Medicare Advantage has exploded over the last decade and a half, with the number of Medicare Advantage beneficiaries increasing by almost 400% in the last 15 years. As a result, provider groups have an increasing percentage of revenue and patients in Medicare Advantage (MA) plans.

Given this, providers are increasingly compensated based on HEDIS quality measures and risk scores through a combination of claims data and supplemental data. Because of the limited amount of data that is reported through claims, submitting supplemental data can be critical to ensuring you receive credit for the quality of care you are delivering and the true complexity of your patient population. Some plans have well-defined reporting programs, while others have little-publicized channels for reporting supplemental HEDIS and risk data. Sometimes there are significant bonuses that MA plans offer to providers for reporting, since the plan benefits immensely from receiving the data.

Why is HEDIS and risk data so important to health plans? What is supplemental data? And how do you as a provider organization report this data efficiently to earn incentives? Here we will give you a clear overview of HEDIS and risk, and examples of how providers are reporting data and benefiting.

Below you will find information on:

For more detailed information on your specific context, you can request a free consultation with an expert from Able Health.

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In this section, you will find information on:

  • How star ratings work
  • How plan payments relate to star ratings
  • How star ratings affect providers

How star ratings work

Medicare uses a Star Rating System to measure how well Medicare Advantage Organizations (MAOs) perform. Medicare scores how well MAOs perform in nearly 50 measures. Those measures spread across five categories and CMS assigns each category a score from one to five stars (five being the highest and one being the lowest). Medicare also assigns one overall star rating to summarize performance as a whole. The five performance categories are:

  • Staying healthy: screening tests and vaccines: Includes whether members received various screening tests, vaccines, and other check-ups to help them stay healthy.
  • Managing chronic (long-term) conditions: Includes how often members with certain conditions received recommended tests and treatments to help manage their condition.
  • Member experience with the health plan: Includes member ratings of the plan.
  • Member complaints and changes in the health plan’s performance: Includes how often Medicare found problems with the plan and how often members had problems with the plan. Includes how much the plan’s performance has improved (if at all) over time.
  • Health plan customer service: Includes how well the plan handles member appeals.

Ratings are set at the Medicare Advantage Organization (MAO) contract level, not the plan level, meaning all plans under the same contract receive the same score. Stars are assigned to each contract for each measure being evaluated, based on performance relative to the other contracts. The overall score for each contract is calculated by averaging the star ratings for each individual measure for a contract.

New plan quality ratings come out each October and affect payments in the following calendar year. For example, plan ratings for 2020 were available in October 2019. The average star rating weighted by enrollment was 4.03 in 2017, 4.07 in 2018, 4.06 in 2019, and 4.16 in 2020.

 

How plan payments relate to star ratings

Star ratings matter immensely for Medicare Advantage Organizations, because bonus payments and rebates are tied to the number of stars achieved. These ratings are extremely important to MAOs because of the amount of money on the line.

Under a provision of the Affordable Care Act (ACA), star ratings began to be used to adjust payments to MAOs beginning in 2012. There are two parts that comprise the rewards:

  1. Direct bonus payments to the plan operator
  2. Rebates which must be returned to the beneficiary in the form of additional or enhanced benefits, such as reduced premiums or expanded coverage

Bonus payments are paid per enrollee and are calculated as a share of the MA benchmarks, which vary by county, and thus bonus payments vary by county. Bonuses for 4-star plans or higher are 5 percent of the area’s benchmark for each member. Double bonuses are awarded in certain counties with demographic factors that indicate a complex population of beneficiaries. In the 2020 Star Ratings, 52% of MA contracts scored between 4 to 5 stars.

 

How Star Ratings affect providers

When a health plan and all contracted providers work together to improve Star Ratings, payments can increase across the board, raising all boats. However, some Medicare Advantage Organizations go further to directly incentive individual providers or provider groups to close HEDIS care gaps, so they don't have to rely on other providers doing their part in order to experience the benefits.

HEDIS measures

Below you can find the list of HEDIS quality measures included in the Star Ratings program. The full list of Star Ratings measures (including patient experience and other measures) and their weighted contributions to health plan ratings can be found on Medicare's page for Part C and D performance dataNote that each payer may prioritize these measures differently in their evaluation and rewarding of provider groups.

