The Fast Health Interoperability Resources (FHIR) standard and homecare, a scoping review

The scoping review reported by this article aimed to analyze the state of the art of the use of Fast Health Interoperability Resources (FHIR) in the development of homecare applications and was informed by the following research questions: (i) what type of homecare applications benefit from the use of FHIR?; (ii) what FHIR resources are being implemented?; (iii) what publicly available development tools are being used?; and (iv) how privacy and security issues are being addressed? An electronic search was conducted, and 27 studies were included in the scoping review after the selection process. The results show a current interest in using FHIR to implement: i) applications to provide interoperable measurement devices for home monitoring; (ii) applications to remotely collected Patient Reported Outcome Measures (PROM); (iii) Personal Health Records (PHR); and (iv) specific applications for self-management. According to the results, the FHIR resources being implemented are quite diverse and contribute for the challenge of handling the variability caused by diverse healthcare processes. However, the use of publicly available development tools (e.g., SMART on FHIR or HAPI) is not yet generalized. Moreover, just a small number of studies reported the validation of the implemented resources using publicly available FHIR validators. Finally, in terms of privacy and security issues, different approaches were identified: authentication and authorizations mechanisms, end-to-end encrypted messaging mechanisms, and decentralized management and audit trail based on blockchain technologies.publishe

Data protection issues in cross-border interoperability of Electronic Health Record systems within the European Union

Abstract This study investigates the data protection concerns arising in the context of the cross-border interoperability of Electronic Health Record (EHR) systems in the European Union. The article first introduces the policies on digital health and examines the related interoperability issues. Second, the work analyses the latest Recommendation of the European Commission on this topic. Then, the study discusses the rules and the obligations settled by the General Data Protection Regulation to be taken into account when developing interoperable EHRs. According to the data protection by design and by default provision, EHR systems should be designed ex ante to guarantee data protection rules

Upaya Aksesibilitas Data Kesehatan Pasien Untuk Pemantauan Kesehatan Secara Mandiri: Interoperabilitas e-PHR

Latar belakang: Melalui kemudahan untuk dapat memelihara catatan pemeriksaan medisnya sendiri dan menentukan hak akses dalam memiliki data pribadi, maka pasien dapat memanfaatkan akses tersebut untuk meningkatkan kesehatan dan mengelola penyakitnya sendiri. Namun, saat ini masyarakat masih kesulitan dalam mengakses data kesehatannya. Data yang diambil dalam EHR hanya dapat diakses oleh fasilitas kesehatan, sedangkan pasien tidak memiliki akses bahkan terhadap data kesehatannya sendiri. Melalui PHR, pasien dapat mengakses hasil tes laboratorium dengan cepat, serta melihat riwayat pemeriksaan dan pengobatan. Dalam pelaksanaannya seringkali fasilitas kesehatan tidak membagikan data pasien mereka. Selain itu, catatan kesehatan biasanya disimpan dalam standar yang berbeda pada masing-masing fasilitas kesehatan, sehingga kesulitan untuk pertukaran catatan kesehatan antar fasilitas kesehatan. Padahal, idealnya berbagai layanan sistem informasi dapat saling bertukar data untuk memperoleh data pasien secara komprehensif dan longitudinal. Sejalan dengan hal tersebut, laboratorium SIMKES UGM mengembangkan aplikasi Nusacare, yaitu bentuk digitalisasi dari PHR yang bertujuan memantau kesehatan individu. Agar pengguna dapat mengakses data kesehatannya dari rekam kesehatan elektronik di fasilitas kesehatan maka diperlukan perancangan sistem interoperabilitas.Metode: Jenis penelitian dalam penelitian ini adalah deskriptif kualitatif dengan desain penelitian action research. Tahapan penelitian terbagi menjadi empat fase yakni (1) Diagnosing Action, (2) Planning Action, (3) Taking Action, dan (4) Evaluation. Cara pengumpulan data dengan metode wawancara mendalam, FGD, dan studi dokumen.Hasil: Tahap diagnosing dengan mengidentifikasi tantangan dalam hal teknis maupun non teknis, serta menganalisis kebutuhan pengguna terkait fitur, standar data dan interoperabilitas aplikasi e-PHR sesuai kebutuhan. Pada tahap planning melalui pemetaan dan gap analysis elemen data yang mengacu standar interoperabilitas HL7 FHIR R4 version menghasilkan profile sistem interoperabilitas yang diunggah dan divalidasi oleh platform Simplifier.net, serta berhasil diuji coba pada aplikasi PHR Nusacare. Pada tahap evaluasi, keseluruhan pengguna menyatakan sistem interoperabilitas bermanfaat terhadap kemudahan akses data kesehatan, membantu pasien dalam melakukan pemantauan kesehatan mandiri, serta mendukung kolaborasi internal organisasi, tetapi terkendala pada interoperabilitas ke organisasi external lainnya yang tidak saling membuka akses untuk interoperabilitas.Kesimpulan: Sistem interoperabilitas e-PHR dapat memberikan manfaat khususnya bagi pasien untuk memudahkan mengakses data kesehatannya dari rekam kesehatan elektronik di fasilitas kesehatan, dengan mendapatkan informasi kesehatan yang dibutuhkan akan membantu pasien dalam melakukan pemantauan kesehatan secara mandiri sehingga perawatan kesehatan pada pasien dapat berkesinambungan

