An analysis of 1.1 million Medicare Advantage beneficiaries across 8 health plans found significantly lower risk scores when using the new Encounter Data System (EDS) compared to the traditional Risk Adjustment Processing System (RAPS). On average, EDS risk scores were 16% lower in 2016 and 26% lower in 2015. Younger disabled beneficiaries and dual-eligible members saw even greater reductions of 25-30% and 19-24% respectively. A full transition to EDS could reduce per-member per-month payments by an average of $260 million annually for a typical plan, posing financial challenges.
The Evolution of Predictive Analytics in Maaged CareAltegra Health
This document discusses predictive analytics in managed care. It begins with an overview of predictive analytics terms and concepts. It then describes the company's approach, which uses a multi-disciplinary team and multiple data sources to develop predictive models. Examples of models discussed include those predicting dual eligibility, likelihood of recertification, and risk scores. Accuracy results are provided for some models showing high prediction rates.
This document summarizes a presentation on analyzing provider capacity under national health reform. It finds that many counties have inadequate primary care physician supply based on population-to-physician ratios. While supply gaps exist nationwide, they are concentrated in the South and non-metropolitan areas. Reallocating physicians from surplus to shortage counties could address gaps in most states. Newly eligible populations under the ACA are heavily concentrated in counties with inadequate supply, which may face barriers to care. Future analysis should use improved provider and population data to better inform monitoring of capacity issues.
Contrasting Measures of Health Insurance Literacy and their Relationship to H...soder145
This document summarizes research contrasting two measures of health insurance literacy and their relationship to health care access. The researchers analyzed data from a 2015 Minnesota health survey. They found that:
1) Understanding insurance terminology was associated with higher confidence in getting needed care and lower odds of forgone care, while proactive insurance use correlated with lower odds of forgone care.
2) Correlates of health insurance literacy, such as education, varied between the two measures.
3) Both measures captured distinct concepts and translated to improved access, though proactive use only predicted forgone care and not confidence in care.
4) The researchers concluded both measures have value but more work is needed to better operationalize
The changing demographics of the uninsured in MN and the nationsoder145
The document analyzes changes in the demographics of the uninsured in Minnesota and nationally between 2013 and 2014 following coverage expansions under the Affordable Care Act. It finds that uninsured rates declined significantly in both Minnesota and all 50 states. While the characteristics of the uninsured remained largely the same, the uninsured population is now more likely to be Hispanic, non-citizens, and Spanish speakers in both Minnesota and nationally. The uninsured are also less likely to be children in Minnesota and very low income or Asian nationally. Continued outreach efforts are needed to enroll groups with historically high uninsurance rates.
The economic burden of prescription opioid overdose... 2013.Paul Coelho, MD
The document summarizes a study that estimates the total economic burden of prescription opioid overdose, abuse, and dependence in the United States in 2013 was $78.5 billion. Over one third of this cost ($28.9 billion) was due to increased healthcare and substance abuse treatment costs. Approximately one quarter of the total cost was borne by the public sector through healthcare, substance abuse treatment, and criminal justice costs. The study utilized national data on opioid overdose deaths and abuse/dependence prevalence to estimate costs across multiple sectors including healthcare, substance abuse treatment, criminal justice, and lost productivity.
Pacing Volume-to-Value Transition and The ROI of Avoiding Antibiotic Overuse PYA, P.C.
PYA Principals Scott Clay and J. Michael Keegan, MD, will join forces to present “Hot Topics: Pacing Volume-to-Value Transition” and “The ROI of Avoiding Antibiotic Overuse” at the AlaHA Annual Meeting, June 8-11, 2016. The two-part presentation first will explore volume- to value-based reimbursement, and how the pace of change is unique to each organization. The presentation will introduce a strategic framework to establish and communicate a pace of change befitting various organizations, explaining:
How government policies “set the floor” on the degree of change requested.
How to determine the pace of change in your market.
How to identify your organization’s current position and culture in relation to value-based payment models.
How to set and communicate the pace of transition consistent with your market and your organization’s culture.
The second portion of the presentation will focus on the importance of antibiotic stewardship programs (ASP) for population health. The presentation will explain:
Why the Centers for Medicare & Medicaid Services is proposing a requirement that hospitals implement ASPs to stem the rise of resistant bacteria.
Why PYA is invested in offering hospitals a proven program for improving patient safety while saving costs.
What constitutes a successful ASP.
1) Nearly 1 in 100 people aged 15-64 in Great Britain is considered a high-risk drug user, defined as injecting drugs or regular long-term use of opioids, cocaine, and/or amphetamines.
2) In 2013-14, there were 47,900 child assessments where alcohol or other drugs were a factor, and 435 children in foster care ran away due to substance misuse.
3) Prisoners have high rates of drug use and mental health problems, and older prisoners are more likely to have used Class A drugs before entering custody.
Medicaid: An Edge of Your Seat View of Medicaid Risk Adjustment by Bonnie BurkeAltegra Health
This document provides an overview of WellPoint's Medicaid business and the challenges of risk adjustment across different states. WellPoint serves over 4 million Medicaid members across 19 states, with 14 states using different risk adjustment methodologies. State Medicaid programs face significant budget pressures that are increasing the focus on risk adjustment to help fund medical costs. Risk adjustment in Medicaid is a zero-sum game where health plans compete through accurate reporting to obtain higher risk scores and payments relative to their membership risks.
The Evolution of Predictive Analytics in Maaged CareAltegra Health
This document discusses predictive analytics in managed care. It begins with an overview of predictive analytics terms and concepts. It then describes the company's approach, which uses a multi-disciplinary team and multiple data sources to develop predictive models. Examples of models discussed include those predicting dual eligibility, likelihood of recertification, and risk scores. Accuracy results are provided for some models showing high prediction rates.
This document summarizes a presentation on analyzing provider capacity under national health reform. It finds that many counties have inadequate primary care physician supply based on population-to-physician ratios. While supply gaps exist nationwide, they are concentrated in the South and non-metropolitan areas. Reallocating physicians from surplus to shortage counties could address gaps in most states. Newly eligible populations under the ACA are heavily concentrated in counties with inadequate supply, which may face barriers to care. Future analysis should use improved provider and population data to better inform monitoring of capacity issues.
Contrasting Measures of Health Insurance Literacy and their Relationship to H...soder145
This document summarizes research contrasting two measures of health insurance literacy and their relationship to health care access. The researchers analyzed data from a 2015 Minnesota health survey. They found that:
1) Understanding insurance terminology was associated with higher confidence in getting needed care and lower odds of forgone care, while proactive insurance use correlated with lower odds of forgone care.
2) Correlates of health insurance literacy, such as education, varied between the two measures.
3) Both measures captured distinct concepts and translated to improved access, though proactive use only predicted forgone care and not confidence in care.
4) The researchers concluded both measures have value but more work is needed to better operationalize
The changing demographics of the uninsured in MN and the nationsoder145
The document analyzes changes in the demographics of the uninsured in Minnesota and nationally between 2013 and 2014 following coverage expansions under the Affordable Care Act. It finds that uninsured rates declined significantly in both Minnesota and all 50 states. While the characteristics of the uninsured remained largely the same, the uninsured population is now more likely to be Hispanic, non-citizens, and Spanish speakers in both Minnesota and nationally. The uninsured are also less likely to be children in Minnesota and very low income or Asian nationally. Continued outreach efforts are needed to enroll groups with historically high uninsurance rates.
The economic burden of prescription opioid overdose... 2013.Paul Coelho, MD
The document summarizes a study that estimates the total economic burden of prescription opioid overdose, abuse, and dependence in the United States in 2013 was $78.5 billion. Over one third of this cost ($28.9 billion) was due to increased healthcare and substance abuse treatment costs. Approximately one quarter of the total cost was borne by the public sector through healthcare, substance abuse treatment, and criminal justice costs. The study utilized national data on opioid overdose deaths and abuse/dependence prevalence to estimate costs across multiple sectors including healthcare, substance abuse treatment, criminal justice, and lost productivity.
Pacing Volume-to-Value Transition and The ROI of Avoiding Antibiotic Overuse PYA, P.C.
PYA Principals Scott Clay and J. Michael Keegan, MD, will join forces to present “Hot Topics: Pacing Volume-to-Value Transition” and “The ROI of Avoiding Antibiotic Overuse” at the AlaHA Annual Meeting, June 8-11, 2016. The two-part presentation first will explore volume- to value-based reimbursement, and how the pace of change is unique to each organization. The presentation will introduce a strategic framework to establish and communicate a pace of change befitting various organizations, explaining:
How government policies “set the floor” on the degree of change requested.
