RESUMEN
BACKGROUND: Systems that enable remote monitoring of patients' symptoms and other health-related outcomes may optimize cancer care outside of the clinic setting. CYCORE (CYberinfrastructure for COmparative effectiveness REsearch) is a software-based prototype for a user-friendly cyberinfrastructure supporting the comprehensive collection and analyses of data from multiple domains using a suite of home-based and mobile sensors. This study evaluated the feasibility of using CYCORE to address early at-home identification of dehydration risk in head and neck cancer patients undergoing radiation therapy. METHODS: Head and neck cancer patients used home-based sensors to capture weight, blood pressure, pulse, and patient-reported outcomes for two 5-day periods during radiation therapy. Data were sent to the radiation oncologist of each head and neck cancer patient, who viewed them online via a Web-based interface. Feasibility outcomes included study completion rate, acceptability and perceived usefulness of the intervention, and adherence to the monitoring protocol. We also evaluated whether sensor data could identify dehydration-related events. RESULTS: Fifty patients consented to participate, and 48 (96%) completed the study. More than 90% of patients rated their ease, self-efficacy, and satisfaction regarding use of the sensor suite as extremely favorable, with minimal concerns expressed regarding data privacy issues. Patients highly valued the ability to have immediate access to objective, self-monitoring data related to personal risk for dehydration. Clinician assessments indicated a high degree of satisfaction with the ease of using the CYCORE system and the resulting ability to monitor their patients remotely. CONCLUSION: Implementing CYCORE in a clinical oncology care setting is feasible and highly acceptable to both patients and providers.
Asunto(s)
Computadoras de Mano , Deshidratación/diagnóstico , Neoplasias de Cabeza y Cuello/radioterapia , Tecnología de Sensores Remotos/instrumentación , Tecnología de Sensores Remotos/métodos , Adulto , Anciano , Anciano de 80 o más Años , Estudios de Factibilidad , Femenino , Humanos , Internet , Masculino , Persona de Mediana Edad , Encuestas y CuestionariosRESUMEN
Improved approaches and methodologies are needed to conduct comparative effectiveness research (CER) in oncology. While cancer therapies continue to emerge at a rapid pace, the review, synthesis, and dissemination of evidence-based interventions across clinical trials lag in comparison. Rigorous and systematic testing of competing therapies has been clouded by age-old problems: poor patient adherence, inability to objectively measure the environmental influences on health, lack of knowledge about patients' lifestyle behaviors that may affect cancer's progression and recurrence, and limited ability to compile and interpret the wide range of variables that must be considered in the cancer treatment. This lack of data integration limits the potential for patients and clinicians to engage in fully informed decision-making regarding cancer prevention, treatment, and survivorship care, and the translation of research results into mainstream medical care. Particularly important, as noted in a 2009 report on CER to the President and Congress, the limited focus on health behavior-change interventions was a major hindrance in this research landscape (DHHS 2009). This paper describes an initiative to improve CER for cancer by addressing several of these limitations. The Cyberinfrastructure for Comparative Effectiveness Research (CYCORE) project, informed by the National Science Foundation's 2007 report "Cyberinfrastructure Vision for 21(st) Century Discovery" has, as its central aim, the creation of a prototype for a user-friendly, open-source cyberinfrastructure (CI) that supports acquisition, storage, visualization, analysis, and sharing of data important for cancer-related CER. Although still under development, the process of gathering requirements for CYCORE has revealed new ways in which CI design can significantly improve the collection and analysis of a wide variety of data types, and has resulted in new and important partnerships among cancer researchers engaged in advancing health-related CI.