Overview
In the healthcare companies, pharmaceutical industry, biotechnology and face an unprecedented challenge for efficiently managing and analyzing vast amounts of drug-related data from diverse sources. Healthcare industry evolving at a rapid space and healthcare industry data is going exponentially. Healthcare has around 30% of the world’s data. With the advent of big data healthcare industries also saw avalanche of data growth. In healthcare, it is also immensely important to protect patient and other health information privacy, align with compliance and adhere to best practices of healthcare data governance. Traditional data analysis methods prove inadequate for processing complex medical documentation that includes a mix of text, images, graphs, charts and tables. Modern data analytics and multi-modal AI capabilities help healthcare organizations to ingest, integrate, analyze and produce actionable intelligence from vast amount of data.
Healthcare organizations such as providers and payers, process a vast number of complex document formats and unstructured data that pose analytical challenges. Beyond traditional data formats, clinical study documents and research papers and public information presents an intricate blend of technical text, detailed tables, charts, and sophisticated statistical graphs, making automated data extraction and analysis particularly challenging. Different institutes also use various data formats, styles and presentations.
An effective data platform and AI services solution helps large enterprise and drug research-based start-ups to efficiently use infrastructure and services to reduce cost to research, rapidly experiment with hundreds of models and improve operational efficiency by focusing energy into more value-added tasks by research scientist and AI developers.
This blog takes you through a solution to extract, analyze and gain data-driven insights from complex research documents through a flexible choice of data processing with data privacy, security and regulatory compliance adherence. Oracle integration solution for healthcare brings solution to integrate and process healthcare data formats in HL7 and FHIR and combine with enterprise applications data seamlessly. The solution analyzes clinical trial data, patient outcomes, molecular diagrams, and safety reports from the research documents. It can help pharmaceutical companies accelerate their research process.
Challenges to effectively manage Healthcare Data
Data Silos: Healthcare ecosystem consists of various entities, healthcare service and patient care providers, payers, pharmaceuticals, drug makers and clinical organizations. Variety of organizations uses vastly different type of applications and have different ways of storing, processing and sharing data across entities creating data sprawls and silos. This creates immense challenge to access, integrate, process and generate actionable intelligence from data. Maintaining governance and security of data becomes a challenge that negatively impact business process and patient care and efficient drug research.
Data Interoperability: Different format of storing and processing data makes it hard to share data across organizations. Healthcare compliance and regulatory requirement also pose challenge to adhere to strict data format and exchange process such as health Level 7 (HL7), American National Standard Institute X12 (ANSI X12) and Fast Healthcare Interoperability (FHIR) which is starkly different from the more typical data formats that healthcare organizations use in their application as in the format JSON, CSV or XML. This creates challenge to integrate various data even within the organization, communicate with the other healthcare entities and conversion issues.
Data Privacy and Security requirements: Healthcare data consists of personally identifiable information (PII), sensitive patient information and health data. It is utmost priority for organizations to safeguard data privacy and security and adhere to compliance and regulatory requirements. Accessing all the healthcare data, integrating them and maintaining data security, privacy and compliance requirements remains the biggest challenge for the healthcare industry.
Data Quality and standards: Healthcare employees in hospitals. Patient care centers, laboratories manually enter patient information and other healthcare data in multiple discounted system manually causing data quality concerns and reduce trust on the data. Delay in finding issue with the data cause inefficiency in critical healthcare service provided to patients and take longer to provide quality healthcare to all. Lack of standardized data formats disconnected, and disparate systems used by different healthcare entities, complex and manual handling of data, missing information cause degraded quality of patient care, increased healthcare service cost, privacy and compliance concerns.
Scalability and Performance Concerns: Healthcare data is ever growing, so application and integration must scale to maintain performance and real time data processing demands.
Impact of fragmented Healthcare Data
The consequence of disintegrated data silos of healthcare data, lack of conformance to standards and delayed processing can have significant negative impact leading to:
- Poor patient care quality and delays
- Increased cost of care and operational overhead
- De-accelerate innovation in medical research and drug discovery
Solve healthcare data management challenges on Oracle Cloud infrastructure and Data Platform.
Efficient Data Integration and Interoperability:
Oracleintegration cloud healthcare edition is designed to solve healthcare data integration challenges, enabling healthcare organizations ingest, process, combine and communicate with healthcare level seven (HL7) and Fast Healthcare Interoperability Resources (FHIR) data formats following healthcare industry standards and compliance requirements.
Oracle integration cloud healthcare edition provides following features on top of oracle integration cloud enterprise capabilities,
- Healthcare Message Editor to customize HL7 v2 message schemas with the built-in editor and includes all HL7 message versions.
- MLLP Adaptor has new bidirectional (trigger and invoke) adapter supporting the TCP-based MLLP protocol and natively transport adapter for HL7 v2 messages.
