Understanding The Scale, Impact, And Care Trajectory For Patients Who Experience A Long Lie After A Fall: Mixed Methods Study Protocol

<ns3:p>Introduction Falls are a major public health concern, particularly among older adults. Without life-threatening symptoms, ambulance calls may be triaged as low priority and people may remain on the floor and experience a “long lie”, risking dehydration, pressure injury, muscle damage and psychological distress. However, there is currently limited evidence on the scale, clinical impact and subsequent care trajectory for people who have experienced a long lie. This study aims to address this gap by exploring the characteristics, outcomes, and potential interventions for people who experience a long lie after a fall. Methods This is a comprehensive, 27-month, mixed-methods study structured across seven interlinked work packages (WPs). Quantitative work (WP1 &amp; WP2) will analyse linked ambulance, emergency department, and hospital data from one ambulance service region to characterise individuals who experience long lies, quantify their care trajectories, estimate resource use, and explore and refine the definition of a ‘harmful long lie’ threshold. WP3 involves a detailed review of 200 patient hospital notes to understand the mechanisms by which long lies impact health outcomes and care trajectories. Qualitative work (WP4, WP5, &amp; WP6) includes analysis of surveys and semi-structured interviews with ambulance staff, care home managers, key stakeholders, and, crucially, individuals with lived experience of a long lie and their carers. WP7 will synthesize all findings in workshops with national stakeholders to co-produce clear, evidence-based guidance and policy recommendations for managing long lies. Discussion By integrating quantitative data on scale and cost of long lies with qualitative data on lived experience and professional practice, this study will provide in-depth understanding of the clinical, social, and economic impact of long lies. The findings will inform the development of interventions to mitigate the harmful effects of prolonged time on the floor leading to improved care pathways and better outcomes for individuals who experience a long lie after a fall.</ns3:p>

Authors

Institutions

Publication Details

Journal
NIHR Open Research
Published
2026-02-25
DOI
https://doi.org/10.3310/nihropenres.14232.1
Primary Topic
Healthcare Decision-Making and Restraints
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Understanding The Scale, Impact, And Care Trajectory For Patients Who Experience A Long Lie After A Fall: Mixed Methods Study Protocol

Stephen Elsmere, Joanne Coster, Fiona Bell, Richard Pilbery et al.
NIHR Open Research
Healthcare Decision-Making and Restraints
article

Understanding The Scale, Impact, And Care Trajectory For Patients Who Experience A Long Lie After A Fall: Mixed Methods Study Protocol

Stephen Elsmere, Joanne Coster, Fiona Bell, Richard Pilbery, Fiona Sampson, Liz Jones, Maxine Kuczawski, Phil Gleeson, Lyn Wilson, Suzanne Mason, Jen Lewis, Simon Dixon, Charlotte Cotterill, Valentine Ngwa
article en

Abstract

<ns3:p>Introduction Falls are a major public health concern, particularly among older adults. Without life-threatening symptoms, ambulance calls may be triaged as low priority and people may remain on the floor and experience a “long lie”, risking dehydration, pressure injury, muscle damage and psychological distress. However, there is currently limited evidence on the scale, clinical impact and subsequent care trajectory for people who have experienced a long lie. This study aims to address this gap by exploring the characteristics, outcomes, and potential interventions for people who experience a long lie after a fall. Methods This is a comprehensive, 27-month, mixed-methods study structured across seven interlinked work packages (WPs). Quantitative work (WP1 &amp; WP2) will analyse linked ambulance, emergency department, and hospital data from one ambulance service region to characterise individuals who experience long lies, quantify their care trajectories, estimate resource use, and explore and refine the definition of a ‘harmful long lie’ threshold. WP3 involves a detailed review of 200 patient hospital notes to understand the mechanisms by which long lies impact health outcomes and care trajectories. Qualitative work (WP4, WP5, &amp; WP6) includes analysis of surveys and semi-structured interviews with ambulance staff, care home managers, key stakeholders, and, crucially, individuals with lived experience of a long lie and their carers. WP7 will synthesize all findings in workshops with national stakeholders to co-produce clear, evidence-based guidance and policy recommendations for managing long lies. Discussion By integrating quantitative data on scale and cost of long lies with qualitative data on lived experience and professional practice, this study will provide in-depth understanding of the clinical, social, and economic impact of long lies. The findings will inform the development of interventions to mitigate the harmful effects of prolonged time on the floor leading to improved care pathways and better outcomes for individuals who experience a long lie after a fall.</ns3:p>

NIHR Open ResearchVol. 6
UK Health Forum (GB), Yorkshire Ambulance Service NHS Trust (GB), Leeds City Region Enterprise Partnership (United Kingdom) (GB), Mid Yorkshire Hospitals NHS Trust (GB), University of Sheffield (GB)
National Institute for Health and Care Research, Department of Health and Social Care, Health and Social Care Delivery Research
Openalex Percentile: Top 47%
Healthcare Decision-Making and Restraints
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.