Abstract
BACKGROUND: Researching medical information is the third most popular activity online, and there are a variety of web-based symptom checker programs available. PURPOSE: This study evaluated a patient's ability to self-diagnose their knee pain from a list of possible diagnoses supplied by an accurate symptom checker. STUDY DESIGN: Cohort study (diagnosis); Level of evidence, 2. METHODS: All patients older than 18 years who presented to the office of 7 different fellowship-trained sports medicine surgeons over an 8-month period with a complaint of knee pain were asked to participate. A web-based symptom checker for knee pain was used; the program has a reported accuracy of 89%. The symptom checker generates a list of potential diagnoses after patients enter symptoms and links each diagnosis to informative content. After exploring the informative content, patients selected all diagnoses they felt could explain their symptoms. Each patient was later examined by a physician who was blinded to the differential generated by the program as well as the patient-selected diagnoses. A blinded third party compared the diagnoses generated by the program with those selected by the patient as well as the diagnoses determined by the physician. The level of matching between the patient-selected diagnoses and the physician's diagnoses determined the patient's ability to correctly diagnose their knee pain. RESULTS: There were 163 male and 165 female patients, with a mean age of 48 years (range, 18-76 years). The program generated a mean 6.6 diagnoses (range, 2-15) per patient. Each patient had a mean 1.7 physician diagnoses (range, 1-4). Patients selected a mean 2 diagnoses (range, 1-9). The patient-selected diagnosis matched the physician's diagnosis 58% of the time. CONCLUSION: With the aid of an accurate symptom checker, patients were able to correctly identify the cause of their knee pain 58% of the time.