[Research and protection of personal data in Primary Care].
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ABSTRACT:
SUBMITTER: Garrido Elustondo S
PROVIDER: S-EPMC7025257 | biostudies-literature | 2012 Mar
REPOSITORIES: biostudies-literature
Publications
[Research and protection of personal data in Primary Care].
Garrido Elustondo Sofía S Cabello Ballesteros Luisa L Galende Domínguez Inés I Riesgo Fuertes Rosario R Rodríguez Barrientos Ricardo R Polentinos Castro Elena E
Atencion primaria 20110729 3
Research is one of the fundamental functions that have to be carried out in Primary Care. The clinical information stored in different records arising from medical care is a basic tool for this activity. The use of personal data for the purposes of research is legitimate according to our laws; however, this information must be treated confidentially at all times. Two alternatives are available for this. One is to obtain the informed consent of the patient, and the other is to dissociate the hand ...[more]
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| S-EPMC8672332 | biostudies-literature
Project description:BackgroundThe recent surge in clinical and nonclinical health-related data has been accompanied by a concomitant increase in personal health data (PHD) research across multiple disciplines such as medicine, computer science, and management. There is now a need to synthesize the dynamic knowledge of PHD in various disciplines to spot potential research hotspots.ObjectiveThe aim of this study was to reveal the knowledge evolutionary trends in PHD and detect potential research hotspots using bibliometric analysis.MethodsWe collected 8281 articles published between 2009 and 2018 from the Web of Science database. The knowledge evolution analysis (KEA) framework was used to analyze the evolution of PHD research. The KEA framework is a bibliometric approach that is based on 3 knowledge networks: reference co-citation, keyword co-occurrence, and discipline co-occurrence.ResultsThe findings show that the focus of PHD research has evolved from medicine centric to technology centric to human centric since 2009. The most active PHD knowledge cluster is developing knowledge resources and allocating scarce resources. The field of computer science, especially the topic of artificial intelligence (AI), has been the focal point of recent empirical studies on PHD. Topics related to psychology and human factors (eg, attitude, satisfaction, education) are also receiving more attention.ConclusionsOur analysis shows that PHD research has the potential to provide value-based health care in the future. All stakeholders should be educated about AI technology to promote value generation through PHD. Moreover, technology developers and health care institutions should consider human factors to facilitate the effective adoption of PHD-related technology. These findings indicate opportunities for interdisciplinary cooperation in several PHD research areas: (1) AI applications for PHD; (2) regulatory issues and governance of PHD; (3) education of all stakeholders about AI technology; and (4) value-based health care including "allocative value," "technology value," and "personalized value."
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