AJMC® Publishes 11th Annual Health IT Special Issue With Focus on Equity
CRANBURY, N.J., Jan. 25, 2022 /PRNewswire/ --
The issue covers research on the expansion of digital care offerings due to COVID-19 and the integration of tech solutions to track performance under value-based contracting. Several articles in this issue discuss the use of health IT to mitigate the effects of social determinants of health and ensure equity in predictive models and patient-facing technologies.
Dori Cross, Ph.D., an assistant professor in the Department of Health Policy and Management at the University of Minnesota School of Public Health, served as the guest editor of this special issue.
"Digital advancement is not the end goal but instead a strategic approach to organizational learning, care process optimization and data-driven outcomes improvement," Cross wrote in an editorial in the special issue. "The areas of research focus in this special issue, and specific insights offered by authors' analyses, help us chart a path forward to integrating and realizing value from our continued commitment to digitally enabled health care."
"We are so pleased to announce the publication of the 11th Annual Health IT Issue," said Mike Hennessy Jr., president and CEO of MJH Life Sciences™, parent company of AJMC®. "The findings within this issue focus on the advancement of digital care offerings throughout the COVID-19 pandemic in addition to several other relevant and timely topics within the managed care industry. A special thank you to Dr. Cross for serving as guest editor for this issue."
Several articles in the issue explore how health IT can be used to advance the goal of health equity.
- A research article by Walker et al describes the key components of cross-sector data sharing between a medical center and a food bank.
- A Trends From the Field article by Tan-McGrory et al covers efforts to alleviate virtual care disparities for patients with limited English proficiency.
- A research article by Nong et al explores ways to incorporate equity into predictive models.
- A research article by Vest et al discusses the feasibility of using structured data elements to evaluate social risk.
To read the articles in the 11th Annual Health IT Special Issue, click
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