Nurses' view of benefits, enablers and constraints to the use of digital health tools with patients: A cross-sectional study.

Introduction: Digital literacy helps patients to be more informed in order to make decisions about their health. Patient empowerment in the digital realm is a duty for all healthcare professionals, but nurses are the most numerous professionals in all healthcare systems worldwide. In addition, they have an important role in health education and patient follow-up. Therefore, the use of digital tools, by nurses to empower and help patients know more about their health, is crucial. Objective: This study was conducted to identify nurses' views on the benefits as well as constraints nurses encounter when using digital resources to empower and educate their patients. We sought to identify enablers that could help nurses use technology with their patients as a means to reinforce the care and advice they offer them. Methods: An online ad hoc questionnaire was answered by 848 currently employed Spanish nurses on the benefits of using digital media with their patients, as well as on the constraints and enablers during implementation. Results: The majority of the nurses considered that reliable digital information would reduce unnecessary consultations. In addition, they think that at least 50% of their patients could benefit from consulting information online. Among the constraints, nurses mainly pointed out the older age and low educational level of their patients. Younger nurses are the most likely nurses to see patient age as a problem. As for enablers, nurses pointed out the training offered to patients as well as digital tools being user-friendly for patients. Conclusions: It is crucial to work while following a lifelong learning strategy, with training from university education as well as training from healthcare institutions to reduce the digital gap that affects patients' digital empowerment.

Process Mining Dashboard in Operating Rooms: Analysis of Staff Expectations with Analytic Hierarchy Process.

The widespread adoption of real-time location systems is boosting the development of software applications to track persons and assets in hospitals. Among the vast amount of applications, real-time location systems in operating rooms have the advantage of grounding advanced data analysis techniques to improve surgical processes, such as process mining. However, such applications still find entrance barriers in the clinical context. In this paper, we aim to evaluate the preferred features of a process mining-based dashboard deployed in the operating rooms of a hospital equipped with a real-time location system. The dashboard allows to discover and enhance flows of patients based on the location data of patients undergoing an intervention. Analytic hierarchy process was applied to quantify the prioritization of the dashboard features (filtering data, enhancement, node selection, statistics, etc.), distinguishing the priorities that each of the different roles in the operating room service assigned to each feature. The staff in the operating rooms (n = 10) was classified into three groups: Technical, clinical, and managerial staff according to their responsibilities. Results showed different weights for the features in the process mining dashboard for each group, suggesting that a flexible process mining dashboard is needed to boost its potential in the management of clinical interventions in operating rooms. This paper is an extension of a communication presented in the Process-Oriented Data Science for Health Workshop in the Business Process Management Conference 2018.

Non-Invasive Blood Glucose Sensor: A Feasibility Study.

Diabetes is a chronic disease characterized by abnormal blood glucose levels which has short and long term complications. Management of diabetes relies on a regular control of blood glucose levels, commonly measured with invasive sensors, which are painful and cause patient discomfort. Scientific community is trying to develop noninvasive monitoring sensors to measure blood glucose continuously. Whereas previous work are focused on single methods and techniques, we present hereby a feasibility study of a non-invasive sensor integrating three different types of techniques: electromagnetic, acoustic speed and near infra-red spectroscopy. Our prototype is subject to different sources of bias, however, the cross-compensation of these three techniques can minimize the low performance of single-technique approaches. The results are promising and show the potential of using combined techniques for non-invasive blood glucose measurement.

Building new computational models to support health behavior change and maintenance: new opportunities in behavioral research.

Adverse and suboptimal health behaviors and habits are responsible for approximately 40 % of preventable deaths, in addition to their unfavorable effects on quality of life and economics. Our current understanding of human behavior is largely based on static "snapshots" of human behavior, rather than ongoing, dynamic feedback loops of behavior in response to ever-changing biological, social, personal, and environmental states. This paper first discusses how new technologies (i.e., mobile sensors, smartphones, ubiquitous computing, and cloud-enabled processing/computing) and emerging systems modeling techniques enable the development of new, dynamic, and empirical models of human behavior that could facilitate just-in-time adaptive, scalable interventions. The paper then describes concrete steps to the creation of robust dynamic mathematical models of behavior including: (1) establishing "gold standard" measures, (2) the creation of a behavioral ontology for shared language and understanding tools that both enable dynamic theorizing across disciplines, (3) the development of data sharing resources, and (4) facilitating improved sharing of mathematical models and tools to support rapid aggregation of the models. We conclude with the discussion of what might be incorporated into a "knowledge commons," which could help to bring together these disparate activities into a unified system and structure for organizing knowledge about behavior.