JHeS (Journal of Health Studie.
e-ISSN 2549-3353 p-ISSN 2549-3345 Vol.
No.
, pp.
https://doi.
org/10.
31101/jhes.
Literature Review Remote health information systems for falls prevention in older adults at home: a scoping review Dian Rizki Ramadhani.
Alfiana Maulida Rahmah* .
Decky Nurhadi Sopyan.
Novi Rohmawati.
Putri Ramadhanti.
Sali Zakiah Muslim Master of Nursing.
Faculty of Medicine.
Public Health and Nursing.
Universitas Gadjah Mada.
Yogyakarta.
Indonesia alfianamaulidar@gmail.
Submitted: June 10, 2025 Revised: August 7, 2025 Accepted: August 23, 2025 Abstract This review is to describe the remote health information system related to falls in the elderly used at home.
conducted a literature review using the Population Content Context (PCC) method.
The databases used include EBSCOHost.
Cochrane, and Scopus.
The keywords used are .
elehealth OR telemedicine OR telenursing OR mhealth OR e-healt.
AND .
lderly OR geriatri.
AND falls AND home.
The article selection process was done with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol.
As a result, 587 publications were identified and screened using the inclusion criteria.
The assessment of article quality is conducted through assessment by design and manual assessment.
The final result was 18 articles.
The results of the article identification discussed the risk of falls, falls prevention, fall events, fear of falls, and response to falls with elderly respondents aged Ou 55 years.
So, there are various types of technologies used, namely sensor-based, phone calls, video conferencing, web, applications, force plates .
tyle plate.
, tablet computers, smartphones.
Artificial Intelligence (AI), and Virtual Reality (VR).
The remote health information system has been proven to provide many benefits related to falls on the elderly at home.
Keywords: elderly.
Introduction Patient safety refers to minimizing preventable harm to patients at an acceptable level.
It involves a system of culture, processes, behaviors, technology, and environment in healthcare that reduces risks, prevents avoidable injuries, and minimizes the impact of errors (WHO, 2.
Common threats to patient safety include medication errors, surgical errors, healthcare-associated infections, sepsis, diagnostic errors, thromboembolism, pressure ulcers, unsafe transfusion or injection practice, misidentification, and patient falls (WHO, 2.
Falls are the second leading cause of accidental injury-related deaths worldwide, with an estimated 000 deaths annually.
More than 80% occur in low- and middle-income countries, and adults over 60 experience the highest rates (WHO, 2.
In Indonesia, data show falls-related injuries among older adults are common 7,7% in the 55-64 age group, 8,1% in those aged 65-74, and 9,2% in those 75 and older (Kemenkes RI, 2.
Risk increases with age due to vision decline, muscle loss, reduced mobility, and delayed responses to hazards such as tripping or slipping (Julianto et al.
, 2.
International Patient Safety Goals (IPSG) emphasize preventing falls across healthcare services (The Joint Commission, 2.
Recommended strategies include education, exercise, environmental modifications, and policy development (WHO, 2.
Research has shown that well-designed exercise programs can reduce falls among community-dwelling older adults by approximately 23% (Sherrington et al.
, 2.
This is an open-access article under the CCAeBY-SA license (Dian Rizki Ramadhani et al.
Integrated intervention involving professionals, nurses, and patients is essential.
These include raising awareness, identifying risks, implementing prevention, and providing treatment and rehabilitation for those who have fallen or are at high risk (Matchar et al.
, 2.
Information and communication technology (ICT) supports these efforts by enabling communication, decision-making, training, and education.
Digital technologies can deliver exercise programs effectively at low cost and with high accessibility, thereby improving motivation and compliance (Valenzuela et al.
, 2.
Based on this, in reducing the risk and occurrence of falls, the elderly can use information technology, for example, telehealth, telemedicine, telenursing, and so on.
Telehealth, which uses ICT to deliver health services remotely, has shown benefits such as improved access, timeliness, and efficiency, including for older adults in remote areas (Elbaz et al.
However, based on our review, we found that no previous scoping review specifically explores remote health information systems related to falls in older adults at home.
Therefore, this study aims to describe the use of remote health information systems in falls prevention and management among older adults living at home.
Research Methods The reference of this scoping review uses three databases, namely EBSCOHost.
Cochrane, and Scopus.
The search was conducted on September 6, 2023, limiting the publication year to between The strategy used to search for articles is the Population Content Context (PCC) framework, where the population (P) is the elderly.
the concept (C) is a falls-related remote health information system.
and context (C) is used at home.
