Mapping the Evidence on the Impact of mHealth Interventions on Patient-Reported Outcomes in Patients With Breast Cancer: A Systematic Review.

PURPOSE: To comprehensively synthesize the existing evidence concerning mHealth interventions for patients with breast cancer (BC). DESIGN: On July 30, 2023, we searched PubMed, PsycINFO, and Google Scholar for articles using the following inclusion criteria: evaluation of mHealth interventions in patients with cancer, at least 30 participants with BC, randomized control trials or prospective pre-post studies, determinants of health (patient-reported outcomes [PROs] and quality of life [QoL]) as primary outcomes, interventions lasting at least 8 weeks, publication after January 2015. Publications were excluded if they evaluated telehealth or used web-based software for desktop devices only. The quality of the included studies was analyzed with the Cochrane Collaboration Risk of Bias Tool and the Methodological Index for Non-Randomized Studies. RESULTS: We included 30 studies (20 focused on BC), encompassing 5,691 patients with cancer (median 113, IQR, 135.5). Among these, 3,606 had BC (median 99, IQR, 75). All studies contained multiple interventions, including physical activity, tailored information for self-management of the disease, and symptom tracker. Interventions showed better results on self-efficacy (3/3), QoL (10/14), and physical activity (5/7). Lifestyle programs (3/3), expert consulting (4/4), and tailored information (10/11) yielded the best results. Apps with interactive support had a higher rate of positive findings, while interventions targeted to survivors showed worse results. mHealth tools were not available to the public in most of the studies (17/30). CONCLUSION: mHealth interventions yielded heterogeneous results on different outcomes. Identifying lack of evidence on clinical scenarios (eg, patients undergoing systemic therapy other than chemotherapy) could aid in refining strategic planning for forthcoming research endeavors within this field.

Brecha digital en cuidadores de pacientes pediátricos de 0 a 12 años. Diseño y validación de un cuestionario / The digital divide among caregivers of pediatric patients aged 0 to 12 years. Design and validation of a questionnaire

Introducción. Las estrategias sanitarias basadas en tecnologías de la información y la comunicación (TIC) podrían perpetuar la inequidad en salud, especialmente en poblaciones vulnerables. Existen escasas herramientas validadas para evaluar el acceso a las TIC en pediatría en nuestro medio. Objetivos. Construir y validar un cuestionario para evaluar el acceso a las TIC para cuidadores de pacientes pediátricos. Describir las características de acceso a las TIC y evaluar si existe correlación entre los tres niveles de la brecha digital. Población y métodos. Construimos y validamos un cuestionario que luego administramos a cuidadores de niños entre 0 y 12 años. Las variables de resultado fueron las preguntas del cuestionario para los tres niveles de brecha digital. Además, evaluamos variables sociodemográficas. Resultados. Administramos el cuestionario a 344 cuidadores. El 93 % poseía celular propio y el 98,3 % utilizaba internet por red de datos. El 99,1 % se comunicaba a través de mensajes de WhatsApp. El 28 % había realizado una teleconsulta. La correlación entre las preguntas fue nula o baja. Conclusión. Por medio del cuestionario validado, evaluamos que los cuidadores de pacientes pediátricos de 0 a 12 años poseen en su mayoría celular, se conectan por red de datos, se comunican principalmente a través de WhatsApp y obtienen pocos beneficios a través de TIC. La correlación entre los diferentes componentes del acceso a las TIC fue baja.

Introduction. Health care strategies based on information and communication technologies (ICTs) may perpetuate health inequity, especially among vulnerable populations. In our setting, there are few validated tools to assess access to ICTs in pediatrics. Objectives. To develop and validate a questionnaire to assess ICT access among caregivers of pediatric patients. To describe the characteristics of ICT access and assess whether there is a correlation among the three levels of the digital divide. Population and methods. We developed and validated a questionnaire and then administered it to the caregivers of children aged 0­12 years. The outcome variables were the questions in the three levels of the digital divide. We also assessed sociodemographic variables. Results. We administered the questionnaire to 344 caregivers. Among them, 93% had their own cell phone and 98.3% had Internet access via a data network; 99.1% communicated via WhatsApp messages; 28% had had a teleconsultation. The correlation among the questions was null or low. Conclusion. The validated questionnaire allowed us to establish that the caregivers of pediatric patients aged 0­12 years mostly own a mobile phone, access the Internet via a data network, communicate mainly through WhatsApp, and obtain few benefits through ICTs. The correlation among the different components of ICT access was low.

Evaluation of OMOP CDM, i2b2 and ICGC ARGO for supporting data harmonization in a breast cancer use case of a multicentric European AI project.

