If you are managing a health plan, how do you measure how well you are doing compared to your local, regional, or even national competition? As importantly, how well do your members know how you are doing? How do you prove it?
One answer to these questions is the Health Effectiveness Data and Information Set, or HEDIS®. In this post, we’ll see how artificial intelligence software like Reveleer for Quality Improvement is making this already essential performance measurement tool even more valuable for payers, and the members they serve.
How Does HEDIS Measure Compliance?
The Centers for Medicare and Medicaid Services contracts with the National Committee for Quality Assurance (NCQA) to maintain HEDIS. Although HEDIS is intended mainly to measure the quality of Medicare Special Needs Plans, which are Medicare Advantage plans limited to people with specific conditions or diseases, the number of people enrolled in health plans that report HEDIS data is more than 190 million – more than half the population of the United States. Nine of every ten health plans are subject to HEDIS quality scoring for patients and members to compare.
HEDIS uses benchmark scores to measure how effective care is, how available it is, what the patient or member’s care experience is like, and how members use care services. HEDIS uses more than 90 performance measures to evaluate these criteria. Consistent with HEDIS being a comprehensive set of standardized performance measures, the NCQA annually reviews the number of HEDIS care quality criteria and performance measures. These have both increased in number over the years.
In addition to quality scoring, for providers HEDIS competition centers on measuring healthcare services against recommended best practices. Missing services, particularly missing preventive care services, create “HEDIS gaps.” Closing HEDIS gaps helps providers improve not only their competitive standing, but also their overall quality of care.
CONNECT WITH US AND SEE HOW REVELEER FOR QUALITY IMPROVEMENT CAN HELP IMPROVE OUTCOMES FOR YOUR MEMBERS.
AI Harnesses the Full Power of HEDIS Data
Now that we see how health plans and healthcare providers use HEDIS to measure and improve quality, the questions become how the NCQA gathers HEDIS data, and how with the help of artificial intelligence software you can gain a competitive advantage.
For HEDIS the NCQA uses questionnaires, surveys, health insurance claims, and clinical data it collects from hospitals, clinics, doctors’ offices, pharmacies, and laboratories. There is no shortage of available data. The difficulty today for healthcare providers and plans, which have been among the earliest adopters of big data, is to avoid being overwhelmed by its increasing volume. The amount of electronic data grows by almost 50 percent annually, and now stands at more than 2,000 exabytes (for comparison, one exabyte is one billion gigabytes).
Although it may seem a daunting challenge to gather and analyze it all, providers and health plans should welcome the growth of what was a sea of data into an ocean of it: because the more data it absorbs, the better artificial intelligence software is at identifying trends and patterns and drawing conclusions from them. This is where advanced deep learning technologies like those integrated into Reveleer for Quality Improvement offer compelling advantages:
- Capture maximum data by automatically retrieving as many relevant EHRs as possible.
- Use natural language processing to accelerate quality reviews and gap closures. Couple this with automated provider outreach to resolve care gaps.
- Identify HEDIS gap closure opportunities down to the individual member level. Improve member care by using pattern-based analytics to improve quality initiatives, track results, and predict and avoid adverse member care outcomes.
- Improve member compliance with treatment plans that use artificial intelligence to monitor member plan adherence and assess treatment effectiveness.
The NCQA is already including artificial intelligence into HEDIS reporting requirements. Among its latest developments is accepting deep learning AI applications to read mobile retina scans for use in diabetic care. This could be the first of many more uses of mobile and other AI technology with HEDIS.
Now more than ever getting the most out of HEDIS quality scoring and benchmarking depends on how much relevant data you gather and analyze. The better you do these tasks, the more easily you can find faster and less expensive ways to close care gaps and improve member care. Having an artificial intelligence software partner like Reveleer streamlines AI integration into your current Quality Improvement programs. By doing so, it positions you to make the best use of AI in HEDIS reporting and quality scoring now and in the future.