Evidence map›Paper›PMID 40046357›Full record

ReviewCureus2025

Implications of Mobile Technology on Hospitalization Rates in Medically Underserved Areas Worldwide: A Systematic Review.

Matthew Heffernan, Rahul Mittal, Barbara Tafuto

Abstract readReview
In one paragraph

Review in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Matthew HeffernanHealth Informatics, Rutgers University, New Brunswick, USA.
Rahul MittalHealth Informatics, Rutgers University, New Brunswick, USA.
Barbara TafutoHealth Informatics, Rutgers University, New Brunswick, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hospitalizations in medically underserved areas remain a significant challenge, often driven by barriers such as limited access to healthcare services due to institutional barriers or physical facility access due to distance and transportation issues, inadequate preventive care, and a higher prevalence of chronic diseases. In recent years, mobile health (mHealth) technology has emerged as a promising tool to bridge healthcare gaps, offering innovative solutions to address these challenges by leveraging mobile devices to improve patient care, health monitoring, and engagement. However, while digital and mHealth interventions hold promise, implementing them in underserved areas presents unique challenges. This scoping review aims to assess the current landscape of mobile technology interventions in medically underserved areas, with a particular focus on their effects on hospitalization rates. A systematic review was conducted utilizing the PubMed, Embase, and CINAHL databases for the identification of articles to include within the review. After using the search terms in each database, a total of 416 articles were found to meet the search query. All articles were screened and reviewed based on the criteria, and 15 articles (n=15) were selected for review. The most commonly studied technologies were telehealth visits (n=9), while mobile apps (n=4), smart glasses (n=1), and remote patient monitoring devices (n=1) made up the remaining technologies studied. Hospitalizations were grouped as either inpatient hospitalizations (n=8), emergency department (ED) visits (n=4), or other hospital referrals in cases where a patient may be referred to a hospital but was not classified as either inpatient hospitalization or emergency. Across the emergency group studies, the experimental arm of the studies had a lower rate of ED visits and inpatient admissions. There could exist potential complications for evaluating these new digital technologies in rural and underserved populations, including level of education and cost. Additionally, while 15 articles were reviewed in this systematic review, there appears to be substantially more literature available for non-rural, non-underserved communities. Within the limited data currently available, we found reductions in inpatient admission rates and ED visits when utilizing digital technologies. Given the potential cost benefits that these technologies could provide, further investigation into this topic may be warranted.

Indexed as

smart health wearablewearable biosensing deviceswearable deviceswearable electronic deviceswearable health devices

Identifiers

PMID40046357
PMCPMC11881032

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.