Clinical trial NCT06784011: SHIFT-Hospital in Motion (Hospital Implementation Study)
Official title: SHIFT-Hospital in Motion: Use of Activity Sensors in the Clinical Setting
Study type: OBSERVATIONAL
Overall status: ACTIVE_NOT_RECRUITING
Conditions: Hospitalized Patients
Physical Inactivity
Keywords: Movement detection
Activity sensors
Algorithm development and validation
Hospital implementation
Lead sponsor: University Hospital, Basel, Switzerland
Sponsor class: OTHER
Collaborators: name: Zurich University of Applied Sciences
First posted: 2025-01-20
Enrollment: 19
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: CASE_ONLY
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: Patients that are hospitalised for at least 3 days on the medical ward 6.1 of the University Hospital Basel and are recruited either mondays or tuesdays.

Brief summary: The goal of this monocentric observational study involving hospitalised patients is to assess the integration of activity sensors into routine clinical practice.

Detailed description: Patients in hospitals spend the majority of their time inactive, sitting or lying down. Not being active is a common problem for patients in hospitals, often causing complications and impairing recovery, as it can lead to issues such as reduced blood volume, unsteady blood pressure when standing, weaker muscles, and a higher risk of infections, blood clots, and other health issues. The inactivity-related changes in the body in combination with the natural ageing process, the stress of being in the hospital, a poor nutritional status, and possibly troubles with thinking, memory, and understanding or depression diminish the ability to regenerate with overall compromised physiological resilience.

A pilot study (NCT06403826) involving 40 patients demonstrated the feasibility and effectiveness of using activity sensors in clinical settings. A subsequent validation study (NCT06396676) validated a classification model based on activity data from 65 patients, which can distinguish between different activities with 89% accuracy.

The integration of activity sensors into routine clinical practice requires a comprehensive infrastructure to support interdisciplinary collaboration. Therefore, the primary objective of this observational, single center study is to evaluate the additional time expenditure associated with using activity sensors in routine clinical practice by physiotherapy and clinical care over a 10-week period. Secondary objectives include assessing the comfort of extended sensor use, the feasibility and benefits for healthcare professionals, the reliability and accuracy of the sensor data, and the optimization of the activity classification algorithm.

The results of this study will contribute to improving patient care through the use of activity sensors, enabling more personalized care.

Eligibility criteria: Inclusion Criteria:

* at least 3 days inpatient on the medical ward 6.1 (Monday to a maximum of Thursday or Tuesday to a maximum of Friday)
* at least restricted bed rest
* patient must be able to walk
* patient must be cognitively able to follow instructions (normal Observation Screening Scale (DOS) und modified Confusion Assessment Method (mCAM))
* ≥ 18 years
* signed informed consent

Exclusion Criteria:

* planned discharge within the next 3 days
* planned surgery during the measurement
* isolated patient
* inability or contraindications to participate in the study or to follow the study procedures, e.g. due to certain neurological disorders, speech problems, mental disorders, or cognitive impairments
* prior inclusion in the study

Primary outcomes:
measure: Evaluation of the time expenditure
timeFrame: Day 1-4
Secondary outcomes:
measure: Assessment of the comfort level associated with wearing the sensors
timeFrame: Day 2-4
measure: Evaluation of the handling
timeFrame: After 10-week period (at recruitment completion)
measure: Assessment of the accuracy of the classification algorithm for the detection of movements parameters
timeFrame: Day 1-3
measure: Optimization of activity classification algorithm
timeFrame: After 10-week period (at recruitment completion)
Other outcomes:
Locations:
city: Basel
country: Switzerland
facility: Universitiy Hospital Basel, Division of Internal Medicine
state: Basel-Stadt
Study officials:
affiliation: University Hospital, Basel, Switzerland
name: Joris Kirchberger
role: PRINCIPAL_INVESTIGATOR
affiliation: University Hospital, Basel, Switzerland
name: Jens Eckstein, Prof. Dr. med.
role: STUDY_CHAIR
References: