Applied Computing to Education on Noncommunicable Chronic Diseases: A Systematic Mapping Study

Digital health integration for noncommunicable diseases: Comprehensive process mapping for full-life-cycle management

AIM

To create a systematic digital health process mapping framework for full-life-cycle noncommunicable disease management grounded in key stakeholder engagement.

METHODS

A triphasic, qualitative methodology was employed to construct a process mapping framework for digital noncommunicable disease management in Shanghai, China. The first phase involved desk research to examine current guidance and practices. In the second phase, pivotal stakeholders participated in focus group discussions to identify prevalent digital touchpoints across lifetime noncommunicable disease management. In the final phase, the Delphi technique was used to refine the framework based on expert insights and obtain consensus.

RESULTS

We identified 60 digital touchpoints across five essential stages of full-life-cycle noncommunicable disease management. Most experts acknowledged the rationality and feasibility of these touchpoints.

CONCLUSIONS

This study led to the creation of a comprehensive digital health process mapping framework that encompasses the entire life cycle of noncommunicable disease management. The insights gained emphasize the importance of a systemic strategic, person-centered approach over a fragmented, purely technocentric approach. We recommend that healthcare professionals use this framework as a linchpin for efficient disease management and seamless technology incorporation in clinical practice.

Telemedicine in non-communicable chronic diseases care during the COVID-19 pandemic: exploring patients' perspectives

Purpose

This study aimed to explore challenges facing patients using Telemedicine consultations in non-communicable chronic disease clinics in primary care settings and to evaluate their satisfaction and willingness to use this service in the future.

Methods

This is an analytical cross-sectional study enrolling participants who were randomly selected from representative primary care centers in Bahrain and providing Telemedicine consultations. A semi-structured questionnaire permitted data collection using telephone interviews.

Results

A total of 251 individuals participated in the study of whom the majority were Bahraini (90.04%), and the mean age was 54.48 ± 10.78 years. Most of the participants 231 (92.03%) were satisfied with the Telemedicine consultation while only 142 (56.80%) were willing to use this service in the future. The main perceived challenges related to Teleconsultations were the lack of physical examination, inadequate time of TM consultation, fear of medical errors, and lack of privacy. The willingness to use TM consultation in the future was mainly determined by the degree of comfort to tell private information (p < 0.01) and to less extent the ease of the communication tool (p = 0.005) on multivariate analysis.

Conclusion

TM consultations could be a good complement to conventional consultation formats in the future. The sustainability of this innovative healthcare delivery tool requires addressing acceptability by users, ease of use, patient-centeredness, and technological advances to ensure privacy.

Applications of Medical Digital Technologies for Noncommunicable Diseases for Follow-Up during the COVID-19 Pandemic

BACKGROUND

Noncommunicable chronic diseases (NCDs) are multifaceted, and the health implications of the COVID-19 pandemic are far-reaching, especially for NCDs. Physical distancing and quarantine can lead to the poor management of NCDs because the visual tracking of them has been replaced with medical digital technology, that is, smartphone apps. This study aimed to explore medical digital technology applications for NCDs for follow-up during the COVID-19 pandemic.

METHODS

The participants in this study were 400 adult patients with NCDs; they were selected by systematic random sampling. A descriptive cross-sectional design was used. The study was conducted in the outpatient department of Yanbu General Hospital and primary-care health centers in Yanbu Al-Baher, Al-Madinah Al-Munawwarah, in the Kingdom of Saudi Arabia. The tools used in this study were a structured questionnaire to collect the sociodemographic characteristics of the patients and their health history, an NCD questionnaire to assess follow-up of the patients during the COVID-19 pandemic, and a medical digital technologies questionnaire to explore the medical digital technology applications.

RESULTS

The mean age of the patients was 47.32 ± 14.362 years, and 62.8% of them were female and 372 were male. Of the patients, 69.2% and 57.5% had been diagnosed with diabetes mellitus and hypertension, respectively; 52.4% were followed up monthly, and 29.75% used medical digital technology applications such as Tabeby Online to monitor their health. Furthermore, 71.75% and 75.5% of the patients used the Sehhaty and Tawakkalna medical digital applications, respectively. Overall, 38.7% of the patients were satisfied with using medical digital technology applications used for follow-up during the COVID-19 pandemic.

CONCLUSIONS

The study concluded that the services that use networks, smartphones, and medical digital technology applications on the Saudi Ministry of Health website and mobile applications to improve the quality of the health-care system, and that provide health services for noncommunicable or communicable diseases, are not effective. This is because the patients lack awareness of these services, with most of the chronic patients being elderly with lower levels of education and computer literacy.

Towards ubiquitous requirements engineering through recommendations based on context histories

The growing technological advance is causing constant business changes. The continual uncertainties in project management make requirements engineering essential to ensure the success of projects. The usual exponential increase of stakeholders throughout the project suggests the application of intelligent tools to assist requirements engineers. Therefore, this article proposes Nhatos, a computational model for ubiquitous requirements management that analyses context histories of projects to recommend reusable requirements. The scientific contribution of this study is the use of the similarity analysis of projects through their context histories to generate the requirement recommendations. The implementation of a prototype allowed to evaluate the proposal through a case study based on real scenarios from the industry. One hundred fifty-three software projects from a large bank institution generated context histories used in the recommendations. The experiment demonstrated that the model achieved more than 70% stakeholder acceptance of the recommendations.

