Prevalence of COPD Diagnosis in Hospitalized Adults

Abstract

Background: COPD has been extensively studied to be underrecognized in patients and most recently has been demonstrated to be over diagnosed in some populations. COPD should be considered in anyone with dyspnea, chronic cough, sputum production and/or a history of risk factors, such as smoking. Spirometry demonstration of persistent airflow limitation continues to be required for an objective diagnosis of COPD. Misdiagnosis of COPD for a patient can lead to unnecessary financial strain and higher morbidity when not addressing the true driver of symptoms. We aimed to evaluate the prevalence of misdiagnosis of COPD in hospitalized patients.

Methods: Three clinicians retrospectively reviewed a sample of 96 patient charts who were hospitalized at a university medical center in 2019. The patient population was identified as having one or more hospitalizations for any cause in 2019, a primary care patient in the health system, and carried a diagnosis of COPD in their electronic medical record (EMR). The reviewers were part of a QI population health initiative, aimed at identifying barriers and needs of patients with COPD. Exemption was obtained through the University of California, Davis IRB #1759094-1.

Results: Of the 96 total charts with COPD, 19 patients (20%) with a history of COPD in their EMR had negative objective data confirming COPD. These patients demonstrated no obstruction on spirometry or FEV₁/FVC > LLN post bronchodilator per GOLD guidelines.

Conclusions: Differentials should be considered in patients with dyspnea and a diagnosis of COPD must be challenged. Signs and symptoms, risk history, and confirmation of obstruction on spirometry must be confirmed. Misdiagnosis is a potential source of health care waste, defined as overtreatment or low-value care by subjecting patients to care that is engrained in outdated habits and ignoring science. Misdiagnosis of COPD provide aimed goals for health system interventions, including workflows for necessary removal of mislabeling in EMR and appropriate identification of symptom causes.