Maintaining an Accurate Problem List

Maintaining an Accurate Problem List

Clinical documentation integrity (CDI) and coding professionals often joke that the problem list itself has become the biggest documentation problem.

It is intended to support care coordination, but too often devolves into an unwieldy collection of duplicative or conflicting diagnosis code titles.

The electronic health record (EHR) problem list requirement was launched during Stage 1 of the Meaningful Use program within the Health Information Technology for Economic and Clinical Health (HITECH) Act. HITECH incentivized hospitals to adopt and “meaningfully use” Certified Electronic Health Record Technology (CEHRT).

Stage 1 required hospitals to maintain an up-to-date problem list of at least one active diagnosis or an entry of “no known problems” within the EHR for greater than 80 percent of patients.

Unfortunately, the measure focused on the presence of a problem list, not content quality. Failure to include requirements regarding accuracy limited its clinical value. Without accuracy, the problem list contributes to record bloat.

Although independent licensed practitioners (ILPs) are legally accountable for establishing a patient’s diagnosis, according to the Official Guidelines for Coding and Reporting, the Centers for Medicare & Medicaid Services (CMS) did not specify who could update the problem list when establishing this requirement.

Many EHRs are designed to automatically populate the problem list by pulling diagnoses forward from prior encounters. This contributes to diagnoses that are no longer current being included on future problem lists.

The American Health Information Management Association (AHIMA) tried to fill this void by recommending that ILPs review and update the problem list with each patient encounter. They also advised hospitals to implement formal policies for problem-list maintenance. In the 2012 “Problem List Guidance in the EHR,” AHIMA cited an ASTM International standard (now withdrawn) reading that “the problem list should be amended as more precise definitions of problems become available.” This underscores the intended dynamic nature of the list.

Validating the accuracy of the problem list would have been a huge undertaking when Stage 1 was implemented in 2011, but it should be easier in today’s environment, as artificial intelligence (AI) is being widely adopted by many hospitals. So many AI tools include natural language processing (NLP) that could search for all embedded ICD-10 diagnosis code titles and group those that are similar, so they can be reviewed, validated, and condensed to the most accurate code by a human. But who should perform such a review?

If the problem list was limited to clinical terminology, it may have been reasonable to expect ILPs to maintain it, but Stage 2 of Meaningful Use mandated Systematized Nomenclature of Medicine – Clinical Terms (SNOMED CT) for problem-list entries to promote standardization. In practice, many EHRs allow providers to select diagnoses from a list of ICD-10-CM code descriptions that are then mapped to SNOMED CT. Depending on the EMR, ICD-10-CM code descriptions may also be embedded as part of the assessment and plan within provider notes, in addition to problem list.

Since physicians are generally not deeply versed in coding terminology, mixing billing-oriented language into clinical notes can lead to imprecise entries that distract from the provider’s intent, underscoring why coding or CDI expertise is increasingly necessary. Problem-list accuracy impacts care coordination, since it can be used to support a query, according to the draft of the 2026 Query Practice Brief.

A 2012 publication by Hummel, J. and Evans, P., titled “Standardizing the Problem List in the Ambulatory Electronic Health Record to Improve Patient Care,” discusses some of the challenges associated with problem lists, including the fact that “EHR nomenclature for diagnoses, symptoms, physical findings, and test abnormalities” are based on billing codes, which are often poorly aligned with clinical concepts. This article also recognized that using coding systems like SNOMED CT or ICD-10-CM to standardize diagnosis entries requires a shared understanding among clinicians of the range of diagnoses that are “considered inclusion criteria.” Providing too many diagnosis options can increase the risk of inaccurate code selection. Even with these issues, the problem list remains a prominent part of the EHR.

Although ILPs establish diagnoses, should they be responsible for accurately selecting the diagnoses that appear on the problem list? To me, it seems more like a coding function. Validating the diagnoses on the problem list involves verifying whether they are supported as “active” or “current” within the health record. Is it time to revisit the accuracy of the problem list, so it can become a relevant clinical communication tool? If so, who should manage the problem list? The lack of accuracy can be associated with a lack of ownership.

