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1.
Postgrad Med ; 134(8): 776-783, 2022 Nov.
Article in English | MEDLINE | ID: mdl-36093684

ABSTRACT

The three horizons model is a framework that helps manage an organization's innovation strategy. This model considers three aspects (horizons) that should be present in the institution and guide the development of new systems. Applied to medical science, the horizons are considered as paradigms that set the guidelines for clinical knowledge. New technologies can influence this model by causing disruptive changes. Horizon 1 (evidence-based medicine) reflects the current paradigm and emphasizes the aspect of continuous improvement needed to strengthen it, such as with the introduction of the GRADE (Grades of Recommendation Assessment, Development, and Evaluation) methodology. Evidence-based medicine has made it possible to stop performing harmful interventions like autologous bone marrow or stem cell transplantation in cancer treatment for women with early poor prognosis breast cancer or to discontinue the erroneous belief that children should not sleep on their backs to prevent sudden infant death syndrome. Horizon 2 (real-world evidence) refers to a new model in which innovation has generated new capabilities. This change makes it possible to correct weaknesses of the previous paradigm, as in the case of pragmatic clinical trials. Real-world evidence has been used to show that drugs such as tofacitinib are effective without using methotrexate as background or to demonstrate the efficacy of chemotherapy in older patients with stage II colon cancer. Horizon 3 (precision medicine) involves a disruptive innovation, leading to the abandonment of the traditional mechanistic model of medical science and is made possible by the appearance of major advances such as artificial intelligence. Precision medicine has been used to assess the use of retigabine for the treatment of refractory epilepsy or to define a genome-adjusted radiation dose using a biological model to simulate the response to radiotherapy, facilitate dose adjustment and predict outcome in breast cancer.


Subject(s)
Artificial Intelligence , Breast Neoplasms , Infant , Child , Humans , Female , Aged , Breast Neoplasms/therapy
2.
JMIR Med Inform ; 9(3): e13182, 2021 Mar 10.
Article in English | MEDLINE | ID: mdl-33709932

ABSTRACT

BACKGROUND: The evidence-based medicine (EBM) paradigm requires the development of health care professionals' skills in the efficient search of evidence in the literature, and in the application of formal rules to evaluate this evidence. Incorporating this methodology into the decision-making routine of clinical practice will improve the patients' health care, increase patient safety, and optimize resources use. OBJECTIVE: The aim of this study is to develop and evaluate a new tool (KNOWBED system) as a clinical decision support system to support scientific knowledge, enabling health care professionals to quickly carry out decision-making processes based on EBM during their routine clinical practice. METHODS: Two components integrate the KNOWBED system: a web-based knowledge station and a mobile app. A use case (bronchiolitis pathology) was selected to validate the KNOWBED system in the context of the Paediatrics Unit of the Virgen Macarena University Hospital (Seville, Spain). The validation was covered in a 3-month pilot using 2 indicators: usability and efficacy. RESULTS: The KNOWBED system has been designed, developed, and validated to support clinical decision making in mobility based on standards that have been incorporated into the routine clinical practice of health care professionals. Using this tool, health care professionals can consult existing scientific knowledge at the bedside, and access recommendations of clinical protocols established based on EBM. During the pilot project, 15 health care professionals participated and accessed the system for a total of 59 times. CONCLUSIONS: The KNOWBED system is a useful and innovative tool for health care professionals. The usability surveys filled in by the system users highlight that it is easy to access the knowledge base. This paper also sets out some improvements to be made in the future.

3.
Stud Health Technol Inform ; 235: 411-415, 2017.
Article in English | MEDLINE | ID: mdl-28423825

ABSTRACT

The Andalusian Health Service is the public healthcare provider for 8.302.923 inhabitants in the South Spain. This organization coordinates primary and specialized care with an IT infrastructure composed by multiple Electronic Health Record Systems. According to the large volume of healthcare professionals involved, there is a need for providing a consistent management of information through multiple locations and systems. The HEMIC project aims to address this need developing and validating a methodology based on a software tool for standardizing information contained within EHR systems. The developed tool has been designed for supporting the participation of healthcare professionals the establishment of mechanisms for information governance. This research presents the requirements and designs for of a software tool focused on the adoption of recognized best practice in clinical information modeling. The designed tool has a Service Oriented Architecture that will be able to integrate terminology servers and repositories of clinical information models as part of the modeling process. Moreover, the defined tool organizes clinicians, IT developers and terminology experts involved in the modeling process in three levels to promote their coordination in the definition, specialization and validation of clinical information models. In order to ensure the quality of the developed clinical information models, the defined tool is based on the requirements defined in the ISO13972 Technical Specification.


Subject(s)
Electronic Health Records , Medical Records Systems, Computerized , Software , Computer Systems , Humans , Spain
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