Star Ratings Measure ID

HEDIS Measure ID

Measure Name

C01

BCS

Breast Cancer Screening

C02

COL

Colorectal Cancer Screening

C07

AMA

Adult BMI Assessment

C09

COA

Care for Older Adults – Medication Review

C10

COA

Care for Older Adults – Functional Status Assessment

C11

COA

Care for Older Adults – Pain Assessment

C12

OMW Osteoporosis Management in Women who had a Fracture

C13

CDC Diabetes Care – Eye Exam

C14

CDC Diabetes Care – Kidney Disease Monitoring

C15

CDC Diabetes Care – Blood Sugar Controlled

C16

CBP Controlling Blood Pressure

C17

ART Rheumatoid Arthritis Management

C20

TRC Medication Reconciliation Post-Discharge

C21

ACR Plan All-Cause Readmissions


HEDIS gap closure

Fundamentally, in order for plans to earn high Star Ratings, providers in their network need to perform well on HEDIS measures. This involved tracking and filling gaps in care on common measures, such as monitoring documentation of patient BMI measurements or tracking A1c results.

There are multiple ways that this tracking and gap closure is done, including:

  • Receiving periodic HEDIS gap lists from payers. Many payers provide lists of current HEDIS gaps on a quarterly or monthly basis. Providers can use these lists to call patients and get them into the office to fill gaps. These lists are helpful for providers to get a full picture of patient gaps at a point in time, but because they are periodic and the data is often delayed by one or more months, sometimes the lists can be frustrating because they don't represent the current reality. Because these lists only incorporate data that has been submitted to the payer, each patient's chart should be reviewed to determine whether the patient should be treated or supplemental data should be submitted to the payer in order to close the gap.
  • Creating morning huddle summaries. Many providers use third party tools to generate gap lists based on the latest medical record data. By pulling gaps for patients coming in to the office that day, providers can plan for the needed tests, screenings, and procedures in a morning huddle, or deliver a paper checklist to providers along with the paperwork for each patient.
  • Integrated EHR flags. Some providers choose to build notifications about HEDIS gaps into EHR systems. This can be a streamlined way to notify clinicians of gaps in care, though clinicians also sometimes suffer from "alert fatigue," where there are so many EHR alerts that they begin to ignore them.

Supplemental data submission

Closing gaps is all well and good, but if the data doesn't make it back to the plan then it won't affect their star rating. Many HEDIS measures in the star ratings program can be calculated off of claims data that the payer has access to, but there may be additional data in the electronic health record system (EHR) that would demonstrate higher performance.

For example, measures such as HEDIS Controlling High Blood Pressure (CBP) and HEDIS Adult BMI Assessment (ABA ) require data that often is found in the EHR and not claims:

  • HEDIS Controlling High Blood Pressure (CBP) requires blood pressure results that cannot be found using claims.
  • HEDIS Adult BMI Assessment (ABA) allows plans to use either BMI Percentile ICD codes from electronic data or, more commonly, BMI vitals from supplemental data.

Therefore, many MA plans pay providers incentives to submit supplemental HEDIS data from the EHR, so that the plan will have a more complete data set for star ratings.

There are two ways that a health plan can calculate a measure:

  1. Electronic Method: Calculate measures based exclusively on electronic data, which is usually drawn from claims, and less commonly other data sources including the EHR.
  2. Hybrid Method: Calculate the eligible population based on the Electronic Method and then calculate the numerator using a combination of electronic and medical record data for a sample of patients.

Plans often seek clinical data from the EHR via either of these two methods in order to ensure a complete HEDIS data set will be evaluated for their star rating.

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In this section you will find information on:

  • How risk adjustment works
  • How plans submit risk data to CMS
  • Payment timeline
  • How risk adjustment affects providers
  • RADV audits

 

How risk adjustment works

The Centers for Medicare and Medicaid Services (CMS) pays Medicare Advantage Organizations (MAOs) using a capitated payment model, meaning a flat fee per patient per month. This rate is adjusted based on each patient's risk score, a measure of how complex that patient is to treat. That ensures a healthcare provider earns more money for treating a patient with multiple chronic conditions compared to a healthy patient.

The formula for determining the monthly capitated rate paid to a MAO is the benchmark rate times the risk score.

  • Benchmark Rate: This is the baseline rate that Medicare pays out for each county in the United States.
  • Risk Score: This is calculated using a model called Hierarchical Condition Categories (HCC), which analyzes the diagnoses each patient has, as well as demographic factors like age and Medicaid eligibility. CMS groups ICD codes into HCCs, each of which is assigned a coefficient. The coefficients are summed to generate the patient's risk adjustment factor (RAF).

Each year, CMS also applies a coding intensity adjustment, which cuts risk scores across the board. This adjustment is calculated based on discrepancies in coding patterns that CMS finds between Medicare Advantage and fee-for-service Medicare. Those discrepancies exist because MA plans work more intensely to identify additional diagnoses. The adjustment is 5.90% in 2020.

Below is a sample calculation of a patient's risk score, or risk adjustment factor (RAF). The coefficients listed are for a patient who is in the community (not institutional) and dual-eligible.

