Experiences of building a medical data acquisition system based on two-level modeling

Li, Bei; Li, Jianbin; Xiao-yun, Lan; An, Ying; Gao, Wuqiang; Jiang, Yuqiao

doi:10.1016/j.ijmedinf.2018.01.016

Cited by 14 publications

(6 citation statements)

References 29 publications

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“…EHRs are repositories storing personal health information in an electronically processable form (18,19) and can either receive data from medical records or from other HIS (e.g., surveillance, laboratory report, medical imaging, and care regulation systems) (20). Such repositories are valuable to healthcare facilities since physicians and other practitioners can benefit from their functionalities (21), which include grouping together the information necessary to ensure patient care and treatment continuity (22)(23)(24)(25). In sum, the main goal of EHRs is to provide health care providers, whenever needed, with the patient's clinical data systematized.…”

Section: Introductionmentioning

confidence: 99%

Electronic health records in Brazil: Prospects and technological challenges

Fernandes

Barros

Henriques

et al. 2022

Front. Public Health

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Electronic Health Records (EHR) are critical tools for advancing digital health worldwide. In Brazil, EHR development must follow specific standards, laws, and guidelines that contribute to implementing beneficial resources for population health monitoring. This paper presents an audit of the main approaches used for EHR development in Brazil, thus highlighting prospects, challenges, and existing gaps in the field. We applied a systematic review protocol to search for articles published from 2011 to 2021 in seven databases (Science Direct, Web of Science, PubMed, Springer, IEEE Xplore, ACM Digital Library, and SciELO). Subsequently, we analyzed 14 articles that met the inclusion and quality criteria and answered our research questions. According to this analysis, 78.58% (11) of the articles state that interoperability between systems is essential for improving patient care. Moreover, many resources are being designed and deployed to achieve this communication between EHRs and other healthcare systems in the Brazilian landscape. Besides interoperability, the articles report other considerable elements: (i) the need for increased security with the deployment of permission resources for viewing patient data, (ii) the absence of accurate data for testing EHRs, and (iii) the relevance of defining a methodology for EHR development. Our review provides an overview of EHR development in Brazil and discusses current gaps, innovative approaches, and technological solutions that could potentially address the related challenges. Lastly, our study also addresses primary elements that could contribute to relevant components of EHR development in the context of Brazil's public health system.Systematic review registration: PROSPERO, identifier CRD42021233219, https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021233219.

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Section: Introductionmentioning

confidence: 99%

Electronic health records in Brazil: Prospects and technological challenges

Fernandes

Barros

Henriques

et al. 2022

Front. Public Health

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“…While NN is used to forecast, LR is used to pinpoint important variables impacting CKD. The cognition model was developed using Microsoft azure to anticipate CKD and support physicians in smart cities.Xu et al [21] tried to combine various techniques. Prediction accuracy, specificity and sensitivity of GA-ANN techniques offer greater classification efficacy.…”

Section: Related Workmentioning

confidence: 99%

A customized stacked dense network model for chronic kidney disease prediction

Shadadi¹,

Alamer

2022

ijhs

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Chronic kidney disease (CKD) is still a health concern, even though surgical care and treatment have improved. Recently, academics throughout the globe have been more interested in creating high-performance approaches for diagnosing, treating, and preventing kidney disease by being more knowledgeable about the aspects that the issue is concerned with, designed to provide better. Evaluation of patient records for patients may assist health care providers detects sickness earlier on. Several have tried to construct sophisticated algorithms that forecast CKD by analyzing health data, but their effectiveness needs improvement. An intelligence categorization and linear regression model are suggested in this paper. The kidney-related disorders are predicted using a customized stacked dense network model (). Compared to current models, the testing of the conceptual scheme reveals that it can predict CKD with 98.5% accuracy. Research suggests that utilizing sophisticated deep learning algorithms is advantageous for treatment decisions and may assist in the early diagnosis of CKD and its associated stages, reducing the development of kidney problems.

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“…[1][2][3] The health system comprises a variety of products and services such as mobile apps, telemedicine and portable monitoring devices attached to the clothing and accessories used by people, Big Data, support systems for clinical decision-making and the Internet of Things (IoT), among others. 4,5 These new trends imply a radical transformation in health, which makes it necessary to achieve more efficiency and safety in health systems, as well as professionals able to handle data and integrate them into the system. 6 Therefore, a health monitoring system would help both people and health care providers obtain relevant information to establish a diagnosis and treatment for diseases.…”

Section: Introductionmentioning

confidence: 99%

“…The health system comprises a variety of products and services such as mobile apps, telemedicine and portable monitoring devices attached to the clothing and accessories used by people, Big Data, support systems for clinical decision-making and the Internet of Things (IoT), among others. 4,5…”

Section: Introductionmentioning

confidence: 99%

Automatized follow-up and alert system for patients with chronic hypertension

Urrea

Venegas

2020

Health Informatics J

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This article presents the development and implementation of a monitoring system for patients with chronic hypertension. Technological advances in wireless communication are increasingly used today to send and receive information through smartphones. This also applies to devices for measuring blood pressure, which can be efficiently integrated with smartphones. Telemedicine is used in a variety of health fields, and in the past 5 years, it has extended its reach to the online monitoring of patients. The objective of this study is to create an integrated system capable of conducting the follow-up, through mobile communication (smartphones), of patients with chronic diseases such as hypertension. An iHealth equipment certified by the Food and Drug Administration is used. The blood pressure values from users are uploaded via Internet and stored in an integral system for processing. The monitoring system developed not only informs users about their disease status but also sends them alerts generated during monitoring. This work uses the telecommunication technology existing through smartphones. The integrated system developed ensures the follow-up of the blood pressure of a large number of users. In addition, this system can be further applied to diseases such as diabetes and metabolic syndrome. The system developed was easy to use and efficient to monitor patients with chronic diseases such as high blood pressure.

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Experiences of building a medical data acquisition system based on two-level modeling

Cited by 14 publications

References 29 publications

Electronic health records in Brazil: Prospects and technological challenges

Electronic health records in Brazil: Prospects and technological challenges

A customized stacked dense network model for chronic kidney disease prediction

Automatized follow-up and alert system for patients with chronic hypertension

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