The complete search strategy for each database is presented in Table Database EBSCOHost Cochrane Scopus Keywords Informatic tools OR telehealth AND elderly AND falls AND home Informatic tools OR m-health AND AuelderlyAy AND falls AND home .
elehealth OR telemedicine OR telenursing OR m-health OR e-healt.
AND .
lderly OR geriatri.
AND falls AND homeAy.
The article selection process in this study uses the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol.
Inclusion criteria: .
published in 2018-2023.
is a full-text article.
article published in English.
the research subjects are the elderly.
explaining remote information systems in health .
home use.
It is a primary research article .
ther than an abstract, poster, narrative review, literature review, scoping review, systematic review, book chapter, proceedings, guidelines, conference and consensu.
The assessment of article quality is conducted through both design-based evaluation and manual evaluation, which considers factors such as currency, relevance, authority, accuracy, and purpose.
The final result was obtained from 18 articles used in the scoping review.
The selection of study articles can be illustrated in the following PRISMA diagram (Figure .
JHeS (Journal of Health Studie.
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Article after duplication .
= 2.
Duplication articles .
= .
Screened articles .
= .
Excluded articles .
= 2.
Full-text articles assessed for quality and .
= .
Full-text articles were excluded, based on certain .
Included Eligibility Screening Identification Articles identified based on data database EBSCOHost: 2437 Cochrane: 22 Scopus: 128 .
= 2.
Selected articles .
Figure 1.
PRISMA Diagram for the Article Screening Process.
Results and Discussion Results Based on the results of the literature search, 18 articles were found explaining falls, consisting of 9 articles discussing the risk of falls, 5 articles discussing falls prevention, 2 articles discussing the occurrence of falls, 1 article discussing the fear of falls, and 1 article discussing responses to falls.
The articles used come from 12 countries from the European continent, 3 countries from the Asian continent, 2 countries from the American continent, and 1 country from the Australian continent.
The elderly who were the respondents to the study were those Ou 55 years old, but the majority of studies included the age of Ou 65 years as an inclusion criterion.
The health information system contained in the 18 articles uses various types of technology, including sensor-based (Greene et al.
, 2021.
Pedrero-Synchez et al.
, 2023.
Qiu et al.
, 2018.
Watson et , 2.
, phone calls (Bernocchi et al.
, 2019.
Pettersson et al.
, 2019.
Pfeiffer et al.
, 2.
, video conference (Bernocchi et al.
, 2019.
Li et al.
, 2021.
Sari et al.
, 2023.
Tomita et al.
, 2.
Web (Gaspar & Lapyo, 2022.
Hamm et al.
, 2.
, application (Hamm et al.
, 2019.
Mansson et al.
, 2.
, force plate (Gallamini et al.
, 2021.
Sadura-Sieklucka et al.
, 2.
, tablet computer (Delbaere et al.
, 2.
smartphone (Yi & Yim, 2.
Artificial Intelligence (AI) (Buisseret et al.
, 2.
, and Virtual Reality (VR) (Sadura-Sieklucka et al.
, 2.
The entire health information system is applied to the elderly at home, and there is a remote data exchange.
Of the 18 articles about remote health information systems related to falls in the elderly used at home, all have positive effects, including can be used to assess the risk of falls, reduce the risk of falls, be useful for falls prevention, reduce the incidence of falls, reduce the fear of falls, and accelerate the response of helpers to falls experienced by the elderly at home.
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Table 1.
Article Review Table Information Data Research Results Systems Outcome Inertial sensors Risk of Accurately (Five body falling between falling and not with an overall accuracy of 4% .
ensitivity of 7% and specificity of 9%).
Thus, this tool is an innovative method for multifactorial fall risk assessment in the elderly.
HomeFalls The Home-TeleHealth TeleHealth program is effective in .
hone reducing the incidence of falls and the fear of falling conferences, and at home for 6 months of home visit.
Author and Year (Qiu et al.
Research Location South Korea Level of Evidence i (Quasiexperimenta.
(Bernocchi Italian II (RCT) (Tomita et , 2.
USA
II (RCT)
Virtual-Group Exercise Home (VGEAH) Program Risk The V-GEAH program during 3 months of use is effective in reducing the risk of falls in the elderly.
(Pettersson Swedish (Qualitativ.
Mobile phonebased physical Falls Prevention Mobile phone-based physical fitness, balance, and confidence to prevent No.
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Strengths/Limitations Limitations:
focused on the major intrinsic factors for fall risk assessment, used retrospective falls.
