How the HARMAN Intelligent Healthcare Platform Revolutionizes Patient-Centric Services

By Dr. Jai Ganesh, Arabinda Behera, Saurabh Singh, Kaushlesh Kumar, Dinkar Londhe – HARMAN
By Venkat Gomatham – AWS

HARMAN

Globally, the healthcare industry is going through a wave of accelerated growth. Some of the key contributing factors to this trend are the growth in the aging population, rising prevalence of chronic diseases, higher labor costs owing to workforce shortage, and expansion of healthcare systems in developing markets.

Rising healthcare costs and the increased focus on patient outcomes has led the healthcare system to increase its efforts on exploring new methods of care delivery. With a shift from volume-based to value-based care, preventive care is emerging as a key focus area for delivering quality patient outcomes. This is leading to a gradual shift in the cost paradigm of healthcare delivery.

Virtual care is fast emerging as an important tool in driving this shift and delivering on the desired outcomes. By ensuring access to care, reducing costs, and improving patient engagement, virtual care enables healthcare stakeholders to proactively reach out to patients and ensure seamless and timely healthcare services.

The HARMAN Intelligent Healthcare Platform (IHP) leverages artificial intelligence (AI), machine learning (ML), cloud services, and data to unlock value for clients. It seamlessly transforms data, analytics, intelligence, and governance functions in a secure, cost effective, and privacy-preserving process.

IHP leverages AI/ML modules to offer improved customer experience and engagement through predictive analytics and actionable insights on data harnessed from disparate sources. The platform is designed to be future-proof and is capable of meeting current demands, while still evolving to meet new digital experiences in the future.

Compliance, privacy, and safety are top of mind as IHP features robust data governance and controls to manage information, confidentiality, integrity, privacy, and more. IHP is also built for agility, and agile and flexible operations are embedded through simplified processes, improved collaboration, and faster decisions from unstructured data.

HARMAN Digital Transformation Services is an AWS Advanced Tier Services Partner and AWS Marketplace Seller with the Healthcare Consulting Competency. It transforms everyday experiences with technology solutions that bring software and hardware together with a people-first perspective to simplify complex tasks and build better products.

HARMAN DTS offers platform and application development, AI and analytics, cloud and testing services across healthcare, communications, industrial, retail, software, and hospitality.

HARMAN Intelligent Healthcare Platform

The HARMAN Intelligent Healthcare Platform is a patent-pending solution comprising of four key components:

• Data Machine: Scalable, reliable, and comprehensive engine to ingest and process batch or stream data and securely store data from various sources.
• Analytics and Visualization Machine: Stores various data types at scale and helps run exploratory and predictive analytics and visualizations to generate actionable insights.
• Intelligence Machine: Comprises machine learning and deep learning algorithms and models which power use cases such as hospital readmission prediction, remote patient care, patient attrition prediction, video patient monitoring, unstructured document processing, insurance claims analytics, demand forecasting, and device management.
• Governance Machine: Provides access to HIPAA-eligible services and compliance standards such as GDPR, HITRUST, ENS High, HDS, and C5.

Figure 1 – IHP solution architecture diagram.

Data Machine

The Data Machine is a scalable, reliable, and comprehensive engine to support various data types. It ingests, processes, and securely stores data from devices, sensors, clinical, genomic, patients, claims, and wellness applications.

Data Machine can process batch or real-time streaming data from various sources, including formats such as FHIR, HL7, CCD, and EDI. It can also process structured, unstructured, semi-structured, and graph data with validation rules to ensure accuracy, quality, and logical consistency.

Data processing is a key component of digital health platforms, as it allows healthcare providers to extract valuable insights from their data. Data processing involves a wide range of activities, including data collection, data cleaning, data integration, data analysis, and data visualization. These activities are essential for enabling healthcare providers to gain a better understanding of their data, and to use that data to improve care, reduce costs, and drive innovation.

Key challenges addressed by the Data Machine include:

• Data quality: Ensuring the quality of data is a critical challenge in data processing. Poor quality data can lead to incorrect insights and decisions and can undermine the value of digital health platforms.
• Data integration: Data from multiple sources is often required for data processing. Integrating data from different sources can be challenging and require specialized tools and expertise.
• Data privacy and security: Data privacy and security are critical concerns in the healthcare industry. Ensuring data is protected and compliant with relevant regulations is essential for data processing in digital health platforms.

Analytics and Visualization Machine

The Analytics and Visualization Machine allows healthcare providers to extract valuable insights from their data. Data analytics involves a wide range of activities, including data collection, data cleaning, data integration, data analysis, and data visualization.

These activities are essential for enabling healthcare providers to gain a better understanding of their data, and to use that data to improve care, reduce costs, and drive innovation.

The data lake stores various data types at scale and helps run exploratory and predictive analytics and visualizations to generate actionable insights. The centralized reporting and analytics portal meets various requirements including self-service business intelligence (BI) option for power users.

