Industry Voices—While HEDIS hibernates, get ahead of the data-reporting curve

An abstract image of data
HEDIS may have hibernated during 2020, but payers can’t afford to sleep on data-quality issues that could hinder their quality metrics in 2021. (whiteMocca/Shutterstock)

Many payers likely breathed a sigh of relief earlier this year when the federal government announced that it was suspending data collection and reporting requirements for a number of high-profile quality-measurement programs.

Due to the COVID-19 pandemic, the Centers for Medicare and Medicaid Services declared in April that it would halt data collection for programs such as the Qualified Health Plan Enrollee Survey, Quality Improvement Strategy, and Healthcare Effectiveness Data and Information Set (HEDIS).

HEDIS is a comprehensive set of standardized performance measures intended to give health insurance buyers the information they need to make reliable comparisons between competing health plans. HEDIS measures include data points such as rates of colorectal cancer screenings, use of high-risk medications in the elderly and follow-up after hospitalization for mental illness.

Qualified health plans are typically expected to report data for HEDIS to CMS between May and June. However, because many HEDIS measures require health plans to perform reviews of patients’ medical records or to obtain information directly from physician offices, CMS officials decided that reporting data for the 2020 plan year would divert resources from the fight against COVID-19.

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Though health plans have been given a temporary reprieve from HEDIS, it’s likely that reporting requirements will resume as usual next year. Thus, CMS has encouraged health insurers to continue capturing important data to drive their own quality-improvement programs.

That means health insurers should use this temporary reprieve to get their HEDIS reporting in order. A significant component of that effort involves ensuring that clinical data can be captured more efficiently through digital charts and is of high-enough quality to reflect the care that members truly received.

What COVID-19 has taught us about data quality

In many regards, the state of clinical data in the healthcare industry is not pretty. Often, clinical data is not structured or codified and appears as an ugly blob of text in patient records. For example, measures such as blood pressure or a diabetic’s HbA1c levels are sometimes recorded in the unstructured “notes” fields of electronic health records (EHRs).

Further, if there is a silver lining from the COVID-19 pandemic, it is the critical importance of obtaining accurate data to inform policy decisions that could affect a broader population. In public health crises, accurate data represents a key element necessary to craft responses, allocate resources, measure the effectiveness of interventions, and direct the reopening of local economies. Now, with flu season upon us, the need to base public health decisions on accurate, reliable data will only accelerate.

Following are four reasons why payers should take advantage of the temporary HEDIS reprieve to get ahead of the data-quality curve.

  • If data is not clean, it’s not accurate: Payers rely upon several data sources that currently deliver inconsistent and inaccurate data, most notably patient information from EHRs and labs. This incomplete clinical data can result in failure to address patients’ gaps in care, diminished quality measures and excessive administrative inefficiencies such as prior authorizations. If the data is bad, the process and reporting will continue to be flawed.
  • The days of manual intervention are gone: Payers have relied on manual, chart-chasing processes for far too long. The pandemic has forced this process to move to a more automated, electronic format. Part of CMS’ stated reasoning for suspending data-reporting requirements this year revolved around promoting COVID-19 safety when payers collect data from providers. In some cases, payers’ data-collection specialists would have inevitably needed to visit provider offices to obtain patient data or review patient records, which is not something healthcare organizations would support during a pandemic. With electronic data collection and greater reliance on digital charts, that concern fades away.
  • Tapping the brakes on “business as usual” will help reduce errors, maximize Star ratings and decrease costs: Payers have been on autopilot for the past decade when it comes to HEDIS reporting. Reviewing processes, technology and data will not only reduce unnecessary costs but could improve Star ratings substantially. During this downtime, payers should work to automate as much of the data collection and reporting process as possible. While automating processes, payers should review the utility of their clinical data. Is the data being collected and reported usable? In many instances, there is an opportunity to optimize clinical data that not only maximizes Star ratings but does so in a cost-effective way.  
  • NCQA has not stopped: It has become clear to most in the healthcare industry that clinical data quality must be improved. To this end, the National Committee for Quality Assurance (NCQA) has launched a pilot program for data aggregators, such as Health Information Exchanges, that collect and transform data from original sources on behalf of vendors and healthcare organizations. The idea behind the Data Aggregator Validation program is to demonstrate that aggregators meeting NCQA standards have achieved high-enough quality that their data can be leveraged by other organizations as standard supplemental data or as abstracted medical records. As a result of these standards, payers could save time and resources by relying on certified vendors as opposed to devoting internal resources towards validating the data.

HEDIS may have hibernated during 2020, but payers can’t afford to sleep on data-quality issues that could hinder their quality metrics in 2021. Payers must take advantage of the pause now to implement the processes that yield clean, concise and accurate clinical data.