of anatomy, namely the Foundational Model of Anatomy [11], it is much too detailed for our goal, which is to harmonize the anatomical representations in the WHO-FIC Foundation, minimizing the changes needed to the classifications, with the aim of continuity and compatibility with current applications.
Methods
To understand the relationship between ICF and ICD-11 anatomy, we decided to begin by mapping anatomical entities in the two classifications. In particular, the specific areas considered were the ICF Body Structures, and the section of ICD-11 Extension codes called “Anatomic Detail”. Both have a partially heterogeneous hierarchical representation, including both partonomic and taxonomic relationships.
Expert mappings
An initial qualitative analysis showed that inside these subsets, some entities have exactly the same title, some others are named differently, and some others do not have a direct correspondence, because an entity explicitly mentioned in one classification may only be found as part of a larger, or as specialization of a more general entity in the other classification.
Thus, three experts were asked to identify, for each entity in the ICF Body Structures, one equivalent entity in the ICD-11 Anatomic Detail if possible; if not, one or more entities that could be considered broader_than or narrower_than. We opted for these generic relationships because they encompass both the partonomic and taxonomic views. Furthermore, for practical aims, we also subdivided the equivalence relationship in two subtypes: identical_to, when the title and concept was substantially the same, and synonym_of, when the title of the concept was different, yet equivalent. Matching has been attempted not only on the terminal entities in the hierarchy, but also for all the higher-level entities.
While this effort is not aimed at mapping electronic health records, when possible, the principles described in the WHO paper on mapping have been respected [12].
Classifications
The source list for ICF Body Structures was obtained from a ClaML representation of ICF version 2017 and included 321 entities. Of these 321, 103 were identified as residuals, i.e., categories of the kinds “not otherwise specified” or “other specified”. Residuals were not mapped, because semantically equivalent to the parent category.
The target ICD-11 list was composed by a subset of the Extension Codes [13], namely the “Anatomical Detail” branch, taken from the Foundation layer. It was not extracted in advance, but dynamically obtained through the ICD-11 API [14] when needed, as explained in the next paragraphs.
Software
To support the matching effort by the three experts, an ad-hoc web-based software has been developed. The main interface of the software shows the ICF Body Structures hierarchy on the left side, with the capability of selecting a kind of relationship among those previously mentioned, and the corresponding ICD-11 entity, for each ICF entity. The ICD-11 entity is identified by accessing an instance of the ICD-11 Foundation coding tool [14] on the right side, set to automatically search for the ICF title in the ICD-11 Foundation, Extension Codes chapter, “Anatomic Detail” branch. However, since this could not always be found, the expert may also edit the search term with synonyms that might be present in ICD-11. Fig 1 shows a screenshot from the Map Editor.
Fig 1. On the left side, part of ICF Body Structures.
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To reduce the effort needed, the software has a module that automatically identifies straightforward relationships, i.e., those where titles are identical, or obvious synonyms. Among the latter, many entities in ICF are named as “Structure of X”, which were automatically mapped as synonyms of “X” if available in ICD-11. Technically “structure of X” is not synonymous with “X.” However, given that parent/child links in both ICD-11 anatomy extension codes and ICF body structures are a mix of taxonomic and partonomic relationship, identifying “structure of X” with “X” yields the most economical set of maps. As an example, ‘Structure of brain’ from ICF is automatically mapped as synonym_of ‘Brain’ in ICD-11.
While doing their work, experts do not see matches already found by the others, in order to allow the computation of a measure of inter-observer agreement.
Another interface shows a tree representation of the ICF Body Structures, with color codings for the different relationships, when available. Fig 2 shows a screenshot depicting part of the ICF Body Structures tree with mappings.
Fig 2. Part of the tree view of the ICF Body Structure, with color-coded matches towards ICD-11.
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Finally, a further module allows the export of matches to a CSV file for further processing.
Results
Of 218 entities considered in the source list and excluding residuals, 113 were found by software to have identical corresponding entities in the ICD-11 Anatomic Detail extension, basing on lexical criteria.
Three independent knowledgeable raters considered the 105 entities for which the tool did not automatically confirm identity matches. The search for the most appropriate matching entity could result in finding identical, equivalent, broader or narrower items or no match. The three mappers independently produced 631 maps to a total of 297 ICD-11 entities, independently and without accessing others’ maps until the end of the experiment. For all the ICF entities, at least one expert found a map in ICD-11. Table 1 shows a breakdown of the experts’ mappings. While identical_to and synonym_of maps were collected, for the sake of simplicity, and considering that they are semantically the same, for the analysis they were collapsed in a single equivalent_to category.