How to determine the pace of change in your market.
How to identify your organization’s current position and culture in relation to value-based payment models.
How to set and communicate the pace of transition consistent with your market and your organization’s culture.
The second portion of the presentation will focus on the importance of antibiotic stewardship programs (ASP) for population health. The presentation will explain:
Why the Centers for Medicare & Medicaid Services is proposing a requirement that hospitals implement ASPs to stem the rise of resistant bacteria.
Why PYA is invested in offering hospitals a proven program for improving patient safety while saving costs.
What constitutes a successful ASP.
1) Nearly 1 in 100 people aged 15-64 in Great Britain is considered a high-risk drug user, defined as injecting drugs or regular long-term use of opioids, cocaine, and/or amphetamines.
2) In 2013-14, there were 47,900 child assessments where alcohol or other drugs were a factor, and 435 children in foster care ran away due to substance misuse.
3) Prisoners have high rates of drug use and mental health problems, and older prisoners are more likely to have used Class A drugs before entering custody.
Medicaid: An Edge of Your Seat View of Medicaid Risk Adjustment by Bonnie BurkeAltegra Health
This document provides an overview of WellPoint's Medicaid business and the challenges of risk adjustment across different states. WellPoint serves over 4 million Medicaid members across 19 states, with 14 states using different risk adjustment methodologies. State Medicaid programs face significant budget pressures that are increasing the focus on risk adjustment to help fund medical costs. Risk adjustment in Medicaid is a zero-sum game where health plans compete through accurate reporting to obtain higher risk scores and payments relative to their membership risks.
Harnessing Data to Improve Health Equity - Dr. Ali MokdadLauren Johnson
1) The document discusses methods used by the Institute for Health Metrics and Evaluation (IHME) to conduct comprehensive analyses of global, national, and subnational disease burden through their Global Burden of Disease (GBD) study.
2) Key methods discussed include garbage code redistribution to reassign unspecified causes of death, Bayesian meta-regression to estimate incidence and prevalence, and small area statistical models that borrow strength across space, time, and covariates to produce estimates of disease burden for locations with limited data.
3) The GBD study aims to quantify health loss from major diseases, injuries, and risk factors globally and over time in order to help identify and address the world's most pressing health challenges.
Accountability For the Care We ProvideCentralPAHEF
On March 3, 2016 at Highmark Blue Shield there were healthcare executives gathered for the Healthcare Executive Forum of Central PA's quarterly event. This American College of Healthcare Executive's event was worth 1.5 face to face credits. We focused on the issues and preparation for changing healthcare landscapes. Three speakers shared their experience, which was bountiful. These speakers are Moderator: Terry Madonna, Director of the Center for Politics and Public Affairs, Franklin and Marshall College; Speakers: Gerald Walsh, VP, Provider Contracting and Relations, Highmark; Thomas Northrop, NorHealth Management Group, CEO; Michael Consuelos, SVP, Clinical Integration at The Hospital & Healthsystem Association of Pennsylvania. Visit our website for full biographies and more at www.centralpa.ache.org.
Insurer Participation in the 2018 Individual MarketplaceKFF
The document summarizes data on health insurance choice and competition in Affordable Care Act marketplace plans for 2018. It finds that fewer exchange enrollees will have a choice of multiple insurers in 2018 compared to previous years, with 48% having a choice of three or more insurers compared to 58% in 2017. It also reports that over 1,600 counties will have only one insurer option on the exchanges in 2018, up from over 1,000 counties the prior year. Competition and choice are lower in non-metro versus metro areas.
Machine Learning to Control Medicare Prescription Drug CostsBen Spiegel
This project used Gradient Boosting to recognize physicians who have much higher prescription drug costs compared to their predicted cost. The Coefficient of Determination using this algorithm was .664. Additionally the accuracy of the model is such that 79.5% of physicians were no more than 40% above their predicted drug costs, while 88.2% were no more than 60% above their predicted costs.
Strategies to Expand Insurance Coverage for Adults: Preliminary Findings for...soder145
Presentation by Sharon Long at the AcademyHealth Annual Research Meeting session, "The Lab Reports: Evaluating State's Actions to Expand Access and Coverage," Chicago, IL, June 30 2009.
The epidemiology workgroup meets regularly to assess drug abuse patterns, trends, and emerging problems in order to inform public health responses. The group aims to eliminate or reduce substance abuse and related consequences in local communities. Their core tasks include identifying drug abuse patterns, changes over time, emerging substances, and communicating findings. The document provides data on drug poisoning mortality rates, opioid prescription rates, tobacco and e-cigarette use among youth, impaired driving incidents, narcotics seizures and violations, HIV and STD rates, family violence incidents, and substance abuse programs in the community.
Analysing the Effectiveness of Government Spending on Health across Countrieeurosigdoc acm
This document outlines a study analyzing the effectiveness of government spending on health across countries. It discusses collecting health spending and outcome data for 217 countries from 1990-2019. The data was prepared by addressing missing values and converting to numeric format. Regression, cluster, and geographical analyses were then used to model relationships. Regression showed health spending significantly increases life expectancy and decreases infant mortality. Clustering grouped countries with similar health profiles. Geographical plots visually depicted relationships between spending and outcomes. The study concluded that higher spending on health generally leads to better outcomes.
This document summarizes a study examining the relationship between socioeconomic factors and rates of HIV/TB co-morbidity in Harris County, Texas. The study used geographic and census data to analyze rates of new HIV and TB diagnoses between 2009-2010 at the census tract level. Factor analysis was used to reduce redundancy among highly correlated socioeconomic variables (e.g. education, marital status) that may predict co-morbidity. Preliminary correlation and factor analysis identified issues with multicollinearity that logistic regression could not initially resolve. Further factor analysis of narrowed variable groups helped reduce variables for eventual logistic regression modeling.
This document discusses Canada's experience with electronic health records (EHRs). It notes that while Canada has invested over $1 billion in EHR projects, physician adoption of electronic medical records remains low at under 26%. The challenges of developing EHRs in a system with shared federal/provincial responsibilities and multiple stakeholders are discussed. Lessons learned include the complexity of a federated system, establishing data stewardship roles, engaging medical licensing authorities, and developing trust while balancing privacy and information sharing.
Insights into the 2020 individual marketplace—increase consumer choice and de...Kim Simoniello
This analysis reflects carrier participation, pricing, and plan type trends for the 2020 individual exchange open enrollment period. Findings are across 50 states and DC.
Hospital Pricing Issues Cost Employers MoneyMark Gall
This five-year study details the wide variation of hospital prices for the same procedure in the same town. It considers the impact on the costs of private insurance plans from insurance companies including CIGNA, Anthem, Aetna and United HealthCare. See highlights on pages 1 through 6.
White House Office of National Drug Control Policy on the implications of health reform in substance abuse prevention and treatment.
(Keith Humphreys
Senior Policy Advisor, White House ONDCP)
Making use of All-Payer Claims Databases for Health Care Reform Evaluationsoder145
This document discusses the uses of all-payer claims databases (APCDs) for health care reform evaluation. APCDs contain claims data from multiple payers and can be used to monitor health care costs, identify cost drivers, foster price transparency, and track quality measures. The document outlines several state case studies that demonstrate how APCDs have been used to monitor statewide spending, evaluate transformation efforts, and promote price transparency. It concludes by discussing future directions for APCDs, including data linkages and payment reform evaluation.
This document provides an overview of changes to HIPAA electronic transactions required for 5010 compliance effective January 1, 2012. Key changes include new standards for 837 claims, 270/271 eligibility inquiries, 999 acknowledgements, and other transactions. Providers must update their billing software and practices to address updated fields, codes, and requirements to remain compliant for electronic billing to MassHealth and other payers. Testing is encouraged before the January 1, 2012 deadline to ensure a smooth transition.
1) The document discusses challenges in healthcare cost containment and the need to base provider payments on quality and efficiency rather than volume.
2) It presents a risk-adjusted payment model using the DCG/HCC system to group diagnoses and adjust provider budgets based on patient risk profiles.
3) Results show the model better predicts hospital admissions counts through linear splines compared to standard distributions, though further refinements are needed to account for coding differences across providers.
The document summarizes different EDI file formats including X12, EDIFACT, TRADACOMS, XML, and positional file formats. It describes the basic structure and components of each format such as interchange headers, batch headers, message headers and trailers. The presentation also covers the objectives of analyzing EDI files and provides an overview of how data is organized and interpreted in XML and application file formats.
