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Record W2159274604 · doi:10.1186/1477-7525-4-41

Public telesurveillance service for frail elderly living at home, outcomes and cost evolution: a quasi experimental design with two follow-ups

2006· article· en· W2159274604 on OpenAlexafffundabout
Claude Vincent, Daniel Reinharz, Isabelle Deaudelin, Mathieu Garceau, Lise R. Talbot

Bibliographic record

VenueHealth and Quality of Life Outcomes · 2006
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsUniversité de SherbrookeCentre for Interdisciplinary Research in RehabilitationUniversité Laval
FundersCanadian Institutes of Health Research
KeywordsChecklistAutonomyMedicineQuality of life (healthcare)Activities of daily livingIndependent livingGerontologyNursingPsychologyPhysical therapy

Abstract

fetched live from OpenAlex

BACKGROUND: Telesurveillance is a technologically based modality that allows the surveillance of patients in the natural setting, mainly home. It is based on communication technologies to relay information between a patient and a central call center where services are coordinated. Different types of telesurveillance systems have been implemented, some being staffed with non-health professionals and others with health professional, mainly nurses. Up to now, only telesurveillance services staffed with non-health professionals have been shown to be effective and efficient. The objective of this study was to document outcomes and cost evolution of a nurse-staffed telesurveillance system for frail elderly living at home. METHODS: A quasi experimental design over a nine-month period was done. Patients (n = 38) and caregivers (n = 38) were selected by health professionals from two local community health centers. To be eligible, elders had to be over 65, live at home with a permanent physical, slight cognitive or motor disability or both and have a close relative (the caregiver) willing to participate to the study. These disabilities had to hinder the accomplishment of daily life activities deemed essential to continue living at home safely. Three data sources were used: patient files, telesurveillance center's quarterly reports and personal questionnaires (Modified Mini-Mental State, Functional Autonomy Measurement System, Life Event Checklist, SF-12, Life-H, Quebec User Evaluation of Satisfaction with Assistive Technology, Caregiver Burden). The telesurveillance technology permitted, among various functionalities, bi-directional communication (speaker-receiver) between the patient and the response center. RESULTS: A total of 957 calls for 38 registered clients over a 6-month period was recorded. Only 48 (5.0%) of the calls were health-related. No change was reported in the elders' quality of life and daily activity abilities. Satisfaction was very high. Caregivers' psychological burden decreased substantially. On a 3 months period, length of hospital stays dropped from 13 to 4 days, and home care services decreased from 18 to 10 visits/client. Total cost of health and social public services used per client dropped by 17% after the first 3 months and by 39% in the second 3 months. CONCLUSION: The ratio of 0.50 calls per client to the call center for health events is three times higher than that reported in the literature. This difference is probably attributable to the fact that nurses rather than non-health professional personnel were available to answer the clients' questions about their health and medications. Cost evolution showed that registering older adults at a telesurveillance center staffed by nurses, upon a health professional recommendation, costs the health care system less and does not have any negative effects on the well-being of the individuals and their families. Telesurveillance for the elderly is effective and efficient.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.864

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.146
GPT teacher head0.400
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations61
Published2006
Admission routes3
Has abstractyes

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