OBJECTIVE: Observational research in cancer poses great challenges regarding adequate data sharing and consolidation based on a homogeneous data semantic base. Common Data Models (CDMs) can help consolidate health data repositories from different institutions minimizing loss of meaning by organizing data into a standard structure. This study aims to evaluate the performance of the Observational Medical Outcomes Partnership (OMOP) CDM, Informatics for Integrating Biology & the Bedside (i2b2) and International Cancer Genome Consortium, Accelerating Research in Genomic Oncology (ICGC ARGO) for representing non-imaging data in a breast cancer use case of EuCanImage. METHODS: We used ontologies to represent metamodels of OMOP, i2b2, and ICGC ARGO and variables used in a cancer use case of a European AI project. We selected four evaluation criteria for the CDMs adapted from previous research: content coverage, simplicity, integration, implementability. RESULTS: i2b2 and OMOP exhibited higher element completeness (100% each) than ICGC ARGO (58.1%), while the three achieved 100% domain completeness. ICGC ARGO normalizes only one of our variables with a standard terminology, while i2b2 and OMOP use standardized vocabularies for all of them. In terms of simplicity, ICGC ARGO and i2b2 proved to be simpler both in terms of ontological model (276 and 175 elements, respectively) and in the queries (7 and 20 lines of code, respectively), while OMOP required a much more complex ontological model (615 elements) and queries similar to those of i2b2 (20 lines). Regarding implementability, OMOP had the highest number of mentions in articles in PubMed (130) and Google Scholar (1,810), ICGC ARGO had the highest number of updates to the CDM since 2020 (4), and i2b2 is the model with more tools specifically developed for the CDM (26). CONCLUSION: ICGC ARGO proved to be rigid and very limited in the representation of oncologic concepts, while i2b2 and OMOP showed a very good performance. i2b2's lack of a common dictionary hinders its scalability, requiring sites that will share data to explicitly define a conceptual framework, and suggesting that OMOP and its Oncology extension could be the more suitable choice. Future research employing these CDMs with actual datasets is needed.

mHealth Technology as a Help Tool during Breast Cancer Treatment: A Content Focus Group.

PURPOSE: To assess the usability and preferences of the contents of mHealth software developed for breast cancer patients as a tool to obtain patient-reported outcomes (PROMs), improve the patient's knowledge about the disease and its side effects, increase adherence to treatment, and facilitate communication with the doctor. INTERVENTION: an mHealth tool called the Xemio app provides side effect tracking, social calendars, and a personalized and trusted disease information platform to deliver evidence-based advice and education for breast cancer patients. METHOD: A qualitative research study using semi-structured focus groups was conducted and evaluated. This involved a group interview and a cognitive walking test using Android devices, with the participation of breast cancer survivors. RESULTS: The ability to track side effects and the availability of reliable content were the main benefits of using the application. The ease of use and the method of interaction were the primary concerns; however, all participants agreed that the application would be beneficial to users. Finally, participants expressed their expectations of being informed by their healthcare providers about the launch of the Xemio app. CONCLUSION: Participants perceived the need for reliable health information and its benefits through an mHealth app. Therefore, applications for breast cancer patients must be designed with accessibility as a key consideration.

Successful Integration of EN/ISO 13606-Standardized Extracts From a Patient Mobile App Into an Electronic Health Record: Description of a Methodology.

BACKGROUND: There is an increasing need to integrate patient-generated health data (PGHD) into health information systems (HISs). The use of health information standards based on the dual model allows the achievement of semantic interoperability among systems. Although there is evidence in the use of the Substitutable Medical Applications and Reusable Technologies on Fast Healthcare Interoperability Resources (SMART on FHIR) framework for standardized communication between mobile apps and electronic health records (EHRs), the use of European Norm/International Organization for Standardization (EN/ISO) 13606 has not been explored yet, despite some advantages over FHIR in terms of modeling and formalization of clinical knowledge, as well as flexibility in the creation of new concepts. OBJECTIVE: This study aims to design and implement a methodology based on the dual-model paradigm to communicate clinical information between a patient mobile app (Xemio Research) and an institutional ontology-based clinical repository (OntoCR) without loss of meaning. METHODS: This paper is framed within Artificial intelligence Supporting CAncer Patients across Europe (ASCAPE), a project that aims to use artificial intelligence (AI)/machine learning (ML) mechanisms to support cancer patients' health status and quality of life (QoL). First, the variables "side effect" and "daily steps" were defined and represented with EN/ISO 13606 archetypes. Next, ontologies that model archetyped concepts and map them to the standard were created and uploaded to OntoCR, where they were ready to receive instantiated patient data. Xemio Research used a conversion module in the ASCAPE Local Edge to transform data entered into the app to create EN/ISO 13606 extracts, which were sent to an Application Programming Interface (API) in OntoCR that maps each element in the normalized XML files to its corresponding location in the ontology. This way, instantiated data of patients are stored in the clinical repository. RESULTS: Between December 22, 2020, and April 4, 2022, 1100 extracts of 47 patients were successfully communicated (234/1100, 21.3%, extracts of side effects and 866/1100, 78.7%, extracts of daily activity). Furthermore, the creation of EN/ISO 13606-standardized archetypes allows the reuse of clinical information regarding daily activity and side effects, while with the creation of ontologies, we extended the knowledge representation of our clinical repository. CONCLUSIONS: Health information interoperability is one of the requirements for continuity of health care. The dual model allows the separation of knowledge and information in HISs. EN/ISO 13606 was chosen for this project because of the operational mechanisms it offers for data exchange, as well as its flexibility for modeling knowledge and creating new concepts. To the best of our knowledge, this is the first experience reported in the literature of effective communication of EN/ISO 13606 EHR extracts between a patient mobile app and an institutional clinical repository using a scalable standard-agnostic methodology that can be applied to other projects, data sources, and institutions.