Evidence map›Paper›PMID 37018019›Full record

ArticleJournal of medical Internet research2023

A "Do No Harm" Novel Safety Checklist and Research Approach to Determine Whether to Launch an Artificial Intelligence-Based Medical Technology: Introducing the Biological-Psychological, Economic, and Social (BPES) Framework.

Waqas Ullah Khan, Emily Seto

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

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

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

  1. Responsible artificial intelligence integration framework for psychiatric guidelines.The international journal of neuropsychopharmacology · 2026
    Guideline
  2. Article
  3. Opportunities and Risks of Large Language Models in Psychiatry.NPP - digital psychiatry and neuroscience · 2024
    Article
  4. Review
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

2 authors.

Waqas Ullah KhanHealth Informatics, Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada.ORCID 0000-0003-1383-6985
Emily SetoHealth Informatics, Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-8723-5915

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Given the impact artificial intelligence (AI)-based medical technologies (hardware devices, software programs, and mobile apps) can have on society, debates regarding the principles behind their development and deployment are emerging. Using the biopsychosocial model applied in psychiatry and other fields of medicine as our foundation, we propose a novel 3-step framework to guide industry developers of AI-based medical tools as well as health care regulatory agencies on how to decide if a product should be launched-a "Go or No-Go" approach. More specifically, our novel framework places stakeholders' (patients, health care professionals, industry, and government institutions) safety at its core by asking developers to demonstrate the biological-psychological (impact on physical and mental health), economic, and social value of their AI tool before it is launched. We also introduce a novel cost-effective, time-sensitive, and safety-oriented mixed quantitative and qualitative clinical phased trial approach to help industry and government health care regulatory agencies test and deliberate on whether to launch these AI-based medical technologies. To our knowledge, our biological-psychological, economic, and social (BPES) framework and mixed method phased trial approach are the first to place the Hippocratic Oath of "Do No Harm" at the center of developers', implementers', regulators', and users' mindsets when determining whether an AI-based medical technology is safe to launch. Moreover, as the welfare of AI users and developers becomes a greater concern, our framework's novel safety feature will allow it to complement existing and future AI reporting guidelines.

Indexed as

Artificial IntelligenceMobile ApplicationsChecklistGovernmentGovernment AgenciesHumansAIAI medical hardware devicesAI medical mobile appsAI medical software programsartificial intelligencebiological-psychological factorsDo No Harmeconomic factorssafety checklistsocial factors

Identifiers

PMID37018019
PMCPMC10131977

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.