dc.contributor.author
Jegzentis, Kati
dc.contributor.author
Nowe, Tim
dc.contributor.author
Brunecker, Peter
dc.contributor.author
Endres, Matthias
dc.contributor.author
Haferkorn, Bernd
dc.contributor.author
Ploner, Christoph
dc.contributor.author
Steinbrink, Jens
dc.contributor.author
Jungehulsing, Gerhard Jan
dc.date.accessioned
2018-06-08T02:55:41Z
dc.date.available
2014-09-17T10:58:11.669Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/14154
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-18351
dc.description.abstract
Background Recruiting stroke patients into acute treatment trials is
challenging because of the urgency of clinical diagnosis, treatment, and trial
inclusion. Automated alerts that identify emergency patients promptly may
improve trial performance. The main purposes of this project were to develop
an automated real-time text messaging system to immediately inform physicians
of patients with suspected stroke and to test its feasibility in the emergency
setting. Methods An electronic standardized stroke algorithm (SSA) was
implemented in the clinical information system (CIS) and linked to a remote
data capture system. Within 10 minutes following the documentation and storage
of basic information to CIS, a text message was triggered for patients with
suspected stroke and sent to a dedicated trial physician. Each text message
provided anonymized information on the exact department and unit, date and
time of admission, age, sex, and National Institute of Health Stroke Scale
(NIHSS) of the patient. All necessary information needed to generate a text
message was already available – routine processes in the emergency department
were not affected by the automated real-time text messaging system. The system
was tested for three 4-week periods. Feasibility was analyzed based on the
number of patients correctly identified by the SSA and the door-to-message
time. Results In total, 513 text messages were generated for patients with
suspected stroke (median age 74 years (19–106); 50.3% female; median NIHSS 4
(0–41)), representing 96.6% of all cases. For 48.3% of these text messages,
basic documentation was completed within less than 1 hour and a text message
was sent within 60 minutes after patient admission. Conclusions The system
proved to be stable in generating text messages using IT-based CIS to identify
acute stroke trial patients. The system operated on information which is
documented routinely and did not result in a higher workload. Delays between
patient admission and the text message were caused by delayed completion of
basic documentation. To use the automated real-time text messaging system to
immediately identify emergency patients suitable for acute stroke trials,
further development needs to focus on eliminating delays in documentation for
the SSA in the emergency department.
en
dc.rights.uri
http://creativecommons.org/licenses/by/2.0/
dc.subject
Notification tool
dc.subject
Patient identification
dc.subject
Selection criteria
dc.subject.ddc
600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit
dc.title
Automated real-time text messaging as a means for rapidly identifying acute
stroke patients for clinical trials
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation
Trials 15 (2014), 1, Artikel Nr. 304
dcterms.bibliographicCitation.doi
10.1186/1745-6215-15-304
dcterms.bibliographicCitation.url
http://www.trialsjournal.com/content/15/1/304
refubium.affiliation
Charité - Universitätsmedizin Berlin
de
refubium.mycore.fudocsId
FUDOCS_document_000000020978
refubium.note.author
Der Artikel wurde in einer Open-Access-Zeitschrift publiziert.
refubium.resourceType.isindependentpub
no
refubium.mycore.derivateId
FUDOCS_derivate_000000003923
dcterms.accessRights.openaire
open access
dcterms.isPartOf.issn
1745-6215