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publisher‐imprint‐name Springer volume‐issue‐count 1 issue‐article‐count 0 issue‐toc‐levels 0 issue‐pricelist‐year 2019 issue‐copyright‐holder The Author(s) issue‐copyright‐year 2019 article‐contains‐esm No article‐numbering‐style Unnumbered article‐registration‐date‐year 2019 article‐registration‐date‐month 4 article‐registration‐date‐day 11 article‐toc‐levels 0 toc‐levels 0 volume‐type Regular journal‐product ArchiveJournal numbering‐style Unnumbered article‐grants‐type OpenChoice metadata‐grant OpenAccess abstract‐grant OpenAccess bodypdf‐grant OpenAccess bodyhtml‐grant OpenAccess bibliography‐grant OpenAccess esm‐grant OpenAccess online‐first false pdf‐file‐reference BodyRef/PDF/40169_2019_Article_233.pdf target‐type OnlinePDF issue‐type Regular article‐type OriginalPaper journal‐subject‐primary Medicine & Public Health journal‐subject‐secondary Medicine/Public Health, general journal‐subject‐collection Medicine open‐access true --> Background: A positive family history for diabetes, cardiovascular diseases or various types of cancer increases the relative risk for these diseases by 2 to 5 times compared to people without a positive family history. Taking a family history in daily general practice is useful for early, pre‐symptomatic risk assessment, but at the moment no standardized family history questionnaire is available in the Dutch language. In this study we used a 9‐item questionnaire, previously developed and applied in an Australian study, to probe family history for 7 specific conditions. The aim of the present qualitative study was to test face and content validity of the Australian family history questionnaire in Dutch general practice and to advance the standardization of intake information at an international level. We conducted 10 cognitive interviews with patients over 4 rounds, using the verbal probing technique. This approach allows the collection of data through a series of probe questions, with the aim of obtaining detailed information. After each interview round we modified the questionnaire based on the answers of the interviewees. We also performed 10 semi‐structured interviews with general practitioners (GPs) to get their opinion on the content and usability of the questionnaire in practice. Results: Patients varied in age and gender, and 4 patients were known to have a genetic disorder. The GPs varied in age, gender, clinical experience, type of practice and location. In the first round, seven problems were identified in the questionnaire in the categories Comprehension (1), Recall (2), Judgement (0), Response process (2) and Completeness, (2); by the fourth and final round no problems remained. The content and usability of the questionnaire were assessed positively. Conclusions: When translated for everyday use in Dutch general practice, the Australian family history questionnaire showed a strong face and content validity, and GPs were positive regarding feasibility. Validation of this family history questionnaire could aid in the standardized integration of genetically relevant information in the electronic health record and clinical research. Conspicuous questionnaire information might alert the GP regarding specific conditions and enable detection of disease at an earlier stage. Additional questionnaire requirements needed however are accurate patient information and consistent, accessible locations in the electronic health record with a possibility to be automatically registered. By deriving a Dutch family history questionnaire convenient for GPs, we adapted a template that might also prove useful for other countries and other medical professionals. This development could make the rapid operationalization of readily available genetic knowledge feasible in daily practice and clinical research, leading to improved medical care. [ABSTRACT FROM AUTHOR]

ABSTRACT Data sharing is essential for a better understanding of genetic disorders. Good phenotype coding plays a key role in this process. Unfortunately, the two most widely used coding systems in medicine, ICD-10 and SNOMED- CT, lack information necessary for the detailed classification and annotation of rare and genetic disorders. This prevents the optimal registration of such patients in databases and thus data-sharing efforts. To improve care and to facilitate research for patients with metabolic disorders, we developed a new coding system for metabolic diseases with a dedicated group of clinical specialists. Next, we compared the resulting codes with those in ICD and SNOMED- CT. No matches were found in 76% of cases in ICD-10 and in 54% in SNOMED- CT. We conclude that there are sizable gaps in the SNOMED- CT and ICD coding systems for metabolic disorders. There may be similar gaps for other classes of rare and genetic disorders. We have demonstrated that expert groups can help in addressing such coding issues. Our coding system has been made available to the ICD and SNOMED- CT organizations as well as to the Orphanet and HPO organizations for further public application and updates will be published online (www.ddrmd.nl and www.cineas.org). [ABSTRACT FROM AUTHOR]