2014 Altegra Health Partners Summit WelcomeAltegra Health
The document summarizes an agenda for the Altegra Health Partners Summit taking place in Las Vegas. The goals of the summit are to provide networking time for attendees, inform them of Altegra's progress, deliver meaningful content through various presenters, and help attendees improve at their jobs. The agenda outlines presentations by industry professionals, as well as logistical details for meals, transportation and evening entertainment planned as part of the summit.
Electronic data interchange (EDI) allows companies to electronically exchange standardized business documents like orders and invoices instead of using paper. It originated in the 1960s when railroad companies wanted to automate document exchange. Standards for EDI formats were developed in the 1970s to facilitate electronic exchange between different companies and industries. EDI reduces costs and errors compared to paper by automating document exchange and processing.
Treat EDPS as a Risk Adjustment program…not an IT function. This Episource presentation walks you through the 3 phases of EDPS, and key aspects to keep in mind to run a successful risk adjustment program.
This document provides an overview of the claims data flow and analysis of the as-is state for an external claims system. It includes a diagram showing the flow of claims and encounters from source systems like EMR and ambulance providers through various data stores and analytical tools to downstream customer reports and underwriting. The analysis notes that the 14-year-old claims engine does not support multi-tiered products, has no web capabilities, and upgrades have never been performed, posing vendor risk.
Edifecs- How to ensure RAPS and EDPS submissions equal revenue successEdifecs Inc
This document discusses challenges health plans may face when transitioning from Risk Adjustment Processing System (RAPS) submissions to Encounter Data Processing System (EDPS) submissions. It outlines differences in the two submission formats that could lead to discrepancies and revenue impacts if not properly managed. The document provides a use case example of how to identify variations, ensure compliance, and reconcile RAPS and EDPS submissions. It concludes with a checklist of steps plans should take to successfully manage the transition.
Harnessing Data to Improve Health Equity - Dr. Ali MokdadLauren Johnson
1) The document discusses methods used by the Institute for Health Metrics and Evaluation (IHME) to conduct comprehensive analyses of global, national, and subnational disease burden through their Global Burden of Disease (GBD) study.
2) Key methods discussed include garbage code redistribution to reassign unspecified causes of death, Bayesian meta-regression to estimate incidence and prevalence, and small area statistical models that borrow strength across space, time, and covariates to produce estimates of disease burden for locations with limited data.
3) The GBD study aims to quantify health loss from major diseases, injuries, and risk factors globally and over time in order to help identify and address the world's most pressing health challenges.
Accountability For the Care We ProvideCentralPAHEF
On March 3, 2016 at Highmark Blue Shield there were healthcare executives gathered for the Healthcare Executive Forum of Central PA's quarterly event. This American College of Healthcare Executive's event was worth 1.5 face to face credits. We focused on the issues and preparation for changing healthcare landscapes. Three speakers shared their experience, which was bountiful. These speakers are Moderator: Terry Madonna, Director of the Center for Politics and Public Affairs, Franklin and Marshall College; Speakers: Gerald Walsh, VP, Provider Contracting and Relations, Highmark; Thomas Northrop, NorHealth Management Group, CEO; Michael Consuelos, SVP, Clinical Integration at The Hospital & Healthsystem Association of Pennsylvania. Visit our website for full biographies and more at www.centralpa.ache.org.
Insurer Participation in the 2018 Individual MarketplaceKFF
The document summarizes data on health insurance choice and competition in Affordable Care Act marketplace plans for 2018. It finds that fewer exchange enrollees will have a choice of multiple insurers in 2018 compared to previous years, with 48% having a choice of three or more insurers compared to 58% in 2017. It also reports that over 1,600 counties will have only one insurer option on the exchanges in 2018, up from over 1,000 counties the prior year. Competition and choice are lower in non-metro versus metro areas.
Machine Learning to Control Medicare Prescription Drug CostsBen Spiegel
This project used Gradient Boosting to recognize physicians who have much higher prescription drug costs compared to their predicted cost. The Coefficient of Determination using this algorithm was .664. Additionally the accuracy of the model is such that 79.5% of physicians were no more than 40% above their predicted drug costs, while 88.2% were no more than 60% above their predicted costs.
Strategies to Expand Insurance Coverage for Adults: Preliminary Findings for...soder145
Presentation by Sharon Long at the AcademyHealth Annual Research Meeting session, "The Lab Reports: Evaluating State's Actions to Expand Access and Coverage," Chicago, IL, June 30 2009.
The epidemiology workgroup meets regularly to assess drug abuse patterns, trends, and emerging problems in order to inform public health responses. The group aims to eliminate or reduce substance abuse and related consequences in local communities. Their core tasks include identifying drug abuse patterns, changes over time, emerging substances, and communicating findings. The document provides data on drug poisoning mortality rates, opioid prescription rates, tobacco and e-cigarette use among youth, impaired driving incidents, narcotics seizures and violations, HIV and STD rates, family violence incidents, and substance abuse programs in the community.
Analysing the Effectiveness of Government Spending on Health across Countrieeurosigdoc acm
This document outlines a study analyzing the effectiveness of government spending on health across countries. It discusses collecting health spending and outcome data for 217 countries from 1990-2019. The data was prepared by addressing missing values and converting to numeric format. Regression, cluster, and geographical analyses were then used to model relationships. Regression showed health spending significantly increases life expectancy and decreases infant mortality. Clustering grouped countries with similar health profiles. Geographical plots visually depicted relationships between spending and outcomes. The study concluded that higher spending on health generally leads to better outcomes.
This document summarizes a study examining the relationship between socioeconomic factors and rates of HIV/TB co-morbidity in Harris County, Texas. The study used geographic and census data to analyze rates of new HIV and TB diagnoses between 2009-2010 at the census tract level. Factor analysis was used to reduce redundancy among highly correlated socioeconomic variables (e.g. education, marital status) that may predict co-morbidity. Preliminary correlation and factor analysis identified issues with multicollinearity that logistic regression could not initially resolve. Further factor analysis of narrowed variable groups helped reduce variables for eventual logistic regression modeling.
This document discusses Canada's experience with electronic health records (EHRs). It notes that while Canada has invested over $1 billion in EHR projects, physician adoption of electronic medical records remains low at under 26%. The challenges of developing EHRs in a system with shared federal/provincial responsibilities and multiple stakeholders are discussed. Lessons learned include the complexity of a federated system, establishing data stewardship roles, engaging medical licensing authorities, and developing trust while balancing privacy and information sharing.
Insights into the 2020 individual marketplace—increase consumer choice and de...Kim Simoniello
This analysis reflects carrier participation, pricing, and plan type trends for the 2020 individual exchange open enrollment period. Findings are across 50 states and DC.
Hospital Pricing Issues Cost Employers MoneyMark Gall
This five-year study details the wide variation of hospital prices for the same procedure in the same town. It considers the impact on the costs of private insurance plans from insurance companies including CIGNA, Anthem, Aetna and United HealthCare. See highlights on pages 1 through 6.
White House Office of National Drug Control Policy on the implications of health reform in substance abuse prevention and treatment.
(Keith Humphreys
Senior Policy Advisor, White House ONDCP)
Making use of All-Payer Claims Databases for Health Care Reform Evaluationsoder145
This document discusses the uses of all-payer claims databases (APCDs) for health care reform evaluation. APCDs contain claims data from multiple payers and can be used to monitor health care costs, identify cost drivers, foster price transparency, and track quality measures. The document outlines several state case studies that demonstrate how APCDs have been used to monitor statewide spending, evaluate transformation efforts, and promote price transparency. It concludes by discussing future directions for APCDs, including data linkages and payment reform evaluation.
This document provides an overview of changes to HIPAA electronic transactions required for 5010 compliance effective January 1, 2012. Key changes include new standards for 837 claims, 270/271 eligibility inquiries, 999 acknowledgements, and other transactions. Providers must update their billing software and practices to address updated fields, codes, and requirements to remain compliant for electronic billing to MassHealth and other payers. Testing is encouraged before the January 1, 2012 deadline to ensure a smooth transition.
1) The document discusses challenges in healthcare cost containment and the need to base provider payments on quality and efficiency rather than volume.
2) It presents a risk-adjusted payment model using the DCG/HCC system to group diagnoses and adjust provider budgets based on patient risk profiles.
3) Results show the model better predicts hospital admissions counts through linear splines compared to standard distributions, though further refinements are needed to account for coding differences across providers.