Strengths: prospective design, large sample size .
, 6-month follow-up, feasibel and safety .
he absence of side effects, patient Limitations: was not blind patients and health care personnel to the group allocation .
ssessors and data analysts were blinde.
, single-center falls were self-reported Limitation:
adherences of this follow-up study was low compared to the adherences level of the VGEAH study, which was very Strengths:
different recruitment settings .
ichness of dat.
and variety of researchers which may Limitation: one of the interviewers had met (Dian Rizki Ramadhani et al.
No.
Author and Year Research Location Level of Evidence Information Systems Data Outcome Research Results (Hamm et , 2.
English i (Mixed Guidetomeasure3D, a web-based Risk The Guidetomeasure-3D application has proven to be more accurate and consistent in assisting the elderly in carrying out self-assessment measurement tasks as part of the fall risk assessment process at home compared to using a booklet.
(Mansson Swedish
II (RCT)
Safe Step v1 Falls Prevention (Pfeiffer et , 2.
German
II (RCT)
"Step by Step", four phone calls and one home visit program Fear Respondents who used digital programs with the Safe Step v1 application had a higher level of compared to those who Respondents also reported high levels of satisfaction and felt supported by the The "Step by Step" reducing the fear of falling and improving physical activity and physical performance in the short term in the elderly.
However, the effect on the duration of daily walking is not significant.
(Buisseret Belgium i (Cohor.
A combination of the Timed Up and Go (TUG) SixMinute Walking test using an Inertial Measurement Risk JHeS (Journal of Health Studie.
The use of a combination of Timed Up and Go (TUG) tests.
Six-Minute Walking Inertial Measurement Units (IMU.
Artificial Intelligence (AI) increases the accuracy of Strengths/Limitations participants during the follow-up meeting.
Strength:
explored and discussed the generalisability and transferability of The Guidetomeasure-3D application and how it may influence and contribute to healthcare Strengths: RCT design, focus on vulnerable elderly groups.
Limitations:
sample size .
, short study duration.
Strengths: RCT study design, the crosectoral design of the programme and the monitoring for quality Limitations:
exclusion of about onethird cognitive impairment and missing data on Strengths: innovative measuring fall risk in the elderly, focus on a six-month prediction rather than on real-time (Dian Rizki Ramadhani et al.
No.
Author
and Year
Research
Location Level of Evidence Information Systems Unit (IMU), and Artificial Intelligence (AI) Data
Outcome (Delbaere Australia
II (RCT)
The computer-based "Standing Tall Balance ExerciseAy Falls (Yi Yim.
South
Korea
II (RCT)
Remote HomeBased Exercise Program based Falls Prevention JHeS (Journal of Health Studie.
Research Results Strengths/Limitations predicting the risk of falls in the elderly.
The AI algorithm achieved 75% accuracy, specificity, and sensitivity in predicting falls risk.
The Standing Tall Balance Exercise program has a significant effect on the reduction of falls rates and injury rates after 24 Limitations:
classification in this study, based on a convolutional neural The Remote Home-Based Exercise Program has a improving physical and .
hich important factor in falls The experienced a decrease in Geriatric Depression Scale Strengths: large sample size, broad inclusion criteria and use of methods designed to reduce the risk of bias such as concealed random allocation to outcome assessment, intention-totreat preregistered statistical analysis plan.
Limitations:
was not possiblen .
isk of bias by expectatio.
, multiple testing of the results could introduce error, the results might not generalise to usage in more rural or less affluent areas, the weekly education fact sheets have induced a behaviour change in control group that might reduce statistical Limitations:
organizations on a volunteer basis, which might restrict generalizability to the wider population.
(Dian Rizki Ramadhani et al.
No.
Author and Year Research Location Level of Evidence Information Systems Data Outcome Research Results (GDS) scores, an increase in hand grip strength and Four Square Step Test (FTSS) scores, and an increase in static balance compared to the control The Tai Ji Quan program at home, virtually and interactively, delivered in real-time, as a balance training and potential falls prevention intervention for the elderly.
(Li et al.
USA
(RCT,
Tai Ji Quan (Balance Exercise Online/Zoo.
Falls Prevention (Watson et , 2.
English (Qualitative Response to Falls Rapid response alarm technology and telecare services encourage elderly seniors and caregivers feel safe, delay or prevent seniors from moving to nursing homes, and reduce stress and anxiety reported by caregivers (Greene et , 2.
Irish i (Study Repor.
