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How NLP and Machine Learning Power Healthcare Analytics

Natural language processing (NLP) and machine learning (ML), two main building blocks of AI, have been applied to a wide range of challenges and opportunities in healthcare including clinical decision support, precision medicine, risk stratification, disease progression modeling and subtype discovery.

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confidence scores enable targeted chart reviews

AI is no replacement for human judgement but it can go a long way towards simplifying and streamlining data management and analysis. ‍AI-enabled chart review helps providers and plans that coordinate care for complex populations work smarter, not harder, by shifting the focus from volume of charts targeted to precision targeting of charts.

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a closer look at unstructured healthcare data

An estimated 80% of healthcare data is unstructured. While the insights contained within unstructured data are essential to risk assessment and population health initiatives, it is typically not incorporated into analysis. Converting unstructured data into structured inputs is an expensive and complex endeavor that requires a specialized combination of machine learning algorithms and clinically trained natural language processing (NLP).

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Why HCC Recapture is Not Enough

HCC code recapture of previously documented, or "known", conditions is a starting point - not a complete strategy - for assessing risk. Recapture updates a patient's risk profile based on codes submitted to payers in the previous calendar year, which does not factor in many common scenarios.

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Provider Education in HCC Risk Adjustment

Hierarchical Condition Category (HCC) risk adjustment depends on accurate documentation at the point of care. All conditions, including manifestations, complications and comorbidities, must be documented to the highest level of specificity to paint an accurate picture of a patient’s complexity. Subtle nuances involved in coding and documentation have a significant impact on risk adjustment factor (RAF) score accuracy, which in turn affects reimbursement and ultimately appropriateness of care for patients.‍

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HCC Coding 101

Hierarchical condition category (HCC) coding is a risk-adjustment model originally designed to estimate future health care costs for patients. The Centers for Medicare & Medicaid Services (CMS) HCC model was initiated in 2004, but is becoming increasingly prevalent as the environment shifts to value-based payment models.

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Chart Reviews - Prospective Vs. Retrospective

Historically, Medicare Advantage Organizations (MAO’s) have relied on retrospective chart review as the primary method of discovering conditions that may not have been coded during the patient encounter. But with the shift to value-based care, emphasis on early intervention and growing regulatory pressure to get coding and documentation right on initial claims, risk-based payer and provider organizations are increasingly incorporating prospective reviews into their workflows.

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Webinar: How To Improve Your HCC Scoring

Join us tomorrow, Aug 20th, for a fireside chat about how to improve your organizations HCC scoring. Jeff Lehrich from MDPortals and Healthmonix President and CEO Lauren Patrick will be discussing how HCC scoring impacts MIPS, Medicare Advantage and other programs, as well as best practices for improving HCC scoring, and more.

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Video: How MDPortals Helps Doctors Deliver Better Care

Learn how MDPortals is helping one of the nation’s largest healthcare companies care for patients across the country.

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MDPORTALS ANNOUNCES SPONSORSHIP OF THE 2020 AAHCM VIRTUAL ANNUAL MEETING

MD Portals will sponsor the 2020 American Academy of Home Care Medicine (AAHCM) Annual Conference. The conference was developed by pioneers in the field to leverage the power of home care medicine.

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MDPortals Appoints David B. Agus, MD, to Chair Medical Advisory Board

MDPortals’ plug-and-play solution enables providers to thrive in the world of value-based care by providing a risk-adjusted, longitudinal health record for their patients. MDPortals’ proprietary knowledge platform collects patient data from multiple electronic health records (EHR), health information exchanges (HIE), diagnostic laboratories, and pharmacies.

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Why Payers Need Clinical Data

Payers in value-based contracts are expected to move beyond their traditional role as insurance purveyors and assume the broader responsibility of improving outcomes and care coordination. Claims data is not a sufficient foundation for successfully fulfilling this role. By leveraging the valuable insights and real-time availability that clinical data offers, plans can carry out the level of proactive outreach and crises prevention that value-based care management demands.

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emerging Non-traditional data sources in healthcare

Research shows that health outcomes are driven by a wide range of factors including lifestyle and living conditions, functional and cognitive impairments, genetics, and personal health behaviors. The explosive growth in availability of health data has made it possible to incorporate these non-traditional data types into care management and risk analysis.

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The Role of New and Suspected Conditions in Risk Adjustment Clinical Workflows

Successful risk-based arrangements incorporate the full picture of risk - including new and suspected diagnoses as well as previously documented conditions - into pre-encounter and point-of-care workflows.

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The Crucial Role Of The Medicare Annual Wellness Visit In Proactive Care Management

The Medicare Annual Wellness Visit (AWV) is a powerful tool for delivering proactive care in the value-based care environment. Created in 2011 by the Centers for Medicare & Medicaid Services (CMS), the service is a free benefit for Medicare beneficiaries that can go a long way towards putting patients on the best possible path to wellness each year.

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The Underestimated Benefits of Risk-Based Arrangements

The benefits of a prospective risk adjustment workflow expand well beyond just revenue cycle management. The shift to proactive workflows that risk adjustment programs require has a significant impact on an organization's day-to-day operations.

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Value-based care in a fee-for-service world

The transition from fee-for-service to value-based care is well under way. But while methodologies have evolved, the systems and processes that plans and providers rely on lag behind.

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Why Specificity Matters When Documenting and Coding HCC’s

Under the HCC risk adjustment model, specificity in documentation and coding is key to providing a complete picture of patient health, establishing accurate benchmarks and ensuring appropriate compensation. HCC codes are used to calculate a patient’s risk adjustment factor (RAF) score, so that predicted cost of care will be more in line with the patient’s health status.

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MDPortals Partners with AAHCM to Improve Clinical Care

‍MDPortals, a healthcare technology company that retrieves and consolidates a patient’s complete healthcare history for national medical practices with 5,000 or more patients, is proud to announce its partnership with the American Academy of Home Care Medicine (AAHCM). As part of AAHCM’s Industry Relations Council (IRC), MDPortals offers services to provide AAHCM member physicians with easy access to all the information they need to care for their patients, even in the home.

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How clinical data helps improve outcomes for patients with multiple chronic conditions

‍Suboptimal health outcomes and rising healthcare expenditures for those with multiple chronic conditions have been identified by the US Department of Health and Human Services as a major public health challenge.

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A closer look at the growth of Medicare Advantage and the HCC risk adjustment model

‍The Centers for Medicare & Medicaid Services (CMS) initiated the Hierarchical Condition Category (HCC) model in 2004 to adjust payments to Medicare Advantage Organizations (MAOs). The model has been more prevalent in recent years as HCCs are becoming more widely recognized as one of value-based programs' most important components. This heightened visibility is due in large part to the growth and success of Medicare Advantage.

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