Information Is Selection-A Review of Basics Shows Substantial Potential for Improvement of Digital Information Representation

Any piece of information is a selection from a set of possibilities. In this paper, this set is called a "domain". Digital information consists of number sequences, which are selections from a domain. At present, these number sequences are defined contextually in a very variable way, which impairs their comparability. Therefore, global uniformly defined "domain vectors" (DVs), with a structure containing a "Uniform Locator" ("UL"), referred to as "UL plus number sequence", are proposed. The "UL" is an efficient global pointer to the uniform online definition of the subsequent number sequence. DVs are globally defined, identified, comparable, and searchable by criteria which users can define online. In medicine, for example, patients, doctors, and medical specialists can define DVs online and can, therefore, form global criteria which are important for certain diagnoses. This allows for the immediate generation of precise diagnostic specific statistics of "similar medical cases", in order to discern the best therapy. The introduction of a compact DV data structure may substantially improve the digital representation of medical information

An Interoperable Electronic Health Record System for Clinical Cardiology

Currently in hospitals, there are several separate information systems that manage, very often autonomously, the patient’s personal, clinical and diagnostic data. An electronic health record system has been specifically developed for a cardiology ward and it has been designed “ab initio” to be fully integrated into the hospital information system and to exchange data with the regional health information infrastructure. All documents have been given as Health Level 7 (HL7) clinical document architecture and messages are sent as HL7-Version 2 (V2) and/or HL7 Fast Healthcare Interoperability Resources (FHIR). Specific decision support sections for specific aspects have also been included. The system has been used for more than three years with a good level of satisfaction by the users. In the future, the system can be the basis for secondary use for clinical studies, further decision support systems and clinical trials

Proposing an International Standard Accident Number for Interconnecting Information and Communication Technology Systems of the Rescue Chain

Background  The rapid dissemination of smart devices within the internet of things (IoT) is developing toward automatic emergency alerts which are transmitted from machine to machine without human interaction. However, apart from individual projects concentrating on single types of accidents, there is no general methodology of connecting the standalone information and communication technology (ICT) systems involved in an accident: systems for alerting (e.g., smart home/car/wearable), systems in the responding stage (e.g., ambulance), and in the curing stage (e.g., hospital). Objectives  We define the International Standard Accident Number (ISAN) as a unique token for interconnecting these ICT systems and to provide embedded data describing the circumstances of an accident (time, position, and identifier of the alerting system). Materials and methods  Based on the characteristics of processes and ICT systems in emergency care, we derive technological, syntactic, and semantic requirements for the ISAN, and we analyze existing standards to be incorporated in the ISAN specification. Results  We choose a set of formats for describing the embedded data and give rules for their combination to generate an ISAN. It is a compact alphanumeric representation that is generated easily by the alerting system. We demonstrate generation, conversion, analysis, and visualization via representational state transfer (REST) services. Although ISAN targets machine-to-machine communication, we give examples of graphical user interfaces. Conclusion  Created either locally by the alerting IoT system or remotely using our RESTful service, the ISAN is a simple and flexible token that enables technological, syntactic, and semantic interoperability between all ICT systems in emergency care

Privacy-Aware Architectures for NFC and RFID Sensors in Healthcare Applications

World population and life expectancy have increased steadily in recent years, raising issues regarding access to medical treatments and related expenses. Through last-generation medical sensors, NFC (Near Field Communication) and radio frequency identification (RFID) technologies can enable healthcare internet of things (H-IoT) systems to improve the quality of care while reducing costs. Moreover, the adoption of point-of-care (PoC) testing, performed whenever care is needed to return prompt feedback to the patient, can generate great synergy with NFC/RFID H-IoT systems. However, medical data are extremely sensitive and require careful management and storage to protect patients from malicious actors, so secure system architectures must be conceived for real scenarios. Existing studies do not analyze the security of raw data from the radiofrequency link to cloud-based sharing. Therefore, two novel cloud-based system architectures for data collected from NFC/RFID medical sensors are proposed in this paper. Privacy during data collection is ensured using a set of classical countermeasures selected based on the scientific literature. Then, data can be shared with the medical team using one of two architectures: in the first one, the medical system manages all data accesses, whereas in the second one, the patient defines the access policies. Comprehensive analysis of the H-IoT system can be useful for fostering research on the security of wearable wireless sensors. Moreover, the proposed architectures can be implemented for deploying and testing NFC/RFID-based healthcare applications, such as, for instance, domestic PoCs