There has been less discussion about problem lists within the industry of late, and Meaningful Use was renamed as the Medicare Promoting Interoperability Program in 2018. It is now defined as a quality program “with the goal of driving quality improvement, safety, and efficiency of healthcare by promoting and prioritizing interoperability and the exchange of health care data using CEHRT.” The problem list continues to be defined as “review of the patient’s current and active diagnoses.” It is currently incorporated into the core measure of Support Electronic Referral Loops by Sending Health Information as part of the summary of care record. The summary also includes the patient’s current medication list and medication allergies.

Physicians may not be the ideal choice to manage the problem list. Most providers, including the attending, are hesitant to edit or remove diagnoses entered by other providers. Providers are also often rushed, and searching for diagnoses is one more barrier for them to complete their notes. Additionally, most EHRs do not require a resolution date for diagnoses that are inactive – or the ability to mark the diagnosis as currently active. These shortfalls contribute to problem lists full of inactive diagnoses. Because the Official Guidelines for Coding and Reporting restrict diagnosing patients to ILPs, some infer that they are the only ones who can alter the problem list.

But I could not find any such regulatory requirement. Medicare Conditions of Participation for medical records requires a system of coding and indexing medical records that allows for the timely retrieval of diagnoses and procedures to support medical care. It also requires that the medical record contains information to support the diagnoses. It does not include a specific statement about who can update problem lists within the EHR.

However, in its initial advice, AHIMA declared the following problem-list activities were “out of scope:”

  • Using it as a source for billing data or revenue management; and
  • Using as a substitute for a final diagnosis list for discharge summaries.

The Coding Clinic edition published for the third quarter of 2021 stated that “coding professionals should not assign codes based solely on diagnosis noted in the history, problem list, and/or medication list.” Their advice continues by noting that “it is the provider’s responsibility to document that the chronic condition affected care and management of the patient for that encounter.”

Health information (HI) professionals are responsible for maintaining the integrity of the health record. Many HI professionals are also certified coders. Who better than coding or CDI professionals to validate that the code descriptions chosen for problem-list entries match actual patient conditions? Should parts of abstracting and coding include a reconciliation process between the current problem list and reportable diagnoses, so only the most specific codes, supported by the health record, appear in the problem list?

Compliant management of the problem list requires updates be completed in a way that reflects the provider’s diagnostic statements, to avoid the perception that a non-provider “diagnosed” a patient. Coders would not be diagnosing the patient; rather, they would validate that the code titles selected by the provider accurately reflect the clinical scenario within the health record. This is a function that coders already perform, for the purpose of hospital billing. This approach would further align the health record and diagnoses reported on claims, which may also mitigate some denials.

The bottom line is that AHIMA does not explicitly prohibit non-ILPs from editing the problem list. In fact, AHIMA recommends that hospitals develop policies and procedures detailing authorization and training requirements for those who participate in maintenance of the problem list. In other words, hospitals can regulate access to the problem list as long as it complies with state regulations and professional scopes of practice.

The American Medical Association (AMA) stance on problem lists was shared in their 2025 publication, “Is Updating the Problem List a Physician-Only Task?” In it, they agree there is “no federal regulation” limiting responsibility for maintaining an accurate, up-to-date problem list to physicians. They recommend care team “members,” including CDI professionals, “adjust” codes to “more specific” ones, based on provider documentation.

I do not think CDI should be the “documentation police,” but if the problem list can be used as a reason to query a provider and is part of the clinical summary to support care continuity, someone needs to ensure it is accurate. Maybe it is time for HI and CDI professionals to fill this gap.

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Cheryl Ericson, RN, MS, CCDS, CDIP

Cheryl is the Senior Director of Clinical Policy and Education, Brundage Group. She is an experienced revenue cycle expert and is known internationally for her work as a CDI professional. Cheryl has helped establish industry guidance through contributions to ACDIS white papers and several AHIMA Practice Briefs in the areas of CDI, Denials, Quality, Querying and HIM Technology.

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