CC BY-NC-ND 4.0 · Yearb Med Inform 2022; 31(01): 228-235
DOI: 10.1055/s-0042-1742509
Section 9: Knowledge Representation and Management

Achieving Inclusivity by Design: Social and Contextual Information in Medical Knowledge

Janna Hastings
1   Department of Clinical, Educational and Health Psychology, University College London, UK
2   Institute for Intelligent Interacting Systems, Otto-von-Guericke University Magdeburg, Germany
› Author Affiliations


Objectives: To select, present, and summarize the most relevant papers published in 2020 and 2021 in the field of Knowledge Representation and Knowledge Management, Medical Vocabularies and Ontologies, with a particular focus on health inclusivity and bias.

Methods: A broad search of the medical literature indexed in PubMed was conducted. The search terms 'ontology'/'ontologies' or 'medical knowledge management' for the dates 2020-2021 (search conducted November 26, 2021) returned 9,608 records. These were pre-screened based on a review of the titles for relevance to health inclusivity, bias, social and contextual factors, and health behaviours. Among these, 109 papers were selected for in-depth reviewing based on full text, from which 22 were selected for inclusion in this survey.

Results: Selected papers were grouped into three themes, each addressing one aspect of the overall challenge for medical knowledge management. The first theme addressed the development of ontologies for social and contextual factors broadening the scope of health information. The second theme addressed the need for synthesis and translation of knowledge across historical disciplinary boundaries to address inequities and bias. The third theme encompassed a growing interest in the semantics of datasets used to train medical artificial intelligence systems and on how to ensure they are free of bias.

Conclusions: Medical knowledge management and semantic resources have much to offer efforts to tackle bias and enhance health inclusivity. Tackling inequities and biases requires relevant, semantically rich data, which needs to be captured and exchanged.

