A Specific Mobile Health Application for Older HIV-Infected Patients: Usability and Patient's Satisfaction.

Background: HIV infection is an increasingly complex chronic disease associated with numerous medical, psychological, and social problems. The life expectancy of affected patients has increased considerably. Medical apps could also play a role in prevention and management of comorbid conditions in the HIV-infected population. Objectives: To determine the usefulness of an app designed specifically for HIV-infected patients aged 60 years or older and to assess changes in patient satisfaction, adherence to treatment, and quality of health care. Methods: A randomized clinical trial was conducted, including 100 patients (50 per group): (1) an experimental group comprising patients using the app + routine medical care (app group) and (2) with routine medical care (control group). The usability of the app and patient satisfaction were evaluated in the app group at week 48. Quality of life, adherence to treatment, and clinical parameters were compared between both groups at 48 weeks, as well as the number of face-to-face visits. Results: We found that 52.2% and 73.8% of patients in the app group used the app at weeks 24 and 48, respectively. Patients used the app for a mean of 23.7 (±2.84) days over the 48 weeks. The most visited screens were health counseling and medical records (24.8% and 22.2%, respectively). At week 48, 85.2% of patients thought that the app was useful and 91.4% would recommend the app to friends or relatives. The app was well valued by participants (4.79 [±0.21] of 5.00) and 64.6% thought that the app improved their health care.

Remote Health Monitoring in the Workplace for Early Detection of COVID-19 Cases during the COVID-19 Pandemic Using a Mobile Health Application: COVIDApp.

Background: COVIDApp is a platform created for management of COVID-19 in the workplace. Methods: COVIDApp was designed and implemented for the follow-up of 253 workers from seven companies in Catalonia. The assessment was based on two actions: first, the early detection and management of close contacts and potential cases of COVID-19, and second, the rapid remote activation of protocols. The main objectives of this strategy were to minimize the risk of transmission of COVID-19 infection in the work area through a new real-time communication channel and to avoid unnecessary sick leave. The parameters reported daily by workers were close contact with COVID cases and signs and/or symptoms of COVID-19. Results: Data were recorded between 1 May and 30 November 2020. A total of 765 alerts were activated by 76 workers: 127 green alarms (16.6%), 301 orange alarms (39.3%), and 337 red alarms (44.1%). Of all the red alarms activated, 274 (81.3%) were activated for symptoms potentially associated with COVID-19, and 63 (18.7%) for reporting close contact with COVID-19 cases. Only eight workers (3.1%) presented symptoms associated with COVID-19 infection. All of these workers underwent RT-PCR tests, which yielded negative results for SARS-CoV2. Three workers were considered to have had a risk contact with COVID-19 cases; only 1 (0.4%) asymptomatic worker had a positive RT-PCR test result, requiring the activation of protocols, isolation, and contact tracing. Conclusions: COVIDApp contributes to the early detection and rapid activation of protocols in the workplace, thus limiting the risk of spreading the virus and reducing the economic impact caused by COVID-19 in the productive sector. The platform shows the progression of infection in real time and can help design new strategies.

COVIDApp as an Innovative Strategy for the Management and Follow-Up of COVID-19 Cases in Long-Term Care Facilities in Catalonia: Implementation Study.

BACKGROUND: The coronavirus disease (COVID-19) pandemic has caused an unprecedented worldwide public health crisis that requires new management approaches. COVIDApp is a mobile app that was adapted for the management of institutionalized individuals in long-term care facilities. OBJECTIVE: The aim of this paper is to report the implementation of this innovative tool for the management of long-term care facility residents as a high-risk population, specifically for early identification and self-isolation of suspected cases, remote monitoring of mild cases, and real-time monitoring of the progression of the infection. METHODS: COVIDApp was implemented in 196 care centers in collaboration with 64 primary care teams. The following parameters of COVID-19 were reported daily: signs/symptoms; diagnosis by reverse transcriptase-polymerase chain reaction; absence of symptoms for ≥14 days; total deaths; and number of health care workers isolated with suspected COVID-19. The number of at-risk centers was also described. RESULTS: Data were recorded from 10,347 institutionalized individuals and up to 4000 health care workers between April 1 and 30, 2020. A rapid increase in suspected cases was seen until day 6 but decreased during the last two weeks (from 1084 to 282 cases). The number of confirmed cases increased from 419 (day 6) to 1293 (day 22) and remained stable during the last week. Of the 10,347 institutionalized individuals, 5,090 (49,2%) remained asymptomatic for ≥14 days. A total of 854/10,347 deaths (8.3%) were reported; 383 of these deaths (44.8%) were suspected/confirmed cases. The number of isolated health care workers remained high over the 30 days, while the number of suspected cases decreased during the last 2 weeks. The number of high-risk long-term care facilities decreased from 19/196 (9.5%) to 3/196 (1.5%). CONCLUSIONS: COVIDApp can help clinicians rapidly detect and remotely monitor suspected and confirmed cases of COVID-19 among institutionalized individuals, thus limiting the risk of spreading the virus. The platform shows the progression of infection in real time and can aid in designing new monitoring strategies.