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The promise of AI in healthcare: transforming communication and decision-making for patients.
J Commun Healthc
January 2025
Venditti Consulting, LLC, Westport, CT, United States.
By addressing communication gaps, the integration of AI tools in healthcare has a greater ability to improve decision-making and to empower patients with more control over their health. Current systems for navigating healthcare - such as finding providers or understanding costs - are fragmented and cumbersome, often leaving patients frustrated and uninformed. An AI Healthcare Assistant App, leveraging advances in health IT interoperability, price transparency, and user-centred design, could simplify these processes.
View Article and Find Full Text PDFExploring the purpose and stages of patient and public involvement and engagement (PPIE) in audiology research: a case study approach.
Res Involv Engagem
January 2025
Patient Researcher and PPI Lead, College of Health and Life Sciences, Aston University, Birmingham, UK.
Background: Patient and Public Involvement and Engagement (PPIE) has become an integral component of contemporary audiology research. It aims to capture diverse views and experiences, essential for evaluating the long-term impact of technological advancements and care models on individuals. Traditional inclusion methods, such as focus groups, may exclude individuals with additional needs or communication difficulties, necessitating the development of more inclusive approaches.
View Article and Find Full Text PDFMitigating bias in AI mortality predictions for minority populations: a transfer learning approach.
BMC Med Inform Decis Mak
January 2025
Department of Clinical Pharmacy and Translational Science, The University of Tennessee Health Science Center, Memphis, TN, USA.
Background: The COVID-19 pandemic has highlighted the crucial role of artificial intelligence (AI) in predicting mortality and guiding healthcare decisions. However, AI models may perpetuate or exacerbate existing health disparities due to demographic biases, particularly affecting racial and ethnic minorities. The objective of this study is to investigate the demographic biases in AI models predicting COVID-19 mortality and to assess the effectiveness of transfer learning in improving model fairness across diverse demographic groups.
View Article and Find Full Text PDFExploring barriers to accessing health care services by young women in rural settings: a qualitative study in Australia, Canada, and Sweden.
BMC Public Health
January 2025
Department of Health Sciences, Carleton University, 2305 Health Sciences Building, 1125 Colonel By Drive, Ottawa, ON, K1S 5B6, Canada.
Background: The aim of this study is to explore young rural women's perceived barriers in accessing healthcare services with a focus on the interrelation between three marginalization criteria: age (youth), gender (female), and place of residence (rural areas) in Australia, Canada, and Sweden.
Methods: Using a qualitative interpretive approach, we conducted semi-structured in-depth interviews with 31 young women aged 18 to 24 in selected rural communities. Data collection took place from May 2019 to January 2021, and the qualitative data were analyzed using NVivo software.
Creating a collaborative culture of learning within a network of community mental health early psychosis programs in Texas.
Schizophr Res
January 2025
Dell Medical School, The University of Texas at Austin, United States; Department of Psychiatry, Indiana University School of Medicine, United States.
Learning Health Systems (LHSs) promise meaningful health care improvement through the ongoing use of data, including the lived experience of diverse constituents, such as people participating in and providing services. Most LHSs operate within a specific healthcare system, typically hospital-based, under a common electronic health record (EHR) and management structure. The Early Psychosis Intervention Network in Texas (EPINET-TX) is a novel case study of a developing LHS across 16 independent community mental health clinics operating state-funded coordinated specialty care (CSC) programs for early psychosis.
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