Commentary: Moving toward more objective standards in COPD management

Health care professionals managing COPD are attempting to embrace objective standards in both clinical and research settings.

Patient self-reporting questionnaires have created a common set of criteria for assessing disease appearance and progression. Today, standardized questionnaires, which have been validated in clinical literature, have helped facilitate the development and utilization of best-practice approaches in the field of pulmonology. However, in everyday practice, important limitations of self-reporting remain, especially as more patients are treated via telehealth and other forms of remote care.

Limitations in self-reporting

First, there is a fair amount of subjectivity to the questions commonly used in questionnaires, both in phrasing and how the questions are delivered.

To illustrate, consider that a standard question set in the Clinical COPD Questionnaire (CCQ) might ask the following questions: 

• In general, how much has your COPD affected your daily functioning? 
• How often do you struggle with shortness of breath?
• How often have you encountered primary symptoms, such as coughing and wheezing?
• How many nights per week do you encounter symptoms? 

Of these four questions, the last one can be considered the most objective, as the set of criteria is fairly limited (focusing on frequency instead of characterization). However, even this question may force a patient to consider what may or may not be considered symptomatic, introducing a degree of subjectivity and complicating the self-reporting process. As a results, practitioners must often dive deep to understand the frequency and severity of a patient’s true experience of their symptoms. Even with more detailed questioning, a great deal of information can be lost through the subjective lens of self-reporting.

Memory and other cognitive factors may impact a patient’s ability to recall signs and symptoms, especially given the advanced age of the average patient with COPD. For example, the St. George’s Respiratory Questionnaire to assess COPD requires a patient to answer the question, “How many attacks of chest trouble did you have in the last year?” with answers ranging from 3 or more times, to 1 or 2 times, to none. The individual completing the questionnaire must not only decide how to interpret what could be considered a COPD attack, but also recall how many times these episodes occurred.

Beyond a patient’s ability to recall and report accurately, there are inherent limitations to rating systems that are based on a number scale. The CCQ, which is commonly used to assess COPD symptoms during a patient visit, uses a 6-point scale to determine how often an individual is having symptoms, and requires a patient to self-assess how often they are having symptoms over the past week. In order to answer each question in the CCQ, a patient must differentiate between a symptom frequency of “a few times” (2 points) and “several times” (3 points), or “many times” (4 points) and “a great many times” (5 points). As it stands, patients can struggle to effectively characterize or quantify their condition, as the manifestation and severity of symptoms can fluctuate greatly day-to-day. Add to that the disparate ways that “a few” vs. “several” might be defined between individuals, and the 6-point scale leaves quite a lot of room for interpretation.

Subjectivity, COVID-19

Additionally, it is also important to note that the degree of subjectivity can be greatly diminished or exacerbated depending on whether a patient is answering questions in the presence of a care provider. When a practitioner is present, a patient may take the opportunity to ask follow-up questions in order to better quantify or characterize their answers. In a remote environment, they are usually not afforded this opportunity, instead relying on their “best guess” or gut instinct to provide answers. However, given that many of these patients only interact with their care provider every 3 to 6 months, or possibly longer, there is a tendency to paint in very broad strokes.

Increased telemedicine utilization during the COVID-19 pandemic — especially among elderly and vulnerable populations, many of whom overlap with populations at risk for COPD — has made these specific challenges more salient. As a result, there  has been a push to adopt standardized, objective measurements for clinical and epidemiological purposes. This health care environment necessitates that practitioners consider new, augmented ways to derive empirical data free from the inherent subjective filters present in patient self-reporting.

Increasing objectivity

One way to increase the degree of objectivity in COPD reporting would be through the collection and use of biometric data in addition to self-reported symptomatic assessments. The advent of contemporary, artificial intelligence-powered solutions — which are capable of recording a patient’s breathing patterns while they sleep, using machine learning to establish baseline patterns and inform practitioners of abnormal patterns and significant deviations — may provide one such solution.

In the past, capturing patient data night-to-night wasn’t technologically feasible. Today, however, these types of solutions are becoming increasingly accessible, as well as integrated as part of broader remote care and telehealth systems.

To be sure, validated questionnaires contain valuable information about patients’ own experience of their symptoms and will continue to play a role in the delivery of care for individuals with chronic respiratory conditions. But, because the use of self-reported questionnaires will always present challenges and a degree of subjectivity, adding objective data such as symptom counts can help close common gaps and give practitioners more information critical to rendering objective, clinical judgements.

For more information:

Gloria Fann, MD, is senior medical director at Curie AI. She can be reached at gloria.fann@curieai.com.

Sridhar Nemala is co-founder and head of Curie AI. He can be reached at sridhar.nemala@curieai.com.