Difference between revisions of "Journal:Implement an international interoperable PHR by FHIR: A Taiwan innovative application"

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[[Personal health record]]s (PHRs) are personalized records that include data related to health.<ref name="TangPerson06">{{cite journal |title=Personal health records: definitions, benefits, and strategies for overcoming barriers to adoption |journal=JAMIA |author=Tang, P.C.; Ash, J.S.; Bates, D.W. et al. |volume=13 |issue=2 |pages=121–6 |year=2006 |doi=10.1197/jamia.M2025 |pmid=16357345 |pmc=PMC1447551}}</ref> The Markle Foundation’s "Connecting for Health" collaborative defines a PHR as “an electronic application through which individuals can access, manage, and share their health information, and that of others for whom they are authorized, in a private, secure, and confidential environment.”<ref name="MarkleConnect03">{{cite web |url=https://www.markle.org/sites/default/files/final_phwg_report1.pdf |format=PDF |title=Connecting for Health: A Public-Private Collaborative |author=Markle Foundation |publisher=Markle Foundation |date=01 July 2003 |accessdate=10 March 2021}}</ref> This differs from the more widely used [[electronic medical record]] (EMR), which focuses on clinical data and is operated by the medical service provider (such as clinics and [[hospital]]s). PHRs have great benefits for health monitoring, [[Epidemiology|epidemiological surveillance]], self-control, linkages with different services, and [[public health]] management in areas such as international health care.<ref name="PowerActive17">{{cite journal |title=Active Use of Electronic Health Records (EHRs) and Personal Health Records (PHRs) for Epidemiologic Research: Sample Representativeness and Nonresponse Bias in a Study of Women During Pregnancy |journal=EGEMS |author=Bower, J.K.; Bollinger, C.E.; Foraker, R.E. et al. |volume=5 |issue=1 |at=1263 |year=2017 |doi=10.13063/2327-9214.1263 |pmid=28303255 |pmc=PMC5340503}}</ref><ref name="BonanderPublic10">{{cite journal |title=Public health in an era of personal health records: Opportunities for innovation and new partnerships |journal=Journal of Medical Internet Research |author=Bonanader, J.; Gates, S. |volume=12 |issue=3 |at=e33 |year=2010 |doi=10.2196/jmir.1346 |pmid=20699216 |pmc=PMC2956336}}</ref>
[[Personal health record]]s (PHRs) are personalized records that include data related to health.<ref name="TangPerson06">{{cite journal |title=Personal health records: definitions, benefits, and strategies for overcoming barriers to adoption |journal=JAMIA |author=Tang, P.C.; Ash, J.S.; Bates, D.W. et al. |volume=13 |issue=2 |pages=121–6 |year=2006 |doi=10.1197/jamia.M2025 |pmid=16357345 |pmc=PMC1447551}}</ref> The Markle Foundation’s "Connecting for Health" collaborative defines a PHR as “an electronic application through which individuals can access, manage, and share their health information, and that of others for whom they are authorized, in a private, secure, and confidential environment.”<ref name="MarkleConnect03">{{cite web |url=https://www.markle.org/sites/default/files/final_phwg_report1.pdf |format=PDF |title=Connecting for Health: A Public-Private Collaborative |author=Markle Foundation |publisher=Markle Foundation |date=01 July 2003 |accessdate=10 March 2021}}</ref> This differs from the more widely used [[electronic medical record]] (EMR), which focuses on clinical data and is operated by the medical service provider (such as clinics and [[hospital]]s). PHRs have great benefits for health monitoring, [[Epidemiology|epidemiological surveillance]], self-control, linkages with different services, and [[public health]] management in areas such as international health care.<ref name="PowerActive17">{{cite journal |title=Active Use of Electronic Health Records (EHRs) and Personal Health Records (PHRs) for Epidemiologic Research: Sample Representativeness and Nonresponse Bias in a Study of Women During Pregnancy |journal=EGEMS |author=Bower, J.K.; Bollinger, C.E.; Foraker, R.E. et al. |volume=5 |issue=1 |at=1263 |year=2017 |doi=10.13063/2327-9214.1263 |pmid=28303255 |pmc=PMC5340503}}</ref><ref name="BonanderPublic10">{{cite journal |title=Public health in an era of personal health records: Opportunities for innovation and new partnerships |journal=Journal of Medical Internet Research |author=Bonanader, J.; Gates, S. |volume=12 |issue=3 |at=e33 |year=2010 |doi=10.2196/jmir.1346 |pmid=20699216 |pmc=PMC2956336}}</ref>


