By linking patients, physicians, and gadgets, the aim is to deliver more individualized, effective, and efficient treatment. It should come as no surprise that ASUS, a prominent technology firm, is contributing significantly to this healthcare revolution with its Gen AI enabled healthcare products and services.
For it healthcare goods and services, ASUS presently uses two types of Gen AI:
- Managed Gen AI systems that engage with users through a question-and-answer style to provide health advice and consultation include Anthropic’s Claude on AWS and OpenAI’s ChatGPT.
- A clinical AI assistant that offers several agents to help patients and physicians improve clinical visit workflows is based on open-source proprietary Gen AI models. Pre-consulting agents help patients fill out a form that includes all of their symptoms and the reason they are there. Clinicians can obtain patient health summaries and write medical notes from summarization agents.
Creating the Future of Healthcare Cyber-Physical Systems
ASUS is making significant investments in AI to make sure it develop into a full-fledged AI company. To assist with incorporating Gen AI into processes and product services, its currently have over 1,000 AI specialists working for us. Big data and Gen AI advancements can maximize hospitals’ digital transformations, enabling them to deliver significantly better healthcare results down the road.
Future healthcare will be more thorough, individualized, accurate, and efficient with the amazing advancements that Smart Healthcare Cyber-Physical Systems (CPS) are poised to bring about. This is exactly in line with the words of ASUS Chairman Jonney Shih, who stated that “the customer’s satisfaction is always the most important thing, regardless of industry or segment.”
Constructing a Smart Healthcare Information Platform of the Future
Healthcare professionals and organizations confront several obstacles, particularly when it comes to deploying AI solutions. The most significant of these is the absence of dependable and cohesive digital infrastructure. As a result, hospital administrators now face challenges like maintaining antiquated systems, resolving conflicts between their systems and outside apps, and negotiating disparate data requirements among institutions. When you combine all of this, it becomes clear why creating and implementing AI healthcare technologies can seem like a fruitless endeavor.
In 2020, ASUS made a major investment to build the ASUS xHIS Next-Generation Smart Healthcare Information Platform (ASUS xHIS) in order to address these issues and guarantee the ongoing improvement of Taiwan’s next-generation digital medical information services. The cutting-edge platform emphasizes an AI-native environment and open data integration. This enables smooth communication between systems, apps, and devices from different hospitals, fosters the development of new AI applications, and establishes an open ecosystem for the smart healthcare sector.
Three layers comprise the ASUS xHIS’s open platform architecture:
First Layer: An open application store that facilitates a developer ecosystem by linking wearable technology, medical equipment from healthcare facilities, home health assessment tools, and user apps. In addition to increasing intelligent applications and fostering information integration, this strives for a more accurate and individualized healthcare experience.
Second Layer: An adaptable modular framework that incorporates microservice architecture, hybrid cloud technology, and data model analysis for AI applications. This guarantees seamless application data communication between the first layer and the third layer databases. In order to guarantee patient safety, healthcare organizations can also dynamically modify interfaces and operational rules with its modular architecture and low-code/no-code tools. For example, it permits pop-up windows for clinical decision support (such as drug interaction alerts).
Third Layer: The creation of globally recognized standardized data formats that break down data silos by utilizing uniform standards to link various databases, systems, and healthcare facilities.
Leveraging Gen AI for Continuous Improvement
By incorporating Gen AI technology into several medical AI solutions, ASUS is revolutionizing healthcare workflows. By simplifying note-taking and recordkeeping, this innovation aims to save time and lessen administrative obligations. In addition to enhancing patient care outcomes by helping physicians uncover probable abnormalities, risk projections, and suggestions, it increases productivity by giving them more time to concentrate on complicated duties and patient care.
Pre-consultation questionnaires, medical note writing, EMR summarization, anomaly detection, and intelligent recommendations are just a few of the features that ASUS Clinical AI Assistant provides by utilizing LLMs (Large Language Models). These features are intended to improve the effectiveness and caliber of care.
Pre-Consultation Questionnaire
This AI-driven application creates follow-up questions based on the patient’s specified concerns, intensity, length, and associated symptoms to help clinicians better understand the patient’s condition prior to the visit, enhancing the pre-consultation process with dynamic, interactive surveys. Doctors can also take the appropriate steps, such ordering diagnostic tests or replenishing prescriptions. Furthermore, healthcare practitioners can refine note drafts using customisable prompt templates, guaranteeing that the documentation process fits their unique requirements and practice preferences.
Medical Note Drafting
Using cutting-edge AI-powered tools, Medical Note Drafting automates the development of multiple medical note forms, including discharge summaries and SOAP (Subjective, Objective, Assessment, and Plan) notes. Clinicians can modify documentation to fit a variety of clinical situations by using adaptable, adjustable templates. The AI helper drastically cuts down on preparation time by standardizing and expediting the documentation process, freeing up healthcare workers to concentrate more on patient care.
EMR Summarization
Physicians can examine keywords before accessing the patient history documents because to Gen AI’s ability to extract important information from long patient reports. EMR summary offers dynamic and succinct summaries of patient data, such as test results, vital signs, and medical history. These summaries are displayed using editable templates that are suited to the particular requirements of various clinical specializations and roles. In addition to summarizing, the application has sophisticated features like risk prediction and anomaly detection, which enable physicians to promptly and effectively identify urgent patient problems.
Anomaly Detection & Smart Recommendations
In the ASUS Clinical AI Assistant, anomaly detection is essential for connecting data insights and evidence-based data support to practical advice, laying the groundwork for the intelligent recommendation function. The Anomaly Detection Agent detects anomalies in patient data, such odd trends in vital signs, aberrant test findings, or sudden changes in a patient’s condition, by utilizing sophisticated AI algorithms and LLM reasoning capabilities.
These early warnings give doctors important information that they might not otherwise have, allowing them to take preventative action and make better judgments about patient care. Building on these insights, the smart suggestion tool enhances clinical workflows by providing a medical ICD-10 code, a prescription for an evidence-based strategy for treatment, and possible diagnoses. A smooth, data-driven method that maximizes clinical decision-making and enhances patient outcomes is produced when anomaly detection and intelligent recommendations work together.
The ASUS Clinical AI Assistant solves persistent issues with productivity, efficiency, and patient care, marking a revolutionary advancement in the healthcare sector. In addition to relieving doctors of administrative constraints, this system guarantees more accurate and consistent documentation by incorporating cutting-edge Gen AI technology and Large Language Model (LLM) into crucial workflows. The ultimate objective is to cut down on time spent on non-clinical duties so that medical personnel may focus on making intricate medical judgments and managing patient interactions.
Additionally, the ASUS Clinical AI Assistant‘s worth is found in its capacity to improve patient care outcomes and quality of care. Clinicians can better grasp patient needs and potential dangers by using intelligent technologies for pre-consultation, medical note production, EMR summarizing, and smart recommendations. By assisting in the identification of abnormalities, risk prediction, and treatment recommendation, the solution guarantees prompt and precise actions, ultimately enhancing patient safety and satisfaction.
The ASUS Clinical AI Assistant revolutionizes the healthcare experience by bridging the gap between clinical excellence and technological innovation. It gives medical professionals the resources they need to provide excellent, patient-centered care while more confidently and effectively negotiating the challenges of contemporary medicine. In addition to improving individual practices, this dedication to improving healthcare workflows advances the larger objective of building a more efficient and humane healthcare system.
