Smile CDR Statement on Spring4Shell Vulnerability. Read More >>

×

What Low HEDIS Scores Cost Plans and How to Improve Them

Author:  Smile CDR

Smile for a Good HEDIS Score 

Failure hurts. It can hurt you physically. It can hurt your pride. And failure can hurt your bottom line.

When you’re in charge of a 100K member health plan, failing gets awfully expensive. We’re talking $17 million USD in missed reimbursements for failure to meet specific quality measures. 

Yes, you read that correctly: health plans can suffer up to $17 million in missed reimbursements just for failing (scoring low) on one Healthcare Effectiveness Data and Information Set (HEDIS) measure. With over 95 measures, and more than 20 tied directly to reimbursements, consistently low HEDIS scores could financially cripple even the most robust health plans.  

But the true cost of failing on HEDIS measurements surpasses any dollar amount. You see, HEDIS "measures how well health plans give service and care to their members," which is consistent with Value-Based Care principles; a model of care the US health system continues to transition to. In a VBC model, plans and Providers are paid based on successful outcomes of patients rather than for providing individual services to the patients. 

A low HEDIS score implies that members of a health plan are receiving lower quality care and experiencing worse health outcomes. Let's take a closer look at what HEDIS is and what it measures, the danger of low HEDIS scores and how a robust FHIR solution can help you do the most good with your HEDIS data.

What Is HEDIS

HEDIS is a performance measurement tool initially developed for consumers to compare and assess plans using standardized markers. Today, however, HEDIS is used by the National Committee for Quality Assurance (NCQA) and Centers for Medicare & Medicaid Services (CMS) to hold plans accountable for providing quality care.

The data points that HEDIS measures are intended to inform actions that improve overall population health. HEDIS measures actions and results across five categories:

  • Effectiveness of Care
  • Access/Availability of Care
  • Utilization 
  • Risk-Adjusted Utilization
  • Measures Reported Using Electronic Clinical Data Systems

Ideally, health plans can use HEDIS scores to identify and address any gaps in care.

(For a deeper dive read the Use Case HEDIS MEASURES & PRIOR AUTHORIZATION WITH CQL AND CDS HOOKS.)

What HEDIS Scores Accomplish

Since HEDIS holds plans accountable for providing quality care, let's see how it applies in a real-life scenario: diabetes clinics.

Diabetes is one of the most common chronic diseases in the US. Unmanaged, diabetes can take a toll on nearly every organ in the body, including heart and blood vessels, eyes, kidneys, nerves, gastrointestinal tract, gums and teeth. In extreme cases, it can lead to blindness, stroke, amputation and even premature death.

At medical treatment facilities, people with diabetes can receive tests, medications, education and therapies that help them control their blood glucose levels. The NCQA requests data from the tests that diabetic patients take (ex: blood glucose levels - HbA1c) or outcomes from treatments they undergo to manage their disease (ex: blood sugar under control). This data is then used to assess the quality of care provided. 

For example, NCQA uses HEDIS data to rate a diabetic clinic based on how often patients receive eye exams, whether their blood pressure is regularly monitored and whether their HbA1c screenings show good or poor control of blood glucose levels. A clinic that shows a strong percentage of its patients receiving these preventative services are awarded a high HEDIS rating. 

However, if the clinic's data show they are not providing preventative screening to a high enough percentage of their patients, their HEDIS score would be reduced. This is how HEDIS quantifies the clinic's ability to care for their diabetic patients.

Consequences of A Low HEDIS Rating

A low HEDIS rating implies that adequate care is not being provided. Furthermore, consistently low HEDIS scores could also mean that:

  • plans will be penalized with a low Medicare Star Rating, which will make them less attractive to new members
  • patients will choose different plans with higher ratings
  • plans will receive reduced reimbursements
  • a plan’s ability to participate in the Marketplace is limited
  • plans can incur CMS penalties, including being shut down.

How HEDIS Scores Have Been Determined in the Past

Health plans collect three types of data and submit it to NCQA, where it is audited:

  • Administrative data–the plan’s claims database
  • Survey data–Provider and member surveys
  • Hybrid data–claims database and review of medical records

Unfortunately, these methods of gathering data can be inaccurate and even biased: 

  • Administrative data is only as complete and accurate as the physicians and medical staff who enter the data. 
  • Surveys are only useful when enough people complete them. 
  • Hybrid data can be manipulated due to the way it is collected, which is referred to as “chart chasing.” (Chart chasing is the process where a team of nurses visits clinics and pulls a random sample of the charts to analyze for specific data.) It’s probable that this random sample of charts isn’t entirely random, or that the data isn’t analyzed objectively, leading to biased results. 