Recently, medical services have placed more focus on precision medicine, which refers to specific medical treatments based on the individual characteristics of each patient.<ref name="TimmermanWhat13">{{cite web |url=https://xconomy.com/national/2013/02/04/whats-in-a-name-a-lot-when-it-comes-to-precision-medicine/ |title=What’s in a Name? A Lot, When It Comes to ‘Precision Medicine’ |author=Timmerman, L. |work=Xconomy |date=04 February 2013}}</ref> PHRs are a crucial component of precision medicine. The [[information]] in PHRs can provide more details for [[Clinical decision support system|clinical decision support]]. Based on a foundation of an electronic [[hospital information system]], we can get plentiful personal health data to create PHRs. Taiwan has implemented national centralized health insurance information systems since the establishment of the Taiwan National Health Insurance Administration (NHIA) in 1995. According to ''CEOWORLD magazine''’s 2019 “Health Care Index” statistics, Taiwan has the best medical system in the world<ref name="IrelandReveal19">{{cite web |url=https://ceoworld.biz/2019/08/05/revealed-countries-with-the-best-health-care-systems-2019/ |title=Revealed: Countries With The Best Health Care Systems, 2019 |author=Ireland, S. |work=CEOWORLD magazine |date=05 August 2019}}</ref>, while the National Health Insurance (NHI) has a coverage rate of more than 99%.<ref name="IqbalIsLong15">{{cite journal |title=Is long-term use of benzodiazepine a risk for cancer? |author=Iqbal, U.; Nguyen, P.-A.; Syed-Abdul, S. et al. |volume=94 |issue=6 |at=e483 |doi=10.1097/MD.0000000000000483 |pmid=25674736 |pmc=PMC4602739}}</ref> The NHIA pays for most of the medical service expenses of all Taiwanese citizens to the hospitals and clinics that provide services. For the reimbursement procedure, hospitals and clinics need to upload patient care data related to the payment, including the diagnosis, prescriptions, treatment information, images, testing data, etc. to NHIA information systems. By doing so, the NHIA has collected almost all individual medical care data in Taiwan and stores it at the NHIA’s data center. To promote personal health management, the NHIA launched the "My Health Bank" (MHB) system in September 2014. The MHB system is a personalized [[Cloud computing|cloud-based]] service that aims to return personal medical data back to the citizens. Individuals can use their citizen digital certificate or password-registered NHI card as identity verification to download their medical data that have been collected by health insurance.
Recently, medical services have placed more focus on precision medicine, which refers to specific medical treatments based on the individual characteristics of each patient.<ref name="TimmermanWhat13">{{cite web |url=https://xconomy.com/national/2013/02/04/whats-in-a-name-a-lot-when-it-comes-to-precision-medicine/ |title=What’s in a Name? A Lot, When It Comes to ‘Precision Medicine’ |author=Timmerman, L. |work=Xconomy |date=04 February 2013}}</ref> PHRs are a crucial component of precision medicine. The [[information]] in PHRs can provide more details for [[Clinical decision support system|clinical decision support]]. Based on a foundation of an electronic [[hospital information system]] (HIS), we can get plentiful personal health data to create PHRs. Taiwan has implemented national centralized health insurance information systems since the establishment of the Taiwan National Health Insurance Administration (NHIA) in 1995. According to ''CEOWORLD magazine''’s 2019 “Health Care Index” statistics, Taiwan has the best medical system in the world<ref name="IrelandReveal19">{{cite web |url=https://ceoworld.biz/2019/08/05/revealed-countries-with-the-best-health-care-systems-2019/ |title=Revealed: Countries With The Best Health Care Systems, 2019 |author=Ireland, S. |work=CEOWORLD magazine |date=05 August 2019}}</ref>, while the National Health Insurance (NHI) has a coverage rate of more than 99%.<ref name="IqbalIsLong15">{{cite journal |title=Is long-term use of benzodiazepine a risk for cancer? |author=Iqbal, U.; Nguyen, P.-A.; Syed-Abdul, S. et al. |volume=94 |issue=6 |at=e483 |doi=10.1097/MD.0000000000000483 |pmid=25674736 |pmc=PMC4602739}}</ref> The NHIA pays for most of the medical service expenses of all Taiwanese citizens to the hospitals and clinics that provide services. For the reimbursement procedure, hospitals and clinics need to upload patient care data related to the payment, including the diagnosis, prescriptions, treatment information, images, testing data, etc. to NHIA information systems. By doing so, the NHIA has collected almost all individual medical care data in Taiwan and stores it at the NHIA’s data center. To promote personal health management, the NHIA launched the "My Health Bank" (MHB) system in September 2014. The MHB system is a personalized [[Cloud computing|cloud-based]] service that aims to return personal medical data back to the citizens. Individuals can use their citizen digital certificate or password-registered NHI card as identity verification to download their medical data that have been collected by health insurance.


