Technology Supported Improvement, Management and Prevention of Accidental Falls in Hospitals (TechSIMPAFiH)

The student will observe fall prevention systems in practice in 2 different hospitals considering how fall prevention technology influences staff behaviour and patients safety in the context of accidental falls in hospital. Accidental falls in hospital are rare but can be life changing for those that suffer them as they are often frail patients who are already vulnerable. Current research shows little improvement with any interventions tested which leaves patient facing clinicians with few resources to assist in the prevention of falls. The investigator believes this is because the measure of accidental falls in hospital is not sensitive enough to calibrate for the different contexts in which patients fall. The student would posit that it is the context that is most influential and addressing the context may lead to improved measures so progress can be made in finding solutions.

Study Overview

• Status: Not yet recruiting
• Conditions: Accidental Falls; Fall Prevention

Detailed Description

The multi-centre study will involve up to 2 wards on each of the 2 Trust sites. The study wards will be randomly selected from a group of wards that have indicated they are happy to be considered as potential research wards. An ethnographic case study with contextual enquiry design will be used to allow a contextual analysis of fall prevention in practice and consider how staff decisions and behaviour contribute to this. Hierarchical task analysis (HTA) will be utilised to inform this and to identify differences between 'work as imagined' compared to 'work as done' . The study will use observations of the staff in clinical practice using their current system of fall prevention measures assisted by their existing technology and will illustrate outcomes with specific and transparent definitions. Calculations of falls occurring measured with local live data will compare with current standard measurements (Falls/1000 occupied bed days) as calculated with central occupancy data. The ward team, patients and relatives attending the wards will have an opportunity to complete a questionnaire about the use of fall prevention technology advertised in the ward environment on fliers and posters as permitted by policy. Recommendations for future technology design, research and use of technology in fall prevention will be provided on conclusion of the study.

• Study Type: Observational
• Enrollment (Estimated): 200

Contacts and Locations

• 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

• United Kingdom
  • 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

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

Healthcare professionals working as a clinical team in practice

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?

Number of groups / cohorts

2

Cohorts and Interventions

Group / 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

Outcome Measure	Measure Description	Time Frame
To discover how work practice and behaviour adheres or varies from policy	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.	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.	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

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	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	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: University of Nottingham
• Collaborators: Northern Care Alliance NHS Foundation Trust; University Hospitals, Leicester
• Investigators: Principal Investigator: James Reid, University Hospitals, Leicester

Study record dates

Study Major Dates

• Study Start (Estimated): April 1, 2026
• Primary Completion (Estimated): March 31, 2027
• Study Completion (Estimated): March 31, 2027

Study Registration Dates

• First Submitted: November 14, 2025
• First Submitted That Met QC Criteria: January 12, 2026
• First Posted (Actual): January 21, 2026

Study Record Updates

• Last Update Posted (Actual): January 21, 2026
• Last Update Submitted That Met QC Criteria: January 12, 2026
• Last Verified: October 1, 2025

More Information

Terms related to this study

• Keywords: mixed methods research; ethnographic case study; contextual enquiry; observation of clinical staff; The use of technology to prevent falls
• Other Study ID Numbers: 25057

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No