Table 1. Mappings proposed by each expert.
Mapper/Relations | equivalent_to | broader_than | narrower_than | total |
---|---|---|---|---|
A | 50 | 106 | 11 | 167 |
B | 55 | 226 | 26 | 307 |
C | 36 | 84 | 37 | 157 |
Total | 141 | 416 | 74 | 631 |
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Interobserver agreement
Among the 26 in disagreement, some typical examples are as follows:
Bronchial tree in ICF equivalent_to or broader_than Bronchus in ICD-11;
Vaginal canal in ICF equivalent_to or narrower_than Vagina in ICD-11;
Ligaments and fasciae of hand in ICF broader_than or narrower_than Ligament of the wrist and hand in ICD-11.
On the other side, by considering the 115 mapped ICF categories, some further differences became visible due to different choices in narrower_than or broader_than relationships (for example, obvious or redundant broader_than relationships). This involved the same ICF source, but possibly different ICD-11 targets. Examples from a total of 12 cases are:
Structure of diencephalon narrower_than Supratentorial region of brain
narrower_than Brain: this one is redundant
broader_than Thalamus
Structure of skin glands broader_than Sebaceous gland
broader_than Apocrine sweat gland
broader_than Eccrine gland
narrower_than Skin
Atria equivalent_to Cardiac atrium
broader_than Right atrium
Discrepancies were examined by the experts to delete from the final set the maps on which there was not an agreement, that were redundant, or that were mistakes.
Mapping details
The mappings have been consolidated in a single set of agreed-upon relationships, including automatically calculated equivalencies.
In order to obtain a consolidated mapping, we prioritized relationships as follows. First of all, if there is agreement on an equivalency, it is considered as the selected relationship, even if others are available. Without an equivalency, if a narrower_than relationship is available, that will be selected. Finally, broader_than relationships are selected.
After this step, the consolidated mappings are as described in Table 2.
Table 2. Consolidated mappings.
Relations | equivalent_to | broader_than | narrower_than | total |
---|---|---|---|---|
Consolidated maps | 164 | 230 | 40 | 434 |
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Discussion
The common Foundation from which the various WHO reference classifications are derived through linearizations requires that every entity be uniquely and unambiguously defined. This might require a process of harmonization of concepts that share similar meanings but may or may not be identical, also to favor joint use of the reference classifications. The process may be more or less complex according to the entities considered but could be easier for entities already sharing strong similarities. For further automatic mappings of concepts that may not be of the same semantic types, lexical mappings resulting in identical maps need to be evaluated to make sure that the concepts are identical. The “low hanging fruits” of harmonization include the anatomy entities as described in ICD-11 and in the body structure domain of ICF, which have been the subject of this paper.
Three main issues arise from this experiment are as follows:
Different levels of specificity: in general, ICF is less detailed than ICD (74 narrower_than vs 416 broader_thanmaps);
ICF favors lumping of structures: e.g. “The eye, ear and related structures”; “Structures of cardiovascular, immunological and respiratory systems”; “Structure of vagina and external genitalia”; “Testes and scrotum”;
The two classifications may have different anatomic models: e.g., Where is the shoulder? For ICD: in upper extremity; for ICF: in structures related to movement.
For these issues, solutions have to be found that are compliant with WHO’s new approach to classification modeling and maintenance, which includes the concept of a common Foundation that integrates all the relevant entities in a coherent terminological system based on semantic web technology. Versions of traditional classifications are generated from the Foundation as linearizations.
Issue A does not represent a real problem: according to the approach for creating linearizations from the Foundation, the “boundary” of specificity is called “shoreline”; and to select different specificities, it is only a matter of defining a different shoreline for each classification. Thus, ICD-11’s shoreline for anatomical concepts will include more detailed concepts than that of ICF.
Issue B might have two different solutions. The solution with least impact, from the point of view of classifications, is to introduce the ICF groupings as new groupings in the Foundation’s Anatomic Detail, while not using them in the ICD-11 linearization. However, such groupings are often heterogeneous and missing a strong semantic similarity (e.g., “The eye, ear and related structures”), and are present only for the sake of aggregation in a classification that was born with a printed edition in mind, but can be useful for aggregation of data at a higher level. Thus, the ideal solution would be to revise the hierarchy organization in ICF, without modifying terminal entities, in order to split heterogeneous groupings into more semantically homogeneous groups.