The NHIA aims to let citizens more directly control and manage their health data. Based on a cloud-based system, people can access their personal health insurance records in the past three years via the NHIA’s MHB portal, and the data can be printed out or downloaded. The NHIA hopes that citizens will have access to MHB when they go to a clinic or hospital as a reference for the physician. This service promotes people to have their health information and know their own health status.
The NHIA aims to let citizens more directly control and manage their health data. Based on a cloud-based system, people can access their personal health insurance records in the past three years via the NHIA’s MHB portal, and the data can be printed out or downloaded. The NHIA hopes that citizens will have access to MHB when they go to a clinic or hospital as a reference for the physician. This service promotes people to have their health information and know their own health status.
Line 54: Line 54:
==Literature review==
==Literature review==
Personal health information is an important foundation for the development of smart medical care. In addition to EMRs for medical consultations, institutional care records, and physiological data measured by medical materials, it also includes daily food content and wound conditions, which can be included in personal health records.
Personal health information is an important foundation for the development of smart medical care. In addition to EMRs for medical consultations, institutional care records, and physiological data measured by medical materials, it also includes daily food content and wound conditions, which can be included in personal health records.
Although there are many standards in the medical domain, the interoperability between different systems is still poor. There are many problems that need to be solved for system interoperability. Therefore, HL7 has developed FHIR as a new foundation to achieve interoperability. FHIR is currently a widely adopted health information standard. It is not a kind of EHR; rather, it describes the data format and data elements of EHRs. FHIR is the new HL7 standard that evolved from the HL7 v2, HL7 v3, and HL7 CDA standards, which aim for easier implementation.<ref name="HL7_FHIR">{{cite web |url=https://hl7.org/FHIR/ |title=Welcome to FHIR |publisher=Health Level 7 |date=01 November 2019 |accessdate=26 April 2020}}</ref> The main goals of FHIR are to promote the effective communication and content of medical information and to widely use medical information on a variety of devices, including computers, tablets, IoT devices, and smartphones, so as to provide medical services to hospitals and individuals more easily. It also provides systematic information to third-party application developers. FHIR has the characteristics and value of being open and easy to expand by publicly providing data elements in a standardized format. It also provides an alternative to document-centric approaches by providing different data elements separately as a service. For example, with the corresponding resource URLs, basic healthcare service elements such as patients, admissions, diagnostic reports, and medications can be accessed and manipulated. The implementation of FHIR is based on the HL7 and HTTPS (HTTP Secure) protocols; therefore, the wire data analysis platform can parse messages for real-time data collection. According to this idea, when FHIR messages are transmitted over the network, the medical service organization will be able to use these messages to collect real-time data. This data can then be fed into the data store where it is associated with other informatics data. FHIR uses a web-based API suite, including HTML, HTTP-based RESTful protocols, and cascading style sheets (CSS) for the user interface. The document format can be based on the JSON or XML format.
Schleyer ''et al.'' created a medical dashboard based on FHIR that integrates clinical information from the HISs with the EHR. Testing in a medical organization showed that the integration dashboard is useful. The clinical information can be integrated effectively based on FHIR.<ref name="SchleyerPrelim19">{{cite journal |title=Preliminary evaluation of the ''Chest Pain Dashboard'', a FHIR-based approach for integrating health information exchange information directly into the clinical workflow |journal=AMIA Joint Summits on Translational Science |author=Schleyer, T.K.L.; Rahurkar, S.; Baublet, A.M. et al. |volume=2019 |pages=656-664 |year=2019 |pmid=31259021 |pmc=PMC6568135}}</ref> FHIR uses widely adopted web technologies, is implementer-friendly and vendor-independent, and offers a useful architecture of applications and formats for EHR providers, healthcare providers, and public health professionals.