Part II. How accurate is 1177 Journal? Perspectives of patients and healthcare professionals

Part II. How accurate is 1177 Journal? Perspectives of patients and healthcare professionals

Wednesday May 6, 2026 10:37 - 10:43 F3

This session explores the accuracy of the information patients read in their 1177 Journal and how it impacts both patients and healthcare professionals. 1177 Journal provides access to structured and unstructured health data, which may at times be incorrect, incomplete, or ambiguous. The talk examines how health record errors influence patient safety, clinical workflow, and patient–clinician communication. It highlights the administrative and work-environment pressures that shape documentation practices. The session concludes by examining why inaccuracies occur even with good intentions, and how emerging AI technologies may support improvement.

This is the second of a three-parts series. The first part, 'Part I. 14 Years of 1177 Journal — what do people think?' introduces patients' and healthcare professionals' experience with 1177 Journal. The final session after it titled, 'Part III. What is the role of generative in 1177 Journal?' will address how AI may help, or complicate, efforts to improve clinical documentation.

Language

English

Topic

Future Health and Care

Seminar type

Live + On site

Lecture type

Short 7 min

Objective of lecture

Inspiration

Level of knowledge

Introductory

Target audience

Management/decision makers
Politicians
Organizational development
Purchasers/acquisitions/eco nomy/HR
Technicians/IT/Developers
Researchers
Students
Care professionals
Healthcare professionals
Patient/user organizations

Keyword

Benefits/effects
Education (verification)
Patient centration
Innovation/research
Follow-up/Report of current status
Documentation
Patient safety
Information security
Usability
Ethics
Informatics/Interoperability

Conference

Vitalis

Lecturers

Anna Kharko Lecturer

Researcher
Uppsala University

Anna Kharko is a researcher in Digital Health at the Uppsala University, Sweden, and research fellow at the University of Manchester, UJ. She is the principal investigator of the EHRrors Project, a project examining errors in electronic health records, their causes, and their impact on patient care and clinical workflows. She also is a researcher within the CLEAR-AI initiative, which focuses on transparent, trustworthy applications of artificial intelligence in healthcare documentation and care decision-making.

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