Issue C is apparently the most complex: different models may mean a totally different hierarchy, and such differences in modeling is intrinsic in the different points of view expressed by ICF and ICD (the former centered on functioning, the latter on clinical aspects). Fig 3 shows a clear and compelling example: in ICF terms, mouth and nose are structures devoted to speech, while in ICD terms, mouth is part of the digestive system, and nose of the respiratory system. Both views are perfectly reasonable, yet both miss the aspect evidentiated by the other classification. Nevertheless, both views may be accommodated in the WHO-FIC Foundation, which differs from traditional classifications in that it allows for multiple parenthood relationships. The use of multiple parents might enable us to express the different views without forcing one classification to adopt the point of view of the other and leaving to the linearization phase the choice of one or the other parent in each classification.
Fig 3. Nose and mouth have different parents in ICF and in ICD-11.
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This work makes three-fold contributions: first, it presents a principled exemplar of an approach to design and conduct terminological mappings; second, it uncovers specific commonalities and discrepancies between the anatomical concepts in ICD-11 and ICF and proposes methods to harmonize them in the context of the WHO-FIC Foundation; third, it pioneered the tools and methods, and provides the first results of a larger program of work to map, integrate, and link concepts in the three core WHO-FIC classifications. Future work will investigate the relationships such as those between ICHI’s anatomical targets and ICD-11’s Anatomical Detail extension codes, between impairments of ICF body functions and ICD-11 signs and symptoms, and between ICF activities and participations and ICD-11 dimensions of external causes, among others. Just as we developed the web-based software to assist subject matter experts performing the mappings, we will investigate additional automated methods to map related concepts, possibly leveraging previously validated mappings as training sets.
The consolidated maps are made available in SSOM format [15] at https://github.com/whoficitc/harmonization/blob/main/ICF-ICD-anatomy-v1.tsv.
Conclusion
The mapping of anatomical concepts in the ICF body structures domains and ICD-11 Anatomy and Topography extension codes yields insights into how the two classifications treat the representation of anatomy structures differently. We present methods for reconciling the differences. The case study points to the way additional work harmonizing the concepts in ICD-11, ICF, and ICHI may be conducted.
Acknowledgments
The support of the Italian Ministry of Health to AM (RC2021-22-23) is gratefully acknowledged.
Data Availability
All relevant data, including consolidated maps, are made available in SSOM format from the GitHub repository (https://github.com/whoficitc/harmonization/blob/main/ICF-ICD-anatomy-v1.tsv).
Funding Statement
Funder Name: Ministero della Salute (Italian Ministry of Health) Grant Number: RC2021-22 Grant Recipient: dr Andrea Martinuzzi The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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PLoS One. doi: 10.1371/journal.pone.0280106.r001
Ernesto Iadanza
16 Jan 2023
PONE-D-22-34808Harmonization of ICF Body Structures and ICD-11 Anatomic Detail: one foundation for two classificationsPLOS ONE
Dear Dr. Martinuzzi,
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Reviewer #1:It's always a useful step to begin creating such links across classification systems, and this appears to be a responsible, exploratory effort to begin building those bridges of equivalence and similarity where existing terminologies and hierarchies permit. However, this represents an admittedly small subset (434 relations) of all the complex and dnamic relationships that exist between the FIC terminologies. ICF has 1400 categories, and ICD-11 has 17,000 unique codes and more than 120,000 codable terms. If we consider the varieties of co-morbid conditions where multiple anatomical, physiological, and interventional factors may interact, our models will require both broader and more precise classifications. It's not clear to me what clinical advantage is gained by mapping 434 relations, in the midst of so many other un-mapped relations. It would be helpful in the Abstract to specify what specific scientific or clinical benefits can be expected from this improved cross-classification mapping.
I'm also a bit concerned about the accepted constraints implicit in the harmonization initiative, which prioritize compliance "with the WHO approach to classification modeling and maintenance." This risks constraining future terminologies and relationships within pre-existing frameworks which may simply be, or become, outdated or too crude to represent emerging complexities of scientific discoveries (e.g., chemotherapy vs. bioelectric field therapeutics). The "least common denominator" of harmony may end up giving us classification models that are less usefully precise.
Finally, I think we need to consider the growing relevance of semantic web data science and graph knowledge-base technologies as relevant platforms for making the vast scope of medical classifications and individual patient informatics more dynamically evolvable, make research more precisely and rapidly searchable, and make health informatics more interoperable. WHO's operational conservatism in classification may be locking the world of clinical research and services into obsolescent relational database frameworks of classification that will increasingly not mirror the dynamism and complex interdependencies of human health, Social Determinants of Health, clinical sciences and technological innovation.