Rapid response alarm technology .
ombination of self-activated sensors i.
sensors, smoke sensors, pressure telecare services Inertial sensors Risk The use of smartphone applications with inertial sensors can be used to measure the risk of falls and balance disturbances in the elderly (Gallamini Italian i (Cohor.
ArgoplusMK1, a balance exercise using a force plate to assess postural control in individuals.
Risk ArgoplusMK1 identify balance deficits in the elderly as a costeffective and non-invasive screening tool to identify individuals at risk of falls.
JHeS (Journal of Health Studie.
Strengths/Limitations Limitations: falls data via self-reports .
isk of recall bia.
, did not older adults at high risk of falling .
e, persons with multiple falls or Limitations:
Strengths: the largest research on the use of smartphones for fall Limitations:
unreliable and underreport the incidence of Strengths:
Limitations:
population, and limited (Dian Rizki Ramadhani et al.
No.
Author and Year Research Location Level of Evidence Information Systems Data Outcome Research Results Strengths/Limitations Limitations: sampling intentional, and the focus groups were conducted remotely via Zoom due to SARSCoV-2 follow-up time period .
hree month.
Strengths:
reliability, simple, easy to use, and costeffective.
Limitations:
(Gaspar & Lapyo.
Portugal i (Explanatory "BALANCE" implemented and integrated with METHIS .
eb Risk The BALANCE digital service is very helpful in the rehabilitation process of patients with balance disorders who have a risk of falling (PedreroSynchez et , 2.
Spanish i (Quasiexperimenta.
Risk The smartphone-based inertial sensors allows for accurate classification of falls risk in the elderly and can be a useful screening tool in clinical settings.
The tool is also easy to use (SaduraSieklucka Polish
II (RCT)
Risk e-Health with Virtual Reality is influential in reducing the vulnerability of falls in the elderly Limitation:
(Sari et al.
Indonesian i (Preexperimen.
Smartphonebased 3D inertial sensor, data is recorded at 100 Hz by the sensor.
The smartphone is attached with a fastener around the participant's Force balance exercise combined with Virtual Reality (VR) Telehealth video Falls Prevention Telehealth through video conferencing for 12 weeks supervised by a nurse affects improving physical activity levels and quality of life as well as preventing disability Strength: first study to provide evidence on feasibility of telehealth home-based exercise programs for older people in Indonesia.
Limitations:
same physiotherapist performed the online assessments with the participant and carer as exercise program, and self-reported assessment conducted Discussion The elderly have a high risk of falling.
The incidence rate of falls among the elderly is 30% for those over 65 years old, and it will double for those over 80 years old.
Falls are the leading cause of JHeS (Journal of Health Studie.
(Dian Rizki Ramadhani et al.
disability among the elderly and can potentially result in mortality (Pedrero-Synchez et al.
, 2.
The experience of falling causes fear and trauma in the elderly, which can disrupt daily activities and potentially lead to social isolation (Mansson et al.
, 2.
To reduce the risk of falls in the elderly, currently health information systems have been developed using various modern information and communication technologies.
The rapid expansion and confluence of digital technologies has a significant impact on daily life.
These technologies have begun to play an important role in health care, and their potential to improve public health is a source of great interest (Falzon et al.
, 2.
Telemedicine is defined as the use of telecommunications and information technology to provide healthcare data and services to patients living far away.
It involves the transfer of data through electronic signals and includes the use of electronic medical records (EMR) to facilitate access to patient Telemedicine encompasses various applications, including remote clinical consultations, diagnostic tests, and patient guidance, which improve communication between healthcare providers and patients across geographical boundaries (Sachdeva & Ali, 2.
Telemedicine provides various benefits, including cost savings, convenience, and enhanced access to healthcare for individuals with mobility restrictions or living in rural areas (Das et al.
, 2.
Teleconferencing services, such as video conferencing through Zoom, are widely used for longdistance communication.
Teleconferencing enables health professionals to work with the elderly to develop exercise programs that increase their physical activity and quality of life (Sari et al.
, 2.
The study found that a 12-week intermittent telehealth-based exercise program delivered via video conferencing improved physical activity levels, several aspects of function .
ower extremity domai.
and disability .
otal frequency dimension and personal role domai.
, health-related sports benefits, exercise enjoyment, and quality of life for the elderly with dementia living in Indonesian communities (Sari et al.
, 2.
The Virtual-Group Exercise at Home (V-GEAH) program, which is an exercise program conducted at least twice a week for three months, can significantly reduce the risk of falls in the elderly who have a history of falls, especially for those who follow the program (Tomita et al.
