Insights from EHR data may help physicians more effectively identify senior patients at an increased risk of falling, according to a study publishing in the Fall 2017 issue of Perspectives in Health Information Management, the online journal of the American Health Information Management Association.
The study, led by Adam Baus, PhD, explored the use of de-identified EHR data to build a decision support model that could help prevent senior patients from falling. The decision support helped improve screening for senior patients at-risk of experiencing a fall in order to administer proactive countermeasures.
The model analyzes data like height, weight, body mass index and blood pressure.
"We find that data germane to fall risk identification are routinely collected in EHRs, providing an opportunity for model building and providing the basis for development of policies and procedures to leverage informatics for fall risk screening and prevention of falls," the researchers wrote in the report, adding that "these data are not recognized as collectively pertinent to risk identification and are instead used only at the point of care in their component pieces."
Researchers added other aspects of a patient's health — vulnerability to a disease, a history of falls, hearing or vision impairments, or certain prescriptions — also contribute to their fall risk. For example, patients age 85 years and older have 2.58 times higher odds of experiencing falls compared to patients age 65 to 84 years. Additionally, female patients have 1.67 times higher odds of experiencing falls compared to male patients. Patients with rheumatoid arthritis, dementia, epilepsy and muscle weakness are also at an increased risk, the study notes.
"Increased public health efforts are needed to help foster a system-based approach to fall risk identification and prevention in primary care," the researchers wrote. "The complex healthcare needs of older adults, combined with brief office visits, result in challenges that can be addressed by enhancing the application of routinely collected data."
Source: Becker's Healthcare