Study Finds 25% of Seriously Ill Patients Experience Delayed or Missed Diagnosis
A new study conducted on seriously ill patients from academic medical centers across the country has revealed concerning findings about diagnostic errors. The study, which represents the largest assessment of diagnostic errors to date, discovered that nearly a quarter of the patients experienced a delayed or missed diagnosis.
The patients involved in the study had either been transferred to the intensive care unit (ICU) after being admitted or had sadly died in the hospital. Shockingly, the researchers determined that three-quarters of these diagnostic errors resulted in temporary or permanent harm. Moreover, the study identified that diagnostic errors played a significant role in approximately one in 15 deaths.
The most common errors documented in the study were related to delayed diagnoses, such as cases where a specialist was consulted too late or an alternate diagnosis was not considered early enough. Problems with ordering the correct test and interpreting the results also contributed to these delays.
If these issues with assessment and testing were eliminated, the researchers estimated that it could reduce the risk of diagnostic errors by approximately 40%.
The study’s findings have significant implications for academic medical centers, which often handle the most challenging cases. The data can be instrumental in improving patient safety by coaching physicians, enhancing communication between healthcare teams and patients, and developing more accurate diagnostic tools and techniques.
The researchers hope that this study serves as a call to action for academic medical centers, researchers, and policymakers, similar to the groundbreaking 1999 Institute of Medicine report To Err is Human that catalyzed the patient safety movement.
In addition to its immediate impact on patient safety, the study’s data can inform the development of artificial intelligence (AI) systems. AI has the potential to summarize lengthy medical records, suggest alternative diagnoses when patients fail to improve, and ensure appropriate tests are ordered.
The study involved an extensive collaboration among 29 academic medical centers participating in the Hospital Medicine ReEngineering Network, including renowned institutions such as the Mayo Clinic, Johns Hopkins Hospital, and Brigham and Women’s Hospital. However, the authors caution that the results may not apply to all acute care hospitals.
The research analyzed a pool of over 24,000 hospitalized adults who were transferred to the ICU or died in the hospital within a one-year period. Of the 2,428 cases reviewed, it was found that 23% of patients experienced a diagnostic error, with 436 of them suffering temporary or permanent harm, and 121 attributed deaths.
Improving clinician training, evaluating physician workloads, and developing more accurate diagnostic tools are critical steps to addressing diagnostic errors. AI systems could play a vital role in evaluating patients, selecting appropriate tests, and reducing delays. However, it is crucial to ensure that these models are reliable and do not introduce errors or exacerbate health disparities.
The study was supported by the U.S. Department of Health and Human Services’ Agency for Healthcare Research and Quality (AHRQ), which has been dedicated to promoting diagnostic excellence since 2019. The findings reinforce the need for a comprehensive approach to prevent and address diagnostic errors.
In conclusion, this study sheds light on the prevalence and impact of diagnostic errors among seriously ill patients. By identifying the common causes of these errors, healthcare professionals can work towards improving patient outcomes and enhancing overall healthcare delivery.
