Study Shows Electronic HIE Could Save Billions in Healthcare Costs
|
By MedImaging International staff writers Posted on 27 Sep 2017 |

Image: A graphic portraying the value of Healthcare Information Exchanges (HIE) (Photo courtesy of HIMSS).
The results of a US study have shown that investing in healthcare Information Technology (IT) could lead to healthcare spending reductions in the billions of dollars, in the US alone.
According to the researchers, Health Information Exchanges (HIEs), which enable healthcare providers and hospitals to exchange and share medical data, are now showing their promised value to the healthcare systems.
The study was carried out by IT researchers at the University of Notre Dame Mendoza College of Business (Notre Dame, IN, USA), and at the University of California San Francisco (UCSF; San Francisco, CA, USA), and was published in April 16, 2017, in the SSRN eLibrary.
The researchers used data from 2003 to 2009, and compared average spending in health care markets with and without operational HIEs. They then analyzed the data they collected using a number of econometric metrics such as patient demographics, and economic factors. Hospitals use HIEs to efficiently exchange medical data, avoiding manual mailing, photocopying, and faxing of medical records. The researchers showed massive cost savings when HIEs were implemented in regional markets, leading to planning for nation-wide implementations in the US.
IT professor, Corey Angst, at the University of Notre Dame, said, "We realize the HIE model is not static -- new vendor-driven models are emerging as market dynamics change. What we show is that the ability to electronically exchange medical data can result in savings in the overall health system, which should encourage new models of exchange.
Related Links:
University of Notre Dame Mendoza College of Business
University of California San Francisco
According to the researchers, Health Information Exchanges (HIEs), which enable healthcare providers and hospitals to exchange and share medical data, are now showing their promised value to the healthcare systems.
The study was carried out by IT researchers at the University of Notre Dame Mendoza College of Business (Notre Dame, IN, USA), and at the University of California San Francisco (UCSF; San Francisco, CA, USA), and was published in April 16, 2017, in the SSRN eLibrary.
The researchers used data from 2003 to 2009, and compared average spending in health care markets with and without operational HIEs. They then analyzed the data they collected using a number of econometric metrics such as patient demographics, and economic factors. Hospitals use HIEs to efficiently exchange medical data, avoiding manual mailing, photocopying, and faxing of medical records. The researchers showed massive cost savings when HIEs were implemented in regional markets, leading to planning for nation-wide implementations in the US.
IT professor, Corey Angst, at the University of Notre Dame, said, "We realize the HIE model is not static -- new vendor-driven models are emerging as market dynamics change. What we show is that the ability to electronically exchange medical data can result in savings in the overall health system, which should encourage new models of exchange.
Related Links:
University of Notre Dame Mendoza College of Business
University of California San Francisco
Latest Imaging IT News
- Ambient AI Reporting Platform Streamlines Radiology Reporting
- Interactive AI Tool Supports Explainable Lung Nodule Assessment
- Breast Imaging Software Enhances Visualization and Tissue Characterization in Challenging Cases
- New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible
- Global AI in Medical Diagnostics Market to Be Driven by Demand for Image Recognition in Radiology
- AI-Based Mammography Triage Software Helps Dramatically Improve Interpretation Process
- Artificial Intelligence (AI) Program Accurately Predicts Lung Cancer Risk from CT Images
- Image Management Platform Streamlines Treatment Plans
- AI-Based Technology for Ultrasound Image Analysis Receives FDA Approval
- AI Technology for Detecting Breast Cancer Receives CE Mark Approval
Channels
Radiography
view channel
Computational X-Ray Technique Enables High-Resolution, Low-Dose Radiography
Reducing radiation in medical X-ray imaging remains a persistent challenge because dose reductions often degrade spatial resolution and diagnostic confidence. This is especially critical in pediatrics,... Read more
AI Tool Predicts Five-Year Breast Cancer Risk from Mammograms
Breast cancer risk assessment during routine screening is difficult because many women who develop the disease have no known genetic mutations or family history. Static risk tools provide limited discrimination... Read moreMRI
view channel
Rapid AI System Detects and Classifies Brain Tumor Subtypes on MRI
Brain tumors are a major cause of cancer mortality worldwide, with roughly a quarter of a million deaths each year. Early detection and accurate subtype classification on magnetic resonance imaging are... Read more
Advanced MRI Reveals Structural Brain Changes Linked to Better Cognitive Health
Objective, noninvasive measures that capture subtle, training-related changes in adult brain structure remain limited in routine clinical practice. Quantifying neuroplasticity with precision is especially... Read moreUltrasound
view channel
Simple 2D Ultrasound Tool Accurately Estimates Placental Volume
Stillbirth remains a major cause of perinatal loss, with about 21,000 cases annually in the United States. Although placental abnormalities are linked to adverse pregnancy outcomes, routine monitoring... Read more
Portable 3D Ultrasound System Enables Reproducible Breast Cancer Monitoring
Breast cancer can develop between annual mammograms, and these interval cancers account for 20% to 30% of cases and tend to be more aggressive. The challenge is pronounced in people with dense breast tissue.... Read moreNuclear Medicine
view channel
Radiotherapy Professionals Embrace AI as a Clinical Support Tool
Radiotherapy planning requires precise identification of organs at risk near a tumor, but manual contouring is repetitive and time-consuming, often delaying plan completion and straining specialist capacity.... Read more
Second PSMA PET Identifies Disease in More Than Half of Negative Cases
Biochemical recurrence of prostate cancer after prostatectomy or radiation can be difficult to localize when imaging is negative. Uncertain disease sites may delay salvage therapy and expose patients to... Read moreGeneral/Advanced Imaging
view channel
PET/CT Improves Diagnosis and Management of Fever of Unknown Origin
Fever of unknown origin (FUO) is persistent fever without an identifiable cause and remains difficult to diagnose because potential etiologies are broad and no single gold-standard pathway exists.... Read more
New PE-RADS Framework Standardizes Pulmonary Embolism Imaging Reports
Pulmonary embolism is a sudden blockage of the lung’s blood vessels that reduces pulmonary blood flow, can strain the right hear,t and may be fatal if untreated. Patients often present with shortness of... Read moreIndustry News
view channel
GE HealthCare Showcases AI-Enabled Nuclear Medicine Portfolio at SNMMI 2026
Nuclear medicine is expanding rapidly as health systems adopt theranostics and broaden access to radiopharmaceuticals, increasing demand for scalable operations and consistent diagnostic confidence.... Read more
GE HealthCare Highlights AI-Supported Radiation Therapy Tools at ESTRO 2026
At the European Society for Radiotherapy and Oncology (ESTRO) 2026 Congress in Stockholm, GE HealthCare is highlighting Intelligent Radiation Therapy (iRT), MIM Software innovations, and BK Medical surgical... Read more







