Technologies for fall risk assessment and conceptual design in personal health record system

Milla Immonen, Heidi Similä, Mikko Lindholm, Raija Korpelainen, Timo Jämsä

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Falls among older people are a major economic and public health problem. Due to the demographic change and aging of populations, there is an urgent need for accurate screening tools to identify those at risk to target effective falls prevention strategies. Clinical fall risk assessments are costly and time-consuming and thus cannot be performed frequently. Technologies provide means for assessing fall risk during daily living, making self-evaluations and fast methods for fall risk assessment for professional use.

This study collects and evaluates existing technological solutions for fall risk assessment including various different sensor technologies. The study also presents one easy to use solution for assessing fall risk and suggests a concept-design for integrating sensor-based solutions into the Finnish national Kanta Personal Health Record.

The optimal solution for technological fall risk assessment is still unclear. A wide implementation still requires extensive validation studies, adoption to health care processes and novel IoT -solutions for collecting large amounts of sensor data. Thorough methods should be utilised in designing the privacy and security aspects of fall risk assessment solutions, as well as different user profiles, to allow suitable interfaces and visualisations to users. It should always be clear what kind of data are collected from users and how the data are utilised. The consent of the users should also always be collected.
Original languageEnglish
Pages (from-to)53-67
JournalFinnish Journal of eHealth and eWelfare
Volume11
Issue number1-2
DOIs
Publication statusPublished - 10 Mar 2019
MoE publication typeNot Eligible

Fingerprint

Conceptual design
Risk assessment
Health
Sensors
Public health
Medical problems
Health care
Screening
Visualization
Aging of materials
Economics

Keywords

  • falls
  • patient generated health data
  • health technology
  • wearable technology
  • primary prevention
  • risk assessment

Cite this

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title = "Technologies for fall risk assessment and conceptual design in personal health record system",
abstract = "Falls among older people are a major economic and public health problem. Due to the demographic change and aging of populations, there is an urgent need for accurate screening tools to identify those at risk to target effective falls prevention strategies. Clinical fall risk assessments are costly and time-consuming and thus cannot be performed frequently. Technologies provide means for assessing fall risk during daily living, making self-evaluations and fast methods for fall risk assessment for professional use.This study collects and evaluates existing technological solutions for fall risk assessment including various different sensor technologies. The study also presents one easy to use solution for assessing fall risk and suggests a concept-design for integrating sensor-based solutions into the Finnish national Kanta Personal Health Record.The optimal solution for technological fall risk assessment is still unclear. A wide implementation still requires extensive validation studies, adoption to health care processes and novel IoT -solutions for collecting large amounts of sensor data. Thorough methods should be utilised in designing the privacy and security aspects of fall risk assessment solutions, as well as different user profiles, to allow suitable interfaces and visualisations to users. It should always be clear what kind of data are collected from users and how the data are utilised. The consent of the users should also always be collected.",
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Technologies for fall risk assessment and conceptual design in personal health record system. / Immonen, Milla; Similä, Heidi; Lindholm, Mikko; Korpelainen, Raija; Jämsä, Timo.

In: Finnish Journal of eHealth and eWelfare, Vol. 11, No. 1-2, 10.03.2019, p. 53-67.

Research output: Contribution to journalArticleScientificpeer-review

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