Using mobile health technology to deliver decision support for self-monitoring after lung transplantation |
| |
| Affiliation: | 1. University of Michigan School of Nursing, 400 N Ingalls, Ann Arbor, MI 48109, United States;2. University of Pittsburgh School of Nursing, 3500 Victoria St., Pittsburgh, PA 15261, United States,;3. University of Pittsburgh School of Medicine, M-172 200 Meyran Ave, Pittsburgh, PA 15260, United States,;1. Columbia Center for Eating Disorders, Division of Clinical Therapeutics, New York State Psychiatric Institute, New York, New York;2. Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, New York;3. Eating and Weight Disorders Program, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York;4. Center for Adolescent Bariatric Surgery, Department of Surgery, Columbia University Medical Center, New York, New York;1. Department of Mechanical Engineering, University of Guilan, P.O. Box 3756, Rasht, Iran;2. Department of Mechanical Engineering, Lahijan Branch, Islamic Azad University, P.O. Box 1616, Lahijan, Iran;3. Department of Engineering Science, Faculty of Technology and Engineering, East of Guilan, University of Guilan, P.C. 44891-63157, Rudsar-Vajargah, Iran;1. Respiratory Medicine Department, Hanoi Medical University Hospital, Hanoi, Vietnam;2. Radiology Department, Hanoi Medical University Hospital, Hanoi, Vietnam;3. Surgery Department, Hanoi Medical University Hospital, Hanoi, Vietnam;4. Pathology Department, Hanoi Medical University Hospital, Hanoi, Vietnam;5. Visceral Surgery Department, Hanoi French Hospital, Hanoi, Vietnam;6. Respiratory Medicine Department, Hanoi French Hospital, Hanoi, Vietnam |
| |
| Abstract: | BackgroundLung transplant recipients (LTR) experience problems recognizing and reporting critical condition changes during their daily health self-monitoring. Pocket PATH®, a mobile health application, was designed to provide automatic feedback messages to LTR to guide decisions for detecting and reporting critical values of health indicators.ObjectivesTo examine the degree to which LTR followed decision support messages to report recorded critical values, and to explore predictors of appropriately following technology decision support by reporting critical values during the first year after transplantation.MethodsA cross-sectional correlational study was conducted to analyze existing data from 96 LTR who used the Pocket PATH for daily health self-monitoring. When a critical value is entered, the device automatically generated a feedback message to guide LTR about when and what to report to their transplant coordinators. Their socio-demographics and clinical characteristics were obtained before discharge. Their use of Pocket PATH for health self-monitoring during 12 months was categorized as low (≤25% of days), moderate (>25% to ≤75% of days), and high (>75% of days) use. Following technology decision support was defined by the total number of critical feedback messages appropriately handled divided by the total number of critical feedback messages generated. This variable was dichotomized by whether or not all (100%) feedback messages were appropriately followed. Binary logistic regression was used to explore predictors of appropriately following decision support.ResultsOf the 96 participants, 53 had at least 1 critical feedback message generated during 12 months. Of these 53 participants, the average message response rate was 90% and 33 (62%) followed 100% decision support. LTR who moderately used Pocket PATH (n = 23) were less likely to follow technology decision support than the high (odds ratio [OR] = 0.11, p = 0.02) and low (OR = 0.04, p = 0.02) use groups. The odds of following decision support were reduced in LTR whose income met basic needs (OR = 0.01, p = 0.01) or who had longer hospital stays (OR = 0.94, p = 0.004). A significant interaction was found between gender and past technology experience (OR = 0.21, p = 0.03), suggesting that with increased past technology experience, the odds of following decision support to report all critical values decreased in men but increased in women.ConclusionsThe majority of LTR responded appropriately to mobile technology-based decision support for reporting recorded critical values. Appropriately following technology decision support was associated with gender, income, experience with technology, length of hospital stay, and frequency of use of technology for self-monitoring. Clinicians should monitor LTR, who are at risk for poor reporting of recorded critical values, more vigilantly even when LTR are provided with mobile technology decision support. |
| |
| Keywords: | Mobile health technology Decision support Health self-monitoring Critical value reporting Patient compliance Lung transplantation |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
