The reality check: Why Healthcare mergers and acquisitions are falling short in improving Quality Care and Public Health
Healthcare mergers and acquisitions (M/A) are a significant part of the overall change in the recent U.S. healthcare landscape. Financial distress and the need for the economic viability of the acquired hospital are the main drivers for M/A. The bigger hospital, which is acquiring a more minor system, hopes to increase its service lines […]
Insider’s Guide to US Regulation of Healthcare Artificial Intelligence (AI/ML)-Enabled Devices: US Healthcare AI/ML Device Oversight Explained
Artificial intelligence and machine learning (AI/ML) have already made their way into the healthcare sector, and their presence is increasingly evident. This is a positive development, as the medical care system in the US is still lagging behind in terms of technology. For instance, it’s surprising that even in the year 2024, doctors’ offices […]
Prescription for change: Redefining solutions for technology-induced physician burnout
Your physician is a time bomb waiting to explode, no kidding! Just in case you were not aware, up to 60% of physicians in the U.S. experience burnout. Add on the fact that the suicide rate is highest amongst physicians compared to other professions [1,2,3]. Clinician burnout reduces the quality of care at the individual […]
Unveiling health data vulnerabilities: The growing threat to our digital Health data privacy and confidentiality
Difference between data security and privacy, as well as their contemporary regulatory enforcement Although data privacy and security are interrelated concepts, they are distinct in that data privacy concerns who can access a particular dataset. It also covers how that data is shared and to whom it is shared. Data security, on the other hand, […]
Breaking Down Healthcare Algorithmic Bias: A Deep Dive.
Exploring the nexus: the relationship between healthcare algorithmic bias and health Outcome Healthcare algorithmic bias can result in heightened inequalities in health outcomes. However, this unfavorable state of health outputs may be unintentional, as the origins and sources of these biases may pre-date the conception and development of the algorithm[1]. Algorithmic bias in healthcare can […]
Exposing the Dark Secrets of Healthcare Artificial Intelligence (AI) Bias Origins and Sources
Algorithmic bias occurs when the application of an algorithm heightens both new or previously identified contemporary inequities in health outcomes. It replicates new or existing health inequity on a massive scale without adequate oversight[1]. This large-scale algorithmic replication of our society’s health disparity can compound existing disadvantages of different groups based on race, gender, religion, […]
