Franco E1,2, Ben-Basat Z1
1Assaf Harofeh Medical Center, Physical Therapy Department, Zrifin, Israel, 2Tel Aviv University, Physical Therapy Department, Tel Aviv, Israel
Background: One out of three elderly people over the age of 65 experience at least one incident of falling per year and one of the major predictors of a serious fall is a prior history of falls. In 2007, The WHO has set fall prevention among the elderly as a global goal. Furthermore, once hospitalized, inpatient fall rates are 1.3-8.9 per 1000 hospitalization days and 30%-50% of these falls result in injuries.
Falls significantly impairs the elderly's independence, life quality and longevity, and burden the health and welfare systems. Research has shown that physiotherapy treatments for the elderly after a fall reduce the risk of recurrent falls and minimize damage.
Purpose: To instantly detect elderly inpatients who were hospitalized following a fall in the community, to treat and educate them from day one at the hospital and during their hospitalization, in order to prevent them from falling again in the future.
Methods: The hospital physiotherapy department initiated and led development and implementation of an innovative intervention program called “Fall No More”.
Two major actions were taken in the program:
· A multi-disciplinary team was established with the aim of recruiting technology to the subject. the team developed a “Fall Detector Radar” - a novel computerized algorithm, which continuously scans the hospital's database, and detects in real-time elderly inpatients (over the age of 65) who have been hospitalized with a fall as part of their anamnestic data.
· As soon as the algorithm detected a “post-fall” inpatient, a structured action plan was executed immediately - a physiotherapist performed a functional assessment to evaluate the patient, provided treatment and education for him, his family and the nursing staff regarding fall prevention. Furthermore, recommendations regarding continued physiotherapy treatment after discharge were given.
Results: The program was implemented throughout 2017 as a pilot, and its results were measured quarterly.
1. The program detected, in real time, 62.7% of all “post-fall” inpatients (who were identified retrospectively by analyzing discharged patients' medical records).
2. 86% of the inpatients who were detected by the program received treatment.
3. During the program, inpatients' fall rate declined from 6.2 (per 1000 hospitalization days) to 1.7.
In light of the program's success, its operation was integrated into daily hospital routine.
Conclusion(s): There was an improvement in the rate of “post-fall” inpatients detection, which led to an improvement in the rate of “post-fall” inpatients who received physiotherapy treatment and a reduction in the rate of inpatients׳ falls.
In light of the project's effectiveness, its implementation will be extended to other fields, such as mental health.
A future study will examine whether recurrent falls were prevented in the long term among patients who were treated as part of the program.
Implications: The program, which was carried out without dedicated financial cost, is applicable with relative ease almost in every hospital. In addition, the program demonstrates how initiative, multidisciplinary cooperation and creative thinking can leverage technology in order to upgrade and refresh physiotherapy even in a classic field such as fall prevention and empower the profession.
Keywords: Fall Prevention, Intervention Program, Algorithm
Funding acknowledgements: The work was unfunded.
Falls significantly impairs the elderly's independence, life quality and longevity, and burden the health and welfare systems. Research has shown that physiotherapy treatments for the elderly after a fall reduce the risk of recurrent falls and minimize damage.
Purpose: To instantly detect elderly inpatients who were hospitalized following a fall in the community, to treat and educate them from day one at the hospital and during their hospitalization, in order to prevent them from falling again in the future.
Methods: The hospital physiotherapy department initiated and led development and implementation of an innovative intervention program called “Fall No More”.
Two major actions were taken in the program:
· A multi-disciplinary team was established with the aim of recruiting technology to the subject. the team developed a “Fall Detector Radar” - a novel computerized algorithm, which continuously scans the hospital's database, and detects in real-time elderly inpatients (over the age of 65) who have been hospitalized with a fall as part of their anamnestic data.
· As soon as the algorithm detected a “post-fall” inpatient, a structured action plan was executed immediately - a physiotherapist performed a functional assessment to evaluate the patient, provided treatment and education for him, his family and the nursing staff regarding fall prevention. Furthermore, recommendations regarding continued physiotherapy treatment after discharge were given.
Results: The program was implemented throughout 2017 as a pilot, and its results were measured quarterly.
1. The program detected, in real time, 62.7% of all “post-fall” inpatients (who were identified retrospectively by analyzing discharged patients' medical records).
2. 86% of the inpatients who were detected by the program received treatment.
3. During the program, inpatients' fall rate declined from 6.2 (per 1000 hospitalization days) to 1.7.
In light of the program's success, its operation was integrated into daily hospital routine.
Conclusion(s): There was an improvement in the rate of “post-fall” inpatients detection, which led to an improvement in the rate of “post-fall” inpatients who received physiotherapy treatment and a reduction in the rate of inpatients׳ falls.
In light of the project's effectiveness, its implementation will be extended to other fields, such as mental health.
A future study will examine whether recurrent falls were prevented in the long term among patients who were treated as part of the program.
Implications: The program, which was carried out without dedicated financial cost, is applicable with relative ease almost in every hospital. In addition, the program demonstrates how initiative, multidisciplinary cooperation and creative thinking can leverage technology in order to upgrade and refresh physiotherapy even in a classic field such as fall prevention and empower the profession.
Keywords: Fall Prevention, Intervention Program, Algorithm
Funding acknowledgements: The work was unfunded.
Topic: Older people; Information management, technology & big data; Health promotion & wellbeing/healthy ageing
Ethics approval required: No
Institution: Assaf Harofeh Medical Center
Ethics committee: The management of the hospital
Reason not required: Since it’s a fall prevention quality project, not a research.
All authors, affiliations and abstracts have been published as submitted.
