Quality Improvement in Athletic Health Care.

J Athl Train

Department of Interdisciplinary Health Sciences, Arizona School of Health Sciences, A.T. Still University, Mesa.

Published: November 2017

Context:   Quality improvement (QI) is a health care concept that ensures patients receive high-quality (safe, timely, effective, efficient, equitable, patient-centered) and affordable care. Despite its importance, the application of QI in athletic health care has been limited.

Objectives:   To describe the need for and define QI in health care, to describe how to measure quality in health care, and to present a QI case in athletic training.

Description:   As the athletic training profession continues to grow, a widespread engagement in QI efforts is necessary to establish the value of athletic training services for the patients that we serve. A review of the importance of QI in health care, historical perspectives of QI, tools to drive QI efforts, and examples of common QI initiatives is presented to assist clinicians in better understanding the value of QI for advancing athletic health care and the profession. Clinical and Research Advantages:  By engaging clinicians in strategies to measure outcomes and improve their patient care services, QI practice can help athletic trainers provide high-quality and affordable care to patients.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5737045PMC
http://dx.doi.org/10.4085/1062-6050-52.10.15DOI Listing

Publication Analysis

Top Keywords

health care
28
athletic health
12
care
10
quality improvement
8
affordable care
8
athletic training
8
athletic
7
health
7
improvement athletic
4
care context
4

Similar Publications

Most people with mental health needs cannot access treatment; among those who do, many access services only once. Accordingly, single-session interventions (SSIs) may help bridge the treatment gap. We conducted the first umbrella review synthesizing research on SSIs for mental health problems and service engagement in youth and adults.

View Article and Find Full Text PDF

Multiple respiratory viruses can concurrently or sequentially infect the respiratory tract, making their identification crucial for diagnosis, treatment, and disease management. We present a label-free diagnostic platform integrating surface-enhanced Raman scattering (SERS) with deep learning for rapid, quantitative detection of respiratory virus coinfections. Using sensitive silica-coated silver nanorod array substrates, over 1.

View Article and Find Full Text PDF

Background: Heart failure (HF) is a chronic, progressive condition where the heart cannot pump enough blood to meet the body's needs. In addition to the daily challenges that HF poses, acute exacerbations can lead to costly hospitalizations and increased mortality. High health care costs and the burden of HF have led to the emerging application of new technologies to support people living with HF to stay well while living in the community.

View Article and Find Full Text PDF

Background: Skin cancers, including melanoma and keratinocyte cancers, are among the most common cancers worldwide, and their incidence is rising in most populations. Earlier detection of skin cancer leads to better outcomes for patients. Artificial intelligence (AI) technologies have been applied to skin cancer diagnosis, but many technologies lack clinical evidence and/or the appropriate regulatory approvals.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!