Reviewer #2:The authors describe the three WHO classification systems (ICD-11, ICF, ICHI) and their different usage. Developed a user-friendly interface for coders to map the ICD-11 with ICF. Elaborated on the detail different between ICD-11 and ICF in anatomy entities.
The article needs to be revised majorly for publication:
1. Describe the usage of this harmonization? Where and under what situation will the scientists or healthcare workers/administrators use this?
2. Consider artificial intelligence methods. Use the experts’ results as training data for developing a model to reduce the experts’ efforts.
3. Map ICD-11, ICF and ICHI.
4. Supplement the Conclusion part.
5. Describe the innovation of this research.
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Reviewer #1:No
Reviewer #2:Yes:Qiong Wang
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PLoS One. 2023 Jul 27;18(7):e0280106. doi: 10.1371/journal.pone.0280106.r002
15 Feb 2023
see attached document
Attachment
Submitted filename: Response to PLOS Reviewers.docx
Click here for additional data file. (16.5KB, docx)
PLoS One. doi: 10.1371/journal.pone.0280106.r003
Ernesto Iadanza
14 Mar 2023
PONE-D-22-34808R1Harmonization of ICF Body Structures and ICD-11 Anatomic Detail: one foundation for multipleclassificationsPLOS ONE
Dear Dr. Martinuzzi,
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Reviewer #2:All comments have been addressed
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Reviewer #2:I deeply appreciate the authors' efforts in advancing the WHO-FIC through their work. It’s always useful to start from the coding step to try to manage and utilize healthcare data. But the author did not expound on the significance of their work. The WHO-FIC Foundation initially comprised the International Classification of Diseases (ICD), International Classification of Functioning, Disability and Health (ICF), and International Classification of Health Interventions (ICHI), which were designed to categorize distinct domains of health information. From a statistical and data analysis perspective, it is unclear how their work will be used in the future. In terms of medical terminology, pairing ICD and ICF appears to conflict with the primary aim of separating different fields of classification. It is worth noting that the citation does not indicate that the WHO-FIC Foundation intends to amalgamate the three coding systems.
Based on my understanding, the involvement of human interaction in the development of natural language processing (NLP) methods for healthcare is critical but can be both time and cost-intensive. If the authors make their data publicly available, it could prove to be a valuable resource for training NLP methods. In this regard, I would encourage the authors to present their matching results in such a way that they could serve as golden standards for algorithm training, particularly with regard to entity recognition.
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Reviewer #2:Yes:Qiong Wang
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While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool,https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS atfigures@plos.org. Please note that Supporting Information files do not need this step.<quillbot-extension-portal></quillbot-extension-portal>
PLoS One. 2023 Jul 27;18(7):e0280106. doi: 10.1371/journal.pone.0280106.r004
31 Mar 2023
see the attached document and also below:
Reviewer #2: I deeply appreciate the authors' efforts in advancing the WHO-FIC through their work. It’s always useful to start from the coding step to try to manage and utilize healthcare data. But the author did not expound on the significance of their work. The WHO-FIC Foundation initially comprised the International Classification of Diseases (ICD), International Classification of Functioning, Disability and Health (ICF), and International Classification of Health Interventions (ICHI), which were designed to categorize distinct domains of health information. From a statistical and data analysis perspective, it is unclear how their work will be used in the future. In terms of medical terminology, pairing ICD and ICF appears to conflict with the primary aim of separating different fields of classification. It is worth noting that the citation does not indicate that the WHO-FIC Foundation intends to amalgamate the three coding systems.
>> Response
ICD, ICF, and ICHI, while each focusing on its specific health and health care domains, are designed to complement each other, not artificially separated. There are already closely related concepts in the classifications, for example, between ICF’s pain body functions and sensation and ICD-11’s pain symptoms. Especially with the introduction of extension codes in ICD-11, there are significant overlaps in the coverage of the three classifications. With joint use of the classifications, collected data need to be consistent (e.g., ICD-11 codes with anatomical details and ICF body structure impairment). Consistent coding practices in joint use of the classifications will facilitate coordinated care and enhance data integration and analysis. In the revised paragraph in the Introduction, we make these points explicitly and cite a couple examples of the joint use of ICD and ICF.
