Employing Environmental Data and Machine Learning to Improve Mobile Health Receptivity

Behavioral intervention strategies can be enhanced by recognizing human activities using eHealth technologies. As we find after a thorough literature review, activity spotting and added insights may be used to detect daily routines inferring receptivity for mobile notifications similar to just-in-time support. Towards this end, this work develops a model, using machine learning, to analyze the motivation of digital mental health users that answer self-assessment questions in their everyday lives through an intelligent mobile application. A uniform and extensible sequence prediction model combining environmental data with everyday activities has been created and validated for proof of concept through an experiment. We find that the reported receptivity is not sequentially predictable on its own, the mean error and standard deviation are only slightly below by-chance comparison. Nevertheless, predicting the upcoming activity shows to cover about 39% of the day (up to 58% in the best case) and can be linked to user individual intervention preferences to indirectly find an opportune moment of receptivity. Therefore, we introduce an application comprising the influences of sensor data on activities and intervention thresholds, as well as allowing for preferred events on a weekly basis. As a result of combining those multiple approaches, promising avenues for innovative behavioral assessments are possible. Identifying and segmenting the appropriate set of activities is key. Consequently, deliberate and thoughtful design lays the foundation for further development within research projects by extending the activity weighting process or introducing a model reinforcement.BMBF, 13GW0157A, Verbundprojekt: Self-administered Psycho-TherApy-SystemS (SELFPASS) - Teilvorhaben: Data Analytics and Prescription for SELFPASSTU Berlin, Open-Access-Mittel - 201

Front-Line Physicians' Satisfaction with Information Systems in Hospitals

Day-to-day operations management in hospital units is difficult due to continuously varying situations, several actors involved and a vast number of information systems in use. The aim of this study was to describe front-line physicians' satisfaction with existing information systems needed to support the day-to-day operations management in hospitals. A cross-sectional survey was used and data chosen with stratified random sampling were collected in nine hospitals. Data were analyzed with descriptive and inferential statistical methods. The response rate was 65 % (n = 111). The physicians reported that information systems support their decision making to some extent, but they do not improve access to information nor are they tailored for physicians. The respondents also reported that they need to use several information systems to support decision making and that they would prefer one information system to access important information. Improved information access would better support physicians' decision making and has the potential to improve the quality of decisions and speed up the decision making process.Peer reviewe

A critical investigation of electronic patient records in the NHS in England : tracing an elusive object through its actor-network

This study is a critical investigation of electronic patient records in the National Health Service in England. It explores whether EPRs benefit clinicians in the context of a technology that has been explicitly designed to fulfil multiple purposes, both clinical and non-clinical, and is critical in its motivation to challenge their apparent sense of inevitability.Against the backdrop of a government vision of a nationally networked EPR the research takes a meso level perspective using primary data from interviews with users across multiple NHS Trusts and healthcare settings. The study uses Actor-Network Theory from the outset as both a methodological and theoretical approach with the aim to be revelatory about the interests at work in sustaining this technology and to question whether clinicians bear the costs of network-building for the EPR. This has shaped the trajectory of the research, which is as a consequence highly reflexive and in which theoretical and methodological concerns are given equal weight to investigation of EPRs.Whilst EPRs undoubtedly benefit clinicians fundamentally through improved access to patient information, benefits are constrained by material and social interests that reproduce existing relations. In particular, non-clinical agendas are strongly inscribed within EPRs, reshaping clinical work practices by defining what may and must be recorded, and shifting attention within clinical care. A performative conception of EPRs acknowledges the messy and multiple realities and enables theorisation of the technology as complicit in a reshaping of reality towards informatized healthcare. EPRs mediate a quantification of clinical practice that implies additional work for clinicians, and new regimes of control based around recording in the EPR. The study paints a complex and subtle picture of the use of EPRs by mapping its actor-network through the experiences of users and conceptualising the EPR as emerging from a messy, heterogeneous network of socio-material relations