Evidence map›Paper›PMID 35443649›Full record

ArticleBMC medical informatics and decision making2022

Development of clinical-guideline-based mobile application and its effect on head CT scan utilization in neurology and neurosurgery departments.

Zahra Meidani, Fatemeh Atoof, Zohre Mobarak, Ehsan Nabovati, Reza Daneshvar Kakhki, Ebrahim Kouchaki, Esmaeil Fakharian, Ali Mohammad Nickfarjam, Felix Holl

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Article in BMC medical informatics and decision making, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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

  1. Pooled it
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  3. 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

9 authors.

Zahra MeidaniHealth Information Management Research Center, Kashan University of Medical Sciences, Kashan, Iran. meydani_za@kaums.ac.ir.
Fatemeh AtoofDepartment of Biostatistics & Epidemiology, Faculty of Health, Kashan University of Medical Sciences, Kashan, Iran.
Zohre MobarakDepartment of Health Information Management and Technology, Faculty of Allied Medical Sciences, Kashan University of Medical Sciences, Kashan, Iran.
Ehsan NabovatiHealth Information Management Research Center, Kashan University of Medical Sciences, Kashan, Iran.
Reza Daneshvar KakhkiAutoimmune Diseases Research Center, Kashan University of Medical Sciences, Kashan, Iran.
Ebrahim KouchakiDepartment of Neurology, Faculty of Medicine, Kashan University of Medical Sciences, Kashan, Iran.
Esmaeil FakharianTrauma Research Center, Kashan University of Medical Sciences, Kashan, Iran.
Ali Mohammad NickfarjamHealth Information Management Research Center, Kashan University of Medical Sciences, Kashan, Iran.
Felix HollDigiHealth Institute, Neu-Ulm University of Applied Sciences, Neu-Ulm, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is little evidence regarding the adoption and intention of using mobile apps by health care professionals (HCP) and the effectiveness of using mobile apps among physicians is still unclear. To address this challenge, the current study seeks two objectives: developing and implementing a head CT scan appropriateness criteria mobile app (HAC app), and investigating the effect of HAC app on CT scan order.

methodsA one arm intervention quasi experimental study with before/after analysis was conducted in neurology & neurosurgery (N&N) departments at the academic hospital. We recruited all residents' encounters to N&N departments with head CT scan to examine the effect of HAC app on residents' CT scan utilization. The main outcome measure was CT scan order per patient for seven months at three points, before the intervention, during the intervention, after cessation of the intervention -post-intervention follow-up. Data for CT scan utilization were collected by reviewing medical records and then analyzed using descriptive statistics, Kruskal-Wallis, and Mann-Whitney tests. A focus group discussion with residents was performed to review and digest residents' experiences during interaction with the HAC app.

resultsSixteen residents participated in this study; a total of 415 N&N encounters with CT scan order, pre-intervention 127 (30.6%), intervention phase 187 (45.1%), and 101 (24.3%) in the post-intervention follow-up phase were included in this study. Although total CT scan utilization was statistically significant during three-time points of the study (P = 0.027), no significant differences were found for CT utilization after cessation of the intervention (P = 1).

conclusionThe effect of mobile devices on residents' CT scan ordering behavior remains open to debate since the changes were not long-lasting. Further studies based on real interactive experiences with mobile devices is advisable before it can be recommended for widespread use by HCP.

Indexed as

Mobile ApplicationsNeurologyNeurosurgeryHumansSurveys and QuestionnairesTomography, X-Ray ComputedCell phoneIntentionMedical recordMobile applicationsPhysiciansTomography X-ray computed

Identifiers

PMID35443649
PMCPMC9020029

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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.