A4 Refereed article in a conference publication

Exploring Delays in Cardiac Care Processes Through Electronic Health Records




AuthorsPeltonen, Laura-Maria; von Gerich, Hanna; Myllymäki, Emmi; Walsh, Julia; Medvecky, Matej

EditorsMantas, John; Hasman, Arie; Demiris, George; Saranto, Kaija; Marschollek, Michael; Arvanitis, Theodoros N.; Ognjanović, Ivana; Benis, Arriel; Gallos, Parisis; Zoulias, Emmanouil; Andrikopoulou, Elisavet

Conference nameMedical Informatics Europe

Publication year2024

JournalStudies in Health Technology and Informatics

Book title Digital Health and Informatics Innovations for Sustainable Health Care Systems

Journal name in sourceStudies in health technology and informatics

Journal acronymStud Health Technol Inform

Volume316

First page 1866

Last page1870

eISBN978-1-64368-533-5

ISSN0926-9630

eISSN1879-8365

DOIhttps://doi.org/10.3233/SHTI240795(external)

Web address https://ebooks.iospress.nl/doi/10.3233/SHTI240795(external)

Self-archived copy’s web addresshttps://research.utu.fi/converis/portal/detail/Publication/457770366(external)


Abstract
Cardiovascular diseases are the leading cause of death globally. Timely health services are fundamental to the appropriate prevention, identification, care and rehabilitation of these diseases. This study aimed to explore the potential of using electronic health records as a data source to help identify health system -related delays in care processes of cardiac patients. This retrospective registry study is based on a sample of electronic health records of 200 cardiac patients admitted to one out of twenty wellbeing services counties in Finland during the years 2021-2022. A total of 426 health system -related delays were identified. All expressions were found in unstructured format and most of these (58.7%) were generated by nurses. These results show that the electronic health records contained a variety of information on health system -related patient care delays, and that most delays were associated with difficulties in finding a bed for the patient in a post-acute care facility (49.8%), but also in-hospital process delays were common (27.7%). These findings show great potential for exploring electronic health record data with natural language processing methods in the future for the development of tools to better identify and monitor different types of delays in care processes. Such tools may support leadership to respond to organisational procedures in need of improvement.

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Last updated on 2025-14-02 at 15:19