The Analytics and Visualization Machine can be applied to a wide range of areas, including:

• Clinical decision-making: By providing valuable insights from data that can help healthcare providers make more informed decisions.
• Population health management: By providing insights on trends, patterns, and risks in the population. This helps healthcare providers identify potential health issues and intervene early.
• Personalized medicine: By providing insights that can be used to tailor treatments and recommendations to individual patients. This leads to better health outcomes and increased satisfaction.
• Research and development: By providing insights that can be used to develop new treatments, therapies, and technologies.

Intelligence Machine

The Intelligence Machine comprises ML and deep learning algorithms and models across areas such as predictive analytics, computer vision, natural language processing (NLP), and graph analytics. It also comes with pre-built software products such as HARMAN Remote Care Platform and HARMAN Intelligent Device Management Platform.

The ML and deep learning algorithms and models power use cases such as hospital readmission prediction, remote patient care, patient attrition prediction, video patient monitoring, unstructured document processing, insurance claims analytics, demand forecasting, and device management.

The Intelligence Machine comes with pre-built components such as remote patient care, anomaly detection, smart device management, video analytics, and conversational AI. The AI/ML modules power customer-centric analysis, detect anomalies, predict future states, and support rapid decision-making.

Governance Machine

The Governance Machine facilitates data governance, which is a critical aspect of digital health platforms as it ensures that data is managed, protected, and compliant with relevant regulations.

Data governance involves the development and implementation of policies, procedures, and processes that govern the management, use, and protection of data in a digital health platform. This can include activities such as data collection, data cleaning, data integration, data analysis, and data visualization.

The Intelligent Healthcare Platform provides access to several HIPAA-eligible services, as well as numerous certifications for industry-relevant global IT and compliance standards, including support for GDPR, HITRUST, ENS High, HDS, and C5.

Data governance in digital health platforms can be applied to a wide range of areas, including:

• Data quality: Ensures the quality of data in a digital health platform by establishing policies and procedures for data collection, cleaning, and validation. This helps make sure data is accurate, complete, and reliable.
• Data integration: Ensures the integrity of data in a digital health platform by establishing policies and procedures for data integration from multiple sources. This helps make sure data is consistent, coherent, and interoperable.
• Data privacy and security: Ensure the privacy and security of data in a digital health platform by establishing policies and procedures for data protection, compliance, and audits. This helps make sure data is protected and compliant with relevant regulations.

Architecture Powered by AWS

The HARMAN Intelligent Healthcare Platform is developed using HARMAN’s patented IP, AWS services, and best-in-class commercial and open-source technologies.

Healthcare organizations today are increasingly turning to the cloud to store, process, and analyze large amounts of data, as well as to support critical applications and services. AWS is leveraged by HARMAN IHP due to its superior scalability, reliability, compliance and security features.

Figure 2 – IHP platform architecture diagram.

• Amazon Simple Storage Service (Amazon S3) and Amazon Redshift are used to store the raw and processed data for BI and analytics
• Data available in the data lake is processed and analyzed using various service like AWS Glue, AWS Glue DataBrew, and Amazon Athena.
• AWS Lambda, Amazon API Gateway, and AWS WAF are used to security deploying the APIs and provide access to consumer applications.
• Data from various sensors are ingested using Amazon Kinesis Data Streams and Amazon Kinesis Data Firehose.
• Amazon SageMaker, Amazon Rekognition, and Amazon Transcribe Medical are used to develop and deploy various AI models and implement healthcare analytics use cases.
• Amazon CloudWatch, AWS CloudTrail, and AWS Config are used for monitoring resources and reporting and alerting various users based on the rules defined.
• Various HIPAA-eligible AWS services are used as the building blocks for developing the platform.
• Clinical and administrative data feeds coming from various sources like electronic medical records (EMR), practice management system (PMS), pharmacy benefits managers (PBM), and payer systems in standard formats like HL7, EDI, and FHIR are ingested and enriched by Amazon HealthLake along with Amazon Comprehend Medical.
• All of the data stored in Amazon HealthLake are encrypted using the keys stored in AWS Key Management Service (AWS KMS), and AWS LakeFormation is used as the data security and governance layer on the HealthLake and restricts access to data based on user roles.

Conclusion

The HARMAN Intelligent Healthcare Platform is designed to help healthcare and life sciences enterprises in their journey towards customer-centric services by seamlessly transforming their data, analytics, intelligence, and governance functions in a secure, cost-effective, and privacy-preserving manner.

Key value propositions of the IHP platform include:

• Customer-centric services: Improved end-customer experience and engagement through AI/ML-driven insights on data harnessed from disparate sources.
• Accelerate innovation: Future-proof platform capable of meeting business requirements through differentiated digital experiences.
• Compliance, privacy, and security: Robust data governance and controls to manage information, confidentiality, integrity, privacy, security, encryption, and availability. Caters to multiple global healthcare compliance requirements.
• Business agility: Agile and flexible operations through simplified processes, improved collaboration, faster decisions from unstructured data, and automation of IT architectures.

For more information, check out the HARMAN Intelligent Healthcare Platform in AWS Marketplace.

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HARMAN Digital Transformation Services is an AWS Partner that transforms everyday experiences with technology solutions that bring software and hardware together with a people-first perspective to simplify complex tasks and build better products.

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