mHealth intervention to improve quality of life in patients with chronic diseases during the COVID-19 crisis in Paraguay: A study protocol for a randomized controlled trial.

BACKGROUND: Patients with chronic disease represent an at-risk group in the face of the COVID-19 crisis as they need to regularly monitor their lifestyle and emotional management. Coping with the illness becomes a challenge due to supply problems and lack of access to health care facilities. It is expected these limitations, along with lockdown and social distancing measures, have affected the routine disease management of these patients, being more pronounced in low- and middle-income countries with a flawed health care system. OBJECTIVES: The purpose of this study is to describe a protocol for a randomized controlled trial to test the efficacy of the Adhera® MejoraCare Digital Program, an mHealth intervention aimed at improving the quality of life of patients with chronic diseases during the COVID-19 outbreak in Paraguay. METHOD: A two-arm randomized controlled trial will be carried out, with repeated measures (baseline, 1-month, 3-month, 6-month, and 12-month) under two conditions: Adhera® MejoraCare Digital Program or waiting list. The primary outcome is a change in the quality of life on the EuroQol 5-Dimensions 3-Levels Questionnaire (EQ-5D-3L). Other secondary outcomes, as the effect on anxiety and health empowerment, will be considered. All participants must be 18 years of age or older and meet the criteria for chronic disease. A total of 96 participants will be recruited (48 per arm). CONCLUSIONS: It is expected that the Adhera® MejoraCare Digital Program will show significant improvements in quality of life and emotional distress compared to the waiting list condition. Additionally, it is hypothesized that this intervention will be positively evaluated by the participants in terms of usability and satisfaction. The findings will provide new insights into the viability and efficacy of mHealth solutions for chronic disease management in developing countries and in times of pandemic. TRIAL REGISTRATION: ClinicalTrials.gov NCT04659746.

Process mining for healthcare: Characteristics and challenges.

Process mining techniques can be used to analyse business processes using the data logged during their execution. These techniques are leveraged in a wide range of domains, including healthcare, where it focuses mainly on the analysis of diagnostic, treatment, and organisational processes. Despite the huge amount of data generated in hospitals by staff and machinery involved in healthcare processes, there is no evidence of a systematic uptake of process mining beyond targeted case studies in a research context. When developing and using process mining in healthcare, distinguishing characteristics of healthcare processes such as their variability and patient-centred focus require targeted attention. Against this background, the Process-Oriented Data Science in Healthcare Alliance has been established to propagate the research and application of techniques targeting the data-driven improvement of healthcare processes. This paper, an initiative of the alliance, presents the distinguishing characteristics of the healthcare domain that need to be considered to successfully use process mining, as well as open challenges that need to be addressed by the community in the future.