In recent years, digital transformation in healthcare has played a crucial role, driven by the exponential increase in medical data. This ranges from administrative information to detailed records of diagnoses, laboratory tests, medical images and prescriptions. This vast volume of data presents significant challenges for hospital systems, which need robust solutions to store, process and make information available in a secure and accessible way. In this scenario, the integration of mobile health technologies (m-Health) into the Electronic Health Record has emerged as an innovative solution. This advance not only facilitates the continuous monitoring and management of patient data, but also contributes to a more efficient approach centered on improving the quality of healthcare.
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inteligência artificial

Publication type: Article Summary
Original title: Meios complementares de diagnóstico e terapêutica no Processo Clínico Electrónico via “m-Health
Article publication date: October 2014
Source: Repositório da Universidade do Minho
Author: Ana Sofia de Amorim Pereira
Supervisors: José Machado & Fernando Marins

What is the goal, target audience, and areas of digital health it addresses?
     The study aims to develop a new methodology to improve medical decision-making, offering clinical reports on patients in a way that doesn’t overload healthcare professionals with too much information. The target audience includes healthcare professionals, such as doctors and nurses, who work in hospital environments, especially those where rapid access to clinical data is critical for decision-making and improving patient care. The project addresses various areas of digital health, particularly m-Health, calm computing and interoperability.

What is the context?
     In recent years, digital transformation in healthcare has played a crucial role, driven by the exponential increase in medical data. This ranges from administrative information to detailed records of diagnoses, laboratory tests, medical images and prescriptions. This vast volume of data presents significant challenges for hospital systems, which need robust solutions to store, process and make information available in a secure and accessible way. In this scenario, the integration of mobile health technologies (m-Health) into the Electronic Health Record has emerged as an innovative solution. This advance not only facilitates the continuous monitoring and management of patient data, but also contributes to a more efficient approach centered on improving the quality of healthcare.

What are the current approaches?
     Today’s hospital information systems focus on integrating health data, providing fast, secure and efficient access to clinical processes. Approaches such as interoperability made possible by platforms such as the Agência para a Integração, Difusão e Arquivo de Informação Médica (AIDA), implemented in Centro Hospitalar do Porto, have been fundamental in enabling the exchange of information between different systems. At the same time, mobile applications (m-Health) are playing an increasingly important role in the modernization of hospital healthcare, enabling healthcare professionals to access clinical data in real time. m-Health applications such as GlucoMen Day CGM for diabetes, Omron Connect for hypertension and Epic Rover for access to clinical records have modernized hospital care, while tools such as Pulsara optimize emergencies and applications such as Amwell and Teladoc Health promote telemedicine.

     Despite the benefits, the use of m-Health in hospitals faces challenges such as the lack of interoperability between old and new systems, difficulties in the usability of interfaces, data security and the management of large volumes of information (big data). In addition, there is a growing need for personalized clinical decision support systems that provide specific insights for each patient.

What does innovation consist of? How is the impact of this study assessed?
     The innovation of this study consists of the development of an m-Health application that combines calm computing principles, advanced integration with hospital systems and personalised clinical decision support. Unlike current m-Health applications, which often overwhelm healthcare professionals with large volumes of data or complex interfaces, this application is based on calm computing principles to discreetly present the most relevant results of patients’ Complementary Means of Diagnosis and Therapy reports, minimizing distractions. It also stands out for its advanced integration with the AIDA Electronic Health Record, making it possible to link patients’ clinical data stored in different hospital systems, promoting interoperability and facilitating the continuous exchange of information between hospitals and healthcare professionals, something that is often a challenge due to the fragmentation of healthcare systems. Another highlight is personalised clinical decision support, using advanced algorithms to provide specific recommendations based on each patient’s clinical history and current conditions. This approach makes it possible to identify patterns in large volumes of data, supporting diagnostic and therapeutic decisions more accurately and efficiently.

     The impact of implementing this m-Health was rigorously assessed through a Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis, which identified the application’s strengths and weaknesses, as well as exploring the opportunities for improvement and the risks associated with its use in the Centro Hospitalar do Porto. This approach made it possible to verify the viability of the application in a real-life context, helping to understand the potential benefits and challenges associated with its implementation. In addition, efficiency tests were carried out, assessing the application’s response times for different functionalities, as well as usability tests, based on surveys with healthcare professionals. These tests made it possible to obtain direct feedback from the healthcare professionals who use the application, enabling adjustments to be made to the interface or functionality of the tool to improve the user experience.

What are the main results? What is the future of this approach?
     The results highlighted that the m-Health application was highly effective in improving access to patients’ clinical information, promoting greater efficiency in the hospital workflow by reducing response times. The adoption of calm computing principles significantly reduced information overload, providing a more intuitive, focused and productive experience for healthcare professionals. In addition, the tests also confirmed the technical feasibility of integration with the AIDA Electronic Health Record, overcoming challenges related to interoperability between heterogeneous systems, as well as the positive acceptance among users at the Centro Hospitalar do Porto, reinforcing the application’s potential as a practical and effective solution for the healthcare sector.

