Rescue inhaler usage prediction in smart asthma management systems using joint mixed effects logistic regression model

ABSTRACT

Asthma is a very common and chronic lung disease that impacts a large portion of population and all ethnic groups. Driven by developments in sensor and mobile communication technology, novel Smart Asthma Management (SAM) systems have been recently established. In SAM systems, patients can create a detailed temporal event log regarding their key health indicators through easy access to a website or their smartphone. Thus, this detailed event log can be obtained inexpensively and aggregated for a large number of patients to form a centralized database for SAM systems. Taking advantage of the data available in SAM systems, we propose an individualized prognostic model based on the unique rescue inhaler usage profile of each individual patient. The model jointly combines two statistical models into a unified prognostic framework. The application of the proposed model to SAM is illustrated in this article and the effectiveness of the method is shown by both a numerical study and a case study that uses real-world data.

Keywords:

• Remote patient monitoring
• smart asthma management
• individualized prognosis

Acknowledgements

We would like to thank Barbara Massoudi, M.P.H., Ph.D., and Stephen Rothemich, M.D., of the BreathEasy Project and Gail Casper, R.N., Ph.D., for their valuable help with the dataset used in the case study. Support of the HealthDesign Project by the Robert Wood Johnson Foundation is gratefully acknowledged. We would also like to thank the Editor and referees for their valuable comments and suggestions that have led to improvements in this article.

Funding

Financial support for this work was provided by the National Science Foundation under grant 1343969.

Additional information

Notes on contributors

Junbo Son

Junbo Son is Ph.D. candidate in Industrial and Systems Engineering at the University of Wisconsin–Madison. He received an M.S. in Statistics (2015) at the University of Wisconsin–Madison and a B.S. in Industrial Systems and Information Engineering (2010) from the Korea University, South Korea.

Patricia Flatley Brennan

Patricia Flatley Brennan is the Lillian L. Moehlman Bascom Professor, School of Nursing and College of Engineering, University of Wisconsin–Madison, Madison, Wisconsin. She received an M.S. in Nursing from the University of Pennsylvania and a Ph.D. in Industrial Engineering from the University of Wisconsin–Madison. She developed the ComputerLink, an electronic network designed to reduce isolation and improve self-care among home care patients and directed HeartCare, a WWW-based tailored information and communication service that helped home-dwelling cardiac patients recover faster and with fewer symptoms. She directed Project HealthDesign, an RWJ-funded initiative designed to stimulate the next generation of personal health records. She also conducts external evaluations of novel HIT architectures and works to repurpose engineering methods for health care purposes. She leads the Living Environments Laboratory at the Wisconsin Institutes for Discovery. She is fellow of both the American Academy of Nursing (1991) and the American College of Medical Informatics (1993). She was elected to the Institute of Medicine in 2002 and in 2009 became an elected member of the New York Academy of Medicine.

Shiyu Zhou

Shiyu Zhou is a Professor in the Department of Industrial and Systems Engineering at the University of Wisconsin–Madison. He received his B.S. and M.S. in Mechanical Engineering from the University of Science and Technology of China in 1993 and 1996, respectively, and his master's in Industrial Engineering and Ph.D. in Mechanical Engineering from the University of Michigan in 2000. His research interests include in-process quality and productivity improvement methodologies by integrating statistics, system and control theory, and engineering knowledge. His research is sponsored by the National Science Foundation, Department of Energy, Department of Commerce, and industries. He is a recipient of a CAREER Award from the National Science Foundation and the Best Application Paper Award from IIE Transactions. He is a member of IIE, INFORMS, ASME, and SME.