Introduction: Hearing impairment is very common in older adults, affecting one-third of people over 65. Despite the many effective technologies available to aid such patients, old and new challenges ask to be answered properly. As for aged people, recent surveys demonstrated that a successful treatment plan shall take into account not only the aspects related to the technology but also other aspects broadly related to auditory disability (e.g. perceived hearing difficulties, impact on quality of life, speech perception). Many valuable instruments are used in clinical practice to measure these different aspects of hearing disability. Unfortunately, most clinicians cannot make profit of this wealth of existing information as it is dispersed into the patient record and it is saved in different repositories with about no sustainable opportunity to collate and analyze data in a multidimensional but tuned approach. Also, most of this information is available as unstructured text that frequently is still to be extracted from clinical notes. At the moment there is no relevant experimentation within the framework described above, thus we did the attempt to design and develop a multi-source and multi-dimensional architecture for extracting and collating together audiological clinical information from diversified sources. Method: Patient sample data consisting of medical records of hearing impaired aged people was considered. The enrolled cases were split into a training and a test set. The proposed architecture aims at the extraction of all information relevant to the planning, management and measurement of the outcomes of the audiological treatment. The design process followed by our multidisciplinary team comprised the modelling of the clinical process and the definition of the hierarchical organization of clinical concepts. Extraction of textual information from the unstructured medical notes was performed using regular expressions and UMLS mapping by MetaMap. Context analysis was performed using a locally-modified version of ConText; temporal information was extracted using regular expressions; clinical concepts were modelled through OpenEHR archetypes. Results: The architecture we built comprises data extracted from different source documents, such as audiometric tests, questionnaires to measures the perceived impact of hearing loss on daily life, technical setup of hearing devices, user preferences, risks factors, etc. In the present pilot evaluation, the different source documents reside on a single archive system. Two different data type are managed: i) textual narrative information related to the past medical history, current complaints, etiology and audiological diagnosis, risk factors for hearing loss and ii) numerical information extracted from the audiometric tests, the technical setup of the hearing device, and from the scores calculated from questionnaires. Data are put on graphical timeline to allow the clinician to monitor the treatment and to adjust it according to the ongoing patient outcomes. Discussion&Conclusions: The proposed architecture is able to model information relevant to the treatment of aged hearing impaired people and can provide the clinician with a multi-source and multi-dimensional view of the main factors relating to hearing disability. The principles we followed to design the architecture may be transferred to other disease domains. Grants: Project 'PNRCNR Aging Program 2012-2018'.
Towards a structured lexicon for the automated extraction of clinical audiology concepts from the multisource medical records of aged people with hearing disabilities
G Tognola;A Paglialonga;R Karmacharya;
2017
Abstract
Introduction: Hearing impairment is very common in older adults, affecting one-third of people over 65. Despite the many effective technologies available to aid such patients, old and new challenges ask to be answered properly. As for aged people, recent surveys demonstrated that a successful treatment plan shall take into account not only the aspects related to the technology but also other aspects broadly related to auditory disability (e.g. perceived hearing difficulties, impact on quality of life, speech perception). Many valuable instruments are used in clinical practice to measure these different aspects of hearing disability. Unfortunately, most clinicians cannot make profit of this wealth of existing information as it is dispersed into the patient record and it is saved in different repositories with about no sustainable opportunity to collate and analyze data in a multidimensional but tuned approach. Also, most of this information is available as unstructured text that frequently is still to be extracted from clinical notes. At the moment there is no relevant experimentation within the framework described above, thus we did the attempt to design and develop a multi-source and multi-dimensional architecture for extracting and collating together audiological clinical information from diversified sources. Method: Patient sample data consisting of medical records of hearing impaired aged people was considered. The enrolled cases were split into a training and a test set. The proposed architecture aims at the extraction of all information relevant to the planning, management and measurement of the outcomes of the audiological treatment. The design process followed by our multidisciplinary team comprised the modelling of the clinical process and the definition of the hierarchical organization of clinical concepts. Extraction of textual information from the unstructured medical notes was performed using regular expressions and UMLS mapping by MetaMap. Context analysis was performed using a locally-modified version of ConText; temporal information was extracted using regular expressions; clinical concepts were modelled through OpenEHR archetypes. Results: The architecture we built comprises data extracted from different source documents, such as audiometric tests, questionnaires to measures the perceived impact of hearing loss on daily life, technical setup of hearing devices, user preferences, risks factors, etc. In the present pilot evaluation, the different source documents reside on a single archive system. Two different data type are managed: i) textual narrative information related to the past medical history, current complaints, etiology and audiological diagnosis, risk factors for hearing loss and ii) numerical information extracted from the audiometric tests, the technical setup of the hearing device, and from the scores calculated from questionnaires. Data are put on graphical timeline to allow the clinician to monitor the treatment and to adjust it according to the ongoing patient outcomes. Discussion&Conclusions: The proposed architecture is able to model information relevant to the treatment of aged hearing impaired people and can provide the clinician with a multi-source and multi-dimensional view of the main factors relating to hearing disability. The principles we followed to design the architecture may be transferred to other disease domains. Grants: Project 'PNRCNR Aging Program 2012-2018'.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
