Harness healthcare data for competitive advantage using AWS
Healthcare organizations are under increasing pressure to reduce costs while improving patient care and outcomes.
Many are pursuing this through increased digitization and better utilization of data to enable more remote care, inform care decisions, and streamline operations. However, complex, siloed systems and a lack of data standardization are seriously hindering these efforts.
Patient Claims,
Pharmacy
EHR Systems
(EPIC, Cerner etc.)
Public Sources
Situation-Specific
The Apexon Healthcare Data Analytics Platform (HDAP), built on AWS managed components, enables healthcare companies to move quickly to centralize, utilize and monetize their data. HDAP on AWS acts as a data accelerator — enabling users to harness healthcare data assets more effectively for diagnostic, exploratory, predictive and prescriptive needs.
Ready access to raw data and the ability to process all standard healthcare data types (HL7, CCDA, DICOM, FHIR, labs, known EMRs)
Support for standard models such as OMOP for persistent healthcare data, enabling normalization and longitudinal data representation
Data management practices that ensure security, reliability and data quality
Streamlined regulatory healthcare reporting, KPI calculations and the ability to leverage data for research
A reference implementation built on AWS using platform components enabling Pay-As-You-Go services
Analysis to prevent revenue loss due to inaccurate data and to identify opportunities for new patient services
Real-time processing and complex event handling to provide decision support for care givers
Exploratory analytics and data science
Support for highly automated operations with DevOps and SRE
Apexon HDAP on AWS can be used by different players in the healthcare ecosystem to address multiple data use cases to improve research, patient care and operational processes. Below are some of the many examples:
HDAP can ingest data— both structured and unstructured—from multiple sources to crystallize, categorize and classify it for practical clinical use.
HDAP can mine clinical notes in unstructured formats like free text and presents it in a consumable format for easy analysis and insights.
HDAP can pull and categorize data such as patient diagnosis and treatment data from EHR systems to help identify patterns and assist in care decision support.
HDAP can integrate different types of data for multiple uses and users; e.g., billing data for administrators; patient diagnostics and treatments for physicians; adverse conditions/reactions for nurses; data analysis for researchers.
HDAP can use a master patient index (MPI) to aggregate an individual’s health information for clinical analysis, research, care coordination, and improved patient outcomes.
HDAP can map and optimize core data that might use different labels in different environments to make it more consumable, searchable and actionable.
HDAP can map and validate critical patient care codes to ensure accurate and complete information is available for accurate patient care, tracking and billing.
HDAP can capture complete patient medication histories and make it easy to share with other providers and public health organizations to ensure safer and more effective care. This data can also be used for administering immunizations.
HDAP helps providers optimize patient care as well as care costs and reimbursements by enabling the benchmarking of effective patient prescriptions and dosages.
HDAP can provide a data tagging engine which can provide added context and checkpoints to existing data. This enables better data visibility, verification and application; e.g. prescription safety, clinical decisions, operational planning.
HDAP can be used to standardize healthcare classification codes, procedure codes, labs results code, medication and drug codes, image- related codes and more to enable more intuitive care analysis and correlation. It also allows for comparative research with other countries.
HDAP’s comprehensive coding structure provides unified data which is accurate, tagged and quality controlled to facilitate improved public health reporting and tracking.
HDAP can act as a complete healthcare data ecosystem to improve clinical, financial, and administrative performance. Administrators can track time and resources spent on procedures, allocate resources, increase billing and payment accuracy and reduce the risk of rejected claims for incorrect coding.
HDAP can accommodate new procedures and techniques such as the expanded coding and granularity introduced by systems like ICD-10. It also helps reduce the hassle of audits and detects and prevents healthcare fraud and abuse.
HDAP can capture, unify and ratify data such as codes, charges and invoices for clinical services, lab tests, and medications. This digitization increases reimbursements, decreases billing errors, optimizes patient care timing, and provides better documentation to resolve any potential financial disputes.
HDAP can enhance patient self-care by offering important follow-up information, instructions, reminders and links to necessary resources. Information technology affects more and more of patients’ lifestyle today and many feel more comfortable accessing services digitally.
HDAP enables clinicians to document services provided and access up-to-date information about their patient. It also streamlines the transition process and knowledge sharing between different care settings for improved communication and coordination.
HDAP can use quantitative analysis of functional values to help clinicians identify patient abnormalities and predict phenotypes. Data from different EHRs can be integrated into a larger database and geo-location specific tracking is also possible.
HDAP can monitor patient flow, bed occupancy, lengths of stay, readmissions, cost analysis vs. industry benchmarks, supply chain, and inventory for more informed decisions about population health, staffing and care.
HDAP can help identify patients at risk of complications, recommend medications and dosage, and alert to early signs of infection, etc. based on patient data analysis.
