Internet of Things in Pervasive Healthcare Systems

Guarda, Teresa; Augusto, Maria Fernanda; Barrionuevo, Oscar; Pinto, Filipe

doi:10.4018/978-1-5225-2851-7.ch002

“…Moreover, these platforms not only offer physicians technologies that simplify the healthcare process but also provide them with tools to aid clinical decision-making. This has widely promoted the use of IoMT to improve healthcare and is now considered a pillar of new ubiquitous healthcare services [4].…”

Section: State Of the Artmentioning

confidence: 99%

Literature Review: Clinical Data Interoperability Models

Abdelouahid¹,

Debauche²,

Mahmoudi³

et al. 2023

Preprint

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0

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A medical entity (hospital, nursing home, rest home, revalidation center, etc.) usually includes a multitude of information systems that allow for quick decision-making close to the medical sensors. The Internet of Medical Things (IoMT) is an area of IoT that generates a lot of data of different natures (radio, CT scan, medical reports, medical sensor data). However, these systems need to share and exchange medical information in a seamless, timely, and efficient manner with systems that are either located within the same entity or located in other healthcare entities. The lack of inter and intra entity interoperability causes major problems in the analysis of patient records and leads to additional financial costs (e.g., redone examinations). In order to develop a medical data interoperability architecture model that will allow providers and different actors in the medical community to exchange patient summary information with other caregivers and partners in order to improve the quality of care, the level of data security, and the efficiency of care, we take stock of the state of knowledge.

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“…Moreover, these platforms not only offer physicians technologies that simplify the healthcare process but also provide them with tools to aid clinical decision-making. This has widely promoted the use of IoMT to improve healthcare and is now considered a pillar of new ubiquitous healthcare services [23].…”

Section: State-of-the-artmentioning

confidence: 99%

Literature Review: Clinical Data Interoperability Models

Abdelouahid

¹

,

Debauche

²

,

Mahmoudi

³

et al. 2023

Information

7

0

View full text Add to dashboard Cite

A medical entity (hospital, nursing home, rest home, revalidation center, etc.) usually includes a multitude of information systems that allow for quick decision-making close to the medical sensors. The Internet of Medical Things (IoMT) is an area of IoT that generates a lot of data of different natures (radio, CT scan, medical reports, medical sensor data). However, these systems need to share and exchange medical information in a seamless, timely, and efficient manner with systems that are either within the same entity or other healthcare entities. The lack of inter- and intra-entity interoperability causes major problems in the analysis of patient records and leads to additional financial costs (e.g., redone examinations). To develop a medical data interoperability architecture model that will allow providers and different actors in the medical community to exchange patient summary information with other caregivers and partners to improve the quality of care, the level of data security, and the efficiency of care should take stock of the state of knowledge. This paper discusses the challenges faced by medical entities in sharing and exchanging medical information seamlessly and efficiently. It highlights the need for inter- and intra-entity interoperability to improve the analysis of patient records, reduce financial costs, and enhance the quality of care. The paper reviews existing solutions proposed by various researchers and identifies their limitations. The analysis of the literature has shown that the HL7 FHIR standard is particularly well adapted for exchanging and storing health data, while DICOM, CDA, and JSON can be converted in HL7 FHIR or HL7 FHIR to these formats for interoperability purposes. This approach covers almost all use cases.

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“…Moreover, these platforms empower the physicians with technologies that simplify the healthcare process in addition to providing them with tools to support clinical decisions. This has made IoMT widely used to enhance healthcare and is now considered to be a pillar in new pervasive health services [8].…”

Section: Introductionmentioning

confidence: 99%

IoMT Platform for Pervasive Healthcare Data Aggregation, Processing, and Sharing Based on OneM2M and OpenEHR

Rubí

¹

,

Gondim

²

2019

Sensors

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Pervasive healthcare services have undergone a great evolution in recent years. The technological development of communication networks, including the Internet, sensor networks, and M2M (Machine-to-Machine) have given rise to new architectures, applications, and standards related to addressing almost all current e-health challenges. Among the standards, the importance of OpenEHR has been recognized, since it enables the separation of medical semantics from data representation of electronic health records. However, it does not meet the requirements related to interoperability of e-health devices in M2M networks, or in the Internet of Things (IoT) scenarios. Moreover, the lack of interoperability hampers the application of new data-processing techniques, such as data mining and online analytical processing, due to the heterogeneity of the data and the sources. This article proposes an Internet of Medical Things (IoMT) platform for pervasive healthcare that ensures interoperability, quality of the detection process, and scalability in an M2M-based architecture, and provides functionalities for the processing of high volumes of data, knowledge extraction, and common healthcare services. The platform uses the semantics described in OpenEHR for both data quality evaluation and standardization of healthcare data stored by the association of IoMT devices and observations defined in OpenEHR. Moreover, it enables the application of big data techniques and online analytic processing (OLAP) through Hadoop Map/Reduce and content-sharing through fast healthcare interoperability resource (FHIR) application programming interfaces (APIs).

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Internet of Things in Pervasive Healthcare Systems

Cited by 9 publications

References 22 publications

Literature Review: Clinical Data Interoperability Models

Literature Review: Clinical Data Interoperability Models

Literature Review: Clinical Data Interoperability Models

IoMT Platform for Pervasive Healthcare Data Aggregation, Processing, and Sharing Based on OneM2M and OpenEHR

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