- Healthcare Action, a new action in the OIC developer palette to provide the tools needed to parse, validate, and transform native HL7 messages in your OIC integration flows.
- FHIR Adapter (outbound) consumes external FHIR resources from your integration flows
High performance and scalable Data Processing
Oracle cloud Infrastructure and data platform services enables healthcare organizations to choose from variety of options for store, process, analyze and gain insights from both structured and unstructured data at scale and performance using both batch and real time processing.
Healthcare Data Staging and long-term retention
Healthcare data from disparate health systems such as healthcare pathways, EHR, EMR, providers and patient information, Government and public data for research and discovery can be ingested and stored at scale in oracle cloud object storage. Historical and ever-growing incremental data can be accessed from other data processing services like Big Data service, dataflow and customized data processing platform and databases from object storage for further processing and analyzing.
Data processing and Machine Learning at scale and in real time
On oracle cloud infrastructure, healthcare organization can choose variety of options to process data at scale and with required security and performance.
Oracle cloud dataflow provides fully managed open-source spark cluster and application development platform to run spark jobs in seconds and can auto scale spark cluster on demand.
Oracle cloud infrastructure data science platform is also a fully managed platform as a service for data scientist and engineers to build, train, evaluate and implement machine learning applications using popular JupyterLab notebook, launching job in predefined on-demand cluster of CPU or GPU VMs.
Take models development to production in days using MLOps capability, model management, version control, repository automated pipelines, model deployments and monitoring features.
You also can connect data science notebook sessions with dataflow to run distributed computation combining user friendly notebook developer interface and tooling of data science and dataflow kernel as compute environment taking advantage of PySpark, Pandas API, MLlib or SparkSQL with customizable Conda and spark environment.
Data Management and Storage at Scale
Big Data processing requires fast data retrieval and data processing in petabytes of data in seconds. For data science, AI and ML applications which are IO latency and throughput sensitive it is imperative to store and access data in a high-performance data store that can scale independently of the compute.
Oracle cloud big data provides scalable HDFS compliant data store to run big data applications using MapReduce framework for large batch data processing. You can flexibly choose scalable file storage and high-performance mount target to get 1 Gbps of read throughput of 1 tb file storage, up to 80 Gbps on a 80 TB file storage at no extra cost. Oracle also offers fully managed open-source Lustre for large scale distributed AI training for low latency and high throughput up to 1 Gbps per provisioned terabytes of storage and inference applications. Healthcare Biomedical Research, Drug Discovery and Genomic Data Analysis run large language models on hundreds and thousands of GPU cluster using terabytes of data a scale using Lustre file storage scaling to multiple PBs.
Oracle cloud provides fully managed scalable autonomous data warehouse to build health lake warehouse, use developer tools like oracle data integration, data loading service ad open-source tools to develop extract, load and transform applications. You can use oracle data catalog a fully serverless catalog service to store, process and manage metadata across all data services on OCI.
Data Analytics and Intelligent Apps
Healthcare customer can easily develop and implement web and mobile analytics applications on top of oracle cloud flexible infrastructure. You can use oracle cloud self-service analytics for data visualization and analytics integrated with built-in Machine learning and oracle GenAI capabilities. Medical professionals including doctors, nurse and pharmacists can leverage advanced AI capabilities using embedded AI and Generative AI Assistant to leverage from data to decisions, improve productivity and deliver actionable intelligence.
Healthcare industries can use fully managed oracle GenAI services to seamlessly integrate GenAI capabilities in wide range of use cases, for example,
- Automate generation and summarization of clinical notes, discharge instructions and referrals.
- Pathological institutes and radiology services can leverage GenAI models for diagnostic services, conduct research and use AI for medical imaging and improve speed and accuracy for detecting patterns and identify anomalies.
- Biomedical pharm and biologists can accelerate the identification of potential drug candidates, simulate molecular interactions, and design novel compounds, significantly reducing the time and cost of bringing new drugs to market.
- GenAI service can help to navigate versatile data from patient history (Genomics and health history), medical information in any data format and generate tailored personalized treatment plan and care service.
- With Oracle Digital Assistant and GenAI service can healthcare service providers can power virtual assistants and chatbots for 24/7 patient support, including appointment scheduling, medication reminders, symptom checking, and delivering personalized, easy-to-understand educational materials in various languages.
Conclusion
The timely availability, accuracy and quality of healthcare data is crucial for patient care. disease management, drug discovery and accelerate innovation using Artificial intelligence. Oracle cloud infrastructure brings flexible, scalable and highly secured services to fuel growth, accelerate innovation and achieve compliance and healthcare industry standards.
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Oracle Healthcare Cloud Infrastructure
Oracle Integration for Healthcare