Technology Supported Improvement, Management and Prevention of Accidental Falls in Hospitals (TechSIMPAFiH)
Study Overview
Status
Status
Conditions
Conditions
Detailed Description
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Jan Christian, RN, Ba(hons)
- Phone Number: +447900180643
- Email: janice.christian@nottingham.ac.uk
Study Contact Backup
- Name: Alexandra Lang, PhD
- Phone Number: 07921 912376
- Email: alexandra.lang@nottingham.ac.uk
Study Locations
-
-
-
Leicester, United Kingdom, LE1 5WW
- University Hospitals of Leicester
-
Contact:
- Dylan Donnelly
- Phone Number: +44 116 2584761
- Email: dylan.donnelly@nhs.net
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Any member of the ward team as defined by the ward manager including students. All healthcare professional groups, ancillary and administrative staff who work on the selected study ward and any temporary staff from agency or other wards who consent to participate.
Exclusion Criteria:
- Any staff under 18 years old
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
|---|
|
clinical ward team UHL1
A clinical ward team in a NHS acute care Trust
|
|
clinical ward team UHL2
A clinical ward team in a NHS acute care Trust
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
To discover how work practice and behaviour adheres or varies from policy
Time Frame: 12 months
|
Data will be gathered by observing staff in their usual work environment over a 12 month period to determine how fall prevention practice is shaped by technology.
Up to 200 staff will be observed by the researcher on various shifts.
Hierarchical task analysis will be used to compare how work varies from the policy/protocol and any workarounds that have been developed (Work as done will be compared to work as imagined).
Adherence to policy/protocol or variance from policy/protocol will be recorded and collated as a count of deviations.
|
12 months
|
|
To collate evidence of the context of falls in a context log to identify potential contributory factors to accidental falls in hospital.
Time Frame: 12 months
|
A thematic analysis of accidental fall incident forms will be undertaken comparing contextual details at the time of the accidental fall to identify common themes.
Previously uncollated facts such as the exact location of fall (bedside or bathroom), lighting at the time and ability to alter the lighting (automatic switch on /off versus dimmer switch), footwear (own or provided in hospital) and whether walking aids in place or not etc.
These will be compared before the implementation of fall prevention alarms versus after implementation to see if the implementation of fall prevention alarms has impacted on falls in any specific contextual category.
This will identify if there is a specific context in which fall prevention alarms prevents falls.
This will allow more accurate measurement of success of technology as there may be a specific type of fall that can be prevented by the technology.
|
12 months
|
|
To discover how accidental falls are being measured and recorded in hospital by observation and comparing live data measurement against standard data measurement.
Time Frame: 12 months
|
The current way of calculating falls/1000 bed days is flawed.
Occupancy rate and number of admissions are not considered.
The outcome will compare standard falls/1000 OBD's versus a contextual measurement that better represents outcomes.
Instead of taking average hospital occupancy data the calculation of the number of falls/1000 occupied bed days will be calculated using actual data from ward level occupancy.
If the hospital uses an electronically generated occupancy measurement it can give falsely high measurements of falls on a specific ward as it reports empty beds at midnight.
These empty beds at midnight are often an electronic delayed transfer rather than actual empty beds.
measurement according to stafff reported figures will be compared.
|
12 months
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
To identify through thematic analysis using Nvivo 15 task critical attributes and user requirements for future fall prevention technology design
Time Frame: 12 months
|
The observation of the use of technology in practice will provide themes where practice is impeded or enhanced by the use of technology.
This will be identified by the themes identified during observation of staff.
These themes will be analysed and recommendations for future fall prevention alarms will be deduced.
|
12 months
|
|
Staff interviews
Time Frame: 12 months
|
Staff will be questioned during their shift with 'go along questions' (quick questions in between work tasks) to record their rationale for completing fall prevention tasks in the way they have.
Answers will be anonymously recorded to provide themes to be analysed using Nvivo 15.
|
12 months
|
Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Investigators
Investigators
- Principal Investigator: James Reid, University Hospitals, Leicester
Study record dates
Study Major Dates
Study Start (Estimated)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Other Study ID Numbers
Other Study ID Numbers
- 25057
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.