The document summarizes different EDI file formats including X12, EDIFACT, TRADACOMS, XML, and positional file formats. It describes the basic structure and components of each format such as interchange headers, batch headers, message headers and trailers. The presentation also covers the objectives of analyzing EDI files and provides an overview of how data is organized and interpreted in XML and application file formats.
2014 Altegra Health Partners Summit WelcomeAltegra Health
The document summarizes an agenda for the Altegra Health Partners Summit taking place in Las Vegas. The goals of the summit are to provide networking time for attendees, inform them of Altegra's progress, deliver meaningful content through various presenters, and help attendees improve at their jobs. The agenda outlines presentations by industry professionals, as well as logistical details for meals, transportation and evening entertainment planned as part of the summit.
Electronic data interchange (EDI) allows companies to electronically exchange standardized business documents like orders and invoices instead of using paper. It originated in the 1960s when railroad companies wanted to automate document exchange. Standards for EDI formats were developed in the 1970s to facilitate electronic exchange between different companies and industries. EDI reduces costs and errors compared to paper by automating document exchange and processing.
Treat EDPS as a Risk Adjustment program…not an IT function. This Episource presentation walks you through the 3 phases of EDPS, and key aspects to keep in mind to run a successful risk adjustment program.
This document provides an overview of the claims data flow and analysis of the as-is state for an external claims system. It includes a diagram showing the flow of claims and encounters from source systems like EMR and ambulance providers through various data stores and analytical tools to downstream customer reports and underwriting. The analysis notes that the 14-year-old claims engine does not support multi-tiered products, has no web capabilities, and upgrades have never been performed, posing vendor risk.
Edifecs- How to ensure RAPS and EDPS submissions equal revenue successEdifecs Inc
This document discusses challenges health plans may face when transitioning from Risk Adjustment Processing System (RAPS) submissions to Encounter Data Processing System (EDPS) submissions. It outlines differences in the two submission formats that could lead to discrepancies and revenue impacts if not properly managed. The document provides a use case example of how to identify variations, ensure compliance, and reconcile RAPS and EDPS submissions. It concludes with a checklist of steps plans should take to successfully manage the transition.
UN/EDIFACT Interchange Processing with Smooks v1.4tfennelly
The document discusses UN/EDIFACT interchange processing with Smooks v1.4. It provides an agenda covering what UN/EDIFACT is, EDI support in Smooks, the EDI Conversion Tool (ECT), the UN/EDIFACT reader, UN/EDIFACT with Java, the EDI Java Compiler (EJC), distribution of mapping models and bindings, and future directions. Examples and a code walkthrough are presented at the end.
The Calm Before the Storm: Enforcement Trends in Risk Adjustment: DOJ and the...Mary Inman
This document summarizes trends in risk adjustment enforcement by the Department of Justice and the False Claims Act. It discusses two settled cases - United States v. Janke for $22.6 million and United States et al. ex rel. Swoben v. Scan Health Plan for $320 million and $3.8 million. While some similar cases were dismissed, the document indicates more investigations may be underway based on reports of document requests to several Medicare Advantage plans. Theories of liability discussed include failure to correct provider upcoding and plan upcoding through chart reviews, home visits, and attestations.
The document provides an overview of EDIFACT (Electronic Data Interchange For Administration, Commerce and Transport), which is an international standard for electronic data interchange (EDI). Key points include that EDIFACT defines syntax rules, data elements and message structures to facilitate electronic interchange between organizations. It describes the different levels of "electronic enveloping" that structure EDIFACT messages and provides examples of common EDI message types and their segment structures.
The document provides an overview of preparing for 837 electronic claim testing, including understanding key concepts like EDI standards, the 837 transaction format, software requirements, implementation guides, and establishing relationships with payers. It emphasizes obtaining implementation guides and a payer's companion guide, communicating with payers to understand testing processes, and completing necessary agreements like trading partner agreements.
ASC X12 is an open standards development organization that develops electronic data exchange standards to enhance business processes. It has over 350 corporate members in over 50 countries that contribute to developing and maintaining over 330 document specifications. Members can get involved by joining subcommittees focused on areas like finance, transportation, supply chain, insurance, and government to help develop new standards and improve existing ones.
Anti-Fraud Challenges for 2013 (Presented at HCCA Managed Care Compliance Con...Mary Inman
This document summarizes anti-fraud challenges for 2013 that health plans may face. It discusses increased audit scrutiny of Medicare risk adjustment payments due to high error rates found in recent audits. It also covers potential issues with fraud under the Affordable Care Act, such as through premium subsidies. Finally, it addresses ensuring compliance programs are prepared to handle new challenges like risk adjustment based on encounter level data and use of electronic medical records.
The document discusses Perficient's solution for healthcare organizations migrating from HIPAA 4010A1 to 5010 standards. It outlines the challenges of the migration, including regulatory deadlines, lack of experienced professionals, and needing to support both standards during transition. Perficient's recommended approach uses Edifecs' Step Up/Step Down solution to allow parallel processing of 4010A1 and 5010 transactions, reducing risk. The solution provides pre-built maps for translation and tools for testing and trading partner management to facilitate the migration.
Surviving the Healthcare World of Risk AdjustmentPYA, P.C.
PYA Principal Bob Paskowski and Senior Staff Consultant Carine Leslie presented a webinar for the Georgia chapter of the Healthcare Financial Management Association Friday, December 16, 2016.
The presentation is tailored for coders in ambulatory/Medicare Advantage settings, providers participating in Medicare Advantage or other risk-based healthcare plans, and leaders in providers’ managed care contracting departments. The webinar is titled “Surviving the Healthcare World of Risk Adjustment.”
The webinar addresses:
• Principles of the Medicare Advantage risk-adjustment model from Medicare Advantage Hierarchical Condition Categories and other risk-based healthcare plans;
• Strategies for reducing compliance risks;
• Methods for accurately, completely, and consistently capturing and documenting a patient’s disease burden to promote effective care management and to reflect the proper risk score.
The Top 9 Questions Every Medical Coder Asks about Risk Adjustment and the CR...Laureen Jandroep
The Top 9 Questions Every Medical Coder Asks About Risk Adjustment and the CRC™ Certification was presented in a webinar by Certification Coaching Org (CCO), www.cco.us. A wealth of information was covered including: what Risk Adjustment (RA) entails, how this field is growing, and RA career opportunities. Also discussed was what to look for in a Risk Adjustment course. Attendees’ questions on careers in RA or preparing for the Certified Risk Adjustment Coder (CRC™) credentialing examination were answered. Presenters were Alicia Scott, CPC, CPC-I, CRC, and Chandra Stephenson, CPC, CIC, COC, CPB, CPCO, CPMA, CPC-I, CCS, CANPC, CEMC, CFPC, CIMC, CGSC, COSC, CRC, CCC. The host for the webinar was Boyd Staszewski.
MiraMed - Risk Adjustment HCC Coding Primer 2016Phil C. Solomon
This document provides an overview of risk adjustment and HCC coding. It discusses how accurate HCC coding is important for provider reimbursement, as CMS uses HCC codes to calculate risk scores and adjust Medicare Advantage plan payments. The document outlines the four steps in the process: 1) providers document clinical information, 2) CMS calculates risk scores, 3) CMS pays insurers based on risk scores, and 4) insurers pay providers based on accurate HCC coding. It also describes MiraMed's HCC coding services which identify missed codes to increase provider revenue through retrospective audits.
The Affordable Care Act of 2010 (ACA) opens the door to a wealth of opportunities for hospitals and physician groups. They are beginning to adapt to the new pay-for-performance and bundled payment systems and develop population-based care management programs. While the goal of ACA is to hold hospitals and physicians jointly responsible for quality and cost of care, the new payment models span the entire care continuum, including primary care physicians (PCPs), specialists, hospitals, post-acute care, and re-admissions. The biggest winners will be those who can improve quality of care while driving down costs. Those that focus first on preventive care for top chronic illnesses will be the first to cross the finish line.
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Using Linked Survey and Administrative Records Studies to Partially Correct S...soder145
1. The document discusses using linked survey and administrative data to partially correct estimates of Medicaid enrollment from the Current Population Survey (CPS), which are known to underestimate actual enrollment levels.
2. The author implements a statistical modeling approach using older linked CPS and Medicaid enrollment data to predict Medicaid enrollment probabilities for more recent CPS data, allowing for adjustment of the estimates.
3. This approach increases the adjusted national Medicaid enrollment estimate by 21 percentage points compared to the unadjusted CPS data, bringing the estimate closer to administrative records while allowing timely analysis. However, the approach also has limitations such as being a partial correction.
