Fall Prevention Guidelines for Patients in Wheelchairs or Patients with Delirium: A Review of Evidence-Based Guidelines
Bibliographic record
Abstract
In general, falls are defined as sudden unintentional changes in position resulting in an individual landing on a lower level. Falls incur two billion dollars per year of direct health care costs in Canada and cause 95% of hip fractures. Falls resulting in injuries increased 43% between 2003 and 2008 while falls resulting in death increased 65% over the same period. Falls are the leading cause of injury among seniors with 20 to 30% experiencing at least one fall per year, accounting for 85% of seniors’ injury-related hospitalizations and over 30% of seniors’ subsequent admissions to long-term care., Even falls that do not incur injury can result in future health care costs since they may lead seniors to limit their activities, leading to declines in health and function and increasing the risk of future falls with serious outcomes., Fall prevention may reduce injuries, long-term care admissions, hospitalizations, and overall health care costs; preventing 20% of falls could reduce 7,500 hospitalizations and save the Canadian health care system $138 million per year.While in theory assistive devices such as wheelchairs promote independence, mobility, and fall prevention, they are not always properly used or maintained. Falls during transfer – defined as transferring one’s body from one surface to another – may result from an improperly maintained wheelchair. For example, if a wheelchair’s locking mechanism is not functioning properly or is not appropriately engaged, then the wheelchair becomes unsafe and can then lead to falls instead of preventing them., Installation of automatic or more robust wheel locks as well as use of a wheelchair maintenance schedule may reduce injurious falls., Improper transfer techniques (from wheelchair to and from bed or toilet) as well as unassisted transfers may also increase the risk of injurious falls., Nearly 60% of people using manual wheelchairs experience falls and face the challenges of independent or assisted recovery. Independent recovery relies on the patient maintaining contact with the wheelchair and having the physical capacity to recover on their own. If independent recovery is not possible, then the patient remains on the ground until assistance is available. If a patient remains on the ground for a prolonged period of time, it is predictive of future injurious falls and is also associated with declines in activities of daily living, increased hospital admissions, and increased long-term care admissions.Another consideration for fall risk is delirium. Delirium, also known as acute confusional state, has an acute onset, developing over one to two days and is a common clinical symptom characterized by fluctuating consciousness, cognitive function, attention, thinking, or perception., Patients presenting with delirium may be: restless, agitated, and aggressive; withdrawn, sleepy, and quiet; or a mixture of these characteristics. Delirium and subsequent confusion are risk factors for falls. Additionally, older patients are at risk of developing delirium after a hip fracture, which itself is a serious consequence of a fall.,, Patients with a hip fracture and delirium have increased hospital stays, falls, pressure sore development, and risk of death than those without delirium., Fall prevention for patients with delirium thus involves preventing delirium or identifying and managing the underlying causes of the delirium such as: orienting the patient to person, place, and time (who the people around them are, their location, what the time and date are); providing an environment with context and familiarity (e.g., a room with a window or clock filled with personal belongings or pictures); talking and providing explanations in a calm, reassuring voice; as well as reviewing and changing medications to limit those that may cause or worsen delirium.–As Canada’s population continues to age, falls and fall prevention will continue to be a growing public health issue. Effective fall prevention accounts for the combination of fall risk factors unique to each senior, tailoring the intervention to target the individual’s specific health status, situation, and environment. Evidence-based fall-prevention guidelines can assist in assessment of individual patients’ fall risks as well as establish standards to decrease the number and effect of falls.The objective of this report is to summarize the relevant evidence-based guidelines associated with the prevention of falls in patients requiring wheelchairs and patients with delirium in institutionalized care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".