Publication History

Article published online:
02 June 2022

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  • References

  • 1 Mishra V, Seyedzenouzi G, Almohtadi A, Chowdhury T, Khashkhusha A, Axiaq A, et al. Health Inequalities During COVID-19 and Their Effects on Morbidity and Mortality. J Healthc Leadersh 2021 Jan 19;13:19-26.
  • 2 The Lancet. Global health: time for radical change? Lancet 2020 Oct 17;396(10258):1129.
  • 3 Fontanet A, Autran B, Lina B, Kieny MP, Karim SSA, Sridhar D. SARS-CoV-2 variants and ending the COVID-19 pandemic. Lancet 2021 Mar 13;397(10278):952-954.
  • 4 Cao Y, Wang J, Jian F, Xiao T, Song W, Yisimayi A, et al. Omicron escapes the majority of existing SARS-CoV-2 neutralizing antibodies. Nature. 2022 Feb;602(7898):657-63.
  • 5 Verspoor K. The Evolution of Clinical Knowledge During COVID-19: Towards a Global Learning Health System. Yearb Med Inform 2021 Aug;30(1):176-84.
  • 6 Braveman P, Gottlieb L. The social determinants of health: it's time to consider the causes of the causes. Public Health Rep 2014 Jan-Feb;129 Suppl 2(Suppl 2):19-31.
  • 7 Weissman DG, Hatzenbuehler ML, Cikara M, Barch D, McLaughlin KA. Antipoverty programs mitigate socioeconomic disparities in brain structure and psychopathology among U.S. youths [Internet]. PsyArXiv; 2021 [cited 2021 Dec 1]. Available from:
  • 8 Buckeridge DL. Precision, Equity, and Public Health and Epidemiology Informatics - A Scoping Review. Yearb Med Inform 2020 Aug;29(1):226-30.
  • 9 Weir RC, Proser M, Jester M, Li V, Hood-Ronick CM, Gurewich D. Collecting Social Determinants of Health Data in the Clinical Setting: Findings from National PRAPARE Implementation. J Health Care Poor Underserved 2020;31(2):1018-35.
  • 10 Breen N, Berrigan D, Jackson JS, Wong DWS, Wood FB, Denny JC, et al. Translational Health Disparities Research in a Data-Rich World. Health Equity 2019 Nov 8;3(1):588-600.
  • 11 Golembiewski E, Allen KS, Blackmon AM, Hinrichs RJ, Vest JR. Combining Nonclinical Determinants of Health and Clinical Data for Research and Evaluation: Rapid Review. JMIR Public Health Surveill 2019 Oct 7;5(4):e12846.
  • 12 McDonald CJ, Huff SM, Suico JG, Hill G, Leavelle D, Aller R, et al. LOINC, a universal standard for identifying laboratory observations: a 5-year update. Clin Chem 2003 Apr;49(4):624-33.
  • 13 Millar J. The Need for a Global Language - SNOMED CT Introduction. Stud Health Technol Inform 2016;225:683-5.
  • 14 International Health Terminology Standards Development Organization. Systematized Nomenclature of Medicine – Clinical Terms (SNOMED-CT); 2022.
  • 15 World Health Organization. International Classification of Diseases and Related Health Problems [Internet]. Twelth. World Health Organization; 2020. Available from:
  • 16 Arons A, DeSilvey S, Fichtenberg C, Gottlieb L. Documenting social determinants of health-related clinical activities using standardized medical vocabularies. JAMIA Open 2018 Dec 24;2(1):81-8.
  • 17 Watkins M, Viernes B, Nguyen V, Rojas Mezarina L, Silva Valencia J, Borbolla D. Translating Social Determinants of Health into Standardized Clinical Entities. Stud Health Technol Inform 2020 Jun 16;270:474-8.
  • 18 Jani A, Liyanage H, Okusi C, Sherlock J, Hoang U, Ferreira F, et al. Using an Ontology to Facilitate More Accurate Coding of Social Prescriptions Addressing Social Determinants of Health: Feasibility Study. J Med Internet Res 2020 Dec 11;22(12):e23721.
  • 19 Kronk CA, Dexheimer JW. Development of the Gender, Sex, and Sexual Orientation ontology: Evaluation and workflow. J Am Med Inform Assoc 2020 Jul 1;27(7):1110-5.
  • 20 Smith B, Ashburner M, Rosse C, Bard J, Bug W, Ceusters W, et al. The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol 2007 Nov;25(11):1251-5.
  • 21 Michie S, Thomas J, Mac Aonghusa P, West R, Johnston M, Kelly MP, et al. The Human Behaviour-Change Project: An artificial intelligence system to answer questions about changing behaviour. Wellcome Open Res 2020 Jun 10;5:122.
  • 22 Wright AJ, Norris E, Finnerty AN, Marques MM, Johnston M, Kelly MP, et al. Ontologies relevant to behaviour change interventions: a method for their development. Wellcome Open Res 2020 Dec 18;5:126.