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Are You Running the Population Management Marathon on One Leg?VitreosHealth
How it feels when you are working very hard and investing millions on population care management programs and the results don’t meet your expectations! Some population care management programs are successful while some are not delivering the expected results. The case study results we are going to share will show you why there are “winners” and “losers” in effective population management programs. We hope that the results we share are not only going to be an “eye-opener” but a “game-changer” as the healthcare providers take on risk for population health.
EDM ForumEDM Forum CommunityeGEMs (Generating Evidence & M.docxgreg1eden90113
EDM Forum
EDM Forum Community
eGEMs (Generating Evidence & Methods to
improve patient outcomes) Publish
4-20-2017
Reducing Healthcare Costs Through Patient
Targeting: Risk Adjustment Modeling to Predict
Patients Remaining High-Cost
Jonathan A. Wrathall
Intermountain Healthcare, [email protected]
Tom Belnap
Intermountain Healthcare, [email protected]
Follow this and additional works at: http://repository.edm-forum.org/egems
Part of the Other Medicine and Health Sciences Commons, and the Social Statistics Commons
This Methods Case Study is brought to you for free and open access by the the Publish at EDM Forum Community. It has been peer-reviewed and
accepted for publication in eGEMs (Generating Evidence & Methods to improve patient outcomes).
The Electronic Data Methods (EDM) Forum is supported by the Agency for Healthcare Research and Quality (AHRQ), Grant 1U18HS022789-01.
eGEMs publications do not reflect the official views of AHRQ or the United States Department of Health and Human Services.
Recommended Citation
Wrathall, Jonathan A. and Belnap, Tom (2017) "Reducing Healthcare Costs Through Patient Targeting: Risk Adjustment Modeling to
Predict Patients Remaining High-Cost," eGEMs (Generating Evidence & Methods to improve patient outcomes): Vol. 5: Iss. 2, Article 4.
DOI: https://doi.org/10.13063/2327-9214.1279
Available at: http://repository.edm-forum.org/egems/vol5/iss2/4
Reducing Healthcare Costs Through Patient Targeting: Risk Adjustment
Modeling to Predict Patients Remaining High-Cost
Abstract
Context: The transition to population health management has changed the healthcare landscape to identify
high risk, high cost patients. Various measures of patient risk have attempted to identify likely candidates for
care management programs. Pre-screening patients for outreach has often required several years of data.
Intermountain Healthcare relied on cost-ranking algorithms which had limited predictive ability. A new risk-
adjusted algorithm shows improvements in predicting patients’ future cost status to facilitate identifying
patient eligibility for care management.
Case Description: A retrospective cohort study design was used to evaluate high-cost patient status for two
of the next three years. Modeling was developed using logistic regression and tested against other decision tree
methods. Key variables included those readily available in electronic health records supplemented by
additional clinical data and estimates of socio-economic status.
Findings: The risk-adjusted modeling correctly identified 79.0% of patients ranking among the top 15% of
costs in one of the next three years. In addition, it correctly estimated 48.1% of the patients in the top 15% cost
group in two of the next three years. This method identified patients with higher medical costs and more
comorbid conditions than previous cost-ranking methods.
Major Themes: This approach improves the predictive accuracy of identifying high cost patients in the future
.
An Update of Lot Quality Assurance Sampling (LQAS) Technologies Handout 1CORE Group
This document compares two survey methods - Lot Quality Assurance Sampling (LQAS) and Demographic Health Surveys (DHS) - for measuring health indicators in Uganda. It analyzes data from 24 matched indicators collected independently by LQAS (n=8876) and DHS (n=1200) in southwest Uganda in 2011. On average, the difference between LQAS and DHS estimates was 0.062, with 75.7% agreement. While both methods provide regional estimates, only LQAS can provide data at more granular district levels needed for local health management. LQAS also allows for more frequent, lower cost surveys.
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PYA Principal Lori Foley and Consulting Senior Aaron Elias co-presented “The Changing Healthcare System and Impact of MACRA” at the Physician Insurers Association of America’s CEO/COO Meeting.
The Medicare Access & CHIP Reauthorization Act (MACRA) dramatically affected Medicare reimbursements to healthcare providers, as well as provided a new framework for rewarding quality care and reporting on quality measurements. This incentive-based system has the potential not only to change how medicine is practiced, but influence patient perception of care. The presentation will provide the latest information on MACRA implementation, and will detail how the aforementioned changes will impact miscellaneous professional liability insurers.
WHEN AND HOW DOES VALUE BASED PURCHASING IMPACT HOSPITAL PERFORMANCE?Kirsty Macauldy, MBA
To improve the overall quality of healthcare, The National Quality Strategy of the U.S. Department of Health and Human Services broadly defines the outcomes that the Centers for Medicare and Medicaid Services (CMS) wants to achieve through the care it purchases for its beneficiaries. The strategies; aims of better health, better care, and lower costs.
Measuring performance on the Healthcare Access and
Quality Index for 195 countries and territories and selected
subnational locations: a systematic analysis from the Global
Burden of Disease Study 2016
FLAACOs 2014 Conference - Cancer Care in an ACO LandscapeMARCYINC
This document provides an overview of cancer care in Accountable Care Organizations (ACOs) presented by Kelly Blair, COO of Oncology Resource Networks. It notes that cancer costs are rising without improved quality. The landscape is evolving towards value-based contracts between payers and providers and more ACOs. Oncology presents challenges for ACOs due to its complexity and costs, but oncologists are well-suited in some ways. The document provides advice on exploring partnerships with like-minded providers and establishing patient-centered care, aligned incentives, evidence-based guidelines, and monitoring performance to improve outcomes and lower costs in high-performing oncology networks.
The Next Revolution in Healthcare: Why the New MSSP Revisions Matter Now More...Health Catalyst
Now more than ever, we are entering a period of rapid change catalyzed by the power of data. On December 21, 2018, the Centers for Medicare and Medicaid Services (CMS) issued a final rule for the Medicare Shared Savings Program (MSSP), strengthening the financial incentives for ACOs to drive improved outcomes. The health systems that embrace data to achieve financial success will grow while the rest will struggle to compete. View this webinar for a discussion on how to prepare.
The US healthcare system didn’t develop overnight, rather, it is the culmination of a series of revolutions within wealthy parts of the world. In this webinar, we explore the high points of history that have led us to our current challenges. While care has steadily improved over time, the cost of that care has risen at a much more dramatic rate. CMS created the MSSP to help mitigate the growth of these costs while providing better care for individuals and populations. On a larger scale, the program serves to shift the healthcare industry towards fee-for-value.
Despite general frustration related to legislative involvement, history has proven that regulatory changes precede attitudinal changes and the MSSP (combined with accurate, timely data) may be just the piece of legislation to help make value-based care a reality. By viewing this webinar you will learn:
- How the US healthcare industry reached its current state.
- Why financial imperatives drive cultural change in our economic model.
- Ways that the MSSP can help your organization achieve financial success.
- Ideas for how to utilize data to develop better healthcare delivery systems.
Dr. Will Caldwell is a strong proponent of the use of data analytics to promote good health and save lives. His area of expertise rests in technology-enabled health care delivery models and value-based care platforms. We hope that you will view this webinar and learn from his 17-years of work as a data-informed clinician.
The Importance of a Quality Reporting Process in a Pay-for-Performance Enviro...Mallory Johnson
This document summarizes key factors for successful reporting in pay-for-performance healthcare programs. It discusses the growing push for pay-for-performance under the Affordable Care Act and in Medicaid programs. Successful reporting requires clearly defined processes, preparation and validation of reports, flexibility to adapt to changing requirements, using data to drive decision-making, and aligning organizational strategy with reporting needs. Reporting is important to demonstrate achievement of quality goals and access incentive payments.
This study assessed the costs and effects of different degrees of task shifting for anti-retroviral therapy (ART) from physicians to other health professionals in Ethiopia. The study found that (1) facilities with maximal task shifting, where non-physicians performed most ART tasks, had similar patient outcomes and costs as facilities with minimal/moderate task shifting; (2) over 88% of patients remained active on ART after two years across all facility types; and (3) maximal task shifting cost $36 more per patient over two years but resulted in 0.4% fewer patients remaining active, though this difference was not statistically significant.
Re-admit Historical using SAS Visual AnalyticsMonika Mishra
- Hospital readmissions are costly and result in $15-20 billion in expenses annually in the US. Preventing avoidable readmissions can improve patient quality of life and reduce healthcare costs.
- The study analyzed a dataset of over 142,000 hospital visits across 10 states from 2011-2012. It found that Florida had the highest number of visits and charges. The heart department had the highest operation count.
