[home] [Personal Program] [Help]

---

Session: Poster session 2 (Odd numbers)
Session starts: Friday 27 January, 10:00
Presentation starts: 10:00

---

Igor Paulussen ()
Supriyo Chatterjea ()
Julia van Tuijl ()
Ben Jansen ()
Tom Defossez ()
Rick Bisschops ()
Gerrit Noordergraaf ()

Abstract:
Main research question: Electronic Medical Record (EMR) data are frequently used as source for quality indicators of hyper-acute clinical pathways. In stroke care, door-to-needle time (DTN, i.e. IntraVenous Thrombolysis, IVT) should be ≤60 minutes. Validity of timestamps, however, remains uncertain. RTLS technology tracks tags (patients, essential equipment and staff: nurses and technicians) within predefined areas and automatically adds timestamps. This data can be aggregated or individually assessed. Using patients presenting to the Emergency Department with suspicion of a stroke and using RTLS supplemented by EMR data, we assessed validity of times, and sought insights into process inefficiency as well as badge-wearing acceptability by professionals. Research method: A clinical, single-center prospective study using the stroke pathway with enrollment from 1-9-2020 through 31-8-2021. Ischemic stroke and IVT and/or intra-arterial thrombectomy (IAT) patients were included after informed consent. The RTLS sensors were placed in the Emergency and Radiology Departments. Patients received tags upon arrival. Interventions using RTLS input into the pathway were introduced (starting 01-07-2021) validating whether RTLS visualizes changes and that these were effective. Results: High inclusion rate was achieved (99%, n=125 patients). EMR time data proved highly inaccurate while RTLS demonstrated high fidelity. For example, maximum difference in DTN time between RTLS and EMR was 26 minutes. The overall compliance in wearing a badge was 81 ± 16%. Compliance (acceptability) was variable: nurses 96%, Neurology residents 64%, and Radiology technicians 85%. Patient tag signals not visible for RTLS (i.c. temporarily under a cover) occurred at least once in 74% of cases, typically during CT-scans. We were able to recognize and suggest adaptations for bottlenecks in the stroke pathway resulting in 25% time saving through: a) using real entry-into-workflow time; b) improving content with an IVT and IAT box, by bundling materials, thus allowing the nurse to stay in the admission rooms; and c) creating a dedicated anesthesia cart including 24/7 stand-by anesthesia care station. Conclusions: RTLS with EMR data offers a detailed, independent insight into hyper-acute care and discerns inefficient constituents. Professionals are ambivalent about badge-wearing.