Interoperability Reference Models for Applications of Artificial Intelligence in Medical Imaging

Medical imaging is currently being applied in artificial intelligence and big data technologies in data formats. In order for medical imaging collected from different institutions and systems to be used for artificial intelligence data, interoperability is becoming a key element. Whilst interoperability is currently guaranteed through medical data standards, compliance to personal information protection laws, and other methods, a standard solution for measurement values is deemed to be necessary in order for further applications as artificial intelligence data. As a result, this study proposes a model for interoperability in medical data standards, personal information protection methods, and medical imaging measurements. This model applies Health Level Seven (HL7) and Digital Imaging and Communications in Medicine (DICOM) standards to medical imaging data standards and enables increased accessibility towards medical imaging data in the compliance of personal information protection laws through the use of de-identifying methods. This study focuses on offering a standard for the measurement values of standard materials that addresses uncertainty in measurements that pre-existing medical imaging measurement standards did not provide. The study finds that medical imaging data standards conform to pre-existing standards and also provide protection to personal information within any medical images through de-identifying methods. Moreover, it proposes a reference model that increases interoperability by composing a process that minimizes uncertainty using standard materials. The interoperability reference model is expected to assist artificial intelligence systems using medical imaging and further enhance the resilience of future health technologies and system development.ope

Challenges and opportunities beyond structured data in analysis of electronic health records

Electronic health records (EHR) contain a lot of valuable information about individual patients and the whole population. Besides structured data, unstructured data in EHRs can provide extra, valuable information but the analytics processes are complex, time-consuming, and often require excessive manual effort. Among unstructured data, clinical text and images are the two most popular and important sources of information. Advanced statistical algorithms in natural language processing, machine learning, deep learning, and radiomics have increasingly been used for analyzing clinical text and images. Although there exist many challenges that have not been fully addressed, which can hinder the use of unstructured data, there are clear opportunities for well-designed diagnosis and decision support tools that efficiently incorporate both structured and unstructured data for extracting useful information and provide better outcomes. However, access to clinical data is still very restricted due to data sensitivity and ethical issues. Data quality is also an important challenge in which methods for improving data completeness, conformity and plausibility are needed. Further, generalizing and explaining the result of machine learning models are important problems for healthcare, and these are open challenges. A possible solution to improve data quality and accessibility of unstructured data is developing machine learning methods that can generate clinically relevant synthetic data, and accelerating further research on privacy preserving techniques such as deidentification and pseudonymization of clinical text

Mobile Health in Remote Patient Monitoring for Chronic Diseases: Principles, Trends, and Challenges

Chronic diseases are becoming more widespread. Treatment and monitoring of these diseases require going to hospitals frequently, which increases the burdens of hospitals and patients. Presently, advancements in wearable sensors and communication protocol contribute to enriching the healthcare system in a way that will reshape healthcare services shortly. Remote patient monitoring (RPM) is the foremost of these advancements. RPM systems are based on the collection of patient vital signs extracted using invasive and noninvasive techniques, then sending them in real-time to physicians. These data may help physicians in taking the right decision at the right time. The main objective of this paper is to outline research directions on remote patient monitoring, explain the role of AI in building RPM systems, make an overview of the state of the art of RPM, its advantages, its challenges, and its probable future directions. For studying the literature, five databases have been chosen (i.e., science direct, IEEE-Explore, Springer, PubMed, and science.gov). We followed the (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) PRISMA, which is a standard methodology for systematic reviews and meta-analyses. A total of 56 articles are reviewed based on the combination of a set of selected search terms including RPM, data mining, clinical decision support system, electronic health record, cloud computing, internet of things, and wireless body area network. The result of this study approved the effectiveness of RPM in improving healthcare delivery, increase diagnosis speed, and reduce costs. To this end, we also present the chronic disease monitoring system as a case study to provide enhanced solutions for RPMsThis research work was partially supported by the Sejong University Research Faculty Program (20212023)S