<ref name="GoodmanHealthy18">{{cite journal |title=Healthy Weight on FHIR - Innovative Technology to Support High Quality Clinical Care & Clinical to Community Linkages for Child Obesity |journal=PEdiatrics |author=Goodman, A.B.; Braun, P.; Braunstein, M. |volume=141 |issue=1 MeetingAbstract |page=12 |year=2018 |doi=10.1542/peds.141.1_MeetingAbstract.12}}</ref> Baihan ''et al.'' implemented FHIR in the m-Health domain and used FHIR to integrate health information technology (HIT) systems with m-Health applications.<ref name="BaihanABlue18">{{cite book |chapter=Chapter 6: A Blueprint for Designing and Developing M-Health Applications for Diverse Stakeholders Utilizing FHIR |title=Contemporary Applications of Mobile Computing in Healthcare Settings |author=Baihan, M.S.; Sánchez, Y.K.R.; Shao, X. et al. |editor=Rajkumar, R. |publisher=IGI Global |pages=85–124 |year=2018 |isbn=9781522550365 |doi=10.4018/978-1-5225-5036-5.ch006}}</ref> Daumke presented an architecture to harmonize commercial clinical text-mining tools by FHIR, which can be used as a clinical information model standard.<ref name="DaumkeClinical19">{{cite journal |title=Clinical Text Mining on FHIR |journal=Studies in Health Technology and Informatics |author=Daumke, P.; Heitmann, K.U.; Heckmann, S. et al. |volume=264 |pages=83–7 |year=2019 |doi=10.3233/SHTI190188 |pmid=31437890}}</ref> Recently, many research and industry products provide examples of how FHIR can be used for healthcare data integration <ref name="StorckInter19">{{cite journal |title=Interoperability Improvement of Mobile Patient Survey (MoPat) Implementing Fast Health Interoperability Resources (FHIR) |journal=Studies in Health Technology and Informatics |author=Storck, M.; Hollenberg, L.; Dugas, M. et al. |volume=258 |pages=141–45 |year=2019 |pmid=30942732}}</ref><ref name="GiordanengoAFHIR18">{{cite web |url=https://ehealthresearch.no/files/documents/Postere/Poster_2018-02_16-9-ATTD-FHIR-based-Data-Flow.pdf |format=PDF |title=A FHIR-based Data Flow Enabling Patients with Diabetes to Share Self-collected Data with the Norwegian National Healthcare Systems and Electronic Health Records Systems |author=Giordanengo, A.; Bradway, M.; Grøttland, A. et al. |publisher=Norwegian Centre for E-health Research |work=2017 Scandinavian Conference on Health Informatics |date=29 August 2017}}</ref><ref name="KiourtisStruct19">{{cite journal |title=Structurally Mapping Healthcare Data to HL7 FHIR through Ontology Alignment |journal=Journal of Medical Systems |author=Kiourtis, A.; Mavrogiorgou, A.; Menychtas, A. et al. |volume=43 |issue=3 |at=62 |year=2019 |doi=10.1007/s10916-019-1183-y |pmid=30721349}}</ref><ref name="GøegAFutur18">{{cite journal |title=A future-proof architecture for telemedicine using loose-coupled modules and HL7 FHIR |journal=Computer Methods and Programs in Biomedicine |author=Gøeg, K.R.; Rasmussen, R.K.; Jensen, L. et al. |volume=160 |pages=95–101 |year=2018 |doi=10.1016/j.cmpb.2018.03.010 |pmid=29728251}}</ref><ref name="AlperAchiev19">{{cite journal |title=Achieving evidence interoperability in the computer age: Setting evidence on FHIR |journal=BMJ Evidence-Based Medicine |author=Alper, B.; Mayer, M.; Shahin, K. et al. |volume=24 |issue=Suppl. 1 |at=A15 |year=2019 |url=https://ebm.bmj.com/content/24/Suppl_1/A15.1}}</ref><ref name="LackerbauerAModel18">{{cite journal |title=A Model for Implementing an Interoperable Electronic Consent Form for Medical Treatment Using HL7 FHIR |journal=European Journal for Biomedical Informatics |author=Lackerbauer, A.M.; Lin, A.C.; Krauss, O. et al. |volume=14 |issue=3 |pages=37–47 |year=2018 |doi=10.24105/ejbi.2018.14.3.6}}</ref><ref name="DixonInteg19">{{cite journal |title=Integration of FHIR to Facilitate Electronic Case Reporting: Results from a Pilot Study |journal=Studies in Health Technology and Informatics |author=Dixon, B.E.; Taylor, D.E.; Choi, M. et al. |volume=264 |pages=940–44 |year=2019 |doi=10.3233/SHTI190362 |pmid=31438062}}</ref><ref name="HussainLearn18">{{cite journal |title=Learning HL7 FHIR Using the HAPI FHIR Server and Its Use in Medical Imaging with the SIIM Dataset |journal=Journal of Digital Imaging |author=Hussain, M.A.; Langer, S.G.; Kohli, M. et al. |volume=31 |issue=3 |pages=334–40 |year=2018 |doi=10.1007/s10278-018-0090-y |pmid=29725959 |pmc=PMC5959839}}</ref>, highlighting how FHIR has realized interoperability between different healthcare systems.




