Evidence map›Paper›PMID 36850433›Full record

ArticleSensors (Basel, Switzerland)2023

Healthy Ageing: A Decision-Support Algorithm for the Patient-Specific Assignment of ICT Devices and Services.

Agnese Brunzini, Manila Caragiuli, Chiara Massera, Marco Mandolini

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Agnese BrunziniDepartment of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy.ORCID 0000-0003-0450-2510
Manila CaragiuliDepartment of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy.
Chiara MasseraDepartment of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy.ORCID 0000-0002-9660-5623
Marco MandoliniDepartment of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy.ORCID 0000-0003-0962-5982

Funding

Marche Region I36J20000910001Ministry of Economic Development I36J20000910001
6 · The paper itself

Abstract

In response to rapid population ageing, digital technology represents the greatest resource in supporting the implementation of active and healthy ageing principles at clinical and service levels. However, digital information platforms that deliver coordinated health and social care services for older people to cover their needs comprehensively and adequately are still not widespread. The present work is part of a project that focuses on creating a new personalised healthcare and social assistance model to enhance older people's quality of life. This model aims to prevent acute events to favour the elderly staying healthy in their own home while reducing hospitalisations. In this context, the prompt identification of criticalities and vulnerabilities through ICT devices and services is crucial. According to the human-centred care vision, this paper proposes a decision-support algorithm for the automatic and patient-specific assignment of tailored sets of devices and local services based on adults' health and social needs. This decision-support tool, which uses a tree-like model, contains conditional control statements. Using sequences of binary divisions drives the assignation of products and services to each user. Based on many predictive factors of frailty, the algorithm aims to be efficient and time-effective. This goal is achieved by adequately combining specific features, thresholds, and constraints related to the ICT devices and patients' characteristics. The validation was carried out on 50 participants. To test the algorithm, its output was compared to clinicians' decisions during the multidimensional evaluation. The algorithm reported a high sensitivity (96% for fall monitoring and 93% for cardiac tracking) and a lower specificity (60% for fall monitoring and 27% for cardiac monitoring). Results highlight the preventive and protective behaviour of the algorithm.

Indexed as

Healthy AgingAdultAgedAgingAlgorithmsDigital TechnologyHumansQuality of Lifedecision-support algorithmdigital healthelderlyhealthy ageingpersonalised carewearable sensors

Identifiers

PMID36850433
PMCPMC9963385

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.