     The future of this approach includes extending integration with other hospital systems, promoting greater interoperability and large-scale uptake. New functionalities based on calm computing will be explored to improve usability and medical decision support. Continuous improvements, in line with feedback from healthcare professionals and the possible integration of artificial intelligence and/or remote monitoring devices will extend predictive and personalization capabilities, consolidating the application as a modern and transformative solution for hospital information systems.

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Home / Publications / Publication

inteligência artificial

Publication type: Article Summary
Original title: Meios complementares de diagnóstico e terapêutica no Processo Clínico Electrónico via “m-Health
Article publication date: October 2014
Source: Repositório da Universidade do Minho
Author: Ana Sofia de Amorim Pereira
Supervisors: José Machado & Fernando Marins

What is the goal, target audience, and areas of digital health it addresses?
     The study aims to develop a new methodology to improve medical decision-making, offering clinical reports on patients in a way that doesn’t overload healthcare professionals with too much information. The target audience includes healthcare professionals, such as doctors and nurses, who work in hospital environments, especially those where rapid access to clinical data is critical for decision-making and improving patient care. The project addresses various areas of digital health, particularly m-Health, calm computing and interoperability.

What is the context?
     In recent years, digital transformation in healthcare has played a crucial role, driven by the exponential increase in medical data. This ranges from administrative information to detailed records of diagnoses, laboratory tests, medical images and prescriptions. This vast volume of data presents significant challenges for hospital systems, which need robust solutions to store, process and make information available in a secure and accessible way. In this scenario, the integration of mobile health technologies (m-Health) into the Electronic Health Record has emerged as an innovative solution. This advance not only facilitates the continuous monitoring and management of patient data, but also contributes to a more efficient approach centered on improving the quality of healthcare.

What are the current approaches?
     Today’s hospital information systems focus on integrating health data, providing fast, secure and efficient access to clinical processes. Approaches such as interoperability made possible by platforms such as the Agência para a Integração, Difusão e Arquivo de Informação Médica (AIDA), implemented in Centro Hospitalar do Porto, have been fundamental in enabling the exchange of information between different systems. At the same time, mobile applications (m-Health) are playing an increasingly important role in the modernization of hospital healthcare, enabling healthcare professionals to access clinical data in real time. m-Health applications such as GlucoMen Day CGM for diabetes, Omron Connect for hypertension and Epic Rover for access to clinical records have modernized hospital care, while tools such as Pulsara optimize emergencies and applications such as Amwell and Teladoc Health promote telemedicine.

     Despite the benefits, the use of m-Health in hospitals faces challenges such as the lack of interoperability between old and new systems, difficulties in the usability of interfaces, data security and the management of large volumes of information (big data). In addition, there is a growing need for personalized clinical decision support systems that provide specific insights for each patient.

What does innovation consist of? How is the impact of this study assessed?
     The innovation of this study consists of the development of an m-Health application that combines calm computing principles, advanced integration with hospital systems and personalised clinical decision support. Unlike current m-Health applications, which often overwhelm healthcare professionals with large volumes of data or complex interfaces, this application is based on calm computing principles to discreetly present the most relevant results of patients’ Complementary Means of Diagnosis and Therapy reports, minimizing distractions. It also stands out for its advanced integration with the AIDA Electronic Health Record, making it possible to link patients’ clinical data stored in different hospital systems, promoting interoperability and facilitating the continuous exchange of information between hospitals and healthcare professionals, something that is often a challenge due to the fragmentation of healthcare systems. Another highlight is personalised clinical decision support, using advanced algorithms to provide specific recommendations based on each patient’s clinical history and current conditions. This approach makes it possible to identify patterns in large volumes of data, supporting diagnostic and therapeutic decisions more accurately and efficiently.

     The impact of implementing this m-Health was rigorously assessed through a Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis, which identified the application’s strengths and weaknesses, as well as exploring the opportunities for improvement and the risks associated with its use in the Centro Hospitalar do Porto. This approach made it possible to verify the viability of the application in a real-life context, helping to understand the potential benefits and challenges associated with its implementation. In addition, efficiency tests were carried out, assessing the application’s response times for different functionalities, as well as usability tests, based on surveys with healthcare professionals. These tests made it possible to obtain direct feedback from the healthcare professionals who use the application, enabling adjustments to be made to the interface or functionality of the tool to improve the user experience.

What are the main results? What is the future of this approach?
     The results highlighted that the m-Health application was highly effective in improving access to patients’ clinical information, promoting greater efficiency in the hospital workflow by reducing response times. The adoption of calm computing principles significantly reduced information overload, providing a more intuitive, focused and productive experience for healthcare professionals. In addition, the tests also confirmed the technical feasibility of integration with the AIDA Electronic Health Record, overcoming challenges related to interoperability between heterogeneous systems, as well as the positive acceptance among users at the Centro Hospitalar do Porto, reinforcing the application’s potential as a practical and effective solution for the healthcare sector.

     The future of this approach includes extending integration with other hospital systems, promoting greater interoperability and large-scale uptake. New functionalities based on calm computing will be explored to improve usability and medical decision support. Continuous improvements, in line with feedback from healthcare professionals and the possible integration of artificial intelligence and/or remote monitoring devices will extend predictive and personalization capabilities, consolidating the application as a modern and transformative solution for hospital information systems.

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