Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Objective: This study aims to explore the opinions on the insurance coverage of artificial intelligence (AI), as categorized based on the distinct value elements offered by AI, with a specific focus on patient-centered outcomes (PCOs). PCOs are distinguished from traditional clinical outcomes and focus on patient-reported experiences and values such as quality of life, functionality, well-being, physical or emotional status, and convenience.

Materials And Methods: We classified the value elements provided by AI into four dimensions: clinical outcomes, economic aspects, organizational aspects, and non-clinical PCOs. The survey comprised three sections: 1) experiences with PCOs in evaluating AI, 2) opinions on the coverage of AI by the National Health Insurance of the Republic of Korea when AI demonstrated benefits across the four value elements, and 3) respondent characteristics. The opinions regarding AI insurance coverage were assessed dichotomously and semi-quantitatively: non-approval (0) vs. approval (on a 1-10 weight scale, with 10 indicating the strongest approval). The survey was conducted from July 4 to 26, 2023, using a web-based method. Responses to PCOs and other value elements were compared.

Results: Among 200 respondents, 44 (22%) were patients/patient representatives, 64 (32%) were industry/developers, 60 (30%) were medical practitioners/doctors, and 32 (16%) were government health personnel. The level of experience with PCOs regarding AI was low, with only 7% (14/200) having direct experience and 10% (20/200) having any experience (either direct or indirect). The approval rate for insurance coverage for PCOs was 74% (148/200), significantly lower than the corresponding rates for other value elements (82.5%-93.5%; ≤ 0.034). The approval strength was significantly lower for PCOs, with a mean weight ± standard deviation of 5.1 ± 3.5, compared to other value elements ( ≤ 0.036).

Conclusion: There is currently limited demand for insurance coverage for AI that demonstrates benefits in terms of non-clinical PCOs.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11058425PMC
http://dx.doi.org/10.3348/kjr.2023.1281DOI Listing

Publication Analysis

Top Keywords

insurance coverage
20
pcos
9
elements provided
8
artificial intelligence
8
patient-centered outcomes
8
opinions insurance
8
clinical outcomes
8
non-clinical pcos
8
insurance
6
coverage
6

Similar Publications

Objective Severe maternal morbidity (SMM) poses a public health dilemma. To ensure continuity of care for 12 months postpartum, the American Rescue Plan Act of 2021 permitted states to extend Medicaid postpartum coverage to 12 months. This study describes the experiences of a major national insurer in the United States.

View Article and Find Full Text PDF

Background:  Social media has become a platform where unheard voices within different communities are shared with government.

Aim:  The study explored and described expressed reactions of social media users regarding the implementation of the National Health Insurance (NHI) in South Africa.

Setting:  This study was conducted online on existing social media platforms that share current news.

View Article and Find Full Text PDF

Hearing Impairment Among Medicare Beneficiaries in the United States: Trends, Comorbidities, and Public Health Consequences.

Ear Nose Throat J

September 2025

Department of Primary Care, Ohio University Heritage College of Osteopathic Medicine, The Ohio University Diabetes Institute, Athens, OH, USA.

Background: Hearing loss is a significant public health issue in the United States, affecting an estimated 72.9 million people, or 22% of the population. Despite its prevalence and clinical impact, insurance coverage for hearing-related interventions remains inconsistent.

View Article and Find Full Text PDF

In standard short-read whole-exome sequencing (WES), capture probes are typically designed to target the protein-coding regions (CDS), and regions outside the exons-except for adjacent intronic sequences-are rarely sequenced. Although the majority of known pathogenic variants reside within the CDS as nonsynonymous variants, some disease-causing variants are located in regions that are difficult to detect by WES alone, such as deep intronic variants and structural variants, often requiring whole-genome sequencing (WGS) for detection. Moreover, WES has limitations in reliably identifying pathogenic variants within mitochondrial DNA or repetitive regions.

View Article and Find Full Text PDF

Background: Mental and behavioral disorders affect approximately 28% of the adult population in Germany per year, with treatment being provided through a diverse health care system. Yet there are access and capacity problems in outpatient mental health care. One innovation that could help reduce these barriers and improve the current state of care is the use of mobile health (mHealth) apps, known in Germany as Digitale Gesundheitsanwendungen (DiGA).

View Article and Find Full Text PDF