Data-work for personalized care: Examining nurses’ practices in remote monitoring of chronic patients

Abstract

Healthcare professionals are increasingly working with data in their care delivery practices. However, there is limited understanding of how data work is enabling novel practices. This study focuses on novel nursing practices emerging in the context of remote monitoring of chronic patients. Specifically, we analyze how personalization of care is achieved in practice through data work. The study is based on a case of a pilot center in Norway where nurses provide remote care to patients by using a specialized system. We examine the practices of the nurses and how data in the form of graphs, alerts, questionnaires and messages are used to personalize care. We identify three main practices of data work for personalization: preparatory work, continuous adjustment and question fine-tuning. Finally, we discuss the pivotal role of nurses’ data work for personalized care in remote care.

The early warning research on nursing care of stroke patients with intelligent wearable devices under COVID-19

“…It is easy to prove that there will be a part of the solution where α i is not equal to 0, and the corresponding sample is a support vector. Therefore, the optimal classification function is the following [ 22 , 23 ]: …”

Good organizational reasons for better medical records: The data work of clinical documentation integrity specialists

“…For example, birth certificate clerks in the U.S. have come under increasing pressure to improve their data entry, because birth certificate data have recently become an important source for research and data-driven accountability of obstetric practices (Pine et al, 2016). Clinicians are also tasked with performing new kinds of data work, for example, to maintain integrations between data in various information systems (Bjørnstad and Ellingsen, 2019) and to interpret patient-generated data (Grisot et al, 2019;Langstrup, 2019).…”

“…For example, since medical records are the major source of data extraction, clinicians are facing new demands for documentation in patient records to be accurate and comprehensive (Kuhn et al, 2015), so that other data workers such as medical coders can extract highquality data for usages such as data-driven accountability. Subsequently, a new line of research has begun to examine the on-the-ground work required to produce, manage, analyze, and deploy data in healthcare carried out by healthcare workers, including both clinicians and non-clinicians (Bjørnstad and Ellingsen, 2019;Bonde et al, 2019;Grisot et al, 2019;Islind et al, 2019;Pine, 2019).…”

Data work in healthcare: An Introduction

“…While data infrastructures are built to enable monitoring of populations and early prevention measures, 20 and to monitor the quality of services, 21,22 healthcare workers increasingly learn to maneuver playfully within these environments. 23 Thus, the papers collected here discuss the data work of different groups: doctors struggling to clarify data ambiguity and use predictive algorithms for personalized medicine; 24 coming to terms with data variability-varying data on the same phenomena; 25 clinicians' response to patients' increasing data literacy; 26 nurses' interpretation of patient-generated data as a means of inclusion in their own care; 27,28 and patients generating data about their health. 29,30 Finally, there is work to produce data itself, including skillfully assessing messy charts to create structured datasets, 22 to sanitizing and validating data, 31 and building data integrations between various information systems.…”