| Literature DB >> 31534325 |
Ahmed M Alrajeh1,2, Yousef S Aldabayan1,2, Abdulelah M Aldhair1,3, Elisha Pickett1, Shumonta A Quaderi1, Jaber S Alqahtani1,4, Marc Lipman1, John R Hurst1.
Abstract
Introduction: Advances in technology offer various solutions that might help optimize the care provided to patients living with chronic non-communicable diseases such as chronic obstructive pulmonary disease (COPD). However, the efficacy of tele-health in COPD is still controversial. Despite this, there appears to be widespread adoption of this technology. Aim: To explore the international use of tele-heath for COPD, to assess the perceptions of clinicians employing tele-health in COPD, and to summarize the techniques that have been used by health care providers to personalize alarm limits for patients with COPD enrolled on tele-health programs.Entities:
Keywords: COPD; alarm limits; chronic obstructive pulmonary disease; home monitoring; perception; tele-health
Year: 2019 PMID: 31534325 PMCID: PMC6682175 DOI: 10.2147/COPD.S202640
Source DB: PubMed Journal: Int J Chron Obstruct Pulmon Dis ISSN: 1176-9106
Figure 1The geographical location of the respondents expressed in percentage. Other includes Serbia, Australia, Switzerland, Austria, Italy, Germany, Netherlands, Norway, Denmark, Slovenia, Malta, Ghana, Guyana, Namibia, Pakistan, Philippines, Niger, Singapore, South Africa, Sir Lanka, and Mongolia.
Figure 2Variables being monitored by tele-health providers.
The participant’s percentage of how alarm limit was set for each variable
| Variables | Arbitrary/what feels right | Local guideline | National guideline | Personalized (based on data from that patient) | Don’t know | Not applicable | Total |
|---|---|---|---|---|---|---|---|
| 6% | 2% | 53% | 34% | 4% | 0% | 47 | |
| 7% | 2% | 57% | 28% | 4% | 2% | 46 | |
| 7% | 5% | 52% | 32% | 2% | 2% | 44 | |
| 5% | 5% | 61% | 21% | 5% | 5% | 43 | |
| 12% | 3% | 49% | 29% | 2% | 5% | 41 | |
| 8% | 10% | 63% | 15% | 5% | 0% | 40 | |
| 10% | 8% | 33% | 43% | 3% | 5% | 40 | |
| 3% | 3% | 47% | 40% | 3% | 5% | 38 | |
| 5% | 5% | 43% | 32% | 5% | 8% | 37 | |
| 6% | 6% | 39% | 31% | 6% | 14% | 36 | |
| 6% | 8% | 70% | 11% | 3% | 3% | 36 | |
| 6% | 6% | 29% | 44% | 6% | 9% | 34 | |
| 9% | 3% | 38% | 27% | 3% | 21% | 34 | |
| 3% | 9% | 44% | 22% | 6% | 16% | 32 | |
| 3% | 6% | 41% | 25% | 3% | 21% | 32 | |
| 3% | 7% | 36% | 36% | 7% | 13% | 31 |
Figure 3Perceived percentage of false alarms triggered from tele-health systems.