HAPI-FHIR Server Implementation to Enhancing Interoperability among
Primary Care Health Information Systems in Sri Lanka: Review of the Technical
Use Case
- URL: http://arxiv.org/abs/2402.02838v1
- Date: Mon, 5 Feb 2024 09:48:46 GMT
- Title: HAPI-FHIR Server Implementation to Enhancing Interoperability among
Primary Care Health Information Systems in Sri Lanka: Review of the Technical
Use Case
- Authors: Prabath Jayathissa, Roshan Hewapathirana
- Abstract summary: This review underscores the vital role of interoperability in digital health, advocating for a standardized framework.
It focuses on implementing a Fast Healthcare Resources (FHIR) server, addressing technical, semantic, and process challenges.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: This review underscores the vital role of interoperability in digital health,
advocating for a standardized framework. It focuses on implementing a Fast
Healthcare Interoperability Resources (FHIR) server, addressing technical,
semantic, and process challenges. FHIR's adaptability ensures uniformity within
Primary Care Health Information Systems, fostering interoperability. Patient
data management complexities highlight the pivotal role of semantic
interoperability in seamless patient care. FHIR standards enhance these
efforts, offering multiple pathways for data search. The ADR-guided FHIR server
implementation systematically addresses challenges related to patient identity,
biometrics, and data security. The detailed development phases emphasize
architecture, API integration, and security. The concluding stages incorporate
forward-looking approaches, including HHIMS Synthetic Dataset testing.
Envisioning FHIR integration as transformative, it anticipates a responsive
healthcare environment aligned with the evolving digital health landscape,
ensuring comprehensive, dynamic, and interconnected systems for efficient data
exchange and access.
Related papers
- CSSDM Ontology to Enable Continuity of Care Data Interoperability [0.0]
We present a methodology for extracting, transforming, and loading data using a Common Semantic Standardized Data Model (CSSDM) to create personalized healthcare knowledge graph (KG)
This approach promotes a novel form of collaboration between companies developing health information systems and cloud-enabled health services.
arXiv Detail & Related papers (2025-01-17T12:48:48Z) - CSSDH: An Ontology for Social Determinants of Health to Operational Continuity of Care Data Interoperability [0.0]
We propose an integrated ontological model, the Common Semantic Data Model for Social Determinants of Health (CSSDH)
CSSDH aims to achieve interoperability within the Continuity of Care Network.
arXiv Detail & Related papers (2024-12-12T12:25:33Z) - Medchain: Bridging the Gap Between LLM Agents and Clinical Practice through Interactive Sequential Benchmarking [58.25862290294702]
We present MedChain, a dataset of 12,163 clinical cases that covers five key stages of clinical workflow.
We also propose MedChain-Agent, an AI system that integrates a feedback mechanism and a MCase-RAG module to learn from previous cases and adapt its responses.
arXiv Detail & Related papers (2024-12-02T15:25:02Z) - Generative AI for Secure Physical Layer Communications: A Survey [80.0638227807621]
Generative Artificial Intelligence (GAI) stands at the forefront of AI innovation, demonstrating rapid advancement and unparalleled proficiency in generating diverse content.
In this paper, we offer an extensive survey on the various applications of GAI in enhancing security within the physical layer of communication networks.
We delve into the roles of GAI in addressing challenges of physical layer security, focusing on communication confidentiality, authentication, availability, resilience, and integrity.
arXiv Detail & Related papers (2024-02-21T06:22:41Z) - Clairvoyance: A Pipeline Toolkit for Medical Time Series [95.22483029602921]
Time-series learning is the bread and butter of data-driven *clinical decision support*
Clairvoyance proposes a unified, end-to-end, autoML-friendly pipeline that serves as a software toolkit.
Clairvoyance is the first to demonstrate viability of a comprehensive and automatable pipeline for clinical time-series ML.
arXiv Detail & Related papers (2023-10-28T12:08:03Z) - Multimodal Federated Learning in Healthcare: a Review [5.983768682145731]
Federated Learning (FL) provides a decentralized mechanism where data need not be consolidated.
This paper outlines the current state-of-the-art approaches to Multimodal Federated Learning (MMFL) within the healthcare domain.
It aims to bridge the gap between cutting-edge AI technology and the imperative need for patient data privacy in healthcare applications.
arXiv Detail & Related papers (2023-10-14T19:43:06Z) - Blockchain-empowered Federated Learning for Healthcare Metaverses:
User-centric Incentive Mechanism with Optimal Data Freshness [66.3982155172418]
We first design a user-centric privacy-preserving framework based on decentralized Federated Learning (FL) for healthcare metaverses.
We then utilize Age of Information (AoI) as an effective data-freshness metric and propose an AoI-based contract theory model under Prospect Theory (PT) to motivate sensing data sharing.
arXiv Detail & Related papers (2023-07-29T12:54:03Z) - The Design and Implementation of a National AI Platform for Public
Healthcare in Italy: Implications for Semantics and Interoperability [62.997667081978825]
The Italian National Health Service is adopting Artificial Intelligence through its technical agencies.
Such a vast programme requires special care in formalising the knowledge domain.
Questions have been raised about the impact that AI could have on patients, practitioners, and health systems.
arXiv Detail & Related papers (2023-04-24T08:00:02Z) - Large Language Models for Healthcare Data Augmentation: An Example on
Patient-Trial Matching [49.78442796596806]
We propose an innovative privacy-aware data augmentation approach for patient-trial matching (LLM-PTM)
Our experiments demonstrate a 7.32% average improvement in performance using the proposed LLM-PTM method, and the generalizability to new data is improved by 12.12%.
arXiv Detail & Related papers (2023-03-24T03:14:00Z) - Information Governance as a Socio-Technical Process in the Development
of Trustworthy Healthcare AI [0.0]
Information Governance (IG) processes govern the use of personal confidential data.
Legal basis for data sharing is explicit only for the purpose of delivering patient care.
IG work should start early in the design life cycle and will likely continue throughout.
arXiv Detail & Related papers (2023-01-04T10:21:46Z) - Unique Device Identification Based Linkage of Hierarchically Accessible
Data Domains in Prospective Hospital Data Ecosystems [0.0]
The electronic health record ( EHR) targets the systematized collection of patient-specific electronically-stored health data.
This paper addresses cross-domain data integration, data fusion and access control using the example of a Unique Device Identification (UDI) expanded hip implant.
The acquisition of social focus databased on mHealth is approached, which also covers data integration and networking with therapeutic intervention or acute diagnostics data.
arXiv Detail & Related papers (2022-02-26T19:45:31Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.