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Perspective
HEDIS® Success: Why Clinical Informatics Matter
Summary
Discover eight best practices that will help your organization optimally apply clinical informatics to your most difficult HEDIS-related challenges
Perspective
Genevieve Morris
Senior Director, Clinical Interoperability Strategy Change Healthcare
Robert Connely
Vice President, Business Development, Provider Networks, Clinical Networks Change Healthcare
Eric Whitley
Independent Health Informatics Consultant
Healthcare Effectiveness Data and Information Set (HEDIS) has become an essential tool for measuring healthcare delivery. But as HEDIS transitions from relying on claims data alone to leveraging both claims and clinical data, healthcare providers are facing many implementation challenges.
The good news is that those challenges are well worth the effort and resources they require. The improved capture and use of clinical data will:
- Benefit patients by supporting better care and better outcomes.
- Benefit providers by helping them elevate their internal standards of care while also driving out inefficiencies.
- Benefit payers by enhancing their ability to coordinate care and prevent care gaps.
These benefits are more important than ever as the healthcare system continues to address both COVID-19’s short-term challenges, including the prevention of avoidable rehospitalizations, and long-term impacts on patient health.
HEDIS-related challenges ultimately boil down to problems of clinical informatics.
The Challenge of Clinical Capture
In calculating quality measures—HEDIS in particular—clinical data provides significant value that claims data alone does not. Clinical data is more comprehensive and timelier than claims data, which cannot represent a full picture of the patient and is often delayed in its availability. But the use of clinical data for quality measurement is easier said than done.
Four issues often hamper the capture and use of clinical data:
- Accurate data capture and maintenance. Providers and their clinical staff are often under significant time pressure when they interact with patients, leaving little time or energy to devote to data capture tasks, including removing resolved problems from the problem list or removing a medication no longer being taken. Consequently, a clear challenge in using clinical data is ensuring the initial capture is as complete and accurate as possible and the data is accurately maintained, while creating as little “friction” as possible for front-line caregivers.
- Common interpretation of clinical data. There can be significant variation in the way individual clinicians record and interpret clinical data despite standardized code sets being used for most clinical data. A second challenge is therefore establishing the syntactic interoperability necessary to ensure that all clinical data across all providers can be interpreted and applied in common manner.
- Data fragmentation. Patient data is dispersed across multiple provider sites and EHR systems—including primary care, specialist practices, satellite clinics, labs, pharmacies, and even increasingly popular personal digital tools for managing conditions such as diabetes and hypertension. A third challenge is thus ensuring that clinical data from all these systems are properly integrated and correlated to the appropriate episode of care.
- Integration of clinical and claims data. Clinical and claims data utilize different code sets, can be at different levels of specificity, and use different patient identifiers. This variation makes the integration of the two challenging. This combination of errors and disconnects presents a fourth challenge for HEDIS implementation.
Simply put, the industry is struggling to extract the full potential value of rich clinical data.
Getting HEDIS Done
These clinical data challenges for HEDIS ultimately boil down to problems of clinical informatics. Clinical informatics, after all, specifically examines issues related to the structure, processing, interpretation, and analysis of healthcare data. So, by applying the principles of clinical informatics— including its proven best practices for vocabularies, data structures, natural language processing (NLP), quality management, and governance—providers and payers can dramatically improve their ability to properly capture, integrate, and utilize their complex portfolios of clinical and claims data.
HEDIS success can be benefited by healthcare providers bringing a clinical informaticist on board internally, engaging with a clinical informatics consultancy, or both. Clinical data management is too critical, too specialized, and evolving too rapidly for anyone other than a specialist—regardless of how adept they may be at data science generally. Only a true clinical informaticist has the expertise and hard-won in-the-field experience to bring together the digital, clinical, process, and regulatory knowledge necessary to optimize the capture and use of high-value clinical data assets across an entire institution and its ecosystem of partners.
The adoption of clinical informatics and associated technologies is not a trivial investment. But that investment consistently yields outcomes that are well worth the efforts and costs involved.
The smarter approach is to pursue a specific objective where data can deliver more value. This focused approach enables HEDIS teams to measure their progress, achieve a well-defined goal, and then use that success to gain broader support for their next objective.
HEDIS success can be benefited by healthcare providers bringing a clinical informaticist on board internally, engaging with a clinical informatics consultancy, or both. Clinical data management is too critical, too specialized, and evolving too rapidly for anyone other than a specialist—regardless of how adept they may be at data science generally. Only a true clinical informaticist has the expertise and hard-won in-the-field experience to bring together the digital, clinical, process, and regulatory knowledge necessary to optimize the capture and use of high-value clinical data assets across an entire institution and its ecosystem of partners.