Revision as of 18:12, 11 March 2021

Full article title Implement an international interoperable PHR by FHIR: A Taiwan innovative application
Journal Sustainability
Author(s) Lee, Yen-Liang; Lee, Hsiu-An; Hsu, Chien-Yeh; Kung, Hsin-Yeh; Chiu, Hung-Wen
Author affiliation(s) Taipei Medical University, Chunghwa Telecom Laboratories, Tamkang University,
Smart Healthcare Center of Excellence, National Taipei University of Nursing and Health Sciences
Primary contact hwchiu at tmu dot edu dot tw
Year published 2020
Volume and issue 13(1)
Article # 198
DOI 10.3390/su13010198
ISSN 2071-1050
Distribution license Creative Commons Attribution 4.0 International
Website https://www.mdpi.com/2071-1050/13/1/198/htm
Download https://www.mdpi.com/2071-1050/13/1/198/pdf (PDF)
Emblem-important-yellow.svg This article should be considered a work in progress and incomplete. Consider this article incomplete until this notice is removed.

Abstract

Personal health records (PHRs) have many benefits for things such as health surveillance, epidemiological surveillance, self-control, links to various services, public health and health management, and international surveillance. The implementation of an international standard for interoperability is essential to accessing PHRs. In Taiwan, the nationwide exchange platform for electronic medical records (EMRs) has been in use for many years. The Health Level Seven International (HL7) Clinical Document Architecture (CDA) was used as the standard for those EMRs. However, the complication of implementing CDA became a barrier for many hospitals to realizing standard EMRs.

In this study, we implemented a Fast Healthcare Interoperability Resources (FHIR)-based PHR transformation process, including a user interface module to review the contents of PHRs. We used “My Health Bank” (MHB), a PHR data book developed and issued to all people by the Taiwan National Health Insurance, as the PHRs' contents in this study. Network Time Protocol (NTP)/Simple Network Time Protocol (SNTP) was used in the security and user authentication mechanism when processing and applying personal health information. Transport Layer Security (TLS) 1.2 (such as HyperText Transfer Protocol Secure or HTTPS) was used for protection in data communication. User authentication is important in the platform. OAuth (OAuth 2.0) was used as a user authentication mechanism to confirm legitimate user access to ensure data security. The contents of MHB were analyzed and mapped to FHIR, and then converted to FHIR format according to the mapping logic template. The function of format conversion was carried out by using ASP.NET. XPath and JSPath technologies filtered out specific information tags. The converted data structure was verified through an HL7 application programming interface (HAPI) server, and a new JSON file was finally created.

This platform can not only capture any PHR based on the FHIR format but also publish FHIR-based MHB records to any other platform to bridge the interoperability gap between different PHR systems. Therefore, our implementation/application with the automatic transformation from MHB to FHIR format provides an innovative method for people to access their own PHRs through MHB. No one has published a similar application like us using a nationwide PHR standard, MHB, in Taiwan. The application we developed will be very useful for a single person to use or for other system developers to implement their own standard PHR software.

Keywords: FHIR, interoperability, PHR, data management, precision health management

Introduction

Personal health records (PHRs) are personalized records that include data related to health.[1] The Markle Foundation’s "Connecting for Health" collaborative defines a PHR as “an electronic application through which individuals can access, manage, and share their health information, and that of others for whom they are authorized, in a private, secure, and confidential environment.”[2] This differs from the more widely used electronic medical record (EMR), which focuses on clinical data and is operated by the medical service provider (such as clinics and hospitals). PHRs have great benefits for health monitoring, epidemiological surveillance, self-control, linkages with different services, and public health management in areas such as international health care.[3][4]

Recently, medical services have placed more focus on precision medicine, which refers to specific medical treatments based on the individual characteristics of each patient.[5] PHRs are a crucial component of precision medicine. The information in PHRs can provide more details for clinical decision support. Based on a foundation of an electronic hospital information system (HIS), we can get plentiful personal health data to create PHRs. Taiwan has implemented national centralized health insurance information systems since the establishment of the Taiwan National Health Insurance Administration (NHIA) in 1995. According to CEOWORLD magazine’s 2019 “Health Care Index” statistics, Taiwan has the best medical system in the world[6], while the National Health Insurance (NHI) has a coverage rate of more than 99%.[7] The NHIA pays for most of the medical service expenses of all Taiwanese citizens to the hospitals and clinics that provide services. For the reimbursement procedure, hospitals and clinics need to upload patient care data related to the payment, including the diagnosis, prescriptions, treatment information, images, testing data, etc. to NHIA information systems. By doing so, the NHIA has collected almost all individual medical care data in Taiwan and stores it at the NHIA’s data center. To promote personal health management, the NHIA launched the "My Health Bank" (MHB) system in September 2014. The MHB system is a personalized cloud-based service that aims to return personal medical data back to the citizens. Individuals can use their citizen digital certificate or password-registered NHI card as identity verification to download their medical data that have been collected by health insurance.

The NHIA aims to let citizens more directly control and manage their health data. Based on a cloud-based system, people can access their personal health insurance records in the past three years via the NHIA’s MHB portal, and the data can be printed out or downloaded. The NHIA hopes that citizens will have access to MHB when they go to a clinic or hospital as a reference for the physician. This service promotes people to have their health information and know their own health status.