- Reducing preventable readmissions requires improving care coordination, patient education, and post-discharge support to ensure patients understand their treatment plan and who to contact if issues arise. The CMS Hospital Readmission Reduction Program financially penalizes hospitals with excess readmissions for certain conditions like heart failure to incentivize lower
Medicaid vs. Marketplace Coverage for Near-Poor Adults: Impact on Out-of-Pock...soder145
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3) Medicaid expansion also increased Medicaid coverage by 11.1 percentage points and decreased the uninsured rate by 4.5 percentage points for this low-income group relative to non-expansion states.
Similar to 1487976446_INV_AVALERE_RAPS_EDS_Final_Report_ (20)
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1487976446_INV_AVALERE_RAPS_EDS_Final_Report_
1. Avalere Health T | 202.207.1300 avalere.com
An Inovalon Company F | 202.467.4455
1350 Connecticut Ave, NW
Washington, DC 20036
RISE RAPS-EDS
Collaboration
Research Project
Final Report
Christie Teigland, Ph.D., Karl Kilgore, PhD,
Edward Charlesworth, Arati Swadi | 02.24.17
3. RISE RAPS-EDS Collaboration Research Project: Final Report 1
RISE RAPS-EDS COLLABORATION RESEARCH PROJECT
FINAL REPORT
Avalere analyzed data from eight Medicare Advantage Organizations (MAOs)
representing 1.1 million beneficiaries in more than 30 unique plans operating across the
country to understand the impact of shifting the determination of plan risk scores from the
traditional Risk Adjustment Processing System (RAPS) to the new Encounter Data
System (EDS).
The Centers for Medicare & Medicaid Services (CMS) originally expressed the intention
to transition gradually to EDS-based payments, starting with 10 percent of the payment
based on EDS scoring in 2016, increasing to 25 percent in 2017 and 50 percent in 2018.1
In spite of recent actions taken by CMS to improve the EDS submission process, a new
Government Accountability Office (GAO) report documents numerous problems MA
plans have had in submitting data and receiving reliable edits from the agency.2 In
recognition of the ongoing operational challenges and other concerns about the accuracy
of EDS, CMS recently proposed to maintain the 2017 blend in 2018.3
CMS has said EDS should capture the same diagnoses identified in RAPS. However, we
found that this transition will significantly reduce the identification of diagnoses used to
calculate the risk scores that reflect the disease burden of the plans membership.
Average risk scores resulting from the EDS process were 26 percent lower in the 2015
payment year (based on 2014 claims data) and 16 percent lower in the 2016 payment
year (based on 2015 claims data) compared to RAPS. The risk score differences ranged
from 14 to 30 percent lower across all age groups, but the adverse impact on the high
cost, high need younger disabled population was significantly greater, ranging from 25 to
30 percent. Average risk scores of dual eligible members were also significantly lower
compared to non-duals. The lower risk scores were the result of up to 40 percent fewer
Hierarchical Condition Category (HCC) diagnoses identified in EDS compared to RAPS.
These risk score differences will put significant downward pressure on MAOs and may
adversely impact the 18 million beneficiaries they serve. As an example, using an $800
bid rate, if there had been a full transition from RAPS to EDS in 2016, this would equate
to an average reduction of 16.1 percent in per-member per-month (PMPM) payment
rates, representing a decrease of $260.4 million per year for the average plan in our
study. A 75/25 blend would have reduced payments by $63.8 million, and the 90/10
blend would have reduced payments by $25.2 million per year for the same average plan
in our study.
An executive summary of the findings was released on January 23, 2017 here.4 This full
report includes additional analyses and supplemental information.
4. RISE RAPS-EDS Collaboration Research Project: Final Report 2
BACKGROUND
CMS uses a risk adjustment process to modify Medicare Advantage (MA) plan payments
to better reflect the relative risk of each plan’s enrollees. Payments to each MA plan are
modified based on risk scores that reflect enrollees’ health status and demographic
characteristics derived from member claims data. MA plans are currently transitioning
from the traditional Risk Adjustment Processing System (RAPS)—where risk adjustment
filter rules are applied by health plans—to the new Encounter Data System (EDS)—
where Medicare Advantage Organizations (MAOs) submit their members’ claims and
CMS applies the filtering logic.
The EDS is intended to be revenue and budget neutral because the change in format to
the encounter data collection process was expected to result in the same risk scoring.5
However, the two approaches involve very different levels of information in their
respective processes. The RAPS system involves only five necessary data elements
(dates of service, provider type, diagnosis code and beneficiary Health Insurance Claim
(HIC) number), while the EDS system utilizes all elements from the claims (i.e., HIPAA
standard 5010 format 837).
The Centers for Medicare & Medicaid Services (CMS) originally expressed the intention
to transition gradually to EDS-based payments, starting with 10 percent of the payment
based on EDS scoring in 2016, increasing to 25 percent in 2017 and 50 percent in
2018.1,6 However, in recognition of the ongoing operational challenges and other
concerns about the accuracy of EDS, CMS recently proposed to maintain the 2017 blend
in 2018.3
Plans are concerned that the continued transition to EDS will lead to lower risk scores,
which is inconsistent with the agency’s intent. While CMS made changes to the EDS
logic in 2016 to correct some identified issues, the 2016 risk scores analyzed in this study
demonstrate that a significant difference between RAPS and EDS scoring still exists (16
percent lower). MAOs seek a solution where RAPS and EDS submissions are in
complete alignment, ensuring the full risk adjustment payment from CMS without loss
attributed solely to system changes.
OBJECTIVE
The goal of this research was to test the risk score neutrality theory of the transition from
RAPS to EDS using sample data from nationally representative MAOs. The study aimed
to evaluate the risk score and financial impact of the transition by comparing results
reported back to plans from running the same set of claims data through the RAPS
process to results from the EDS process.
METHODOLOGY
Eight MA health plans submitted their 2014 and 2015 claims to CMS and provided
Inovalon/Avalere with the results from the two sources of data used for risk adjustment
for the 2015 and 2016 payment years. We received (1) the RAPS Return files that inform
plans of the disposition of diagnosis clusters submitted to CMS; and (2) the MAO-004
5. RISE RAPS-EDS Collaboration Research Project: Final Report 3
reports that inform plans of risk adjustment eligible diagnoses submitted to the EDS.
Avalere researchers aggregated and analyzed results from the RAPS Return versus
MAO-004 files, and compared resulting risk scores and estimated payment impact. Risk
score differences were investigated for the sample as a whole, as well as subset
analyses examining differences by age, region, dual eligible status and across plans.
Finally, we compared the most common HCCs identified using RAPS to those identified
with the new EDS.
RESULTS
Member Characteristics
The MA plan and study population characteristics are shown in Table 1. The eight
participating health plans ranged in size from small (5,200 members) to large (409,000
members) in 2015 and were similar size in 2014 (see Appendix 1). The study analyzed a
large representative sample that included 1.1 million Medicare beneficiaries in each year,
with members represented from all 50 states. We used the same plans in 2014 and 2015
so the composition of plans in the study was consistent across the two years. The
distribution of the study population by gender and age was also stable from 2014 to 2015.
Thus, any changes in risk scores observed over this period are not attributable to shifts in
demographics of participating plan memberships or to inclusion of different plans.
To assess the comparability of the study sample to the national MA population, Table 1
also shows the corresponding distributions for all MA plans nationwide. Gender and age
distributions are highly similar to MA plans as a whole, but the West Census Region is
underrepresented in our sample. The percent of dual eligible members is slightly higher
in the study sample than in the nation as a whole, but this difference is negligible.
Table 1: Study Population Plan and Member Characteristics
2014 2015 National MA
(Percentage
Only)7,8
Plan & Member Characteristics
Number of Plans
(H-Contracts):
8 (36) 8 (33) -
Number of Members:
Total
1,078,000 1,116,000 -
Mean
Range
135,000
5,500 - 408,000
140,000
5,200 - 409,000
-
Gender: N (%)
Male 465,000 (43.2%) 482,800 (43.3%) 44%
Female 613,000 (56.8%) 633,300 (56.7%) 56%
6. RISE RAPS-EDS Collaboration Research Project: Final Report 4
Age in years: N (%)
< 65 160,200 (14.9%) 178,200 (16.0%) 14%
65-69 208,000 (19.3%) 254,700 (22.8%) 22%
70-74 264,400 (24.5%) 268,000 (24.0%) 23%
75-79 192,000 (17.8%) 187,800 (16.8%) 17%
80 and over 253,400 (23.5%) 227,300 (20.4%) 24%
Census Region: N (%)
Midwest 331,900 (30.7%) 360,500 (33.3%) 20%
Northeast 280,400 (25.9%) 290,400 (26.8%) 19%
South 429,700 (39.7%) 460,500 (42.6%) 33%
West 40,400 (3.7%) 6,700 (0.6%) 24%
Dual Eligible: N (%)
Non-Duals 789,500 (73.2%) 816,700 (73.2%) 82%
Duals 288,700 (26.8%) 299,400 (26.8%) 18%
Risk Scores
Average risk scores from EDS were significantly lower compared to RAPS (Table 2).