Machine Learning and IoT Applied to Cardiovascular Diseases Identification through Heart Sounds: A Literature Review

This article presents a systematic mapping study dedicated to conduct a literature review on machine learning and IoT applied in the identification of diseases through heart sounds. This research was conducted between January 2010 and July 2021, considering IEEE Xplore, PubMed Central, ACM Digital Library, JMIR—Journal of Medical Internet Research, Springer Library, and Science Direct. The initial search resulted in 4372 papers, and after applying the inclusion and exclusion criteria, 58 papers were selected for full reading to answer the research questions. The main results are: of the 58 articles selected, 46 (79.31%) mention heart rate observation methods with wearable sensors and digital stethoscopes, and 34 (58.62%) mention care with machine learning algorithms. The analysis of the studies based on the bibliometric network generated by the VOSviewer showed in 13 studies (22.41%) a trend related to the use of intelligent services in the prediction of diagnoses related to cardiovascular disorders.

Ontology-Based Reasoning for Educational Assistance in Noncommunicable Chronic Diseases

Noncommunicable chronic diseases (NCDs) affect a large part of the population. With the emergence of COVID-19, its most severe cases impact people with NCDs, increasing the mortality rate. For this reason, it is necessary to develop personalized solutions to support healthcare considering the specific characteristics of individuals. This paper proposes an ontology to represent the knowledge of educational assistance in NCDs. The purpose of ontology is to support educational practices and systems oriented towards preventing and monitoring these diseases. The ontology is implemented under Protégé 5.5.0 in Ontology Web Language (OWL) format, and defined competency questions, SWRL rules, and SPARQL queries. The current version of ontology includes 138 classes, 31 relations, 6 semantic rules, and 575 axioms. The ontology serves as a NCDs knowledge base and supports automatic reasoning. Evaluations performed through a demo dataset demonstrated the effectiveness of the ontology. SWRL rules were used to define accurate axioms, improving the correct classification and inference of six instantiated individuals. As a scientific contribution, this study presents the first ontology for educational assistance in NCDs.

Ambient Intelligence Based on IoT for Assisting People with Alzheimer’s Disease Through Context Histories

New Internet of Things (IoT) applications are enabling the development of projects that help with monitoring people with different diseases in their daily lives. Alzheimer’s is a disease that affects neurological functions and needs support to maintain maximum independence and security of patients during this stage of life, as the cure and reversal of symptoms have not yet been discovered. The IoT-based monitoring system provides the caregivers’ support in monitoring people with Alzheimer’s disease (AD). This paper presents an ontology-based computational model that receives physiological data from external IoT applications, allowing identification of potentially dangerous behaviors for patients with AD. The main scientific contribution of this work is the specification of a model focusing on Alzheimer’s disease using the analysis of context histories and context prediction, which, considering the state of the art, is the only one that uses analysis of context histories to perform predictions. In this research, we also propose a simulator to generate activities of the daily life of patients, allowing the creation of data sets. These data sets were used to evaluate the contributions of the model and were generated according to the standardization of the ontology. The simulator generated 1026 scenarios applied to guide the predictions, which achieved average accurary of 97.44%. The experiments also allowed the learning of 20 relevant lessons on technological, medical, and methodological aspects that are recorded in this article.

A Narrative Review of the Patient Journey Through the Lens of Non-communicable Diseases in Low- and Middle-Income Countries

Low- and middle-income countries (LMICs) are challenged with a disproportionately high burden of noncommunicable diseases (NCDs) and limited healthcare resources at their disposal to tackle the NCD epidemic. Understanding the patient journey for NCDs from the patients' perspective can help healthcare systems in these settings evolve their NCD care models to address the unmet needs of patients, enhance patient participation in their management, and progress towards better outcomes and quality of life. This paper aims to provide a theoretical framework outlining common touchpoints along the patient journey for NCDs in LMICs. It further aims to review influencing factors and recommend strategies to improve patient experience, satisfaction, and disease outcomes at each touchpoint. The co-occurrence of major NCDs makes it possible to structure the patient journey for NCDs into five broad touchpoints: awareness, screening, diagnosis, treatment, and adherence, with integration of palliative care along the care continuum pathway. The patients' perspective must be considered at each touchpoint in order to inform interventions as they experience first-hand the impact of NCDs on their quality of life and physical function and participate substantially in their disease management. Collaboratively designed health communication programs, shared decision-making, use of appropriate risk assessment tools, therapeutic alliances between the patient and provider for treatment planning, self-management tools, and improved access to palliative care are some strategies to help improve the patient journeys in LMICs. Long-term management of NCDs entails substantial self-management by patients, which can be augmented by pharmacists and nurse-led interventions. The digital healthcare revolution has heralded an increase in patient engagement, support of home monitoring of patients, optimized accurate diagnosis, personalized care plans, and facilitated timely intervention. There is an opportunity to integrate digital technology into each touchpoint of the patient journey, while ensuring minimal interruption to patients' care in the face of global health emergencies.