Defining ‘sensitive’ health status: a systematic approach using health code terminologies.

ABSTRACT Objectives “Clearly, details about an individual’s mental health, for example, are generally much more ‘sensitive’ than whether they have a broken leg.” UK Information Commissioners Office There is a perceived wisdom – based on issues such as social taboos, religious sensitivities,...

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Main Authors: Andy Boyd, Rosie Cornish, Jennifer Provis, Alison Teyhan, John Macleod
Format: Article
Language:English
Published: Swansea University 2017-04-01
Series:International Journal of Population Data Science
Online Access:https://ijpds.org/article/view/267
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author Andy Boyd
Rosie Cornish
Jennifer Provis
Alison Teyhan
John Macleod
author_facet Andy Boyd
Rosie Cornish
Jennifer Provis
Alison Teyhan
John Macleod
author_sort Andy Boyd
collection DOAJ
description ABSTRACT Objectives “Clearly, details about an individual’s mental health, for example, are generally much more ‘sensitive’ than whether they have a broken leg.” UK Information Commissioners Office There is a perceived wisdom – based on issues such as social taboos, religious sensitivities, or financial implications linked to health status – that some health data is more sensitive than others. This distinction is present in many of the regulatory interpretations of privacy law (e.g. the UK Information Commissioners Office interpretation of the EU Data Directive, illustrated above), and is factored into the thinking of ethics and other regulatory decision-making committees. However, these particularly ‘sensitive’ data are defined at a regulatory level in broad terms (e.g. mental health), yet need implementing by researchers in precise terms. In 2013 our longitudinal research study was given approval by the UK Secretary of State for Health to access identifiable patient health records with the exception of those relating to mental health, sexual health or termination of pregnancy. Our objective therefore was to develop a generalisable informatics approach which enabled us to filter out sensitive records at the point of extraction. Approach We developed a methodology based on the Cochrane systematic review approach: firstly using internationally recognised definitions of health concepts and reference texts (e.g. British National Formulary drug manual) we identified keywords associated with sensitive health events (including symptom and diagnostic terms, drug and appliance codes, community and secondary care references); secondly, through data-mining code terminologies – using both code terms and information embedded within the structure of the schema itself - we identified code values relating to these terms; thirdly we minimised our results through filtering out spurious results via manual review; finally, the resulting code lists were then crossed-referenced with other terminologies to ensure interoperability. Results We produced separate definitions of mental health and sexual health events initially using Read codes. Using NHS cross-reference tables we were able to translate Read observation and diagnostic codes to the SNOMED CT vocabulary, but were unable to translate Read drug codes into the SNOMED/DM+D vocabulary. Conclusion We have demonstrated a systematic and partially interoperable approach to defining ‘sensitive’ health information. However, any such exercise is likely to include decisions which will be open to interpretation and open to change over time. As such, the application of this technique should be embedded within an appropriate governance framework which can accommodate misclassification while minimising potential patient harm.
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spelling doaj.art-29f255a6e7064d9f8f0f7a0c0acf62072023-12-02T05:24:48ZengSwansea UniversityInternational Journal of Population Data Science2399-49082017-04-011110.23889/ijpds.v1i1.267267Defining ‘sensitive’ health status: a systematic approach using health code terminologies.Andy Boyd0Rosie Cornish1Jennifer Provis2Alison Teyhan3John Macleod4ALSPAC; University of BristolALSPAC; University of BristolALSPAC; University of BristolALSPAC; University of BristolALSPAC; University of BristolABSTRACT Objectives “Clearly, details about an individual’s mental health, for example, are generally much more ‘sensitive’ than whether they have a broken leg.” UK Information Commissioners Office There is a perceived wisdom – based on issues such as social taboos, religious sensitivities, or financial implications linked to health status – that some health data is more sensitive than others. This distinction is present in many of the regulatory interpretations of privacy law (e.g. the UK Information Commissioners Office interpretation of the EU Data Directive, illustrated above), and is factored into the thinking of ethics and other regulatory decision-making committees. However, these particularly ‘sensitive’ data are defined at a regulatory level in broad terms (e.g. mental health), yet need implementing by researchers in precise terms. In 2013 our longitudinal research study was given approval by the UK Secretary of State for Health to access identifiable patient health records with the exception of those relating to mental health, sexual health or termination of pregnancy. Our objective therefore was to develop a generalisable informatics approach which enabled us to filter out sensitive records at the point of extraction. Approach We developed a methodology based on the Cochrane systematic review approach: firstly using internationally recognised definitions of health concepts and reference texts (e.g. British National Formulary drug manual) we identified keywords associated with sensitive health events (including symptom and diagnostic terms, drug and appliance codes, community and secondary care references); secondly, through data-mining code terminologies – using both code terms and information embedded within the structure of the schema itself - we identified code values relating to these terms; thirdly we minimised our results through filtering out spurious results via manual review; finally, the resulting code lists were then crossed-referenced with other terminologies to ensure interoperability. Results We produced separate definitions of mental health and sexual health events initially using Read codes. Using NHS cross-reference tables we were able to translate Read observation and diagnostic codes to the SNOMED CT vocabulary, but were unable to translate Read drug codes into the SNOMED/DM+D vocabulary. Conclusion We have demonstrated a systematic and partially interoperable approach to defining ‘sensitive’ health information. However, any such exercise is likely to include decisions which will be open to interpretation and open to change over time. As such, the application of this technique should be embedded within an appropriate governance framework which can accommodate misclassification while minimising potential patient harm.https://ijpds.org/article/view/267
spellingShingle Andy Boyd
Rosie Cornish
Jennifer Provis
Alison Teyhan
John Macleod
Defining ‘sensitive’ health status: a systematic approach using health code terminologies.
International Journal of Population Data Science
title Defining ‘sensitive’ health status: a systematic approach using health code terminologies.
title_full Defining ‘sensitive’ health status: a systematic approach using health code terminologies.
title_fullStr Defining ‘sensitive’ health status: a systematic approach using health code terminologies.
title_full_unstemmed Defining ‘sensitive’ health status: a systematic approach using health code terminologies.
title_short Defining ‘sensitive’ health status: a systematic approach using health code terminologies.
title_sort defining sensitive health status a systematic approach using health code terminologies
url https://ijpds.org/article/view/267
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