In addition to the possible inaccuracies and biases, these manual methods of obtaining data provide only a retrospective view of the patient care provided. They struggle to proactively address the gaps in care they identify.

How HEDIS Scores Will Be Determined

(Hint: all roads lead to FHIR)

To simplify electronic sharing and reduce the likelihood of biased or inaccurate results, CMS adopted Clinical Quality Language (CQL), "a human-readable language standard."  CQL standardizes and integrates data, making it more transparent and consistent. Similarly, the NCQA is now designing digital quality measures using CQL to "make it easier to transfer measures into IT systems; reduce interpretation, recoding, and human error; and ease use across the care continuum." Further streamlining data collection, the NCQA will release FHIR-CQL HEDIS measures to be used in 2022 and reported in June 2023.

Moving forward, it’s expected that most HEDIS scores will be collected in FHIR-CQL. This is actually great news for plans and Providers alike because FHIR is the standard for the interoperability of healthcare data (FHIR stands for Fast Healthcare Interoperability Resources). It makes data exchange faster, more accurate and more meaningful. FHIR-CQL affords automated data reporting, which paves the way for greater efficiencies, monetary benefits, accountability and value in healthcare. Furthermore, this new, automated method of obtaining data will provide a prospective view of patient care, making it easier to address gaps before they occur.

Michael Klotz, a Health IT data expert who writes for the NCQA, is also optimistic that FHIR-CQL could “blaze a trail” for all measures to be in a single DQM (digital quality measures) standard—“especially given that clinical data is becoming more structured, standardized and universally accessible, thanks to interoperability initiatives already underway."

Ways to Improve HEDIS Scores

Providers and plans look to the annual HEDIS quality measures distributed by the NCQA to find gaps where they could improve access to care and promote greater population health. These include ways to:

  • maintain accurate clinical documentation;
  • adopt new IT solutions, for example, automating data submission using FHIR-CQL for HEDIS;
  • document which patient services are completed;
  • increase preventative screening rates and meet specific patient-age-related deadlines;
  • improve provider-patient engagement;
  • transition fee-for-service to value-based care payment models.

Let's go back to that hypothetical diabetes clinic to see how HEDIS on FHIR helps improve population health.

The clinic's EHR was storing data about patients for years, but much of it was inaccessible. Clinicians reported high burnout rates, citing burdensome hours of documentation. After receiving a low HbA1c screening score, the clinic knew too many patients were missing a significant aspect of their care. The clinic knew they needed a better solution—not only to avoid future penalties, but to better care for their patients and give them access to the health data they needed.

To capture and better understand the data held in their EHR, the clinic implemented Smile CDR. Using FHIR, they can run more robust reports and automate data exchange without burdening clinicians with added documentation. Because Smile CDR is a comprehensive FHIR solution that delivers on all requirements (instead of just a few), the clinic will save valuable time collecting and interpreting data. They can compare their reports against the HEDIS measures to identify gaps in care and target patients with health reminders, educational content and more advanced patient outreach.

HEDIS-on-FHIR Improves Documentation and Can Lead to Better Population Health

Automated data reporting of HEDIS measures, made possible by FHIR, will help Payers quickly act on valid data insights and better collaborate with Providers. When data is accessible in a FHIR-based data management platform, like Smile CDR, Providers will be able to view, understand and use data to engage more patients in their own care. These automated methods of data collection will provide a more prospective view of patient care, as organizations will be able to use the data to identify and close gaps. Plans will also be able to realize greater returns on Value-Based Payments instead of missing out on millions in reimbursements. In fact, the Council for Affordable Quality Healthcare (CAQH) estimates a savings of $9.9 billion for plans and Providers

Over 90% of US Payers use HEDIS by the NCQA to measure performance. As the NCQA continues to implement greater automation and standardization of data collection with FHIR-CQL, be sure your EHR is ready to share its data. 

Choose a flexible, FHIR-based platform, like Smile CDR, so you can do the most good with your data.