A tool implemented into the EHR can be utilized to address the issue of missed or late diagnoses of dementia and can flag the patient record for a future follow up, according to a study published in the Journal of the American Geriatrics Society.
One of the top concerns of America’s aging population is the misdiagnosis or under-recognition of dementia.
Using this tool, clinicians can give patients an early diagnosis of dementia, which would allow for earlier, timelier patient care. However, roughly half of the patients with dementia are left undiagnosed.
So far, little work has been done to translate findings from models of future risk of dementia into EHR systems that could be used in primary care settings to detect undiagnosed cases.
Researchers from University of California, San Francisco; the University of Washington, Seattle; and the Kaiser Permanente Washington (KPWA) Health Research Institute, conducted a study on patients age 65 and older at Kaiser Permanente Washington health system to examine the impact and accuracy of the EHR-based tool.
Researchers selected 31 markers that were observed in the EHR linked to a higher likelihood of dementia. The tool, called the EHR Risk of Alzheimer’s and Dementia Assessment Rule (eRADAR), used the markers to identify patients who may have been under or misdiagnosed.
The 31 markers are highlighted by demographic data and dementia-related symptoms. The markers are based on age, sex, psychosis, use of antidepressant prescriptions, emergency department visits, and health conditions such as cerebrovascular disease and diabetes.
Researchers sifted through the EHRs of the individuals who had been classified as having no dementia, recognized dementia, or unrecognized dementia during their study visit.
To diagnose patients with dementia, providers would have noted individuals to have memory complaints, prescribed dementia medication within the last two years, or given a positive dementia diagnosis.
Of the 4,330 patients and 16,665 visits observed, 1,015 visits resulted in a positive dementia diagnosis. Out of those positive diagnoses, 49 percent were not previously diagnosed with dementia in their EHRs.
The study showed that those who had eRADAR scores in the top 5 percent were more than 5 times more likely than the rest of the patients to have undiagnosed dementia. Due to that result, researchers said it would be vital to screen patients with high eRADAR scores.
Researchers then analyzed the 31 markers to identify the important predictors of undiagnosed dementia. Those predictors helped develop the eRADAR model, which provides a score that increases with the likelihood that an individual has dementia.
Patients in this study undergo cognitive screening every two years and are seen at Kaiser health system. This makes it easier for researchers to identify the average number of patients whose dementia goes misdiagnosed or undiagnosed in the average health system, which shows the importance of the EHR tool by targeting the most at-risk patients.
Researchers said the study needs additional research due to its limitations, such as the patients being primarily Caucasian, well-educated, and English-speaking from one health system. They also suggest that more information and research is needed on the eRADAR model to determine the accuracy and impact it would have on other health systems.
This study showed that the eRADAR tool could accurately identify patients who should be screened for dementia. Not only does it detect an earlier diagnosis but that early diagnosis can allow for quicker patient care, which then allows for better financial and long-term care planning.
The researchers also noted that earlier diagnosis could begin a trend of more evidence-based care tools, triggering better symptom management for patients.