Discover key insights about global health informatics, the related competencies and how these can be applied in the workforce.
In today’s world, discover how cybersecurity in healthcare—and protecting information—is vital for essential functions within an organization.
Discover key insights about interoperability and better understand how data sharing can make a difference in healthcare.
The HIMSS TIGER (Technology Informatics Guiding Education Reform) Initiative’s Global Informatics Definitions define core global health informatics terminology, including varying terms for similar concepts applied locally, regionally and nationally to maximize the integration of informatics on...
This resource helps executive leaders and IT, informatics, clinical leadership and managers at large- to medium-size providers and research organizations who are exploring big data drive your business to improve ROI and optimize patient care metrics and workflow.
The aim of this report in OJNI is to synthesize nursing studies leveraging artificial intelligence technology and to offer suggestions for future studies.
This pilot study outlined for OJNI focused on helping providers to identify personal bias towards obese patients through an online self-paced educational tool, raise awareness of weight bias, and support evidence-based solutions.
Learn about salary and benefits in the field of nursing informatics.
The aim of this study was to evaluate the informatics competencies of nurses working in hospitals.
Personal Health Information: Federal Trade Commission Health Breach Notification Rule Regulatory Review Response Letter
This response aims to ensure that individuals’ personally identifiable health data is protected, and that the appropriate actions are taken when a breach of unsecured personal health information occurs.
Novice Nurse Preparedness to Effectively Use Electronic Health Records in Acute Care Settings: Critical Informatics Knowledge and Skill Gaps
This paper proposes a Complexity Segmentation and Care Integration Model (CSCIM) that integrates population and primary-care data, using a chronic-disease algorithm that divides the population into cohorts based on complexity and comorbidity.