Health Information Management: Implications of Artificial Intelligence on Healthcare Data and Information Management

Overview

Journal Yearb Med Inform

Publisher Thieme

Specialty Medical Informatics

Date 2019 Aug 17

PMID 31419816

Citations 24

Authors

Mary H Stanfill

David T Marc

Affiliations

Soon will be listed here.

Abstract

Objective: This paper explores the implications of artificial intelligence (AI) on the management of healthcare data and information and how AI technologies will affect the responsibilities and work of health information management (HIM) professionals.

Methods: A literature review was conducted of both peer-reviewed literature and published opinions on current and future use of AI technology to collect, store, and use healthcare data. The authors also sought insights from key HIM leaders via semi-structured interviews conducted both on the phone and by email.

Results: The following HIM practices are impacted by AI technologies: 1) Automated medical coding and capturing AI-based information; 2) Healthcare data management and data governance; 3) Fbtient privacy and confidentiality; and 4) HIM workforce training and education.

Discussion: HIM professionals must focus on improving the quality of coded data that is being used to develop AI applications. HIM professional's ability to identify data patterns will be an important skill as automation advances, though additional skills in data analysis tools and techniques are needed. In addition, HIM professionals should consider how current patient privacy practices apply to AI application, development, and use.

Conclusions: AI technology will continue to evolve as will the role of HIM professionals who are in a unique position to take on emerging roles with their depth of knowledge on the sources and origins of healthcare data. The challenge for HIM professionals is to identify leading practices for the management of healthcare data and information in an AI-enabled world.

Citing Articles

Ethical and Practical Dimensions of Artificial Intelligence (AI) in Healthcare: A Comprehensive Study of Professional Perceptions.

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Leveraging Artificial Intelligence to Predict and Manage Complications in Patients With Multimorbidity: A Literature Review.

Chaparala S, Pathak K, Dugyala R, Thomas J, Varakala S Cureus. 2025; 17(1):e77758.

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AI in the Health Sector: Systematic Review of Key Skills for Future Health Professionals.

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Advancements in Artificial Intelligence in Noninvasive Cardiac Imaging: A Comprehensive Review.

Tolu-Akinnawo O, Ezekwueme F, Omolayo O, Batheja S, Awoyemi T Clin Cardiol. 2025; 48(1):e70087.

PMID: 39871619 PMC: 11772728. DOI: 10.1002/clc.70087.

Role of artificial intelligence in predicting neurological outcomes in postcardiac resuscitation.

Khawar M, Abdus Saboor H, Eric R, Arain N, Bano S, Mohamed Abaker M Ann Med Surg (Lond). 2024; 86(12):7202-7211.

PMID: 39649879 PMC: 11623902. DOI: 10.1097/MS9.0000000000002673.

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