Are you ready for the transition to digital quality measures?

The future of quality improvement is clear: both payers and providers must be prepared to submit quality measures digitally. Paper-based reporting methods are often inefficient, prone to error, and unable to provide a holistic, comprehensive view of quality performance.  

The Centers for Medicare & Medicaid Services (CMS) has been explicit about its goal to transition all quality measures across its programs to digital reporting methodologies. Healthcare organizations have been adopting digital methods into their operations and clinical care delivery for decades—now it is time to be ready for quality measurement to evolve.

What are healthcare quality measures?

In the healthcare quality improvement space, quality measures help payers, providers, and regulators align on goals and track performance over time. Quality measures are used for a range of programs to determine the effectiveness of healthcare dollars being spent, close care gaps, ensure patient safety, and improve patient outcomes.

What are digital quality measures?

Digital quality measures (dQM) include a broad range of digital measures that include clinical data pulled from provider EHRs as well as claims data, registry data, and patient-generated health data. Reporting dQMs entails sending data to the reporting agency in a standard interoperable format (such as Fast Healthcare Interoperability Resources, or FHIR), in an integrated package of files.  

Electronic clinical quality measures represent a subset of dQMs that only include clinical data from the EHR, also packaged in an interoperable format. The National Committee for Quality Assurance (NCQA) collects data specifically for HEDIS through Electronic Clinical Data Systems (ECDS) reporting. The digital reporting system aggregates electronic data and securely shares it with NCQA for HEDIS quality measures.

CMS plans to use dQMs for reporting in the Merit-Based Incentive Payment System (MIPS), Hospital Outpatient Quality Reporting, and Hospital Inpatient Quality Reporting.  

By 2030, all health plans must submit HEDIS measures data to NCQA through ECDS or via administrative methods.  

9 HEDIS quality measures that are required to be digital today

Under HEDIS, payers are required to work with providers to submit data on a subset of around 90 quality measures. Starting in 2025, nine of these measures must be submitted digitally, with the number gradually increasing until most HEDIS measures are submitted via ECDS by 2030.

HEDIS measures list – digital-only measures:

• Breast Cancer Screening (BCS-E)

• Blood Pressure Control for Patients with Hypertension (BPC-E)  

• Cervical Cancer Screening (CCS-E)

• Childhood Immunization Status (CIS-E)

• Colorectal Cancer Screening (COL-E)

• Depression Remission or Response for Adolescents and Adults (DRR-E)

• Depression Screening and Follow-Up for Adolescents and Adults (DSF-E)  

• Immunization for Adolescents (IMA-E)

• Prenatal Immunization Status (PRS-E)

Benefits of digital healthcare quality measures

Just as the transition away from paper medical records to EHRs was challenging but delivered significant benefits for providers, payers, and patients, the entire healthcare ecosystem will benefit from the full transition to dQMs. Digital transmission of critical quality data points will save countless hours of staff time and increase efficiency for both payers and providers. Digital reporting also significantly boosts quality improvement programs by allowing for more comprehensive and real-time data. It can also support programs to increase patient access to care with targeted data on care gaps, enhance patient access to their own data, and contribute to clinical research.

Ultimately, for both payers and providers, dQMs will drive cost savings, improve regulatory compliance, and enable seamless data-sharing across teams and programs.

Challenges payers and providers face in the transition to digital measures

Even though in the long term, dQMs will yield countless benefits, many health plans and providers are still unprepared for the significant changes in quality reporting workflows and processes digital quality measures require.  

Payers and providers need efficient ways to conduct data acquisition and aggregation.

At present, collecting the data necessary for quality reporting from providers and integrating it into a readable, measurable format is often clunky, inefficient, and time-consuming. The NCQA identified that simply accessing necessary clinical data is one of the top three barriers to digital quality reporting.

First, payers and providers need to work together to secure permissions from their data systems to set up interoperable access. Then, they need efficient, accurate, and secure processes to extract the data they need for quality reporting. However, relying on outdated, manual processes for this important step slows down quality reporting, creating  inefficiencies that cost the healthcare system over $15 billion a year.

Payers and providers also need to ensure a high level of data integrity—across the entire member population.

