Keeping the Problem List Accurate

The problem list provides structured data that can be used by Risk Adjustment tools to suspect opportunities to code diseases that are associated with the CMS HCC risk adjustment model. 

The role of the problem list in healthcare is an important one. It provides a main point for documenting elements that affect patient health such as disease, injuries and many other conditions. A typical problem list will identify the date of the event or condition and the caregivers plan to resolve the condition. This makes problem lists in healthcare an essential tool of communication throughout the care process. But despite that, in the digital system of today, a patient’s problem list can become laden with outdated and often incorrect information.     

With the ever-expanding importance of the problem list, so also increases the challenge of keeping them properly updated and accurate. When a problem list is not reviewed regularly it can fall victim to an overabundance of misinformation and redundancy. A problem list in this state is of little clinical value, which defeats its purpose altogether. If the goal of the problem list is to convey an accurate read on what problems the patient is having, routine upkeep is necessary to achieve improved patient care.        

Current EHR standards have vastly grown the role of the problem list for a variety of reasons. But, at the same time, they’ve also created challenges, mostly around the use of text notes, menu options, abbreviations, and how data is entered. If the ability to add and remove active problems within the EHR is at all arduous or challenging, therein lies the problem, and the problem list can quickly become unreliable and inaccurate.      

Strategies to Keep Problem Lists Accurate 

Plan a cleanup whereas the coding team processes the problem lists of patients seen the same month the prior year. The coding team then updates them based on the evidence present for that patient during that month’s and any subsequent visits during the prior year. All patients seen the prior year will have been evaluated as the year goes on, and their problem list will have been updated if they return during the current year. Then moving forward, only patients not seen for two or more years would need problem list review. 

Assign problem list safeguarding to certified coding professionals. Certified coders are experienced and capable of reviewing physician documentation on what conditions are being evaluated and treated. Make the process more manageable by piecing out the process of annual reviews into steps or smaller tasks.    

Utilize patient portals by letting patients review their own problem lists and give them an option to report any errors. Any additional documentation can help physicians and coders update problem lists with conditions that may not have been known because they were treated by other physicians. This also allows caregivers to address new conditions and encourages better treatment plans avoiding duplications and medication overlaps.

Problem list inaccuracies hinder clinical quality in population health management by lessening the dependability of clinical support tools such as risk adjustment software. At ForeSee Medical we use the problem list, but because we also have a robust NLP pipeline that reads all of the appropriate clinical notes we are able to offer greater perspective with regard to problem list entries. When problem list entries are associated with a date, we use a proprietary algorithm to decrease the “value” of a problem list entry for an acute disease that is probably no longer active. Our system also has the capability of looking at a list of problem list entries and combining two entries into a single suspect. For example, an entry for diabetes without complications and an entry for chronic kidney disease may be combined to meet the higher HCC risk score for diabetes with complications.

Unfortunately, problem lists are like other computer data - as they say “garbage in, garbage out”. With ForeSee Medical we use NLP technology and other algorithms to make the most sense of problem lists especially as they relate to the CMS HCC risk adjustment model.

 

Blog by: The ForeSee Medical Team