A Preliminary Implementation of HL7 FHIR to Achieve Interoperability in Indonesia's Local EHR

Hidayat, Inten Fauziah; Hermanto, Beni Rio

doi:10.1109/ict49546.2020.9239534

Cited by 6 publications

(4 citation statements)

References 10 publications

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“…The difference is that this study made use of Java and Python programming languages, instead of the concept of relational databases. It can also be a substitute for the gap analysis technique used in representing Indonesian EHR data in the FHIR standard [13].…”

Section: Discussionmentioning

confidence: 99%

An Automatic Data Mapping for Interoperability of OpenEMR Medical Practice Management Software Using the Fast Healthcare Interoperability Resources

Sujudi

Heryawan

2022

ABE

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Data compatibility in Electronic Medical Records (EMR) among healthcare facilities is necessary, especially for medical practitioners such as doctors or physicians, so that they can grant a more accurate decision on what treatments should be carried out for their patients, since a precise treatment or medication will increase the chance that patients would successfully heal from their disease. The compatibility of EMR data can also be called interoperability. This research attempts to apply interoperability of healthcare data by implementing an automatic mapper of an EMR data from one EMR management system called OpenEMR so that its data can meet the FHIR (Fast Healthcare Interoperability Resources) standard. Speci cally, a classi er to categorize the OpenEMR data into the appropriate FHIR format is discussed in this paper. There are three classi ers developed in Java and Python, which utilize the concepts of machine learning classi cation techniques; in this case, Naïve-Bayes and Decision Tree. Implementations of both machine learning algorithms showed a classication accuracy of 100%, which resulted in the additional implementation of rule-based technique, which also resulted in 100% accuracy. After running similar tests on all three implementations, the results infer that the rule-based technique is better than Naïve-Bayes for development in Java programming language.

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Section: Discussionmentioning

confidence: 99%

An Automatic Data Mapping for Interoperability of OpenEMR Medical Practice Management Software Using the Fast Healthcare Interoperability Resources

Sujudi

Heryawan

2022

ABE

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“…Researchers such as (Adams et al, 2017) considered interoperability as fundamental to improving health care delivery. Results from other studies indicate that interoperability can minimize delayed action in a patient, reduce repetitive examinations, simplify the process of searching for complex information, and reduce medical errors (Hidayat and Hermanto, 2020). The research (Sfakianakis et al, 2007) presented their insights into the impact of FOSS on the interoperability of health information systems.…”

Section: Factors Affecting the Adoption Of Technologymentioning

confidence: 98%

Factors influencing free and open-source software adoption in developing countries—an empirical study

Silva¹,

Coutinho²,

Costa³

2023

Journal of Open Innovation: Technology, Market, and Complexity

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“…The ISPf performs API calling authorization to verify the calling rights and then routes the API calls to the respective organization to which the API belongs. This process facilitates data exchange among multiple organizations [62][63][64][65][66][67][68][69][70][71][72][73][74][75]. An example of this mode is the efficient transfer of medical records when a patient referral occurs.…”

Section: Data Integrationmentioning

confidence: 99%

“…Nan et al [62], 2021; Taechoyotin et al [63], 2021; Maxi and Morocho [64], 2022; Rosenau et al [65], 2022; Corici et al [66], 2020; Papaioannou et al [67], 2021; Hidayat and Hermanto [68], 2020; Sloane et al [69], 2021; Mukhiya and Lamo [70], 2021; Gruendner et al [71], 2022; Gruendner et al [72], 2020; Park et al [73], 2022; Ziminski et al [74], 2021; De et al [75], 2021…”

Section: Integrated Service Platformmentioning

confidence: 99%

Designing Interoperable Health Care Services Based on Fast Healthcare Interoperability Resources: Literature Review

Nan¹,

Xu²

2023

JMIR Med Inform

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Background With the advent of the digital economy and the aging population, the demand for diversified health care services and innovative care delivery models has been overwhelming. This trend has accelerated the urgency to implement effective and efficient data exchange and service interoperability, which underpins coordinated care services among tiered health care institutions, improves the quality of oversight of regulators, and provides vast and comprehensive data collection to support clinical medicine and health economics research, thus improving the overall service quality and patient satisfaction. To meet this demand and facilitate the interoperability of IT systems of stakeholders, after years of preparation, Health Level 7 formally introduced, in 2014, the Fast Healthcare Interoperability Resources (FHIR) standard. It has since continued to evolve. FHIR depends on the Implementation Guide (IG) to ensure feasibility and consistency while developing an interoperable health care service. The IG defines rules with associated documentation on how FHIR resources are used to tackle a particular problem. However, a gap remains between IGs and the process of building actual services because IGs are rules without specifying concrete methods, procedures, or tools. Thus, stakeholders may feel it nontrivial to participate in the ecosystem, giving rise to the need for a more actionable practice guideline (PG) for promoting FHIR’s fast adoption. Objective This study aimed to propose a general FHIR PG to facilitate stakeholders in the health care ecosystem to understand FHIR and quickly develop interoperable health care services. Methods We selected a collection of FHIR-related papers about the latest studies or use cases on designing and building FHIR-based interoperable health care services and tagged each use case as belonging to 1 of the 3 dominant innovation feature groups that are also associated with practice stages, that is, data standardization, data management, and data integration. Next, we reviewed each group’s detailed process and key techniques to build respective care services and collate a complete FHIR PG. Finally, as an example, we arbitrarily selected a use case outside the scope of the reviewed papers and mapped it back to the FHIR PG to demonstrate the effectiveness and generalizability of the PG. Results The FHIR PG includes 2 core elements: one is a practice design that defines the responsibilities of stakeholders and outlines the complete procedure from data to services, and the other is a development architecture for practice design, which lists the available tools for each practice step and provides direct and actionable recommendations. Conclusions The FHIR PG can bridge the gap between IGs and the process of building actual services by proposing actionable methods, procedures, and tools. It assists stakeholders in identifying participants’ roles, managing the scope of responsibilities, and developing relevant modules, thus helping promote FHIR-based interoperable health care services.

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A Preliminary Implementation of HL7 FHIR to Achieve Interoperability in Indonesia's Local EHR

Cited by 6 publications

References 10 publications

An Automatic Data Mapping for Interoperability of OpenEMR Medical Practice Management Software Using the Fast Healthcare Interoperability Resources

An Automatic Data Mapping for Interoperability of OpenEMR Medical Practice Management Software Using the Fast Healthcare Interoperability Resources

Factors influencing free and open-source software adoption in developing countries—an empirical study

Designing Interoperable Health Care Services Based on Fast Healthcare Interoperability Resources: Literature Review

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