Evidence map›Paper›PMID 38199790›Full record

ArticleBMJ open ophthalmology2024

Feasibility of an artificial intelligence phone call for postoperative care following cataract surgery in a diverse population: two phase prospective study protocol.

Amin Hatamnejad, Aisling Higham, Sohel Somani, Eric S Tam, Ernest Lim, Sarah Khavandi, Nick de Pennington, Hannah H Chiu

Open access · goldAbstract read
In one paragraph

Article in BMJ open ophthalmology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
3.1field-weighted citation impact, top 9% of its field
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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. A Review of Recent Developments in Artificial Intelligence and Big Data Technologies for Ophthalmology Referrals and Clinical Practice.Medical science monitor : international medical journal of experimental and clinical research · 2026
    Review
  2. Review
  3. Review
  4. Applications of Artificial Intelligence in Cataract Surgery: A Review.Clinical ophthalmology (Auckland, N.Z.) · 2024
    Review
  5. 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

8 authors at 4 institutions in 2 countries.

Amin HatamnejadMcMaster University Michael G DeGroote School of Medicine, Hamilton, Ontario, Canada.ORCID 0000-0002-4714-738X
Aisling HighamUfonia Limited, Oxford, UK.
Sohel SomaniDepartment of Opthalmology and Vision Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
Eric S TamDepartment of Opthalmology and Vision Sciences, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
Ernest LimUfonia Limited, Oxford, UK.
Sarah KhavandiUfonia Limited, Oxford, UK.
Nick de PenningtonUfonia Limited, Oxford, UK.
Hannah H ChiuMcMaster University Michael G DeGroote School of Medicine, Hamilton, Ontario, Canada hannah.chiu@mail.utoronto.ca.
University of Toronto · CAMcMaster University · CARoyal Berkshire Hospital · GBUniversity of York · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionArtificial intelligence (AI) development has led to improvements in many areas of medicine. Canada has workforce pressures in delivering cataract care. A potential solution is using AI technology that can automate care delivery, increase effectiveness and decrease burdens placed on patients and the healthcare system. This study assesses the use of 'Dora', an example of an AI assistant that is able to deliver a regulated autonomous, voice-based, natural-language consultation with patients over the telephone. Dora is used in routine practice in the UK, but this study seeks to assess the safety, usability, acceptability and cost-effectiveness of using the technology in Canada. METHODS AND ANALYSIS: This is a two-phase prospective single-centred trial. An expected 250 patients will be recruited for each phase of the study. For Phase I of the study, Dora will phone patients at postoperative week 1 and for Phase II of the study, Dora will phone patients within 24hours of their cataract surgery and again at postoperative week 1. We will evaluate the agreement between Dora and a supervising clinician regarding the need for further review based on the patients' symptoms. A random sample of patients will undergo the System Usability Scale followed by an extended semi-structured interview. The primary outcome of agreement between Dora and the supervisor will be assessed using the kappa statistic. Qualitative data from the interviews will further gauge patient opinions about Dora's usability, appropriateness and level of satisfaction. ETHICS AND DISSEMINATION: Research Ethics Board William Osler Health System (ID: 22-0044) has approved this study and will be conducted by guidelines of Declaration of Helsinki. Master-linking sheet will contain the patient chart identification (ID), full name, date of birth and study ID. Results will be shared through peer-reviewed journals and presentations at conferences.

Indexed as

Artificial IntelligenceCataractFeasibility StudiesHumansPostoperative CareProspective StudiesTelemedicine

Identifiers

PMID38199790
PMCPMC10806655
OpenAlexW4390709033

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.