The Remote Home-Based Exercise Program, which includes training videos and is monitored remotely by a therapist who contacts patients twice a week, significantly improves physical and psychological function, improves balance, and prevents falls in the elderly (Yi & Yim, 2.
Another study suggests that exercise programs for fall prevention can increase muscle strength, which is directly related to improved physical function in the elderly (Lacroix et al.
, 2.
By designing the right exercise program and using media that can be used by the elderly will be very helpful in the rehabilitation programs of older individuals at risk of falling (Gaspar & Lapyo, 2.
Some of the benefits of digital health services for patient rehabilitation include increased comfort, doctor-patient interaction .
eeling clos.
, potential motivation, and patient involvement in self-care.
Furthermore, the availability of video tutorials with balancing exercises is seen to be a good effect, since it helps patients recall exercises and motivates them to exercise, including outdoors (Wynn et al.
, 2.
These videos also allow caregivers to understand the recommended exercises (Van Vugt et al.
, 2.
The experience of using a mobile phone-based exercise application for falls prevention has a positive Some respondents said that the program supplied is simple to use, motivates them, and allows them to exercise by adjusting their abilities and the training environment they like (Hamm et al.
, 2.
Applications used and managed by the elderly themselves in their communities have proven to be very effective in reducing the risk of falling among the elderly (Delbaere et al.
, 2.
The use of the application has also proven to be more accurate and consistent than using media such as booklets or other manual faults (Hamm et al.
, 2.
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The Timed Up and Go (TUG) test is a reliable predictor of fall risk, with studies showing significant correlations between TUG performance and fall incidents (Oliveira-Zmuda et al.
, 2.
The TUG test is not only used to assess fall risk, but it also measures gait, motor speed, and physical function, making it a useful tool in geriatric care (Brucki, 2.
The use of a custom-made sensor, the ultralow-cost wearable wearable inertial sensor (DYSKIMOT), serves to capture locomotor movements during a six-minute running test, which enhances the predictive power of the TUG test regarding fall risk among elderly individuals in nursing homes, regardless of whether they have previously fallen, across two sets of measurements taken at sixmonth intervals (TUG tes.
(Buisseret et al.
, 2.
The position of the inertia of the sensor in the lumbar area is relevant because it is close to the center of body mass (Buisseret et al.
, 2.
Other studies show that this position is best for distinguishing between those who fall and those who don't (Howcroft et al.
, 2.
This study also presents kinematic data analysis based on variability assessment and Artificial Intelligence (AI) techniques.
The role of AI is to analyze data collected from wearable sensors and predict the risk of falls in nursing home residents (Buisseret et al.
, 2.
According to Avron Barr and Edward E.
Feigenbaum .
in Tjahyanti et al.
, .
Artificial Intelligence (AI) is a part of computer science that studies .
n the sense of designin.
intelligent computer systems, i.
systems that have human-like thinking characteristics.
Another study found that a rapid smartphone-based 3D inertial sensor can accurately classify the risk of falls in the elderly and could be a useful screening tool in clinical settings.
This tool is also easy to use because it is only installed around the elderly's waist (Pedrero-Synchez et al.
, 2.
The use of inertial sensor devices includes elements of all these assessments that are embedded in functional tests .
, modified TUG.
The use of this technology can allow clinicians to conduct evaluations in an average of 105 seconds, including one minute of initial explanation, making it 38 minutes shorter than the PPA protocol .
hich takes 40 minute.
(Pedrero-Synchez et al.
, 2.
This is in line with research in South Korea which states that inertial sensors can accurately distinguish between the elderly with a history of falls and those with an accuracy of 89.
4% when inertial sensors are used in assessing the risk of falls in the elderly (Qiu et al.
, 2.
In addition to being installed on the body, this inertial sensor device can also be embedded in a smartphone and linked to an application that records important data such as falls history, polypharmacy, and mobility problems (Greene et al.
, 2.
Balance exercises using force plates combined with Virtual Reality (VR) technology are effective in reducing the susceptibility of falls in the elderly (Sadura-Sieklucka et al.
, 2.
Virtual Reality (VR) is a technology that allows users to enter and interact within a virtual world, as it combines special input and output devices to enable deep interaction with the virtual environment, making it feel as if they are in the real world (Musril et al.
, 2.
The main advantage of VR is an experience that makes users feel the sensation of the real world in the virtual world (Wardhana et al.
, 2.