However, despite the rich content of MHB and the data quality of the information confirmed in diagnosis, medicine, and other items, the information continues to use the original insurance declaration form and does not follow the relevant medical information standards. This makes it difficult to integrate and apply information. In addition, the official MHB system is mainly used as a data provider. The content is mainly based on the qualified medical insurance service records of various contracted hospitals, clinics, or institutions. Individuals are not allowed to add other personalized information themselves. Additionally, cloud-based systems can make it hard to share data with the doctor. When people see a doctor for an urgent reason, there may not be enough time to log into the MHB system and search for data. Although individuals can download data from the website, the data will be in the XML or JSON format, which most individuals cannot read. In addition, the content of PHRs does not follow any international format, making it quite difficult to exchange data or interoperate with other health information systems. The application and sharing of PHRs are very important. In order to achieve precision medicine, PHRs need to comply with international standards before they can be accepted, integrated, and applied by different systems.

Jung et al.[8] agree that an integrated personal health record is more valuable than a single record. The impact of interoperability on PHRs has been the focus of interdisciplinary researchers in recent years. A survey article by Alyami and Song[9] emphasized the vital role of interoperability in the implementation and adoption of PHRs. Plastiras and O'Sullivan[10] developed an ontology-driven intermediary layer to achieve interoperability between PHRs and electronic health records (EHRs) of various standards. Li[11] developed a service-oriented interoperable integrated PHR system and explained that it can be used to overcome interoperability problems between medical systems. Urbauer et al.[12] compared the interoperability procedures for the communication of medical systems and personal health devices to analyze the advantages and gaps, including presenting a total solution for interoperability. And Roehrs et al.[13] presented the crucial concept of interoperability for developing and using PHRs.

According to other related studies, the key point of PHR applications from different sources is application integration and content standardization. In general, currently, most of the interoperability of medical information is still based on standardized data exchange and integration through the development of intermediary layers, data standard conversion, or ontology design. Taiwan has an advanced health insurance system and has collected complete personal health records since 1995. The huge health database gives Taiwan a good opportunity for precision medicine to use. However, due to the delayed process of government authority on the implementation of the data standardization and formatting, the data still cannot meet the requirements of international interoperability at present.

In Taiwan, the nationwide exchange platform for EMRs has been in use for many years. Although the [[Health Level Seven International (HL7) CDA was used as the standard of the EMRs, people outside the hospitals, including patients and many health management organizations, did not have the method to access the EMRs, and the complication of implementing CDA became a barrier for hospitals to realize the standard EMRs. As such, a concept was developed: the implementation with an automatic transformation from MHB to a [[Fast Healthcare Interoperability Resources (FHIR) format provides an innovative method for people to access their own PHRs through MHB. No one has published a similar application like us to use nationwide PHRs, i.e., MHB, in Taiwan. The application we developed will be very useful for a single person to use or for other system developers to implement their own standard PHR software.

This research focuses on converting Taiwan’s personal health information into a standardized international standard format and provide a management platform for personal health records. Based on an innovative application model of personal data (MHB) unique to Taiwan’s health insurance, we designed a demonstration framework to enable Taiwan to have better exemplary measures in personal health management, and take the lead in completing “patient-centered” precise health management. The goal of this study was to develop an interoperable international personal health record using HL7 FHIR as the data standard and MHB data as the data content. This study designed a personal health management platform that could fit international standards and support users to manage personal health based on MHB. As long as the FHIR format health record is uploaded, people from different countries can use it all over the world to manage their [[personal health information, allow physicians to conduct precise medical treatment, and provide clinical decision-making support to users.

Literature review

Personal health information is an important foundation for the development of smart medical care. In addition to EMRs for medical consultations, institutional care records, and physiological data measured by medical materials, it also includes daily food content and wound conditions, which can be included in personal health records.

Although there are many standards in the medical domain, the interoperability between different systems is still poor. There are many problems that need to be solved for system interoperability. Therefore, HL7 has developed FHIR as a new foundation to achieve interoperability. FHIR is currently a widely adopted health information standard. It is not a kind of EHR; rather, it describes the data format and data elements of EHRs. FHIR is the new HL7 standard that evolved from the HL7 v2, HL7 v3, and HL7 CDA standards, which aim for easier implementation.[14] The main goals of FHIR are to promote the effective communication and content of medical information and to widely use medical information on a variety of devices, including computers, tablets, IoT devices, and smartphones, so as to provide medical services to hospitals and individuals more easily. It also provides systematic information to third-party application developers. FHIR has the characteristics and value of being open and easy to expand by publicly providing data elements in a standardized format. It also provides an alternative to document-centric approaches by providing different data elements separately as a service. For example, with the corresponding resource URLs, basic healthcare service elements such as patients, admissions, diagnostic reports, and medications can be accessed and manipulated. The implementation of FHIR is based on the HL7 and HTTPS (HTTP Secure) protocols; therefore, the wire data analysis platform can parse messages for real-time data collection. According to this idea, when FHIR messages are transmitted over the network, the medical service organization will be able to use these messages to collect real-time data. This data can then be fed into the data store where it is associated with other informatics data. FHIR uses a web-based API suite, including HTML, HTTP-based RESTful protocols, and cascading style sheets (CSS) for the user interface. The document format can be based on the JSON or XML format.

