As people and as patients, none of us is an open book. While some parts are plain to see, others hide beneath the surface – a reality closely paralleled in the electronic health record (EHR). When well-utilized, EHRs do a sound job of illuminating a patient’s condition. If previous encounters, problems, treatments, labs, etc., have been well documented, the patient record should contain a wealth of information. But when patient data is stored in various places through the EHR, and in a host of different formats and file types, how does a clinician really know if they’re looking at the full patient story?
For those who rely heavily on clinical notes, one might (or perhaps should) wonder if the data they contain are detailed enough. As for sifting through those notes for the right information, can that process be efficient or truly productive with data that is unstructured and dispersed? Alternatively, for clinicians who depend on the medical problem list for the data they need, what if a problem wasn’t documented as – or where – it was expected? If the EHR isn’t designed to flag what’s missing, the answer is likely that the provider will turn to the clinical notes, setting in motion an inefficient and time-consuming cycle of search and (maybe) discover.
The consequences of missing data at the point of care
The implications of missing data at the point of care are straightforward and potentially quite serious for the patient. Gaps in information can lead to unaddressed problems, misdiagnoses, issues with contraindicated medications, missed opportunities for follow up, and more.
Beyond the individual, insufficient patient data can have a troubling domino effect, impacting billing and reimbursement, clinician satisfaction, and a number of downstream initiatives in areas like population health, research, and clinical trials.
Those who treat the problem list as the heart of the EHR, may find it reassuring to think of it as a single source of truth for the patient. But the reality isn’t quite so simple. If problems lists are poorly maintained or inconsistently used, they can become ineffective and data quality can suffer. So, what’s undermining the problem list?
Obstacles to effective medical problem list
There are plenty of ways in which a problem list can grow ineffective:
- Problems can be miscoded, often lacking the specificity and detail required for proper reimbursement
- Lists can easily become cluttered with duplicative and outdated problems that are no longer relevant
- Problems that are relevant may not be captured in the list at all, and instead may be “lurking” in other parts of the EHR like clinical notes or previous encounter diagnoses
- Lists are often just that – lists – which means that related problems aren’t connected or categorized in a way that makes sense to the clinician
- Provider organizations may have an ill-defined (or total lack of) governance strategy establishing the rules for who manages the list including clean up and deletions
Making the case for the medical problem list
With so many potential obstacles to productive problem lists one might wonder are they even worth the effort? The short answer is yes. (Check out this on-demand webinar on the problem-oriented medical record if you’re not convinced). A well-managed and organized medical problem list means:
- More (pertinent) patient information at the point of care: This helps with clinical decision support, saves clinicians time, and eases the stress and burden of sifting through irrelevant data.
- Easier identification of hierarchical condition categories (HCCs): A clean and current problem list can clearly display persistent HCCs which means fewer oversights and greater reimbursement.
- Higher quality and more structured patient data: When documented using a robust terminology and appropriate code mapping, this data enables better patient care as well as better reimbursement.
Thinking outside of what’s ‘out of the box’
Effective problem lists don’t just happen but building them isn’t as difficult as one might think. A variety of solutions can be integrated into the EHR to help clean and organize the problem list; enable more specific documentation and coding; identify HCCs; access other relevant data like medications and labs; and leverage new(er) technologies like NLP to surface relevant problems that may be trapped in other parts of the EHR. The out-of-the-box EHR problem list is just a starting point, a foundation to be built upon by provider organizations that understand the problem list’s potential – and in many cases, help is just a click away.