The EDS average risk score was 26 percent lower (0.86 versus 1.16) than the RAPS risk
score in the 2015 payment year, and 16 percent lower (1.01 versus 1.20) in the 2016
payment year. The smaller difference between EDS and RAPS risk scores in 2016 can
be attributed in part to the corrections CMS made to the EDS logic by improving the
MAO-004 reports (e.g., fixing excluded reason for visit codes on header records, assuring
valid HIC numbers, linking diagnoses from chart reviews to encounter records), and in
part to plans taking actions to address errors identified in their claims data and EDS
submissions, but the gap in risk scores from the two systems remains significant.
Table 2: RAPS and EDS—Risk Score Summary
2015 Payment Year
(2014 Dates of
Service)
2016 Payment Year
(2015 Dates of
Service)
Average Risk Score: Mean (Range)
100% RAPS 1.16 (1.00 - 1.74) 1.20 (0.98 - 1.73)
100% EDS 0.86 (0.41 - 1.10) 1.01 (0.88 - 1.46)
90% / 10% Blend 1.13 (0.95 - 1.68) 1.18 (0.97 - 1.70)
75% / 25% Blend 1.09 (0.86 - 1.58) 1.16 (0.95 - 1.66)
100% RAPS versus 100% EDS
Difference: Mean (Range) 0.30 (0.12 - 0.64) 0.19 (0.02 - 0.39)
7. RISE RAPS-EDS Collaboration Research Project: Final Report 5
% Reduction from 100% RAPS 25.9% (10.6% -
59.4%)
15.8% (1.8% - 28.3%)
100% RAPS versus 90% / 10%
Blend
Difference: Mean (Range) 0.03 (0.01 - 0.06) 0.02 (0.00 - 0.04)
% Reduction from 100% RAPS 2.6% (0.9% - 5.9%) 1.7% (0.0% - 2.9%)
100% RAPS versus 75% / 25%
Blend
Difference: Mean (Range) 0.07 (0.03 - 0.16) 0.04 (0.00 - 0.09)
% Reduction from 100% RAPS 6.0% (2.7% - 14.9%) 3.3% (0.0% - 6.5%)
Figure 1 graphically represents the average risk scores for the 2016 payment year (2015
dates of service) by health plan and overall based on 100 percent RAPS and 100 percent
EDS. Though individual plans experienced reductions in average risk scores ranging
from 2 percent to 28 percent, it is apparent that the 16 percent lower risk scores on
average observed in the overall sample is not due to just one or two large plans and that
all plans are impacted regardless of size. (See Appendix 2 for 2015 payment year data
which is not displayed here because the results were highly similar).
Figure 1: RAPS and EDS—Risk Scores by Health Plan and Overall
28%
7%
9% 10%
2%
7% 7%
16% 16%
0%
5%
10%
15%
20%
25%
30%
35%
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
A B C D E F G H Overall
PercentReduction
AverageRiskScores
MA Plans
Average Risk Score by Health Plan: 2016 Payment Year
RAPS EDS % Reduction
8. RISE RAPS-EDS Collaboration Research Project: Final Report 6
Figure 2 displays the average risk scores by age group of the beneficiaries. Average risk
scores are shown for 100 percent RAPS versus 100 percent EDS (left axis). The line
represents the percent difference between RAPS and EDS for each age group (right
axis). While all age groups are impacted significantly, we see that the impact on risk
scores of the high cost, high need younger disabled MA beneficiaries is greater than for
those age 65+.
Figure 2: RAPS and EDS—Risk Scores by Member Age
25%
28%
30% 29% 28%
19%19%
18% 16%
14%
0%
5%
10%
15%
20%
25%
30%
35%
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
00-34 35-44 45-54 55-59 60-64 65-69 70-74 75-79 80-84 85+
PercentReduction
AverageRiskScores
Age Group
Average Risk Scores by Age Group:
2016 Payment Year
RAPS EDS % Reduction
9. RISE RAPS-EDS Collaboration Research Project: Final Report 7
Figure 3 displays average risk scores by Census Region. The observed impact of EDS
appears to be significantly greater in the South with 24 percent lower risk scores on
average compared to the Northeast and Midwest. The risk score impact is lowest in the
West but, as noted above, the sample is underrepresented in that region so the evidence
is not conclusive for that region.
Figure 3: RAPS and EDS—Risk Scores by Census Region
10% 9%
24%
3%
16%
0%
5%
10%
15%
20%
25%
30%
35%
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
Midwest
Region
Northeast
Region
South
Region
West Region Overall
PercentReduction
AverageRiskScore
Census Regions
Average Risk Scores by Census Region:
2016 Payment Year
RAPS EDS % Reduction
10. RISE RAPS-EDS Collaboration Research Project: Final Report 8
Figure 4 displays average risk scores by dual eligible status of the member. Although
dual eligible beneficiaries have higher risk scores than non-duals under both systems, the
percent reduction in average risk scores for dual eligible beneficiaries is significantly
higher than the reduction for non-duals. This indicates that dual eligible members with
lower incomes and more complex conditions on average are more adversely affected by
the transition to EDS.
Figure 4: RAPS and EDS—Risk Scores by Dual Eligible Status
Financial Impact
The potential estimated impact on per-member per-month (PMPM) revenue is significant
based on our sample of plans and MA beneficiaries (Table 3). For demonstration
purposes, we assumed a default bid rate of $800 PMPM (risk score = 1.0). The average
payment rate for the 2016 payment year was $963 based on 100 percent RAPS. It is
only slightly lower with the 90/10 blend ($948 reduction), $925 applying the 75/25 blend,
and $809 with a full transition to EDS. This represents a 16 percent reduction in risk
adjusted payments in 2016 based on a 100 percent shift to EDS, a 1.6 percent reduction
based on the proposed 90/10 blended rate, and a 4.0 percent reduction based on the
75/25 blended rate,
To demonstrate the potential financial impact using the average study plan of 140,000
members in 2015 and the PMPM difference of $155 based on a 100 percent shift to EDS,
a full transition to EDS would result in a decrease of $260.4 million per year in risk
adjusted funds for the average plan. Applying the 90/10 blend, the difference translates
to a decrease of $25.2 million per year, and applying the 75/25 blend, the decrease is
$68.3 million for the average plan in the study.
20%
14.5%
0%
5%
10%
15%
20%
25%
30%
35%
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
Duals Non-Duals
PercentReduction
AverageRiskScores
Dual Status
Average Risk Scores by Dual Eligible Status: 2016
Payment Year
RAPS EDS % Reduction
11. RISE RAPS-EDS Collaboration Research Project: Final Report 9
Table 3: RAPS and EDS—Financial Impact Summary
2016 Payment Year
(2015 Dates of Service)
Financial Impact: PMPM; Mean (Range)
100% RAPS $963 ($781 - $1,383)
100% EDS $809 ($700 - $1,167)
90% / 10% Blend $948 ($773 - $1,361)
75% / 25% Blend $925 ($761 - $1,329)
100% RAPS versus 100% EDS
Difference: Mean (Range) $155 ($18 - $310)
% Reduction: from 100% RAPS 16.1%
100% RAPS versus 90% / 10% Blend
Difference: Mean (Range) $15 ($2 - $31)
% Reduction: from 100% RAPS 1.6%
100% RAPS versus 75% / 25% Blend
Difference: Mean (Range) $38 ($5 - $78)
% Reduction: from 100% RAPS 4.0%
Heirarchical Chronic Conditions (HCCs)
A difference in risk scores implies either a difference in the total number of chronic
conditions identified based on HCCs, a difference in which specific HCCs were identified
(because HCCs have different weights and therefore make differential contributions to
the risk score), or a combination of both. In general, our findings did not reveal any
significant differences in which individual HCCs were identified for scoring. Rather, the
data suggest there was difference in the overall number of HCCs identified and accepted.
