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Friday, June 21, 2024

Cortex Analytics - Comprehensive and Customizable Healthcare Analytics

Government-regulated health insurance payers and provider groups (e.g., private Medicare and Medicaid plans, ACA Marketplace issuers, and Accountable Care Organizations  participating in Medicare and Medicaid) are struggling to harness ever increasing volumes of data while complying with ever evolving government standards & regulations.  Whether the requirements are in risk adjustment, data interoperability, encounter data submission, quality measurement, EMR integration, or a plethora of other complicated initiatives, they are losing big as a result.  Hiring data scientists to fix data leak issues and to modernize legacy data systems is near impossible as the few qualified individuals who exist are already employed or extremely costly.

Government-regulated health plans cover more Americans (over 160 million) than do the totality of employer-sponsored and union-sponsored health insurance plans.  They will continue to grow by leaps and bounds because of the aging of the baby boomer population, the popularity of ACA Marketplace health plans (now at 14 million enrollees), Medicare’s stated goal to have all Medicare beneficiaries enrolled in a risk-based contract by 2030, and the increasing mainstreaming of Medicaid programs in many states to cover middle income Americans.

Meanwhile, businesses are also typically confronted by the complicated data collection, submission, and compliance requirements devised by a multitude of government agencies at the state and federal levels.  Because they rarely lack the internal data science or data analytics staff and systems to comply with these requirements, government-regulated plans and providers routinely must rely on multiple external vendors.  In addition, regulatory compliance tends to be a tough slog.  While it is vital to comply with government statutes, regulations, and sub-regulatory guidance, compliance rarely can be reduced to a good sales and marketing slogan! 

That is why Cortex Analytics developed comprehensive, accurate, and secure data management solutions that give healthcare organizations the ability to clearly see the insights and impacts their strategies and campaigns create. The Cortex Analytics software platform provides a unified Extraction, Transformation, and Load (ETL), data quality, and a risk adjustment modelling engine, in either SaaS or API deployments. Moreover, Cortex Analytics is building descriptive models to help reign in emergency department use and to help redirect patients to more appropriate sites of care.  “As with medication adherence, we rely on our three decade long relationship with The Johns Hopkins Bloomberg School of Public Health.  Johns Hopkins has expanded and updated the definitions for the ACG System based on the NYU Emergency Department Visit Classification algorithm. Cortex Analytics has then added its own proprietary metrics to the Johns Hopkins/NYU scheme for categorization emergency department utilization,” explains Richard Lieberman, CEO, Cortex Analytics.

Master Data Management for Healthcare

The company currently have two products generally available for commercial off-the-shelf deployment including the CortexETL and Cortexrisk. CortexETL ingests raw data from disparate systems (e.g., CMS, state agencies, private payors, and provider groups) in a variety of different agency-specific formats.  After ingestion, cortexETL consolidates and de-duplicates, normalizes, standardizes, edits, aggregates, performs Master Data Management, performs Reference Data Management, and loads the resulting client supplied data to a proprietary data schema.  Both structured and unstructured data can be managed in the same enterprise data warehouse. 

Whereas, the Cortexrisk measures patients’ illness burden, producing risk adjustment scores to predict future health care resource consumption and identifies suspect gaps in administrative claims data and clinical documentation.  Cortexrisk operates on the following risk adjustment models: CMS-HCC for Medicare-Advantage, Medicare Shared Savings Plans, and the ACO REACH plans operating in all states; HHS-HCCs for ACA Marketplace issuers operating in all states; and the CDPS+Rx, CDPS, MedicaidRx, and ACG risk adjustment models applicable to most Medicaid Managed Care Organizations.  Cortexrisk’s suspecting (documentation gap closure) capabilities finds potential members whose chronic conditions may not have been identified correctly, and identifies risk exposure to highlight chronic conditions for which there appears to be insufficient documentation.

Social determinants of health (SDoH) are built into Cortex Analytics by relying on spatial analysis (where people live).  During data loading and transformation, member and provider addresses are geocoded to latitudes and longitudes using the HIPAA-compliant ArcGIS Enterprise Server.  The geocoding process also assigns the statistical subdivisions of census tracts and census block groups to street addresses.  Using census block groups, the solution enables to access the Area Deprivation Index.  The Area Deprivation Index (ADI) is based on a measure created by the Health Resources & Services Administration (HRSA) over three decades ago, and has since been refined, adapted, and validated to the Census Block Group neighbourhood level by Amy Kind, MD, PhD and her research team at the University of Wisconsin-Madison. It allows for rankings of neighbourhoods by socioeconomic disadvantage in a region of interest (e.g. at the state or national level). It includes factors for the theoretical domains of income, education, employment, and housing quality. It can be used to inform health delivery and policy, especially for the most disadvantaged neighbourhood groups. “Medication adherence is built into Cortex Analytics by way of a license agreement with the Johns Hopkins Bloomberg School of Public Health,” adds Lieberman.

The Blend of Experience and Expertise

Cortex Analytics evolved out of its decades of experience providing consulting services to government-regulated health plans and financially at-risk provider groups.  The company have worked with over 100 of these entities advising them on risk adjustment, quality measurement, and encounter data management since the late 1990s.  Cortex Analytics was founded for the purpose of productizing that wealth of experience and insights into software while at the same time continuing to provide high-level management consulting to the health plans and provider groups. “Cortex Analytics is miles ahead from the competition in the marketplace because we understand and appreciate that the seemingly mundane data governance activities, such as master data management, reference data management, ontology management, data aggregation, spatial analytics, risk adjustment, and quality measure assignment are far more important to health plan payers than unproven artificial intelligence models, natural language processing, machine learning and other mathematical models that will one day prove their mettle but today are still in the development stages,” points Lieberman.

In the long run, Cortex Analytics’ overarching goal is to create a Data Science-As-A-Service “toolbox” of analytical tools that can be applied to both structured and unstructured data used by health care payers and provider groups.  “We also have several other products planned on our product development roadmap.  With the impending start of the ACO REACH (Realizing Equity, Access, and Community Health) program geared to Medicare ACOs on January 1, 2023, Cortex Analytics will be offering a software product specific to the risk adjustment and quality measurement needs of ACO REACH participants.  We are working on Cortexhorizons, which will be a digital patient app, placing members healthcare in the palm of their hands as well as caregiver insights.  Members and their informal or paid caregivers will have access to all their data and the information from the Cortexhorizons will then flow to the plan or provider group for a more holistic approach for member care,” concludes Lieberman.


Cortex Analytics

Richard Lieberman, CEO


“As with medication adherence, we rely on our three decade long relationship with The Johns Hopkins Bloomberg School of Public Health. ”


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