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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

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Published on: July 11, 2025

Supporting Imagers' VOICE: A National Training Program in Comparative Effectiveness Research and Big Data Analytics.

Stella K Kang¹, James V Rawson², Michael P Recht³

¹Department of Radiology, NYU School of Medicine, New York, New York; Department of Population Health, NYU School of Medicine, New York, New York.

Journal of the American College of Radiology : JACR

|December 10, 2017

Summary

This program trains imaging professionals in comparative effectiveness research methods. Enhanced training enables better evidence generation for diagnostic imaging value and outcomes.

Keywords:

Comparative effectiveness research big data research methods research training

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Area of Science:

Health Services Research
Medical Informatics
Health Economics

Background:

Diagnostic imaging research requires robust methodologies to demonstrate value.
Comparative effectiveness research (CER) is crucial for evidence-based healthcare decisions.
Big data analytics offers new opportunities for advancing imaging research.

Purpose of the Study:

To introduce a training program for enhancing research skills in diagnostic imaging.
To equip imagers with expertise in comparative effectiveness and big data research.
To foster a community of researchers capable of generating high-value evidence in imaging.

Main Methods:

A mixed-format educational program combining web-based modules and in-person sessions.
Training covers decision analysis, cost-effectiveness analysis, evidence synthesis, and big data principles/applications.
Participants from diagnostic radiology subspecialties and cardiology were recruited.

Main Results:

The program successfully trained a diverse group of imaging professionals.
Participants gained practical skills in key areas of comparative effectiveness research.
The initiative highlights the potential for expanding CER within the imaging community.

Conclusions:

Methodologic training is essential for advancing diagnostic imaging research.
The developed program effectively enhances researchers' capacity in CER and big data analytics.
Investing in such training can significantly contribute to demonstrating the value of imaging in healthcare.