These best practices include:
Focus on specific goals. It is usually fruitless and frustrating to simply chase after more data. The smarter approach is to pursue a specific objective where data can deliver more value—such as the pre- and post-operative care associated with a particular type of surgery. This focused approach enables HEDIS teams to measure their progress, achieve a well-defined goal, and then use that success to gain broader support for their next objective.
Get buy-in from leadership. Because clinical informatics is a cross-disciplinary practice, someone at the top of the organization needs to support it. Leadership support should also keep everyone focused on a specific goal that benefits your organization and your patients—rather than a boil-the-ocean undertaking that suffers from perpetual scope creep.
Create cross-disciplinary teams. Successful HEDIS initiatives should involve IT, clinical staff, legal/ regulatory specialists, and, where appropriate and useful, outside contractors. It is rarely wise to simply hope these people all somehow find each other. Instead, it is best to be diligent and intentional about bringing them all together at the start with a common goal and common vision.
Maintain a patient-centric view. When organizations view data as merely data, they can spend a lot of money and create a lot of technical complexity without actually delivering much value. So never lose sight of the fact that clinical data is descriptive of real issues in real people’s lives.
Don’t ask too much of clinicians. One sure way to derail a HEDIS initiative is to ask more of your frontline clinicians than they can reasonably give. Always try to minimize the burden put on those who are already being asked to do too much.
Don’t ask tools to solve all problems. Technology is an indispensable requirement for HEDIS success. But technology is just a tool that people use to get a job done. It is people who will ultimately solve your problem—using the best tools you can give them.
Win and iterate. By focusing on achievable goals, you can demonstrate benefits to your internal constituencies. This will help you get buy-in from clinicians, managers, and others for an assault on your next chosen incremental goal.
Make HEDIS and clinical informatics a core function, not a project with a goal. Data is a valuable asset to your organization, and it is only becoming more valuable. So just like your other assets—clinical skills, diagnostic technology, medical equipment, beds, vehicles, etc.—data requires continuous attention and optimization.
Data and the COVID-19 New Normal
With the advent of COVID-19, it has become even more urgent that the industry increase the skill with which we collect and analyze clinical data. In the short term, we have all experienced the intense scramble of figuring out how to diagnose and treat patients, how to triage limited resources, and how to respond to the impact on frazzled staff members. But the long term is full of even more unknowns, and those unknowns will only reveal themselves to us if we capture the right clinical data and diligently apply it to the emerging trends we face.
One of those trends is the post-critical care needs of patients who have been hospitalized and, in many cases, intubated. These patients have survived the worst that COVID has to offer in the short term— but we have yet to discover exactly what impact the virus will have on their health in the long term. Nevertheless, we are already seeing a number of chronic syndromes emerge that may correlate to both the severity of the initial episode and the particular variant from which the patient suffered.
By diligently capturing, aggregating, and analyzing clinical and claims data from across the postcritical COVID-19 patient’s care experience, providers should be able to quickly and accurately determine appropriate treatment regimens, while also identifying care events that will not affect patient outcomes.
Less clear at present is the long-term outlook for those who have been infected by COVID-19 but have either been asymptomatic or have only suffered relatively mild symptoms. Because these cases represent a much larger percentage of the population—and because the organic linkage between their original infection and any later chronic conditions is less immediately obvious during the course of routine care—it will be critical to apply clinical informatics to this cohort. Social determinants of health (SDoH) may also be hidden underneath the surface of these patients, whose post-COVID-19 syndromes may take years to reveal themselves.
An Urgent, Strategic Investment
HEDIS and COVID-19 are not the only forces driving adoption of clinical informatics. A new generation of intelligent medical devices is putting data at the very center of the clinical enterprise. To reap the full value offered by these devices, healthcare providers must become even more adept at capturing, aggregating, interpreting, and sharing clinical data.
In fact, the ability to adeptly capture and leverage data is not just a matter of clinical outcomes, financial expediency, or regulatory compliance. Our entire society and culture are becoming increasingly data driven. Data aptitude is, therefore, what will ultimately define every healthcare institution’s capabilities, brand, value, and role in the community it serves. This inexorable trend towards datacentricity makes the investment in clinical informatics as urgent as it is wise.
