Poster Session III. - X: Conservative Medicine
Bogner Luca Laura
Pediatric Centre, Semmelweis University
Luca Laura Bogner1
1: Pediatric Centre, Semmelweis University
Introduction
Delivery room care of a newborn has crucial impact on short- and long-term outcome. International recommendations include critical and time-sensitive interventions based on the assessment of physiological parameters and monitoring data. Documentation of care steps is often done retrospectively, whereas real-time, structured, unbiased data are much needed for successful decision support and quality improvement.
Aims
Our aim is to develop and test a digital delivery room event log ("NeoTracker").
Method
The development of NeoTracker was carried out in the Department of Obstetrics and Gynaecology in four stages: 1. Needs assessment, during which we carried out the retrospective processing of the PICU’s 2023 data; 2. Medical specification of the data content based on the Newborn Life Support (NLS) algorithm under the supervision of a neonatologist. 3. Development of a prototype of the event diary in Excel format; 4. Development of an application in collaboration with an IT company.
Results
The annual number of births in the study centre was 2906, of which 291 newborns required complex delivery room care and associated PICU admission (10%) and 203 (7%) received non-invasive ventilatory support in the delivery room. Data content specification was based on 7 main domains: birth information, neonatal care records, first physical examination records, Apgar scores, events and interventions, resuscitation, short-term outcome. Within the domains, 51 panels contain text fields, numerical data, and data selectable from drop-down lists. During the development of the prototype, interventions and events are recorded with an automatic timestamp, and notifications are used to draw the attention of providers to tasks that need to be performed at a given time
Conclusion
The use of NeoTracker is reasonable for 10% of neonates. It is a promising innovation that, in addition to reducing the administrative burden on health care providers, could contribute to improving the quality of patient care and more accurate prediction of patient outcomes.
Funding: EKÖP 2024-232