Implementing Artificial Intelligence in Family Medicine: Challenges and Limitations.

General practice/family medicine is a primary healthcare discipline that focuses on providing comprehensive, patient-centered care to individuals and families across their lifespan. This study aimed to assess the implementation of artificial intelligence (AI) in general practice/family medicine regarding the 12 characteristics of its discipline as described in the recently revised European Definition of General Practice/Family Medicine. AI has the potential to revolutionize family medicine practice by improving the accuracy, efficiency, and effectiveness of various clinical tasks.

Current State of Community-Driven Radiological AI Deployment in Medical Imaging.

Artificial intelligence (AI) has become commonplace in solving routine everyday tasks. Because of the exponential growth in medical imaging data volume and complexity, the workload on radiologists is steadily increasing. AI has been shown to improve efficiency in medical image generation, processing, and interpretation, and various such AI models have been developed across research laboratories worldwide.

A community-centric model for conference co-creation: the world conference on CDG for patients, families and professionals.

Background: Patient and public co-creation and involvement in health initiatives have been witnessing great expansion in recent years. From healthcare to research settings, collaborative approaches are becoming increasingly prevalent and diverse, especially in the field of rare diseases which faces complex challenges. Conference development and implementation, however, have been primarily guided by passive, information-sharing models.

Leveraging Health Services Research to Address Aging Health Equity.

To achieve optimal, equitable health outcomes for all older adults, the United States desperately needs equity in access to, quality of, and cost of aging care. To illustrate these needs, we discuss the current inequitable state of frailty care. Frailty disproportionately affects marginalized populations, yet these populations struggle to access high-quality geriatrics care and long-term care services and supports (LTSS) that mitigate frailty, leading to accelerated frailty trajectories.

Developing feasible person-centred care alternatives to emergency department responses for adults with epilepsy: a discrete choice analysis mixed-methods study.

Background: Calls have been made for paramedics to have some form of care pathway that they could use to safely divert adults with epilepsy away from emergency departments and instigate ambulatory care improvements. Different configurations are possible. To know which to prioritise for implementation/evaluation, there is a need to determine which are acceptable to service users and likely National Health Service-feasible.

End-of-life care for the devout Jewish patient.

Rationale: The Joint Commission emphasizes the importance of cultural competence and effective communication in quality medical care, particularly during end-of-life (EOL), when decisions are influenced by diverse cultural and religious backgrounds. For Orthodox Jewish patients, the philosophical framework used for EOL decision-making may conflict with that used in traditional Western medical ethics. In this paper, we explore the complexities of EOL decision-making for devout Jewish patients and highlight how approaches may differ from a Western ethical framework.

Person-centred decisions in emergency care for older people living with frailty: principles and practice.

Older people living with frailty are frequent users of emergency care and have multiple and complex problems. Typical evidence-based guidelines and protocols provide guidance for the management of single and simple acute issues. Meanwhile, person-centred care orientates interventions around the perspectives of the individual.

Integrating and Adopting AI in the Radiology Workflow: A Primer for Standards and Integrating the Healthcare Enterprise (IHE) Profiles.

The deployment of artificial intelligence (AI) solutions in radiology practice creates new demands on existing imaging workflow. Accommodating custom integrations creates a substantial operational and maintenance burden. These custom integrations also increase the likelihood of unanticipated problems.

Methods for pragmatic randomized clinical trials of pain therapies: IMMPACT statement.

Pragmatic, randomized, controlled trials hold the potential to directly inform clinical decision making and health policy regarding the treatment of people experiencing pain. Pragmatic trials are designed to replicate or are embedded within routine clinical care and are increasingly valued to bridge the gap between trial research and clinical practice, especially in multidimensional conditions, such as pain and in nonpharmacological intervention research. To maximize the potential of pragmatic trials in pain research, the careful consideration of each methodological decision is required.

Preferences for Postacute Care at Home vs Facilities.

Importance: Two in 5 US hospital stays result in rehabilitative postacute care, typically through skilled nursing facilities (SNFs) or home health agencies (HHAs). However, a lack of clear guidelines and understanding of patient and caregiver preferences make it challenging to promote high-value patient-centered care.

Objective: To assess preferences and willingness to pay for facility-based vs home-based postacute care among patients and caregivers, considering demographic variations.

Disparities in Mistreatment During Childbirth.

Importance: Lack of respectful maternity care may be a key factor associated with disparities in maternal health. However, mistreatment during childbirth has not been widely documented in the US.

Objectives: To estimate the prevalence of mistreatment by health care professionals during childbirth among a representative multistate sample and to identify patient characteristics associated with mistreatment experiences.

Guiding Principles to Address the Impact of Algorithm Bias on Racial and Ethnic Disparities in Health and Health Care.

Importance: Health care algorithms are used for diagnosis, treatment, prognosis, risk stratification, and allocation of resources. Bias in the development and use of algorithms can lead to worse outcomes for racial and ethnic minoritized groups and other historically marginalized populations such as individuals with lower income.

Objective: To provide a conceptual framework and guiding principles for mitigating and preventing bias in health care algorithms to promote health and health care equity.

Nothing About Patients Without Patients: More Than Just a Catchphrase!

Health care is sometimes called a "team sport," yet patients were traditionally not considered to be "on the team" in medicine. In 2001, the Institute of Medicine (now National Academy of Medicine) published its seminal book , in which patient-centered care was identified as 1 of 6 quality aims. Many organizations have since included patient-centered care as an important aspect of quality, including The Joint Commission, Centers for Medicare and Medicaid, and many large employers.

Enhancing reporting quality and impact of early phase dose-finding clinical trials: CONSORT Dose-finding Extension (CONSORT-DEFINE) guidance.

The CONSORT (CONsolidated Standards Of Reporting Trials) 2010 statement is the standard guideline for reporting completed randomised trials. The CONSORT Dose-finding Extension (DEFINE) extends the guidance (with 21 new items and 19 modified items) to early phase dose-finding trials with interim dose escalation or de-escalation strategies. Such trials generally focus on safety, tolerability, activity, and recommending dosing and scheduling regimens for further clinical development.