Author(s)

Name

Publication Year

Study Location

Study Objective

AI Technology

Healthcare Area or Disease Studied

Type of Evaluation Employed

Key Findings

Pifer, R.

2023

United States

To estimate potential cost savings from implementing AI in healthcare

Not Specified

Healthcare

system

Cost

analysis

Implementation of AI could save:

Ÿ The US healthcare system $200 - 360 billion annually.

Ÿ Private payers between $80 - 110 billion annually.

Ÿ Physician groups between $20 - 60 billion annually.

Spatharou et al.

2020

Europe

To explore how AI can support improvements in care outcomes, patient experience and access to healthcare

services.

Various AI applications

Healthcare

system

Cost

analysis

AI can Minimize inefficiencies, create cost-effective healthcare ecosystem, and maximize

return on investment.

Sahni et al.

2023

United States

To estimate potential impact of wider AI adoption on US healthcare spending

Various AI applications

Healthcare

system

Cost

analysis

Wider AI implementation could result in 5% - 10% savings in US healthcare spending annually.

Ramessur et al.

2021

Not

specified

To examine cost impact of integrating AI and telemedicine in ophthalmology

AI and telemedicine

Ophthalmology

Literature

Review

Integration led to 15% reduction in urgent transfers and 24% reduction in outreach consultations, saving $1.1 million

Ruamvibo- onsuk et al.

2021

Not specified

To discuss

economic evaluations of AI in ophthalmology

AI software

Ophthalmology

(retinopathy

screening)

Literature

review

AI could enhance quality and reduce cost

Leeuwenthe et al.

2022

Not specified

To discuss how

AI improves efficiency and outcomes in radiology

Various AI applications relevant to radiology

Radiology

Literature

review

AI shows promise in streamlining workflow, speeding interpretation, and improving accuracy and personalization.

Rossi et al.

2022

Not specified

To analyze cost-effectiveness of AI applications in medicine

Various AI applications

Healthcare

system

Literature

review

Results are diverse. Cost-effectiveness depends on use cases and assumed effects of diagnosis.

Khanna et al.

2022

Not specified

To evaluate AI technology in the context of healthcare costs, namely in the areas of diagnosis and treatment

Various AI applications

Diagnosis

&

treatment

Literature

review

AI can save time for diagnosis & treatment which in turn results in cost-saving.

Rossi et al.

2022

Not specified

To analyze cost-effectiveness of AI as decision-support system for disease detection

AI models

dermatology,

dentistry,

and

ophthalmology

Cost- effectiveness

analysis

using

Markov

models

AI can effectively detect and assess melanoma, dental caries, and diabetic retinopathy at a lower cost compared to standard care

De Vos et al.

2022

Not specified

To investigate cost-effectiveness of machine

learning tool for ICU patients

Prediction model

(Pacmed Critical)

Intensive

care

units

Literature

Review

Pacmed Critical for ICE was a cost-effective strategy and continued to be cost-effective when compared to standard care