  • 23 Michie S, West R, Finnerty AN, Norris E, Wright AJ, Marques MM, et al. Representation of behaviour change interventions and their evaluation: Development of the Upper Level of the Behaviour Change Intervention Ontology. Wellcome Open Res 2021 Jan 6;5:123.
  • 24 Norris E, Marques MM, Finnerty AN, Wright AJ, West R, Hastings J, et al. Development of an Intervention Setting Ontology for behaviour change: Specifying where interventions take place. Wellcome Open Res 2020 Jun 10;5:124.
  • 25 Marques MM, Carey RN, Norris E, Evans F, Finnerty AN, Hastings J, et al. Delivering Behaviour Change Interventions: Development of a Mode of Delivery Ontology. Wellcome Open Res 2021 Feb 26;5:125.
  • 26 Norris E, Wright AJ, Hastings J, West R, Boyt N, Michie S. Specifying who delivers behaviour change interventions: development of an Intervention Source Ontology. Wellcome Open Res 2021 Apr 8;6:77.
  • 27 Bolock AE, Abdennadher S, Herbert C. An Ontology-Based Framework for Psychological Monitoring in Education During the COVID-19 Pandemic. Front Psychol 2021 Jul 22;12:673586.
  • 28 Chen Y, Yu C, Liu X, Xi T, Xu G, Sun Y, et al. PCLiON: An Ontology for Data Standardization and Sharing of Prostate Cancer Associated Lifestyles. Int J Med Inform 2021 Jan;145:104332.
  • 29 NCIt Developers. NCI Thesaurus OBO Edition: Disease or Disorder [Internet]. Ontology Lookup Service. 2020 [cited 2020 Sep 24]. Available from:
  • 30 Cox S, Hastings J, West R, Notley C The case for development of an E-cigarette Ontology (E-CigO) to improve quality, efficiency and clarity in the conduct and interpretation of research. Qeios [Internet]. 2020 Apr 3 [cited 2020 Nov 17]. Available from:
  • 31 Cox S, Notley C. Cleaning up the science: the need for an ontology of consensus scientific terms in e-cigarette research. Addiction 2021 May;116(5):997-8.
  • 32 Chatterjee A, Prinz A, Gerdes M, Martinez S. An Automatic Ontology-Based Approach to Support Logical Representation of Observable and Measurable Data for Healthy Lifestyle Management: Proof-of-Concept Study. J Med Internet Res 2021 Apr 9;23(4):e24656.
  • 33 Compton M, Barnaghi P, Bermudez L, García-Castro R, Corcho O, Cox S, et al. The SSN ontology of the W3C semantic sensor network incubator group. J Web Semant 2012 Dec 1;17:25”32.
  • 34 Søvold LE, Naslund JA, Kousoulis AA, Saxena S, Qoronfleh MW, Grobler C, et al. Prioritizing the Mental Health and Well-Being of Healthcare Workers: An Urgent Global Public Health Priority. Front Public Health 2021 May 7;9:679397.
  • 35 Zhou Y, Yang WFZ, Ma Y, Wu Q, Yang D, Liu T, Wu X. Doctor-Patient Relationship in the Eyes of Medical Professionals in China During the COVID-19 Pandemic: A Cross-Sectional Study. Front Psychiatry 2021 Oct 28;12:768089.
  • 36 Maitra A, Kamdar MR, Zulman DM, Haverfield MC, Brown-Johnson C, Schwartz R, et al. Using ethnographic methods to classify the human experience in medicine: a case study of the presence ontology. J Am Med Inform Assoc. 2021 Aug 13;28(9):1900-9.
  • 37 Brown-Johnson C, Schwartz R, Maitra A, Haverfield MC, Tierney A, Shaw JG, et al. What is clinician presence? A qualitative interview study comparing physician and non-physician insights about practices of human connection. BMJ Open 2019 Nov 3;9(11):e030831.
  • 38 Katzman JG, Katzman JW. Primary Care Clinicians as COVID-19 Vaccine Ambassadors. J Prim Care Community Health 2021 Jan-Dec;12:21501327211007026.
  • 39 Amith M, Lin RZ, Cui L, Wang D, Zhu A, Xiong G, et al. Conversational ontology operator: patient-centric vaccine dialogue management engine for spoken conversational agents. BMC Med Inform Decis Mak 2020 Dec 14;20(Suppl 4):259.
  • 40 Amith M, Roberts K, Tao C. Conceiving an application ontology to model patient human papillomavirus vaccine counseling for dialogue management. BMC Bioinformatics 2019 Dec 23;20(Suppl 21):706.
  • 41 Ammar N, Shaban-Nejad A. Explainable Artificial Intelligence Recommendation System by Leveraging the Semantics of Adverse Childhood Experiences: Proof-of-Concept Prototype Development. JMIR Med Inform 2020 Nov 4;8(11):e18752.
  • 42 Brenas JH, Shin EK, Shaban-Nejad A. Adverse Childhood Experiences Ontology for Mental Health Surveillance, Research, and Evaluation: Advanced Knowledge Representation and Semantic Web Techniques. JMIR Ment Health 2019 May 21;6(5):e13498.
