healthcare technology

The past several decades have seen an alarming spike in communicable disease outbreaks worldwide. Given a confluence of host, virologic, environmental, and human factors, experts agree that the next pandemic could already be on the horizon.

In a globalized world, changes in how people use land and interact with their ecosystems—such as rapid deforestation and agricultural expansion—have resulted in humans and animals coming into more frequent and intense contact with one another, increasing opportunities for what is known as "zoonotic disease spillover."

In the past few years alone, numerous disease outbreaks have had suspected or confirmed zoonotic origin, including mpox (formerly known as monkeypox), Ebola virus disease, dengue fever, and COVID-19.

Experts also recognize the need to prepare for another possible Disease X, a term used to describe a currently unknown pathogen with pandemic potential.

To direct resources toward the most high-consequence pathogens, it is paramount that leaders have an accurate concept of pandemic risk—for individual viruses as well as viral families. Several institutions are developing disease rankings at national and global levels, including the Priority Zoonotic Diseases Lists facilitated by the U.S. Centers for Disease Control and Prevention and the Research and Development (R&D) Blueprint created by the World Health Organization. 

The original SpillOver risk ranking framework (SpillOver 1.0), an open-source webtool launched by researchers at the University of California, Davis One Health Institute, estimated the relative spillover potential of wildlife-origin viruses to humans based on a series of host, viral, and environmental risk factors determined via expert opinion and scientific evidence. 

Its next iteration, SpillOvers 2.0, has rebranded to better describe the diversity and frequency of virus spillovers to people. The new platform uses a One Health approach, which recognizes the interdependence of human, animal, and environmental health. It will expand to include domestic animal and vector-borne viruses and assess pandemic risk rather than just spillover risk for wildlife viruses.

South Korea introduced a new health care IT system named the Narcotics Information Management System (NIMS) with the objective of managing all aspects of opioid use, including manufacturing, distribution, sales, disposal, etc.

The authors conducted an analysis using national claims data from 45,582 patients diagnosed with musculoskeletal and connective tissue disorders between 2016 and 2020.  The approach included using an interrupted time-series analysis and constructing segmented regression models. Within these models, the authors considered the primary intervention to be the implementation of NIMS, while we treated the COVID-19 outbreak as the secondary event.

To comprehensively assess inappropriate opioid use, we examined 4 key indicators, as established in previous studies:

(1) the proportion of patients on high-dose opioid treatment,

(2) the proportion of patients receiving opioid prescriptions from multiple providers,

(3) the overlap rate of opioid prescriptions per patient, and

(4) the naloxone use rate among opioid users.

This study suggests that, in its current form, the NIMS may not have brought significant improvements to the identified indicators of opioid overuse and misuse. Additionally, the COVID-19 outbreak exhibited no significant influence on opioid use patterns.

The absence of real-time monitoring feature within the NIMS could be a key contributing factor. Further exploration and enhancements are needed to maximize the NIMS’ impact on curbing inappropriate opioid use.

read the original at https://publichealth.jmir.org/2024/1/e47130/

The recent SARS-CoV-2 pandemic underscored the effectiveness and rapid deployment of digital public health interventions, notably the digital proximity tracing apps, leveraging Bluetooth capabilities to trace and notify users about potential infection exposures.

Digital proximity tracings showcased the promise of digital public health.

As the world pivots from pandemic responses, it becomes imperative to address noncommunicable diseases (NCDs) that account for a vast majority of health care expenses and premature disability-adjusted life years lost.

The narrative of digital transformation in the realm of NCD public health is distinct from infectious diseases.

The power of artificial intelligence (AI) in this digital transformation is noteworthy.

• AI can automate repetitive tasks, facilitating health care providers to prioritize personal interactions, especially those that cannot be digitalized like emotional support.
• Moreover, AI presents tools for individuals to be proactive in their health management. However, the human touch remains irreplaceable;
• AI serves as a companion guiding through the health care landscape.

Digital evolution, while revolutionary, poses its own set of challenges.

Issues of equity and access are at the forefront. Vulnerable populations, whether due to economic constraints, geographical barriers, or digital illiteracy, face the threat of being marginalized further.

This transformation mandates an inclusive strategy, focusing on not amplifying existing health disparities but eliminating them.

Population-level digital interventions in NCD prevention demand societal agreement.

Policies, like smoking bans or sugar taxes, though effective, might affect those not directly benefiting. Hence, all involved parties, from policy makers to the public, should have a balanced perspective on the advantages, risks, and expenses of these digital shifts.

For a successful digital shift in public health, especially concerning NCDs, AI’s potential to enhance efficiency, effectiveness, user experience, and equity—the “quadruple aim”—is undeniable.

However, it is vital that AI-driven initiatives in public health domains remain purposeful, offering improvements without compromising other objectives.

The broader success of digital public health hinges on transparent benchmarks and criteria, ensuring maximum benefits without sidelining minorities or vulnerable groups.

Especially in population-centric decisions, like resource allocation, AI’s ability to avoid bias is paramount.

Therefore, the continuous involvement of stakeholders, including patients and minority groups, remains pivotal in the progression of AI-integrated digital public health.

read the original paper at https://publichealth.jmir.org/2024/1/e49575/

As we progress deeper into the digital age, the robust development and application of advanced artificial intelligence (AI) technology, specifically generative language models like ChatGPT (OpenAI), have potential implications in all sectors including medicine.

ChatGPT, a generative language model launched by OpenAI in November 2022 has essentially has essentially revolutionized the IT world.. What makes ChatGPT a promising tool is the vast amounts of data used in its training and its ability to generate human-like conversations covering diverse topics.

The unprecedented capacity of ChatGPT to generate human-like responses, refined through Reinforcement Learning with Human Feedback, could significantly reshape the pedagogical methodologies within medical education.

The use of AI in medicine, including the use of generative language models, is often accompanied by challenges and contentions. Some common challenges include privacy, data security, algorithmic transparency and explainability, errors and liability, as well as regulatory issues associated with AI medicine.

Lately, the use of generative language models in scientific writing has also stirred up controversies in the academic and publishing communities. Some journals have declined ChatGPT as a coauthor, whereas others have happily accepted manuscripts authored by ChatGPT

Through a comprehensive review and the authors’ personal experiences, this viewpoint article elucidates the pros, cons, and ethical considerations of using ChatGPT within clinical medicine and notably, its implications for medical education.

This exploration is crucial in a transformative era where AI could potentially augment human capability in the process of knowledge creation and dissemination, potentially revolutionizing medical education and clinical practice.

The importance of maintaining academic integrity and professional standards is highlighted. The relevance of establishing clear guidelines for the responsible and ethical use of AI technologies in clinical medicine and medical education is also emphasized.

read the whole article at https://mededu.jmir.org/2023/1/e47274

The world of healthcare is ever-evolving. We are learning and growing every day, which means we are also coming up with new ideas, technologies, and practices every day.

what emerging technologies in Health IT are currently shaping the landscape,

and how do they contribute to improved patient outcomes and healthcare delivery?

This Healthcare IT today's article has a collection of opinions from people from the ever growing digital health community.

includes thoughts like

- proactive patient communication and automated text updates for patient approved people

- using adaptive AI for patient communication

- using AI in billing to bring about a fairness to costs

- using ambient documentation to improve patient provider connections in the presence of an EHR

- use of digital therapeutics

amongst others

read the article at

https://www.healthcareittoday.com/2024/02/12/emerging-technologies-shaping-the-health-it-landscape-and-how-they-contribute-to-improving-patient-outcomes-and-healthcare-delivery/