Abstract
Background Health information technology (HIT) can improve the screening and delivery of care to patients with chronic illnesses. To date there are no published data describing the use of HIT for screening patients with obstructive sleep apnea (OSA), a prevalent under-diagnosed chronic condition representing a substantial and growing socio-economic burden. Geisinger Clinic is a physician-led, multi-specialty group practice in rural Central Pennsylvania with integrated electronic medical records.
Aim We sought to determine whether HIT could be used to identify OSA amongst patients at risk for the disease through the use of a simple questionnaire and a physician approved referral protocol.
Methods Using an internet-based portal through which patients can review their Electronic Health Record (EHR), schedule appointments, and receive communication, patients with a body mass index (BMI) >40 and without a diagnosis or prior evaluation for sleep apnea were invited to complete the “STOP” questionnaire, a self-administered validated screening tool consisting of 4 “yes/no” questions; “yes” answers to 2 questions identify individuals at high risk of having OSA. Patients who screened positive were then contacted to schedule a sleep medicine evaluation.
Results Electronic invitations were sent to 2,283 eligible patients to take the questionnaire; 279 (12%) completed and submitted their responses. Based on their answers, 122/279 (44%) were identified as being at high risk for having OSA and recommended to undergo evaluation in the sleep clinic. To date, 104/122 patients (85%) were offered an appointment with a sleep specialist; the remaining 18 (15%) are waiting scheduling. Of those offered a clinic appointment, 41/104 (40%) have undergone a sleep medicine evaluation, 38/104 (36%) are waiting to be scheduled, and 25/104 (24%) cancelled or did not keep their appointment. Of the evaluated patients, 38/41 (93%) were diagnosed with OSA, 2/41(5%) had negative sleep studies, and 1/41(2%) are awaiting polysomnographic evaluation. The positive predictive value of the STOP questionnaire among patients who underwent polysomnography was 95%.
Conclusions This pilot study suggests that utilizing an internet-based patient portal via the EHR can identify patients at high risk of OSA and facilitate their ultimate evaluation and diagnosis through the administration of a simple questionnaire.
