Primary objective:1. To investigate to what extent continuous vital sign monitoring can improve detection of adverse events in surgical ward patients as compared to current MEWS and nurse-worry assessmentSecondary objectives:2. To explore the…
ID
Source
Brief title
Condition
- Other condition
- Gastrointestinal therapeutic procedures
Synonym
Health condition
pre- en postoperatieve complicatie na hoog risico chirurgie
Research involving
Sponsors and support
Intervention
Outcome measures
Primary outcome
The primary endpoint includes the time to detect adverse events. Adverse events
of interest include pre- and postoperative complications with a Clavien Dindo
class of II or higher, diagnosed according to standard guidelines.
A predefined Continuous Early warning score (CEWS) is used to assess presence
of abnormalities in continuous vital signs where detection is defined as
CEWS*3. Detection of complications by the MEWS method is defined as MEWS*3.
Event detection by nurse observations is defined by annotation of nurse worry
in the nurse checklists.
In patients where adverse events are diagnosed, the time to detect adverse
events is calculated as the time difference between event identification and
the moment that therapeutic actions targeting the event are started.
The time to detect adverse events of the CEWS is compared with 1) MEWS, 2)
nurse observations, and 3) the combination of MEWS and nurse observations.
Secondary outcome
The quality and availability of vital sign data and robustness of the wireless
connection is verified to investigate the technical feasibility of remote vital
sign monitoring. The practical feasibility of mobile monitoring system and use
of the patient diary and nurse checklist for routine care is explored using the
patient and nurse evaluations. This evaluation includes user comfort, user
friendliness, time consumption, adherence, applicability, difficulty, and
meaningfulness of the methods.
To explore potential decision support methods, we will investigate which vital
sign patterns (i.e. absolute values, time trends and shapes) are related with
adverse events using visual inspection and regression analysis. From this
knowledge, various statistical models predicting adverse events serving will be
tested as novel continuous warning score. To verify whether clinical context
information improves detection of adverse events, the accelerometry data,
patient symptoms and nurse worry indicators will be integrated in the
prediction models.
Background summary
Patients admitted to the hospital for surgical care are at risk for developing
adverse events in the pre- and postoperative trajectory. To identify clinical
deterioration in surgical ward patients, the status of patients is monitored
using routine nurse controls and the early warning score system (MEWS).
However, current practice reveals that first signs of deterioration may remain
unnoticed for hours or days while early intervention is critical to prevent
secondary damage. This is of particular concern in patients undergoing upper
gastrointestinal (GI) surgery or geriatric patients with traumatic hip
fracture, which are known with high rates of complications developing during
ward stay. To promote patient safety in wards, it might be interesting to use
wireless sensor technologies that allow continuous vital sign tracking with
minimal patient burden. These technologies can be integrated with decision
support methods to assist medical professionals in the identification of
deviant trends and abnormalities in vital signs.
Study objective
Primary objective:
1. To investigate to what extent continuous vital sign monitoring can improve
detection of adverse events in surgical ward patients as compared to current
MEWS and nurse-worry assessment
Secondary objectives:
2. To explore the feasibility of continuous mobile vital sign monitoring in
surgical ward patients
3. To explore how automatic analytical methods and integration of clinical
context information can support early identification of adverse events from
vital signs
Study design
The prospective observational design includes patients admitted to the surgical
ward for post- or perioperative care. Patients will receive standard ward care,
including routine vital sign and MEWS measurements and observations by nurses.
In addition to usual care, a selection of vital signs (heart rate, respiratory
frequency, oxygen saturation, skin temperature) and accelerometry is
continuously registered using wireless mobile sensors, blinded for medical
professionals and patients. Besides, patients are asked to fill out a short
questionnaire one time a day to indicate their current condition and presence
of symptoms. Furthermore, nurses will register the presence and corresponding
reason for nurse worry in a checklist. At the end of the study period, the
feasibility and added value of the wireless vital sign tracking method, patient
diary, and nurse checklist are evaluated by patients and nurses using surveys.
The study is realized in a stepwise manner, including a pilot phase (Phase I)
to explore the feasibility of the measurement protocol, and an explorative
phase (Phase II) for optimization of detection criteria and exploration of the
potential of vital sign measurements and decision support methods. Last, a
validation phase (Phase III) is performed for verification of the primary
endpoints and first evaluation of decision support methods.
Study burden and risks
The quality and availability of vital sign data and robustness of the wireless
connection is verified to investigate the technical feasibility of remote vital
sign monitoring. The practical feasibility of mobile monitoring system and use
of the patient diary and nurse checklist for routine care is explored using the
patient and nurse evaluations. This evaluation includes user comfort, user
friendliness, time consumption, adherence, applicability, difficulty, and
meaningfulness of the methods.
To explore potential decision support methods, we will investigate which vital
sign patterns (i.e. absolute values, time trends and shapes) are related with
adverse events using visual inspection and regression analysis. From this
knowledge, various statistical models predicting adverse events serving will be
tested as novel continuous warning score. To verify whether clinical context
information improves detection of adverse events, the accelerometry data,
patient symptoms and nurse worry indicators will be integrated in the
prediction models.
Zilvermeeuw 1
Almelo 7609PP
NL
Zilvermeeuw 1
Almelo 7609PP
NL
Listed location countries
Age
Inclusion criteria
The study population includes two patient groups:
1. Patients aged > 18 years undergoing elective oesophageal and gastric resection admitted to the gastrointestinal surgical ward for postoperative care
2. Patients aged > 70 undergoing hip fracture surgery acutely admitted to the geriatric-trauma ward for pre- and postoperative care
Exclusion criteria
1. Contraindications for use of vital sign sensor patch (i.e. skin allergy, implanted medical devices, contact isolation, etc.)
2. Diagnosed or suspected delirium, cognitive impairment, or dementia
Design
Recruitment
Followed up by the following (possibly more current) registration
No registrations found.
Other (possibly less up-to-date) registrations in this register
No registrations found.
In other registers
| Register | ID |
|---|---|
| CCMO | NL65885.044.18 |