Evidence map›Paper›PMID 35935375›Full record

ArticleFrontiers in pediatrics2022

Using a route planner to optimize door-to-door visits for a pediatric home-hospitalization program: Feasibility study.

Astrid Batlle, Imma Boada, Santiago Thió-Henestrosa, Mariona Fernández de Sevilla, Juan José García-García

Abstract read
In one paragraph

Article in Frontiers in pediatrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Astrid BatlleHospital Sant Joan de Déu, Barcelona, Spain.
Imma BoadaGraphics and Imaging Laboratory, University of Girona, Girona, Spain.
Santiago Thió-HenestrosaDepartament Informàtica, Matemàtica Aplicada i Estadística, University of Girona, Girona, Spain.
Mariona Fernández de SevillaHospital Sant Joan de Déu, Barcelona, Spain.
Juan José García-GarcíaHospital Sant Joan de Déu, Barcelona, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hospital Sant Joan de Déu (Barcelona) initiated a pediatric acute home-hospitalization program. Due to high patient turnover and the health staff's lack of planning training, daily scheduling was a time-consuming task. Home-hospitalization planning is a vehicle routing problem that can be solved with a technological solution. It was therefore decided to evaluate the efficacy and necessity of the SmartMonkey.io planner. Objectives: To compare traditional manual route planning with a route optimizer, and to evaluate the technical feasibility of the implementation of a route planner into a homecare program. Methods: Eight participants (experienced homecare staff and inexperienced hospital staff) were included. Personal interviews were performed to assess their eagerness to try a technological solution to the planning problem. Objective benefits including reduced travel time (time planning, distance traveled, and time traveled) were evaluated. Paired Results: Homecare staff were initially reluctant to use the technology. Significant differences ( Conclusions: Route-planning technology saved planning time and generated better plans than manual planning. The route planner's learning curve was fast and results were obtained in the same amount of time regardless of difficulty and expertise. SmartMonkey.io also has the potential to reduce internal and environmental costs and increase staff productivity.

Indexed as

door-to-doorenvironmental costshome-hospitalizationoptimization algorithmroute planner applicationvehicle routing problem (VRP)

Identifiers

PMID35935375
PMCPMC9353305

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Registered trials

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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.