Asthma patient self-care plans, consisting of regular home peak expiratory flow (PEF) monitoring, use of prophylactic medications and patient action plans, have become the standard of care in asthma, indorsed by the National Asthma Education and Prevention Program. However, the value of this approach has been questioned because patient non-compliance with self-care plans is common. The internet-based Home Asthma Telemonitoring (HAT) system was designed to provide continuous individualized help to asthma patients following their self-care plans, and to notify their health care providers if clinically significant events occur. The goal of the study is to evaluate whether use of HAT leads to improved clinical outcomes and better patient compliance with self-care plans. This application proposes to: (1) modify HAT to fully implement the NAEPP guidelines, and (2) evaluate the modified HAT system in a randomized controlled study. Patients using HAT will have in their home, an electronic flow meter and palmtop computer linked, by telephone, to a Web-based asthma information system. Patients will be instructed to use the system daily by first obtaining a maximum PEF measurement using the flow meter and by answering questions on the palmtop about their asthma status and messages designed to improve their compliance with self-care plans. An asthma nurse case manager will also be notified by HAT if patients do not follow their self-care plans and if clinically significant conditions occur. This will enable the nurse to contact those patients in a timely manner to reinforce self-management skills dealing with an exacerbation, and if necessary, to involve the patients' physician. A randomized clinical trial will be conducted with 240 inner-city adult asthma patients, cared for at BMC Health Clinics Network. The study will compare patients assigned to HAT or not. All subjects will receive the current standard of asthma care, recommended by NEAPP. Each subject will be followed for 12 months. Clinical outcomes will be: utilization of urgent care services, including emergency department use and hospitalization. The patient compliance with self-care plans will be assessed in terms of PEF monitor use, medication adherence, and ability to follow personal action plan. Lastly, we will evaluate the HAT impact on behavioral and cognitive components of asthma self-care, including phase of asthma self-regulation, asthma self-efficacy and knowledge.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
7R01HL065355-05
Application #
6832035
Study Section
Special Emphasis Panel (ZRG1-RPHB-2 (01))
Program Officer
Taggart, Virginia
Project Start
2000-09-01
Project End
2005-07-31
Budget Start
2003-09-01
Budget End
2005-07-31
Support Year
5
Fiscal Year
2003
Total Cost
$170,402
Indirect Cost
Name
University of Maryland Baltimore
Department
Public Health & Prev Medicine
Type
Schools of Medicine
DUNS #
188435911
City
Baltimore
State
MD
Country
United States
Zip Code
21201
Finkelstein, Joseph; Jeong, In Cheol (2017) Machine learning approaches to personalize early prediction of asthma exacerbations. Ann N Y Acad Sci 1387:153-165