For the WHO-FIC Foundation to realize its promise, it needs to reorganize the ICD-11, ICHI, and ICF concepts so that they form a logically consistent and semantically integrated and linked whole. Even though they cover different needs, the classifications share common concepts that are currently present in different forms in the Foundation. ICF, for example, includes body functions such as “Sensation of pain” (b280) that are closely related to ICD-11’s pain symptoms. Furthermore, with the introduction of post-coordination (8), ICD-11 includes extension codes, such as anatomical entities and health devices, equipment, and supplies, that are not in past versions of ICD and that increase the possibility of overlaps among the classifications. Identifying, characterizing, and harmonizing all the possible shared concepts is a huge and complex task. It is the aim of a current WHO effort to harmonize the shared concepts among the reference classifications of the family so that duplicates are removed and related concepts are organized in consistent hierarchies. Such harmonized concepts across classifications will facilitate the joint use of the classifications, for example in documenting disability characteristics of children in early intervention (9) or determining functioning and disability profiles of chronic stroke patients (10). ICD-11 codes post-coordinated with anatomical details and ICF-coded data on body structure impairments can be made interoperable just as ICHI health intervention codes already use ICF body functions and activities and participation codes as targets. Such consistent coding practices will facilitate coordinated care and enhance data integration and analysis. These benefits to users of the classifications and of the Foundation cannot be realized until this harmonization is completed.
(8) Mabon K, Steinum O, Chute CG. Postcoordination of codes in ICD-11. BMC Med Inform Decis Mak. 2022;21(Suppl 6):379.
(9) Martins EF, de Sousa PH, Barbosa PH, de Menezes LT, Costa AS. A Brazilian experience to describe functioning and disability profiles provided by combined use of ICD and ICF in chronic stroke patients at home-care. Disabil Rehabil. 2011;33(21-22):2064-74.
(10) Simeonsson RJ, Scarborough AA, Hebbeler KM. ICF and ICD codes provide a standard language of disability in young children. J Clin Epidemiol. 2006;59(4):365-73.
We are surprised that the reviewer said "the citation does not indicate that the WHO-FIC Foundation intends to amalgamate the three coding systems.” While the integration of the three classification in a single WHO-FIC Foundation is work in progress and is not yet described in journal publications, the Foundation reference (#6 in the reviewed submission) points to a web page that clearly shows that the three classifications are in the Foundation. If the reviewer’s point is that the three classifications will continue to exist as separate classifications for coding, that is true, but misses the point that they should be generated as linearizations from the single WHO-FIC Foundation where all of the classification concepts are amalgamated and made consistent.
>> Reviewer’s comment
Based on my understanding, the involvement of human interaction in the development of natural language processing (NLP) methods for healthcare is critical but can be both time and cost-intensive. If the authors make their data publicly available, it could prove to be a valuable resource for training NLP methods. In this regard, I would encourage the authors to present their matching results in such a way that they could serve as golden standards for algorithm training, particularly with regard to entity recognition.
>> Response
As stated in the reviewed manuscript "The consolidated maps are made available in SSOM format (12) at https://github.com/whoficitc/harmonization/blob/main/ICF-ICD-anatomy-v1.tsv.” SSOM format is a simple tabular structure that is easy for anyone who wants to re-use the data to reformat for their purpose.
Attachment
Submitted filename: 2nd Response to PLOS Reviewers Comments.docx
Click here for additional data file. (15.2KB, docx)
PLoS One. doi: 10.1371/journal.pone.0280106.r005
Ernesto Iadanza
10 Apr 2023
Harmonization of ICF Body Structures and ICD-11 Anatomic Detail: one foundation for multipleclassifications
PONE-D-22-34808R2
Dear Dr. Martinuzzi,
We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.
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Kind regards,
Ernesto Iadanza
Academic Editor
PLOS ONE
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Reviewers' comments:
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PLoS One. doi: 10.1371/journal.pone.0280106.r006
Ernesto Iadanza
13 Apr 2023
PONE-D-22-34808R2
Harmonization of ICF Body Structures and ICD-11 Anatomic Detail: One Foundation for Multiple Classifications
Dear Dr. Martinuzzi:
I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.
If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.
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on behalf of
Dr. Ernesto Iadanza
Academic Editor
PLOS ONE
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Attachment
Submitted filename: Response to PLOS Reviewers.docx
Click here for additional data file. (16.5KB, docx)
Attachment
Submitted filename: 2nd Response to PLOS Reviewers Comments.docx
Click here for additional data file. (15.2KB, docx)
Data Availability Statement
All relevant data, including consolidated maps, are made available in SSOM format from the GitHub repository (https://github.com/whoficitc/harmonization/blob/main/ICF-ICD-anatomy-v1.tsv).