Evidence map›Paper›PMID 40873609›Full record

ReviewDigital health

The climate impacts of healthcare digitalization: A scoping review.

Ari Nissinen, Atte Pitkänen, Anton Barchuk, Aida Hosseinian, Annika Johansson, Matti Kaisti, Jaakko Karvonen, Pekka Marttinen, Hans Moen, Emilia Peltola and 2 more

Abstract readReview
In one paragraph

Review in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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

3 citing papers in PubMed.

  1. Article
  2. Review
  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

12 authors.

Ari NissinenClimate Solutions Unit, Finnish Environment Institute (Syke), Helsinki, Finland.ORCID https://orcid.org/0000-0003-3413-2581
Atte PitkänenClimate Solutions Unit, Finnish Environment Institute (Syke), Helsinki, Finland.ORCID https://orcid.org/0000-0003-4253-5735
Anton BarchukFaculty of Medicine, University of Helsinki, Helsinki, Finland.ORCID https://orcid.org/0000-0002-4629-3326
Aida HosseinianClimate Solutions Unit, Finnish Environment Institute (Syke), Oulu, Finland.ORCID https://orcid.org/0000-0001-8903-3156
Annika JohanssonClimate Solutions Unit, Finnish Environment Institute (Syke), Helsinki, Finland.ORCID https://orcid.org/0000-0003-2669-9545
Matti KaistiDepartment of Computing, University of Turku, Turku, Finland.ORCID https://orcid.org/0000-0001-8118-2851
Jaakko KarvonenCircular Economy Solutions Unit, Finnish Environment Institute (Syke), Joensuu, Finland.ORCID https://orcid.org/0000-0002-9972-3801
Pekka MarttinenDepartment of Computer Science, Aalto University, Espoo, Finland.ORCID https://orcid.org/0000-0001-7078-7927
Hans MoenDepartment of Computer Science, Aalto University, Espoo, Finland.ORCID https://orcid.org/0000-0003-1418-7892
Emilia PeltolaDepartment of Mechanical and Materials Engineering, University of Turku, Turku, Finland.ORCID https://orcid.org/0000-0002-8868-9273
Laura SokkaClimate Solutions Unit, Finnish Environment Institute (Syke), Helsinki, Finland.ORCID https://orcid.org/0000-0003-3469-9297
Kari A O TikkinenFaculty of Medicine, University of Helsinki, Helsinki, Finland.ORCID https://orcid.org/0000-0002-1389-8214

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The rapid digitalization of healthcare has implications for its carbon footprint. The goal of this scoping review was to identify how digitalization is proceeding in healthcare and the mechanisms through which it can affect the climate impacts of healthcare. Methods: The scoping review was conducted following PRISMA guidelines and utilized the databases Web of Science and PubMed to identify literature on the climate impacts of digitalization in healthcare. The literature search identified 32 relevant studies. In addition, diagnostics, overdiagnosis, self-tracking technologies, and artificial intelligence (AI) were identified as key topics not sufficiently represented in the literature review, and related articles were added into the material. Results: Most carbon footprint analyses focused on telemedicine solutions, but research topics also included health informatics, education, diagnoses, overdiagnosis, treatments, medical appliances, robotics, and AI. Regarding telemedicine, the carbon footprint of the virtual consultations ranged between 0·005 and 3 kgCO2e, while the in-person healthcare clinic visits ranged between 0·57 and 178 kgCO2e depending on the mode of transport used, the difference in the carbon footprint being 79-99%. Although the transparency of carbon footprint analyses was often low, system boundaries were often different, and the evidence for digitalization decreasing or increasing climate impacts was limited. Conclusions: The findings highlight the need for future research on these topics and that leadership and setting strategic goals in particular were missing in the literature. Our scoping review also presents a framework for digitalization-related topics and means for advancing a lower carbon footprint in healthcare.

Indexed as

artificial intelligencecarbon footprintdiagnosesdigital healthDigitalizationgreenhouse gas emissionshealthcarehospitalsleadershipmedical appliancesprocurementtelemedicine

Identifiers

PMID40873609
PMCPMC12378540

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.