Figure 5 shows the percent of members by the total number of HCCs identified based on
the two scoring systems. RAPS HCC counts are consistent across the two study years,
with 28-30 percent of members with no HCCs identified and about the same proportion of
members with three or more HCCs. In contrast, EDS results in almost half the members
with no HCCs identified in 2014, and more than 39 percent with no HCCS in 2015.
We also evaluated the top ten HCCs and their frequency of occurrence for both RAPS
and EDS. The frequency of each of the top ten HCCs was consistently lower in EDS
than in RAPS. On average, the most frequent HCCs were identified in approximately 12
percent of the members based on RAPS in both years. However, when assessed using
EDS, the average prevalence was only 6.9 percent based on 2014 data and 9.2 percent
based on 2015 data after CMS and health plan corrective actions (see Table 4 in
Appendix 2).
12. RISE RAPS-EDS Collaboration Research Project: Final Report 10
Figure 5: RAPS and EDS—Distribution of HCCs per Member
In summary, up to 40 percent fewer HCCs were identified on average by EDS compared
to RAPS using a large representative sample of MAO claims data for the 2015 and 2016
payment years. This difference results in significantly lower risk scores and lower risk
adjusted payment rates using EDS compared to RAPS.
CONCLUSION
The transition to calculating risk scores based on plan encounter data submissions was
projected to be revenue neutral to Medicare Advantage plans. A recent GAO study
documented numerous technical difficulties experienced by plans in submitting their data
and receiving accurate and actionable reports from the agency to correct the problems,
and CMS has now proposed to slow the phase in to EDS, maintaining the blend at 75
percent RAPS and 25 percent EDS in 2017 and 2018.
This report shows that a continued transition to an encounter data system is likely to have
significant impact on Medicare Advantage plan risk scores and risk adjusted payments.
Risk scores and reimbursement rates that do not reflect the full resource needs of the
population could influence plans’ benefit design decisions and ultimately adversely
impact the most high need, high cost beneficiaries who are younger, disabled, and dual
eligible.
Until increased transparency in EDS reporting is provided and rigorous measures are
taken to evaluate and resolve the differences, the continued transition to an encounter
data-based system will have a significant adverse impact on the Medicare Advantage
program and the beneficiaries served by the plans.
This project represents a collaboration between RISE, industry health plan partners,
Inovalon and Avalere.
29.9%
48.4%
28.2%
39.3%
25.8%
24.3%
25.3%
24.7%
17.3%
13.3%
17.5%
15.3%
27.0%
14.0%
29.0%
20.7%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
RAPS EDS RAPS EDS
2014 2015
%ofParticipants
Distribution of HCCs
3 or more
2
1
0
# of HCCs:
13. RISE RAPS-EDS Collaboration Research Project: Final Report 11
REFERENCES
1. CMS 2017 Final Rate Announcement (April 4, 2016), p. 61.
(https://www.cms.gov/Medicare/Health-
Plans/MedicareAdvtgSpecRateStats/Downloads/Announcement2017.pdf)
2. GAO-17-223 (January 2017). (http://www.gao.gov/assets/690/682145.pdf)
3. CMS Advance Notice and Draft Call Letter, released February 1, 2017 accessed
at (https://www.cms.gov/Newsroom/MediaReleaseDatabase/Fact-sheets/2017-
Fact-Sheet-items/2017-02-01.html) on February 19, 2017
4. Impact of Medicare Advantage Data Submission System on Risk Scores,
(http://avalere.com/expertise/managed-care/insights/impact-of-medicare-
advantage-data-submission-system-on-risk-scores)
5. See for example GAO-17-223, page 2, “CMS does not expect the diagnoses in
MA encounter data to differ from those in RAPS.”
6. HPMS memo from Dec 29th, 2016
7. Centers for Medicare & Medicaid Services (2013). Medicare Current Beneficiary
Survey (MCBS): https://www.cms.gov/Research-Statistics-Data-and-
Systems/Research/MCBS/index.html Accessed January 13, 2017.
8. Omitted US Territory/Unknown Census Regions from benchmark data, so
percentages will not sum to 100 percent.
14. RISE RAPS-EDS Collaboration Research Project: Final Report 12
APPENDIX 1: STUDY PARTICIPANTS
2014 2015
MA Plans
Blue Cross Blue Shield of Michigan 284,000 305,000
Blue Cross Blue Shield of Minnesota 5,500 5,200
Blue Cross Blue Shield of North Carolina 105,000 92,000
Blue Care Network 53,000 62,000
Cigna 408,000 409,000
Gateway Health Plan 45,000 51,000
Geisinger Health System 63,000 71,000
Healthfirst 115,000 121,000
Total Number of Beneficiaries 1,078,000 1,116,000
15. RISE RAPS-EDS Collaboration Research Project: Final Report 13
APPENDIX 2: 2015 PAYMENT YEAR—TABLES AND FIGURES*
*Table and figure numbers are the same as the corresponding data in the body of the
report
Figure 1: RAPS and EDS—Risk Scores by Health Plan and Overall
Figure 2: RAPS and EDS—Risk Scores by Member Age
34%
15%
23%
17%
11%
59%
19%
37%
26%
0%
10%
20%
30%
40%
50%
60%
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
A B C D E F G H Overall
MA Plans
PercentReduction
AverageRiskScores
Average Risk Score by Health Plan: 2015 Payment Year
RAPS EDS
19%
24%
25% 27% 28%
25% 25% 26% 26% 26%
0%
5%
10%
15%
20%
25%
30%
35%
-0.2
0.3
0.8
1.3
1.8
00-34 35-44 45-54 55-59 60-64 65-69 70-74 75-79 80-84 85+
Age Group
PercentReduction
AverageRiskScores
Average Risk Scores by Age Group: 2015 Payment Year
RAPS EDS % Reduction
16. RISE RAPS-EDS Collaboration Research Project: Final Report 14
Figure 3: RAPS and EDS—Risk Scores by Census Region
Figure 4: RAPS and EDS—Risk Scores by Dual Eligible Status
23%
21%
31%
-4%
25%
-5%
0%
5%
10%
15%
20%
25%
30%
35%
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
Midwest
Region
Northeast
Region
South
Region
West Region Overall
Census Regions
PercentReduction
AverageRiskSocres Average Risk Scores by Census Region: 2015
Payment Year
RAPS EDS % Reduction
30%
23%
-5%
5%
15%
25%
35%
0.0
0.5
1.0
1.5
Duals Non-Duals
PercentReduction
AverageRiskScores
Dual Status
Average Risk Scores by Dual Eligible Status: 2015
Payment Year
RAPS EDS % Reduction
17. RISE RAPS-EDS Collaboration Research Project: Final Report 15
Table 3: RAPS and EDS—Financial Impact Summary
2015 Payment Year
(2014 Dates of Service)
Financial Impact: PMPM; Mean (Range)
100% RAPS $927 ($798 - $1,392)
100% EDS $692 ($332 - $882)
90% / 10% Blend $904 ($758 - $1,341)
75% / 25% Blend $869 ($687 - $1,264)
100% RAPS versus 100% EDS
Difference: Mean (Range) $235 ($94 - $510)
% Reduction: from 100% RAPS 25.4%
100% RAPS versus 90% / 10% Blend
Difference: Mean (Range) $24 ($9 - $51)
% Reduction: from 100% RAPS 2.5%
100% RAPS versus 75% / 25% Blend
Difference: Mean (Range) $58 ($23 - $128)
% Reduction: from 100% RAPS 6.3%
Table 4: Top Ten Most Frequently Occurring HCCs
HCC
Description Prevalence (% of Members)
2014 2015
RAPS EDS RAPS EDS
18
Diabetes with Chronic
Complications
16.5% 10.4% 19.2% 15.1%
108 Vascular Disease 16.4% 8.0% 17.4% 12.5%
111
Chronic Obstructive Pulmonary
Disease
16.2% 9.4% 16.4% 12.1%
19 Diabetes without Complication 13.5% 9.8% 13.2% 10.9%
85 Congestive Heart Failure 12.7% 7.5% 13.0% 9.9%
96 Specified Heart Arrhythmias 12.1% 8.4% 12.3% 10.2%
58
Major Depressive, Bipolar, and
Paranoid Disorders
8.9% 4.5% 10.1% 6.5%
22 Morbid Obesity 7.4% 3.5% 8.1% 5.4%
40
Rheumatoid Arthritis and
Inflammatory Connective
Tissue Disease
6.0% 3.8% 6.3% 4.8%
12
Breast, Prostate, and Other
Cancers and Tumors
5.8% 4.4% 6.0% 5.1%
Average Prevalence of Top 10 HCCs 11.5% 6.9% 12.2% 9.2%
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