The Future of Health Care: Protocol for Measuring the Potential of Task Automation Grounded in the National Health Service Primary Care System

This project utilizes a multimethod research design comprising two phases: a qualitative observational phase and a quantitative data analysis phase; each phase addresses one of the two project aims. Our first aim is to address the lack of task data by collecting high-quality, detailed task-specific data from UK primary health care practices. This phase employs ethnography, observation, interviews, document collection, and focus groups. The second aim is to propose a formal machine learning approach for probabilistic

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Automating Documentation: A critical perspective into the role of artificial intelligence in clinical documentation

The current conversation around automation and artificial intelligence technologies creates a future vision where humans may not possibly compete against intelligent machines, and that everything that can be automated through deep learning, machine learning, and other AI technologies will be automated. In this article, we focus on general practitioner documentation of the patients’ clinical encounter, and explore how these work practices lend themselves to automation by AI.

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iConference 2018 Automation Workshop Summary

On March 25, 2018 Dr. Matt Willis and Professor Eric T. Meyer organized a workshop on Automation and the next wave of computerisation: Sociotechnical approaches to automation, robots, machine learning and artificial intelligence. We had sixteen attendees, from PhD students to tenured faculty, heads of department, computer scientists, and industry… Read More »

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Work that Enables Care: Understanding Tasks, Automation, and the National Health Service

Automation of jobs is discussed as a threat to many job occupations, but in the UK healthcare sector many view technology and automation as a way to save a threatened system. However, existing quantitative models that rely on occupation-level measures of the likelihood of automation suggest that few healthcare occupations are susceptible to automation. In order to improve these quantitative models, we focus on the potential impacts of task-level automation on health work, using qualitative ethnographic research to understand the mundane information work in general practices. By understanding the detailed tasks and variations of information work, we are building a more complete and accurate understanding of how healthcare staff work and interact with technology and with each other, often mediated by technology.

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iConference 2018 Automation Workshop: Call for Participation

Automation and the next wave of computerisation: Sociotechnical approaches to automation, robots, machine learning and artificial intelligence Background Progress made in mobile robotics, machine learning, natural language processing, and machine vision, coupled with the availability of large data sets and ubiquity of sensors have captured scholars interests in understanding the… Read More »

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Socio-technical Infrastructures for Healthcare Automation in NHS Primary Care.

Automation and computerisation technologies are poised to impact some 47 percent of the U.S. labour market. While automation is typically seen as a threat to workers in many economic sectors, it is an opportunity in the current state of NHS England primary care and general practice services. The early findings reported here are from a recently approved research program that employs ethnography to understand the socio-technical interactions of all primary care staff. With a keen eye on the occupational roles, the tasks those occupations perform, and the tasks technologies perform.

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