Unfortunately, no matter how efficient the data extraction process is, if the data being collected isn’t highly accurate, it does little to support the goals of quality measurement—namely, empowering payesr and providers with the data necessary to drive quality improvement. The accuracy of clinical quality data depends on a healthy foundation of clinical documentation.

To overcome this challenge, providers need efficient ways to document conditions at the point of care. And payers need to work with providers across their network to standardize documentation best practices. Sometimes this means going beyond what data points exist in the EHR. For example, the United States Core Data for Interoperability’s requirements for the data fields in the EHR don’t line up exactly with HEDIS requirements, and billing codes do not translate directly into the data needed for quality measurement. Payers and providers must ensure all relevant quality reporting fields are captured, even if it requires enhancements beyond the EHR’s standard data set.

The measurement population is larger, making year-round review harder.

As quality reporting requirements transition to digital reporting methods, payers and providers must be prepared to report data on the entire eligible population, not just a sample. Measuring performance on the entire population increases measurement accuracy and provides the necessary data to identify care gaps and conduct year-round quality improvement. However, it can also be a challenge. Payers and providers will need to conduct reviews on the eligible population year-round, and doing so at the population level instead of the sample level requires substantially more work.  

To make this happen, payers and providers must set up year-round quality improvement workflows with key stakeholders to segment, target, and provide appropriate interventions to patients in the reporting off-season.

How to prepare: three areas advanced technology helps enable digital HEDIS measures and other healthcare quality measures

Though the challenges to digital quality reporting seem like a lot of work, the benefits it will yield are considerable. To succeed, payers and providers need to work with key stakeholders throughout the year to conduct deep data reviews and strengthen quality improvement workflows. Additionally, advanced technology is empowering payers and providers to prepare for digital quality reporting by increasing the efficiency, accuracy, and effectiveness of the quality reporting process.

#1: Technology powered by artificial intelligence (AI) in healthcare can drastically accelerate data collection.

Using AI for medical record retrieval can accelerate the process by 80%, matching medical data to the right patient with incredible precision. AI can also drive improvements in provider outreach. For example, one health plan using Reveleer’s Quality Improvement Solution saved 1,400 hours by leveraging automation to identify chases that met specific criteria.  

Using technology to power data collection makes the process more efficient for both payers and providers. Health lans can easily automate provider outreach, and providers can rely on streamlined, interoperable avenues to submit their data.  

#2: Advanced technology can also support data accuracy by enhancing provider documentation.

AI-powered technology transforms data accuracy to make quality reporting more effective at measuring performance over time. Integrating solutions at the point of care can assist providers to improve documentation, uncovering clinical evidence for suspected diagnoses.  

Following the patient encounter, AI can also help verify documentation accuracy during abstraction, pinpointing any potential errors or documentation gaps to help coders focus their time on follow-ups, not on manually sorting through an incredibly high volume of data.

#3: Finally, advanced technology can support cleaning up and standardizing core data.

A presentation by CMS noted: “Data standardization is the foundation to successful digital quality measurement.” Without clean, integrated, and standardized data, providers and payers will be left scrambling as reporting deadlines quickly approach. Next HEDIS season, you can reduce a heavy reliance on manual processes and clean up data quickly, decreasing the risk of human error that can negatively impact quality performance.

Fortunately, advances in technology can help do the bulk of the work of cleaning up and standardizing core data systems so that reporting season becomes much more efficient and accurate. AI can integrate disparate sources of data, including both structured and unstructured data as well as structured data with varying units of measurement. Then, provider and health plan coding staff can easily verify potential anomalies the AI system flags, making the best use of valuable staff time and reducing potential errors.

Take the steps now that you need to transition successfully to digital quality measures

Payers and providers that are starting now to prepare for a full transition to dQMs will be best positioned for success. Advanced technology that can accelerate data collection, improve data accuracy, and standardize core system data will help drive improvements in quality performance and, as such, competitiveness and success in value-based care.  

In addition to transforming internal workflows and prioritizing quality measurement year-round, consider a technology partner that can help:

• Accelerate medical record retrieval by 80%

• Integrate and standardize disparate sources of data

• Predict care gaps with 99% accuracy to help target quality improvement

• Assist providers at the point of care with clinical insights and M.E.A.T.-standard documentation

Schedule a demo with Reveleer to tour our Quality Improvement Solution and prioritize success in digital quality measures today.