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David C Houghton,1,2 Christina R Merritt,1,3 Sierra N Miller,1 Jasmine M Mitchell,4 David Parker,1 Jonathan D Hommel,1,3 Kathryn A Cunningham,1– 3,&ast; Denise M Wilkes1,5,&ast; 1Center for Addiction Sciences and Therapeutics, University of Texas Medical Branch, Galveston, TX, USA; 2Department of Psychiatry and Behavioral Sciences, University of Texas Medical Branch, Galveston, TX, USA; 3Department of Pharmacology and Toxicology, University of Texas Medical Branch, Galveston, TX, USA; 4Department of Family and Community Medicine, UT McGovern Medical School, Houston, TX, USA; 5Department of Anesthesiology, University of Texas Medical Branch, Galveston, TX, USA&ast;These authors contributed equally to this workCorrespondence: David C Houghton, Center for Addiction Sciences and Therapeutics, University of Texas Medical Branch, 301 University Blvd, Texas, Galveston, TX 77555, USA, Tel +1 (409)747-9785, Email dahought@utmb.eduBackground: Pain management physicians are increasingly focused on limiting prescription opioid abuse, yet existing tools for monitoring adherence have limited accuracy. Medication event monitoring system (MEMS) is an emerging technology for tracking medication usage in real-time but has not been tested in chronic pain patients on long-term opioid regimens.Objective: We conducted a pilot clinical trial to investigate the utility of MEMS for monitoring opioid adherence and compared to traditional methods including self-report diaries, urine drug screen (UDS), and physicians’ opinions.Methods: Opioid-maintained chronic pain patients were recruited from a pain management clinic. Participants (n=28) were randomly assigned to either receive MEMS bottles containing their opioid medication for a 90-day period or to continue using standard medication bottles. MEMS bottles were configured to record and timestamp all bottle openings and the number of pills that were removed from the bottle (via measurement of weight change).Results: Participants who received MEMS demonstrated highly heterogenous dosing patterns, with a substantial number of patients rapidly removing excessive amounts of medication and/or “stockpiling” medication. By comparison, physicians rated all participants as either “totally compliant” or “mostly compliant”. UDS results did not reveal any illicit drug use, but 25% of participants (n=7) tested negative for their prescribed opioid metabolite. MEMS data did not correlate with physician-rated adherence (P=0.24) and UDS results (P=0.77). MEMS data consistently revealed greater non-adherence than self-report data (P< 0.001).Conclusion: These results highlight the limits in our understanding of naturalistic patterns of daily opioid use in chronic pain patients as well as support the use of MEMS for detecting potential misuse as compared to routine adherence monitoring methods. Future research directions include the need to determine how MEMS could be used to improve patient outcomes, minimize harm, and aid in clinical decision-making.Trial Registration: This study was preregistered on ClinicalTrials.gov (NCT03752411).Keywords: medication event monitoring systems, chronic pain, medication adherence

Sarah N Miller,1 Michelle Nichols,1 Ronald J Teufel II,2 Erin P Silverman,3 Marta Walentynowicz4 1College of Nursing, Medical University of South Carolina, Charleston, South Carolina, SC, USA; 2College of Medicine, Medical University of South Carolina, Charleston, South Carolina, SC, USA; 3Division of Pulmonary, Critical Care, and Sleep Medicine, University of Florida, Gainesville, FL, USA; 4Center for the Psychology of Learning and Experimental Psychopathology, KU Leuven, Leuven, BelgiumCorrespondence: Sarah N Miller, Medical University of South Carolina, College of Nursing, 99 Jonathan Lucas Street, Charleston, SC, 29425, USA, Tel +18437921692, Email millesar@musc.eduAbstract: Dyspnea is an unpredictable and distressing symptom of chronic obstructive pulmonary disease (COPD). Dyspnea is challenging to measure due to the heterogeneity of COPD and recall bias associated with retrospective reports. Ecological Momentary Assessment (EMA) is a technique used to collect symptoms in real-time within a natural environment, useful for monitoring symptom trends and risks of exacerbation in COPD. EMA can be integrated into mobile health (mHealth) platforms for repeated data collection and used alongside physiological measures and behavioral activity monitors. The purpose of this paper is to discuss the use of mHealth and EMA for dyspnea measurement, consider clinical implications of EMA in COPD management, and identify needs for future research in this area.Keywords: COPD, ecological momentary assessment, mobile health, dyspnea, mHealth, telehealth