A clinical decision support system (CDSS) can help eye care practitioners diagnose dry eye disease quickly and accurately, according to a study published in Eye.
Investigators conducted a study to develop a CDSS to diagnose and determine 4 levels of dry eye severity (mild, moderate, severe, very severe) based on clinical signs, patient symptoms, examination findings, and clinical testing results. The research was divided into 2 phases. First, corneal eye specialists (n=37; 83.79% men) identified the most important diagnostic factors for determining dry eye severity through a questionnaire. Next, the research team designed a CDSS and evaluated it using patient data.
During phase 1, clinicians used a 5-point Likert scale to rate the use of specific parameters for diagnosing dry eye and determining severity (0, not important; 5, very important. The clinical team determined that filamentous keratitis, meibomian gland dysfunction (MGD), ocular surface diseases index (OSDI) score, Schirmer test results, tear meniscus height, tear breakup time (TBUT), and fluorescein staining score were the most important diagnostic parameters.
The CDSS was designed during phase 2 and 5 corneal specialists (separate from those participating in phase 1) input data from 50 patients into the system to determine diagnosis and disease severity. The system’s performance was compared with the specialists’ diagnoses from the patients’ records.
According to the report, there was a very good agreement between the system’s performance and the diagnoses provided by the specialists (K=89.7%). The system’s accuracy (96.9%), sensitivity (97.5%), and specificity (93.7%) demonstrated its ability to quickly and accurately diagnose dry eye disease.
“Given that determining severity of dry eye plays a significant role in providing care plans, it seems that the designed system can greatly assist ophthalmologists and can improve quality of care,” according to the researchers. “By providing appropriate treatment plans, the severity of the disease will be reduced, which in turn will improve quality of life for patients with dry eye.”
Study limitations include a small sample size, the use of convenience sampling to recruit corneal specialists, and failure to investigate the cost-effectiveness and efficiency of the system.
Ebrahimi F, Ayatollahi H, Aghaei H. A clinical decision support system for diagnosing and determining severity of dry eye disease. Eye (Lond). Published online August 22, 2022. doi:10.1038/s41433-022-02197-x