Guides

These guides are resources for aspiring and current healthcare administration professionals. They include scholarship databases, salary tables, conference schedules, and lists of the top degrees and careers in this field.

Medical Mistrust: How Healthcare Leaders Can Combat Racial Disparities October 26, 2023

Medical Mistrust: How Healthcare Leaders Can Combat Racial Disparities

An October 2020 survey by the Kaiser Family Foundation (KFF) found that nearly six out of ten Black Americans trusted the nation’s healthcare system only some or almost none of the time to do what was right for their communities. That mistrust is understandable: the nation’s healthcare system has a long history of mistreating its non-white racial and ethnic communities.

Fighting Bias in Healthcare: Ageism & Nursing Homes September 20, 2023

Fighting Bias in Healthcare: Ageism & Nursing Homes

According to the World Health Organization (WHO), a profound number of people are ageist: half of the global population. This staggering statistic reveals how prevalent discrimination against older adults is and how insidious. Psychologists have called it the last socially acceptable form of discrimination.

Medical Mistrust: Organizational Approaches to Increasing Patient Confidence September 14, 2023

Medical Mistrust: Organizational Approaches to Increasing Patient Confidence

Medical mistreatment and the mistrust it engenders isn’t confined to history, nor is it limited to the Black population: today, women, people of color, Native Americans, and members of the LGBTQIA+ community experience minor or major discriminations that justifiably leave them distrustful of traditional healthcare services.

Collaborative Skills in Healthcare Administration September 13, 2023

Collaborative Skills in Healthcare Administration

In the healthcare industry, collaboration is key. For doctors, nurses, and administrative professionals, collaboration is essential to providing the highest quality of care. However, collaboration only happens with thoughtful intervention from healthcare administrators. They are responsible for developing those skills personally and teaching their staff how to work together. Working collaboratively can have a significant impact on patient outcomes.

Artificial Intelligence & Machine Learning in Clinical Practice August 28, 2023

Artificial Intelligence & Machine Learning in Clinical Practice

The influence of physician expertise tends to be weighted more heavily in collaborative decision-making discussions at the highest levels of HCOs. The opinion of this writer is that such weighting is expected and is appropriate for patient safety. This may change over time as regulatory bodies have formalized and adopted more AI/ML frameworks for best practices and standards.

Universities with an Outstanding Faculty in Regulatory Affairs August 22, 2023

Universities with an Outstanding Faculty in Regulatory Affairs

Five universities, in particular, boast outstanding faculty in regulatory affairs: Duke University, George Washington University, Northeastern University, the University of Southern California, and the University of Washington. Learn more about them.

Challenges of Delivering High-Quality Healthcare August 15, 2023

Challenges of Delivering High-Quality Healthcare

While the U.S. has some of the best hospitals and medical schools in the world, our healthcare system is fraught with systemic issues that limit access to quality healthcare and ultimately compromise public health.

How Healthcare Leaders Can Combat Vaccine Hesitancy August 9, 2023

How Healthcare Leaders Can Combat Vaccine Hesitancy

Vaccination rates in the US have lagged behind other rich countries. The reasons for that lag are multivariate, but sometimes grouped under the generic label of vaccine hesitancy: the refusal or reluctance to have oneself or one’s children vaccinated against an infectious disease or diseases.

Basics of Machine Learning for Rising Healthcare Leadership July 31, 2023

Basics of Machine Learning for Rising Healthcare Leadership

Machine learning (ML) refers to a set of computational algorithms that apply statistical modeling to a specific task. Think of a task as a question or an input. The algorithm uses logic applied to that question to generate an answer or output. To emphasize the distinction between AI and ML, remember that AI refers to computational systems which mimic human behavior—ML refers to specific types of algorithms. Systems are built from algorithms; algorithms work inside of systems.