  • 43 Gaudet-Blavignac C, Raisaro JL, Touré V, Österle S, Crameri K, Lovis C. A National, Semantic-Driven, Three-Pillar Strategy to Enable Health Data Secondary Usage Interoperability for Research Within the Swiss Personalized Health Network: Methodological Study. JMIR Med Inform 2021 Jun 24;9(6):e27591.
  • 44 Bibbins-Domingo K. Integrating Social Care Into the Delivery of Health Care. JAMA 2019 Nov 12;322(18):1763-4.
  • 45 Cook LA, Sachs J, Weiskopf NG. The quality of social determinants data in the electronic health record: a systematic review. J Am Med Inform Assoc 2021 Dec 28;29(1):187-96.
  • 46 Das S, Hussey P. ContSOnto: A Formal Ontology for Continuity of Care. Stud Health Technol Inform 2021 Oct 27;285:82-87.
  • 47 Marwaha JS, Kvedar JC. Cultural adaptation: a framework for addressing an often-overlooked dimension of digital health accessibility. NPJ Digit Med 2021 Oct 1;4(1):143.
  • 48 Gan DZQ, McGillivray L, Han J, Christensen H, Torok M. Effect of Engagement With Digital Interventions on Mental Health Outcomes: A Systematic Review and Meta-Analysis. Front Digit Health 2021 Nov 4;3:764079.
  • 49 Ninomiya K, Takatsuki T, Kushida T, Yamamoto Y, Ogishima S. Choosing preferable labels for the Japanese translation of the Human Phenotype Ontology. Genomics Inform 2020 Jun;18(2):e23.
  • 50 Köhler S, Gargano M, Matentzoglu N, Carmody LC, Lewis-Smith D, Vasilevsky NA, et al. The Human Phenotype Ontology in 2021. Nucleic Acids Res 2021 Jan 8;49(D1):D1207-D1217.
  • 51 McCarthy M, Birney E. Personalized profiles for disease risk must capture all facets of health. Nature 2021 Sep;597(7875):175-7.
  • 52 Li F, Du J, He Y, Song HY, Madkour M, Rao G, et al. Time event ontology (TEO): to support semantic representation and reasoning of complex temporal relations of clinical events. J Am Med Inform Assoc 2020 Jul 1;27(7):1046-56.
  • 53 Flynn E, Chang A, Altman RB. Large-scale labeling and assessment of sex bias in publicly available expression data. BMC Bioinformatics 2021 Mar 30;22(1):168.
  • 54 Robinson PN, Haendel MA. Ontologies, Knowledge Representation, and Machine Learning for Translational Research: Recent Contributions. Yearb Med Inform 2020 Aug;29(1):159-62.
  • 55 Bauer DC, Metke-Jimenez A, Maurer-Stroh S, Tiruvayipati S, Wilson LOW, Jain Yet al. Interoperable medical data: The missing link for understanding COVID-19. Transbound Emerg Dis 2021 Jul;68(4):1753-60.
  • 56 Averitt AJ, Weng C, Ryan P, Perotte A. Translating evidence into practice: eligibility criteria fail to eliminate clinically significant differences between real-world and study populations. NPJ Digit Med 2020 May 11;3:67.
  • 57 Miron L, Gonçalves RS, Musen MA. Obstacles to the reuse of study metadata in Sci Data 2020 Dec 18;7(1):443.
  • 58 Wirth FN, Meurers T, Johns M, Prasser F. Privacy-preserving data sharing infrastructures for medical research: systematization and comparison. BMC Med Inform Decis Mak 2021 Aug 12;21(1):242.
  • 59 Aung YYM, Wong DCS, Ting DSW. The promise of artificial intelligence: a review of the opportunities and challenges of artificial intelligence in healthcare. Br Med Bull 2021 Sep 10;139(1):4-15.
  • 60 Madai VI, Higgins DC. Artificial Intelligence in Healthcare: Lost In Translation? ArXiv210713454 Cs [Internet] 2021 Jul 28 [cited 2021 Sep 20]. Available from:
  • 61 WHO issues first global report on Artificial Intelligence (AI) in health and six guiding principles for its design and use [Internet]. [cited 2021 Aug 26]. Available from:
  • 62 Obermeyer Z, Powers B, Vogeli C, Mullainathan S. Dissecting racial bias in an algorithm used to manage the health of populations. Science 2019 Oct 25;366(6464):447-53.
  • 63 Kompa B, Snoek J, Beam AL. Second opinion needed: communicating uncertainty in medical machine learning. NPJ Digit Med 2021 Jan 5;4(1):4.
  • 64 Berisha V, Krantsevich C, Hahn PR, Hahn S, Dasarathy G, Turaga P, Liss J. Digital medicine and the curse of dimensionality. NPJ Digit Med 2021 Oct 28;4(1):153.
  • 65 Richardson JP, Smith C, Curtis S, Watson S, Zhu X, Barry B, et al. Patient apprehensions about the use of artificial intelligence in healthcare. NPJ Digit Med 2021 Sep 21;4(1):140.
  • 66 Bing S, Dittadi A, Bauer S, Schwab P. Conditional Generation of Medical Time Series for Extrapolation to Underrepresented Populations. ArXiv220108186 Cs [Internet] 2022 Jan 20 [cited 2022 Jan 26]. Available from: