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Health Care System Transformation and Integration: A Call to Action for Public Health

Overview of attention for article published in The Journal of Law, Medicine & Ethics, January 2021
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4 X users
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1 Facebook page

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25 Mendeley
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Title
Health Care System Transformation and Integration: A Call to Action for Public Health
Published in
The Journal of Law, Medicine & Ethics, January 2021
DOI 10.1177/1073110517703335
Pubmed ID
Authors

Lindsay F Wiley, Gene W Matthews

Abstract

Restructured health care reimbursement systems and new requirements for nonprofit hospitals are transforming the U.S. health system, creating opportunities for enhanced integration of public health and health care goals. This article explores the role of public health practitioners and lawyers in this moment of transformation. We argue that the population perspective and structural strategies that characterize public health can add value to the health care system but could get lost in translation as changes to tax requirements and payment systems are rapidly implemented. We urge public health leaders to take a more active role in hospital assessments of community health needs and evaluation of the patient outcomes for which providers are accountable.

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X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 4 16%
Researcher 4 16%
Lecturer 2 8%
Student > Ph. D. Student 2 8%
Professor 2 8%
Other 3 12%
Unknown 8 32%
Readers by discipline Count As %
Business, Management and Accounting 4 16%
Social Sciences 3 12%
Nursing and Health Professions 2 8%
Medicine and Dentistry 2 8%
Psychology 2 8%
Other 2 8%
Unknown 10 40%