The Problem with Problem Lists—and How EHR Functionality Can Help Fix Them

May 3, 2021
Andrew S. Kanter, M.D., M.P.H.

Andrew S. Kanter, M.D. M.P.H., is the chief medical officer, Intelligent Medical Objects.

The problem list is meant to present clinicians with a quick snapshot of the patient’s active diagnoses and key health issues. However, most problem lists do not live up to their potential.

The electronic health record (EHR) is a mainstay of the medical encounter. Originally developed out of practice management systems to capture billing codes for insurance reimbursement, the EHR is now the go-to source for viewing a patient’s medical history, documenting the details of an appointment, and creating summaries to share with other members of the care team.

Clinical staff members typically expect to find the most important information in the EHR’s problem list, which includes a patient’s current medical conditions, relevant past medical history as well as any non-clinical factors impacting overall health. Ideally, the problem list would be presented as a clean summary that can be reviewed quickly, helping a nurse or physician focus their care, and allow for more face time with a patient during a visit.

All too often, though, the list is not only disorganized and outdated, but it is also disconnected from other parts of the patient’s chart which document the problems’ relevant details. This means clinicians spend valuable time searching for information within the record or documenting something that’s already on the problem list but buried from view.

Today’s EHR systems are making it easier to manage problem lists, but the industry still has a way to go before the problem list can truly live up to its potential, reducing clinician burden while ensuring comprehensive and appropriate care for the patient.

A Powerful Tool With Unrealized Potential

Lawrence Weed, MD, pioneered the concept of the problem list in the 1960s. Weed developed what he called the problem-oriented medical record, which consisted of a database of records such as X-rays and lab results, a list of defined medical problems, and plans and progress notes for each item in the problem list. Weed’s goal was to clearly define a patient’s medical problems based on supporting data and track what a clinical team was trying to do to solve those problems.

Decades later, maintaining an up-to-date problem list of current and active diagnoses was a core requirement for the meaningful use of EHR systems under the Health Information Technology for Economic and Clinical Health (HITECH) Act.

The American Health Information Management Association (AHIMA) indicates in its Problem List Guidance in the EHR that a problem list incorporated into the EHR “offers a powerful tool for clinical decision-making and quality improvement initiatives.”

However, AHIMA adds, a lack of structure can lead to an increase in clinical or administrative errors, which only makes it more difficult to maintain an accurate, up-to-date, and reliable problem list. This forces clinical staff to search for information when they should be providing patient care, limits the value of the problem list as a clinical decision-support tool, and increases the time spent documenting (often after hours). None of these effects support Weed’s initial vision for the problem list.

Challenges With Problem List Create Clutter, Physician Burnout

Some of the challenges associated with the problem list surround policy issues. AHIMA notes that organizations should convene key stakeholders to develop a range of problem list policies and assign accountability for problem list tasks. These include the scope of the problem list, who has the authority to update a list and resolve problems, what is the proper workflow for developing the list, and who maintains the sets of terms used to code the problem list within the EHR.

To date, there are no industry-wide standards or best practices for setting and implementing problem list policies. This has led to substantial gaps in how institutions use problem lists. In a 2015 paper in the International Journal of Medical Informatics, researchers evaluated how 10 health systems in three countries documented diabetes in a problem list for patients with a known hemoglobin A1C level above 7.0%. More than 20% of all problem lists for these patients excluded any term for “diabetes,” and at the institutions with the poorest performance, nearly 40% of problem lists were missing the term.

Without standards-based, intuitive workflows for creating and updating problem lists, two challenges immediately arise.

  • Lists become cluttered. More than 40% of medication errors can be traced to inadequate reconciliation in handoffs during admission, transfer or discharge. Once an error occurs, it is likely to remain on the problem list if there are not good oversight and governance policies. This clutter can make the problem list an unreliable tool for clinical decision support or analytics.
  • Organizing the problem list is time-consuming. Removing the clutter requires identifying duplicate problems, resolving inactive problems, and reconciling diagnoses supplied by ancillary providers or patients themselves. Attending physicians with limited time during an appointment may skip this step, and this further contributes to physician burden.

These problems with the problem list mean that clinical staff spend more time searching for data in EHR systems and less time caring for patients. This has a clear, measureable impact on job satisfaction. According to one 2019 paper in the Journal of the American Medical Association, 40% of clinicians attribute their burnout to EHR use. A second JAMA paper, also from 2019, found that 64% of clinicians say the EHR adds frustration to their day, while 70% report stress related to the use of health information technology in general.

Better Input Leads to Informed Decision-Making

Despite these challenges, EHRs are necessary for care delivery. Together, they are capable of storing petabytes of patient data to provide a complete view of patient care and inform evidence-based clinical decisions. As with any software, though, garbage in is garbage out. If the input side of the EHR remains a challenge, then the EHR cannot do a good job with the output functions of clinical care delivery such as ordering tests, writing prescriptions, making referrals, and adjusting care plans.

Enabling clinicians to make better sense of all the data aggregated in the EHR means improving the way that data is initially captured, organized and then displayed. When it comes to the problem list, there are a three key places to start.

  1. Let clinicians document in their own language, capturing the details important to their care of the patient. Instead of forcing clinicians to think like medical coders, organizations can leverage clinical interface technology software that allows users to capture diagnoses in medical terms with the correct level of clinical specificity, and then apply the required coding behind the scenes.
  2. Create flexible problem list displays. Since not all users need to see the same information, customizable displays enable specialists to primarily see the problems that matter to them. A significant amount of cognitive burden on clinicians can be removed by organizing the patient’s problems by specialty or relevant system. This allows similar problems to be viewed together, quickly identifying duplicate or conflicting entries and ensuring that key problems are not overlooked. This saves data-entry time and also reduces the risk of inaccurate coding, which further cuts down on denied claims and delayed reimbursements.
  3. Link the problem list to the rest of the chart. EHRs are filled with data scattered throughout many different sections of the chart. The less that clinicians have to jump around while evaluating the patient, executing a care plan or documenting a visit, the more likely they are to provide better care, catch errors and omissions and more accurately document. This also leads to downstream improvements to problem list accuracy and overall data integrity within the EHR.

The problem list was initially developed to give clinicians a quick summary of a patient’s medical history. As part of today’s EHR systems, the problem list has the potential to support clinical decision-making – but the lack of good problem list management tools has made many problem lists out-of-date and inaccurate.

Fortunately, there are solutions. A variety of tools are available that can speed improvements in EHR functionality, either via traditional EHR development or through SMART onFHIR add-on components. These have the potential to reduce clinician burden while improving clinical workflows, data input, and problem list management. These tools enable the creation and maintence of reliable problem lists, which benefit not just clinicians at the point of care but users throughout the organization developing care plans, analyzing data, processing claims, and monitoring care quality. A little bit of investment in solving the problems with problem lists can go a long way.

Author Information

Andrew S. Kanter, M.D. M.P.H., is the chief medical officer, Intelligent Medical Objects. IMO delivers intelligent solutions that allow clinicians to capture their clinical intent at the point-of-care which is vitally important to ensure that crucial data is not lost. Dr. Kanter provides thought leadership on IMO’s clinical roadmap and helps guide the company in addressing key challenges within the industry. He is an assistant professor of Clinical Biomedical Informatics and Clinical Epidemiology at Columbia University and has served as the former director of Health Information Systems/Medical Informatics for the Millennium Villages Project at the Earth Institute. He is a Fellow of the American College of Medical Informatics and the American Medical Informatics Association.