9 results match your criteria: "Institute for Medical Informatics I4MI.[Affiliation]"

Article Synopsis
  • This research focuses on identifying risk factors for wrong-patient medication orders in emergency departments based on a specific metric called "retract-and-reorder" (RaR) events.
  • Over a five-year period, the study analyzed 561,099 medication orders and uncovered 1,031 RaR events, with a higher incidence among males and when patients were assigned to closer exam rooms in the electronic medical records layout.
  • The findings highlight that while factors like similar names and birthdates were not significant, proximity of exam rooms and matching sex were notable risk factors for these errors.
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Background: Trauma poses a significant global health challenge. Despite advancements in the management of severely injured patients, (poly)trauma continues to be a primary contributor to morbidity and mortality worldwide. In the context of trauma resuscitation, supplemental oxygen is commonly administered generously as suggested by guidelines.

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Article Synopsis
  • Versatile large language models (LLMs) have the potential to enhance diagnostic decision-making for clinicians by providing support and facilitating natural conversations, but their newness raises concerns about users' critical engagement with their suggestions.
  • The study investigates the effects of using an LLM versus a human coach, alongside varying levels of training, on medical students' diagnostic processes and outcomes.
  • Conducted with 158 fourth-year medical students, the research will analyze factors like information search, diagnostic accuracy, and attitudes toward AI in medicine, while being exempt from a full ethical review.
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Social media provide easy ways to autistic individuals to communicate and to make their voices heard. The objective of this paper is to identify the main themes that are being discussed by autistic people on Twitter. We collected a sample of tweets containing the hashtag #ActuallyAutistic during the period 10/02/2022 and 14/09/2022.

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In this paper we present first findings of the Digi-Care project, a multidisciplinary, multi-stakeholder research project investigating the impacts of digitization on nursing work practices and in particular the transmission of patient care information within and beyond nursing work practices. We completed the initial data collection of the funded 3-year research project and report on a plethora of significant and critical IT-related events. Some of them can be attributed to usability issues.

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Multiple challenges await third-party digital health services when trying to enter the health market. Prominent examples of such services are clinical decision support systems provided as external software. Uncertainty about their challenges, technical as well as legal, pose serious hurdles for many innovations to be adopted early on.

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Legal Challenges for IT Service Providers in Pharmacogenomics.

Stud Health Technol Inform

June 2020

Institute for Medical Informatics I4MI, Bern University of Applied Sciences, Switzerland.

IT providers offering services based on genetic data face serious challenges in managing health data in compliance with the General Data Protection Regulation (GDPR). Based on a literature research and our experiences, an overview of GDPR compliant processing of sensitive data is given. The GDPR requirements for processing sensitive data were specified for a use case concerning a service provider of a pharmacogenomic decision support system.

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A precise and timely care delivery depends on an efficient triage performed by primary care providers and smooth collaboration with other medical specialities. In recent years telemedicine gained increasing importance for efficient care delivery. It's use, however, has been limited by legal issues, missing digital infrastructures, restricted support from health insurances and the digital divide in the population.

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Background: Today, cancer documentation is still a tedious task involving many different information systems even within a single institution and it is rarely supported by appropriate documentation workflows.

Methods: In a comprehensive 14 step analysis we compiled diagnostic and therapeutic pathways for 13 cancer entities using a mixed approach of document analysis, workflow analysis, expert interviews, workflow modelling and feedback loops. These pathways were stepwise classified and categorized to create a final set of grouped pathways and workflows including electronic documentation forms.

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