Variable

Coefficient

Female, 65-69

0.425

Cyclic neutropenia (HCC47)

0.529

Leukemia (HCC8)

2.542

HCC47-Cancer Interaction

0.815

Total RAF

4.311

This patient's benchmark rate would be multiplied by 431.1%. From this example, you can see that not all HCC categories are created equal. You can also see how complete diagnoses documentation changes capitated rates. Note that the effects of HCC categories can compound through interactions, as in the HCC47-Cancer example above.

 

How plans submit risk data to CMS

MAOs make significant efforts to improve coding of diagnoses for each patient, as well as submit their diagnosis data to CMS. Diagnosis data is submitted to CMS using a combination of the data formats:

CMS calculates a "blended risk score" using a combination of the two data formats. CMS originally indicated that they would transition to 100% EDS by 2020, and then slowed the transition with a reversal of the trend in 2018 in order to account for operational issues with the EDS process. CMS continued the transition again starting in 2019. And this transition impacts the data elements and format of data that plans will collect from providers.

To blend the two, each MAO is assigned a risk score for each of the data sources, which is then weighted into a final risk score. The following table outlines the changing annual weights:

 

Payment Year

EDS Weight

RAPS Weight

2017

25%

75%

2018

15%

85%

2019

25%

75%

2020

50%

50%

2021 (proposed)

75%

25%

 

Payment timeline

Risk-adjusted payments for each year are based on diagnoses submitted for the prior year, so 2020 risk scores are based on 2019 diagnoses. However, the initial payments for 2020 are paid out before all diagnoses are due for 2019, so payments are first made prospectively using diagnoses from 7/1/18 - 6/30/2019 and then retroactively adjusted based on 1/1/2019 - 12/31/2019 diagnoses to resolve any payment discrepancies. These retroactive payments are called sweeps, and can involve additional payment to the plan or the plan returning a portion of revenue to CMS.

Below is the 2020 timeline for data submission and payment:

Payment Schedule

Dates of Service Used for Risk Scores

Submission Deadline for Data During Dates of Service

January - June 2020 Prospective

7/1/2018 - 6/30/2019

September 2019

August 2020 Retroactive (Midyear Sweep)

1/1/2019 - 12/31/2019

March 2020

July - December 2020 Prospective

1/1/2019 - 12/31/2019

March 2020

July 2021 Retroactive (Final Sweep)

1/1/2019 - 12/31/2019

January 2021

 

How risk adjustment affects providers

Hierarchical Condition Category (HCC) coding

CMS uses Hierarchical Condition Categories (HCCs) to establish the health of the members in a given MA population and reimburse the plan according to the health of the population they serve. The intention is that plans covering sicker patients will be paid additional money to care for their patients based on a higher predicted cost of care. The cost prediction depends on demographic information and patient health status in a given year.

Therefore, if conditions belonging to a sick patient are not documented by a provider each year, then the plan will not get credit for caring for a sick patient, and will only be paid for taking care of a healthy patient. As a result, it is of utmost importance to plans that providers in their network accurately record the conditions of patients in their population. 

For HCC coding, diseases and conditions are organized into categories. Examples of top HCC categories include:

  • Diabetes
  • Asthma and pulmonary disease
  • Major depressive and bipolar disorders
  • Congestive Heart Failure
  • Breast and prostate cancer
  • Rheumatoid arthritis

Patients can be added to more than one category, indicating a higher risk factor, and qualifying for a higher level of reimbursement. MA plans often encourage providers to have systems in place that ensure accurate and up-to-date coding. Because coding must be done annually, many providers encourage patients to attend annual wellness visits or fairs to ensure that coding is up to date each year. Some providers also use home visits, gift cards, or other perks like massage therapy to motivate patients to come into the office. 

Supplemental data submission

Similar to Star Ratings, MA plans are at an advantage if they can collect the most complete dataset for risk adjustment. For example, if there is a diagnosis for a patient in the EHR that was not billed on a claim this year, the plan wants to know that in case it affects the risk score. Therefore, many plans will incentivize providers to submit supplemental data related to risk.

The formats that plans use to collect risk data from providers are informed by the formats that plans use to submit to CMS, though oftentimes the plan will use a simpler format to collect data from providers. The formats that plans use to submit data to CMS are:

You can read about examples of real data submission incentive programs in the last section of this primer.  

RADV Audits

Medical record documentation is required for the Risk Adjustment Data Validation (RADV) process administered by the US Department of Health and Human Services (HHS). The purpose of RADV audits is to ensure that the HCC diagnosis coding submitted by plans to HHS for risk adjustment is valid. Read more about how to ensure you are prepared for RADV audits here.

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In this section you will find the following information:

  • Supplemental submission method overview
  • Case study 1: UnitedHealthcare PATH
  • Case study 2: Humana Medicare Rewards
  • Case study 3: Anthem Risk Adjustment

 

Supplemental data submission methods

Each MA plan has the leeway to collect supplemental data in different ways. In the next sections, we will dive into examples of incentives and data collection methods in three different performance payment programs. But first, here is an overview of common data collection methods that we have seen used across payers, sometimes more than one at a time.

  • Chart request: Some payers request specific patient charts for use in HEDIS patient samples, risk coding, or CMS audits. In this case you may receive a request for a limited set of charts. Depending on the payer, these may be submitted via fax, an online portal, Secure File Transfer Protocol (SFTP), or other means.
  • Bulk data submission: Other payers want a more complete set of data on an ongoing basis. Providers submit any available documentation via flat file or other file upload process, which cover a broader population of patients. In some cases, it can be difficult to know what data to submit in this case. Many payers send providers quarterly or monthly HEDIS gap lists and risk suspect lists, which can be used to inform the gathering of supplemental data.
  • Automation: The most forward-thinking plans are beginning to automate the collection of supplemental data. This requires connecting with the providers' EHR systems throughout the plan network to pull the data directly. This drastically reduces the burden on providers, removing the need for manual submission through a spreadsheet or portal, and also improves the completeness and quality of data submitted. This is often done through a third party intermediary, like Able Health, so that providers can maintain control over the data that is shared with the plan, rather than giving the plan full access to the EHR.

Learn how Able Health streamlines supplemental data submission:

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Case study 1: UnitedHealthcare PATH

Program Overview

UnitedHealthcare offers Medicare Advantage providers support and financial incentives to close Star Ratings care gaps through its PATH program. The PATH program includes:

  • Financial incentives and recognition
  • Tools and support to identify care gaps
  • Outreach to members to assist with care management
  • Access to guidance on care and documentation related to quality measures

In 2020, financial incentives are offered as follows:

Care Provider Average Star Rating

Payment Amount for Star Rating Bonus

4.75 and above

$135 PMPY

4.5 - 4.74

$110 PMPY

4 - 4.49

$50 PMPY

3.76 - 3.99

$25 PMPY

3.75 and below

$0

 

Data Submission

Participating providers are able to review their performance in the UHCCareConnect online portal, as well as monthly Patient Care Opportunity Reports (PCOR), which compile results from medical and pharmacy claims data, as well as supplemental data. Supplemental data may be submitted through a variety of means, including:

  • Uploading documentation to the UHCCareConnect tool
  • Submitting data in a structured data format
  • Establishing an electronic connection to your EHR via HL7 interoperability standards
  • Establishing a remote connection to your EHR for clinical data review
  • On-site review of EHR records

 

Case study 2: Humana Medicare Rewards

Program Overview

Humana offers Medicare Advantage providers incentives for meeting quality and cost benchmarks through a tiered approach they call the Accountable Care Continuum. 

Tier

Program

Evaluation

Opportunity

1

Star Rewards Program

Evaluation is based on HEDIS measures

Annual reward payments are made to physicians who meet four of five HEDIS metrics

2

Model Practice Program

Evaluation is based on HEDIS measures, as well as achieving specific clinical initiative targets

Quarterly reward payments are made for meeting quality and shared savings targets, and annual payments are made to practices that see at least 75% of their patients two or more times

3

Medical Home Program

Must be recognized as a patient-centered medical home (PCMH) or in process of obtaining recognition

Eligible for same rewards as a model practice, as well as a quarterly care coordination payment

 

Data Submission Format

Providers have access to Humana Health Alerts, which uses a member summary format to share care gaps with clinicians. Supplemental data in support of closed care gaps may be submitted to Humana via an online portal.

Learn how Able Health helps automate data submission for MA HEDIS and Risk:

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Case study 3: Anthem Risk Adjustment

Program Overview

Anthem collects diagnosis data for risk adjustment through multiple means, including:

  • Claims data
  • Supplemental encounter data
  • Medical record reviews

Additionally, Anthem may request medical records from providers in the case that the plan is selected by CMS for a RADV audit and a provider’s patients fall into the audit sample.

 

Data Submission

Anthem collects supplemental data in accordance with CMS’s Encounter Data Submission (EDS) requirements. While the file includes a detailed set of information required for EDS submission, Anthem requests a flat file format that is far less complicated than the X12 format required by CMS. In their specification, Anthem notes that because CMS requirements for EDS change often, they suggest that providers collaborate closely with Anthem to meet the necessary requirements.

Schedule a Free HEDIS & Risk Consultation  Click here to schedule a consultation with an Able Health expert, including a  Q&A on HEDIS, risk scoring, supplemental data submission, and more.  Schedule →