Schleyer et al. created a medical dashboard based on FHIR that integrates clinical information from the HISs with the EHR. Testing in a medical organization showed that the integration dashboard is useful. The clinical information can be integrated effectively based on FHIR.[15] FHIR uses widely adopted web technologies, is implementer-friendly and vendor-independent, and offers a useful architecture of applications and formats for EHR providers, healthcare providers, and public health professionals.[16] Baihan et al. implemented FHIR in the m-Health domain and used FHIR to integrate health information technology (HIT) systems with m-Health applications.[17] Daumke presented an architecture to harmonize commercial clinical text-mining tools by FHIR, which can be used as a clinical information model standard.[18] Recently, many research and industry products provide examples of how FHIR can be used for healthcare data integration [19][20][21][22][23][24][25][26], highlighting how FHIR has realized interoperability between different healthcare systems.





References

  1. ↑ Tang, P.C.; Ash, J.S.; Bates, D.W. et al. (2006). "Personal health records: definitions, benefits, and strategies for overcoming barriers to adoption". JAMIA 13 (2): 121–6. doi:10.1197/jamia.M2025. PMC PMC1447551. PMID 16357345. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1447551. 
  2. ↑ Markle Foundation (1 July 2003). "Connecting for Health: A Public-Private Collaborative" (PDF). Markle Foundation. https://www.markle.org/sites/default/files/final_phwg_report1.pdf. Retrieved 10 March 2021. 
  3. ↑ Bower, J.K.; Bollinger, C.E.; Foraker, R.E. et al. (2017). "Active Use of Electronic Health Records (EHRs) and Personal Health Records (PHRs) for Epidemiologic Research: Sample Representativeness and Nonresponse Bias in a Study of Women During Pregnancy". EGEMS 5 (1): 1263. doi:10.13063/2327-9214.1263. PMC PMC5340503. PMID 28303255. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5340503. 
  4. ↑ Bonanader, J.; Gates, S. (2010). "Public health in an era of personal health records: Opportunities for innovation and new partnerships". Journal of Medical Internet Research 12 (3): e33. doi:10.2196/jmir.1346. PMC PMC2956336. PMID 20699216. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2956336. 
  5. ↑ Timmerman, L. (4 February 2013). "What’s in a Name? A Lot, When It Comes to ‘Precision Medicine’". Xconomy. https://xconomy.com/national/2013/02/04/whats-in-a-name-a-lot-when-it-comes-to-precision-medicine/. 
  6. ↑ Ireland, S. (5 August 2019). "Revealed: Countries With The Best Health Care Systems, 2019". CEOWORLD magazine. https://ceoworld.biz/2019/08/05/revealed-countries-with-the-best-health-care-systems-2019/. 
  7. ↑ Iqbal, U.; Nguyen, P.-A.; Syed-Abdul, S. et al.. Is long-term use of benzodiazepine a risk for cancer?. 94. e483. doi:10.1097/MD.0000000000000483. PMC PMC4602739. PMID 25674736. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4602739. 
  8. ↑ Jung, S.Y.; Lee, K.; Hwang, H. et al. (2017). "Support for Sustainable Use of Personal Health Records: Understanding the Needs of Users as a First Step Towards Patient-Driven Mobile Health". JMIR mHealth and uHealth 5 (2): e19. doi:10.2196/mhealth.6021. PMC PMC5344982. PMID 28232300. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5344982. 
  9. ↑ Alyami, M.A.; Song, Y.-T. (2016). "Removing barriers in using personal health record systems". Proceedings of the 2016 IEEE/ACIS 15th International Conference on Computer and Information Science: 1–8. doi:10.1109/ICIS.2016.7550810. 
  10. ↑ Plastiras, P.; O'Sullivan, D.M. (2017). "Combining Ontologies and Open Standards to Derive a Middle Layer Information Model for Interoperability of Personal and Electronic Health Records". Journal of Medical Systems 41 (12): 195. doi:10.1007/s10916-017-0838-9. PMID 29081012. 
  11. ↑ Li, J. (2017). "A Service-Oriented Approach to Interoperable and Secure Personal Health Record Systems". Proceedings of the 2017 IEEE Symposium on Service-Oriented System Engineering. doi:10.1109/SOSE.2017.20. 
  12. ↑ Urbauer, P.; Sauermann, S.; Frohner, M. et al. (2015). "Applicability of IHE/Continua components for PHR systems: Learning from experiences". Computers in Biology and Medicine 59: 186–93. doi:10.1016/j.compbiomed.2013.12.003. PMID 24374230. 
  13. ↑ Roehrs, A.; da Costa, C.A.; da Rosa Righi, R. et al. (2017). "Personal Health Records: A Systematic Literature Review". Journal of Medical Internet Research 19 (1): e13. doi:10.2196/jmir.5876. PMC PMC5251169. PMID 28062391. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5251169. 
  14. ↑ "Welcome to FHIR". Health Level 7. 1 November 2019. https://hl7.org/FHIR/. Retrieved 26 April 2020. 
  15. ↑ Schleyer, T.K.L.; Rahurkar, S.; Baublet, A.M. et al. (2019). "Preliminary evaluation of the Chest Pain Dashboard, a FHIR-based approach for integrating health information exchange information directly into the clinical workflow". AMIA Joint Summits on Translational Science 2019: 656-664. PMC PMC6568135. PMID 31259021. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6568135. 
  16. ↑ Goodman, A.B.; Braun, P.; Braunstein, M. (2018). "Healthy Weight on FHIR - Innovative Technology to Support High Quality Clinical Care & Clinical to Community Linkages for Child Obesity". PEdiatrics 141 (1 MeetingAbstract): 12. doi:10.1542/peds.141.1_MeetingAbstract.12. 
  17. ↑ Baihan, M.S.; Sánchez, Y.K.R.; Shao, X. et al. (2018). "Chapter 6: A Blueprint for Designing and Developing M-Health Applications for Diverse Stakeholders Utilizing FHIR". In Rajkumar, R.. Contemporary Applications of Mobile Computing in Healthcare Settings. IGI Global. pp. 85–124. doi:10.4018/978-1-5225-5036-5.ch006. ISBN 9781522550365. 
  18. ↑ Daumke, P.; Heitmann, K.U.; Heckmann, S. et al. (2019). "Clinical Text Mining on FHIR". Studies in Health Technology and Informatics 264: 83–7. doi:10.3233/SHTI190188. PMID 31437890. 
  19. ↑ Storck, M.; Hollenberg, L.; Dugas, M. et al. (2019). "Interoperability Improvement of Mobile Patient Survey (MoPat) Implementing Fast Health Interoperability Resources (FHIR)". Studies in Health Technology and Informatics 258: 141–45. PMID 30942732. 
  20. ↑ Giordanengo, A.; Bradway, M.; Grøttland, A. et al. (29 August 2017). "A FHIR-based Data Flow Enabling Patients with Diabetes to Share Self-collected Data with the Norwegian National Healthcare Systems and Electronic Health Records Systems" (PDF). 2017 Scandinavian Conference on Health Informatics. Norwegian Centre for E-health Research. https://ehealthresearch.no/files/documents/Postere/Poster_2018-02_16-9-ATTD-FHIR-based-Data-Flow.pdf. 
  21. ↑ Kiourtis, A.; Mavrogiorgou, A.; Menychtas, A. et al. (2019). "Structurally Mapping Healthcare Data to HL7 FHIR through Ontology Alignment". Journal of Medical Systems 43 (3): 62. doi:10.1007/s10916-019-1183-y. PMID 30721349. 
  22. ↑ Gøeg, K.R.; Rasmussen, R.K.; Jensen, L. et al. (2018). "A future-proof architecture for telemedicine using loose-coupled modules and HL7 FHIR". Computer Methods and Programs in Biomedicine 160: 95–101. doi:10.1016/j.cmpb.2018.03.010. PMID 29728251. 
  23. ↑ Alper, B.; Mayer, M.; Shahin, K. et al. (2019). "Achieving evidence interoperability in the computer age: Setting evidence on FHIR". BMJ Evidence-Based Medicine 24 (Suppl. 1): A15. https://ebm.bmj.com/content/24/Suppl_1/A15.1. 
  24. ↑ Lackerbauer, A.M.; Lin, A.C.; Krauss, O. et al. (2018). "A Model for Implementing an Interoperable Electronic Consent Form for Medical Treatment Using HL7 FHIR". European Journal for Biomedical Informatics 14 (3): 37–47. doi:10.24105/ejbi.2018.14.3.6. 
  25. ↑ Dixon, B.E.; Taylor, D.E.; Choi, M. et al. (2019). "Integration of FHIR to Facilitate Electronic Case Reporting: Results from a Pilot Study". Studies in Health Technology and Informatics 264: 940–44. doi:10.3233/SHTI190362. PMID 31438062. 
  26. ↑ Hussain, M.A.; Langer, S.G.; Kohli, M. et al. (2018). "Learning HL7 FHIR Using the HAPI FHIR Server and Its Use in Medical Imaging with the SIIM Dataset". Journal of Digital Imaging 31 (3): 334–40. doi:10.1007/s10278-018-0090-y. PMC PMC5959839. PMID 29725959. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5959839. 

Notes

This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added. The original reference 12 (Crabtree et al.) seems to have no bearing on the text and appears to have been accidentally included; it was omitted for this version.

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