Background: Patient reported pain is subjective, requiring individuals to grade the feeling of pain as “high” or “low”, typically using a numeric scale. As a supplement to self-reported pain, monitoring the dosage and type of treatment needed to keep pain at a tolerable or comfortable level has been suggested. However, differences in treatments can complicate the ability to compare analgesic effects. One approach to this problem uses a 30 mg oral dose of morphine as a standard to quantify the relative analgesic strength of different pain medications. Methods: For use in clinical research, we developed an application on a handheld device for logging opioid consumption and supporting automated determination of oral morphine equivalents (OME) for commonly prescribed analgesics. We reviewed the literature to prepare a comprehensive database of OMEs for more than 450 commonly prescribed pain medications. From treatment logs (time, dose, and route of administration), the application determines a daily “OME Score” in standardized units of mg of oral morphine. Results: As prescriptions change, the daily OME Score gives a comparable measure to track the utilization of diverse analgesic medications. OME Scores can be categorized using the Analgesic Quantification Algorithm (AQA scale) developed by Chung (1). The AQA scale has eight categories and provides 5 gradations for patients in advanced pain who receive strong opioids, each gradation reflecting adoubling in the daily OME Score. The impact of a therapy on pain may be considered clinically significant depending on the changes in self-reported pain and AQA scores related to the treatment. Conclusions: We have developed a method and associated application for easily logging the time, dose, and route of administration of analgesic treatments. This information can be used to compute the daily OME Score for a wide variety of analgesics. The daily OME score can then be tracked and used to report the AQA score alongside self-reported pain for evaluating pain relief in clinical studies. Reference: 1) Chung KC, Barlev A, Braun AH, Qian Y, Zagari M. Pain Medicine 2014; 15:225-232.