Evidence map›Paper›PMID 38929777›Full record

ReviewJournal of personalized medicine2024

Exploring Health Informatics in the Battle against Drug Addiction: Digital Solutions for the Rising Concern.

Shakila Jahan Shimu, Srushti Moreshwar Patil, Ebenezer Dadzie, Tadele Tesfaye, Poorvanshi Alag, Gniewko Więckiewicz

Abstract readReview
In one paragraph

Review in Journal of personalized medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Recent Advances in AI and GenAI for Health Informatics.Healthcare (Basel, Switzerland) · 2026
    Review
  2. Article
  3. Review
  4. 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

6 authors.

Shakila Jahan ShimuDepartment of Health Informatics, Harrisburg University of Science and Technology, Harrisburg, PA 17101, USA.ORCID 0009-0007-6701-2101
Srushti Moreshwar PatilSMBT Medical College, Dhamangaon, Nashik 422403, India.
Ebenezer DadzieSchool of Clinical Medicine, Inner Mongolia University for the Nationalities, Tongliao 028000, China.
Tadele TesfayeCareHealth Medical Practice, Addis Ababa 9023, Ethiopia.ORCID 0009-0008-2531-1741
Poorvanshi AlagPsychiatry Department, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA.
Gniewko WięckiewiczDepartment of Psychiatry, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, 40-055 Katowice, Poland.ORCID 0000-0003-2404-393X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug addiction is a rising concern globally that has deeply attracted the attention of the healthcare sector. The United States is not an exception, and the drug addiction crisis there is even more serious, with 10% of adults having faced substance use disorder, while around 75% of this number has been reported as not having received any treatment. Surprisingly, there are annually over 70,000 deaths reported as being due to drug overdose. Researchers are continually searching for solutions, as the current strategies have been ineffective. Health informatics platforms like electronic health records, telemedicine, and the clinical decision support system have great potential in tracking the healthcare data of patients on an individual basis and provide precise medical support in a private space. Such technologies have been found to be useful in identifying the risk factors of drug addiction among people and mitigating them. Moreover, the platforms can be used to check prescriptions of addictive drugs such as opioids and caution healthcare providers. Programs such as the Prescription Drug Monitoring Program (PDMP) and the Drug and Alcohol Services Information Systems (DASIS) are already in action in the US, but the situation demands more in-depth studies in order to mitigate substance use disorders. Artificial intelligence (AI), when combined with health informatics, can aid in the analysis of large amounts of patient data and aid in classifying nature of addiction to assist in the provision of personalized care.

Indexed as

drug addictionelectronic health recordsPrescription Drug Monitoring Programsubstance abuse

Identifiers

PMID38929777
PMCPMC11204661

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.