A4 Vertaisarvioitu artikkeli konferenssijulkaisussa
Exploring Delays in Cardiac Care Processes Through Electronic Health Records
Tekijät: Peltonen, Laura-Maria; von Gerich, Hanna; Myllymäki, Emmi; Walsh, Julia; Medvecky, Matej
Toimittaja: Mantas, John; Hasman, Arie; Demiris, George; Saranto, Kaija; Marschollek, Michael; Arvanitis, Theodoros N.; Ognjanović, Ivana; Benis, Arriel; Gallos, Parisis; Zoulias, Emmanouil; Andrikopoulou, Elisavet
Konferenssin vakiintunut nimi: Medical Informatics Europe
Julkaisuvuosi: 2024
Journal: Studies in Health Technology and Informatics
Kokoomateoksen nimi: Digital Health and Informatics Innovations for Sustainable Health Care Systems
Tietokannassa oleva lehden nimi: Studies in health technology and informatics
Lehden akronyymi: Stud Health Technol Inform
Vuosikerta: 316
Aloitussivu: 1866
Lopetussivu: 1870
eISBN: 978-1-64368-533-5
ISSN: 0926-9630
eISSN: 1879-8365
DOI: https://doi.org/10.3233/SHTI240795
Verkko-osoite: https://ebooks.iospress.nl/doi/10.3233/SHTI240795
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/457770366
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.
Ladattava julkaisu This is an electronic reprint of the original article. |  |