VR transports us to another dimension where the depiction of the state resembles the original shape of the object, when in reality we are still in the same place (Musril et al.
, 2.
These results are in line with the research of Gallamini et al.
who examined the ArgoplusMK1, a balance exercise using a force plate to assess balance and postural control in individuals.
The study's findings revealed that ArgoplusMK1 was able to identify balance deficits in the elderly as a cost-effective and non-invasive screening tool to identify individuals at risk of falling (Gallamini et al.
, 2.
Force plate-based exercises provide an effective method for teaching patients to control their physical exertion, allowing them to precisely adjust the position of their center of gravity without generating excessive inertial forces.
These excessive forces are often a direct cause of falls because they can shift the center of pressure (COP) outside the area of the foot.
Visual-motor feedback .
in posturographs consists of relating the images observed by the person standing on the force plate to his motor activity.
Over the years.
VR devices have become increasingly popular and affordable.
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makes it a good way to continue the patient's self-improvement at home, as well as to monitor their progress (Bevilacqua et al.
, 2.
Training using VR technology can be more effective in improving mental condition, mobility, and overall quality of life in older people (Maranesi et al.
, 2.
In the context of a digital approach to preventing falls, the use of technology for patient-led data capture, such as balance and falls risk assessment, is critical to enabling personalized interventions to encourage users to adopt strength and balance training routines (Hughes et al.
, 2019.
McGarrigle et al.
, 2.
Patientled data collection supports a customized rehabilitation program at home, which helps determine physiotherapist-assisted exercise protocols (Palestra et al.
, 2.
and monitor the progress of the exercise (Uzor & Baillie, 2.
Strength training, which focusses primarily on improving lower limb strength, and classical balance exercises, which should be progressive in difficulty: reducing the field of support, reducing base stability, limiting eye control, and so on.
However, the success of this exercise is also influenced by the level of patient compliance in participating in a predetermined exercise program.
Compliance with reporting training results in realtime is very useful in determining the next training program to reduce the risk of falling (Li et al.
, 2.
Overall, families or caregivers can supervise and encourage people with dementia to participate in a home exercise program with intermittent physiotherapist guidance through regular online visits, however it is more difficult to encourage them to participate when physiotherapist supervision stops.
Previous study has found that caregivers support is critical to the success of sports programs for adults with cognitive impairments/disabilities and dementia (Suttanon et al.
, 2.
Other research states that the involvement of patients, caregiver, and healthcare workers is one of the key points for the success of digital interactive solutions (Goldsack & Zanetti, 2020.
Tossaint-Schoenmakers et al.
, 2.
Despite the numerous benefits of using technology, there are several barriers to the use of digital devices in clinical settings, including the elderly's limitations in accessing and using technology, a lack of digital training, and caregiver support (Heponiemi et al.
, 2020.
Jun, 2020.
Orton et al.
, 2018.
Ricciardi et al.
, 2019.
Trenerry et al.
, 2.
Therefore, in the development of digitalization in healthcare, it is important to listen and engage with patients, family members, caregivers, healthcare professionals, and policymakers to improve the implementation of digital solutions in clinical settings (Kim et al.
, 2021.
Tossaint-Schoenmakers et al.
, 2.
Conclusion Remote health information systems currently use various types of technology, including sensorbased, phone calls, video conferencing, web, applications, force plates .
tyle plate.
, tablet computers, smartphones.
Artificial Intelligence (AI), and Virtual Reality (VR The various benefits of using these technologies include assessing the risk of falls, reducing the risk of falls, being useful for preventing falls, reducing the incidence of falls, reducing the fear of falls, and accelerating the response of rescuers to falls experienced by the elderly at home.
All of these benefits can help the elderly get the health services they need at home without having to always come to a hospital or certain health facilities.
The success of a remote health information system is also influenced by the compliance and support of various parties involved in implementing fall-related interventions in older adults, such as neighborhood associations, elderly cadres, community health centers, and local governments.
Therefore, the role of family and caregivers for the elderly is crucial.
In addition, the ease of use of technology also needs to be considered due to various limitations in the functions of the elderly.
This scoping review identified several limitations, including the varying designs, information systems, and outcomes of the journal articles used.
Therefore, the study results cannot be generalized across situations, and it cannot be determined which technology is most effective.
Therefore, future researchers can conduct experimental studies on older adults using different information systems to compare outcomes, which can then be applied to healthcare facilities and local government services.
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Acknowledgements The authors thank the institutions for their support of this study.
The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
References