News | February 24, 2011

FDA Creates New Approval Guidelines for Medical Device Data Systems

February 24, 2011 – The U.S. Food and Drug Administration (FDA) will no longer require review or approval of technology that helps increase interoperability between devices and information systems. The move is being made to simplify the flow of information between medical devices and electronic medical record systems.

On Feb. 15, the FDA issued a final rule formally reclassifying medical device data systems (MDDSs) from Class III into Class I, so they will not be subject to FDA review or clearance. MDDS manufacturers will be required to register as medical device manufacturers and list their commercially distributed devices with the FDA by April 18, 2011. Manufacturers also must establish compliant quality systems for the design, manufacturing and validation of their MDDSs, as well as adverse event reporting procedures, by April 17, 2012.

Medical Device Data Systems

A medical device data system is a new category of medical device that acts as a communication conduit for electronic data obtained from other medical devices. An MDDS may be used for the electronic transfer, storage, conversion or display of data. It may include software, electronic or electrical hardware such as a physical communications medium (including wireless hardware), modems, interfaces and a communications protocol. MDDSs do not include devices that control or alter the functions of any connected medical devices or that are intended to be used in connection with active patient monitoring. Examples of MDDSs include devices that collect and store data from glucose meters for future use or that transfer lab results for future use at a nursing station.

Implications for MDDS Vendors, Hospitals, and Other Health Care Facilities

The FDA describes the reclassification of MDDSs as a de-regulatory move. While the FDA’s assertion is technically correct, in practice the FDA has historically exercised enforcement discretion not to subject such software products to active regulation. As a result, most MDDS vendors have not established FDA-compliant systems and procedures. For many vendors, establishing FDA-compliant systems will require adoption of more rigorous design, validation, complaint handling and change control procedures than they are accustomed to following.

This new rule may also affect hospitals and other health care facilities that purchase and integrate MDDSs into health IT (HIT) systems. To take advantage of federal and state HIT incentive programs, it will often be beneficial for systems to download electronic medical data directly from devices used in patient monitoring or treatment. The FDA acknowledged that such purchasers may become medical device manufacturers subject to the FDA oversight and regulation if they modify an MDDS outside the parameters of the original manufacturer’s specifications. Hospitals and other healthcare facilities that wish to avoid the FDA regulation need to review their use of MDDSs, paying particular attention to any customization that they may have done or are planning to do to such systems.

The FDA’s action also may complicate the regulatory landscape for manufacturers of software that falls outside the narrow MDDS definition. In the preamble to the rule, the FDA says that devices such as clinical decision support tools (such as may be found in some HIT systems), software used for active patient monitoring, electronic health records (EHR), and Personal Health Records, are not MDDSs. At the same time, the FDA emphasizes that it has withdrawn its earlier guidance describing the agency’s generally lenient approach to software regulation and that it considers unclassified software devices to be Class III, thus requiring FDA approval. These statements may create interpretive and compliance challenges for some software vendors.

For more information: www.fda.gov

Related Content

FDA Clears Bay Labs' EchoMD AutoEF Software for AI Echo Analysis
Technology | Cardiovascular Ultrasound | June 19, 2018
Cardiovascular imaging artificial intelligence (AI) company Bay Labs announced its EchoMD AutoEF software received 510(...
News | Remote Viewing Systems | June 14, 2018
International Medical Solutions (IMS) recently announced that the American College of Radiology (ACR) added IMS'...
Wake Radiology Launches First Installation of EnvoyAI Platform
News | Artificial Intelligence | June 13, 2018
Artificial intelligence (AI) platform provider EnvoyAI recently completed their first successful customer installation...
How AI and Deep Learning Will Enable Cancer Diagnosis Via Ultrasound

The red outline shows the manually segmented boundary of a carcinoma, while the deep learning-predicted boundaries are shown in blue, green and cyan. Copyright 2018 Kumar et al. under Creative Commons Attribution License.

News | Ultrasound Imaging | June 12, 2018 | Tony Kontzer
June 12, 2018 — Viksit Kumar didn’t know his mother had...
Zebra Medical Vision Unveils AI-Based Chest X-ray Research
News | Artificial Intelligence | June 08, 2018
June 8, 2018 — Zebra Medical Vision unveiled its Textray chest X-ray research, which will form the basis for a future
Konica Minolta Launches AeroRemote Insights for Digital Radiography
Technology | Analytics Software | June 07, 2018
Konica Minolta Healthcare Americas Inc. announced the release of AeroRemote Insights, a cloud-based, business...
Vinay Vaidya, Chief Medical Information Officer at Phoenix Children’s Hospital

Vinay Vaidya, Chief Medical Information Officer at Phoenix Children’s Hospital

Sponsored Content | Case Study | Artificial Intelligence | June 05, 2018
The power to predict a cardiac arrest, support a clinical diagnosis or nudge a provider when it is time to issue medi
How image sharing through a health information exchange benefits patients while saving time and money is depicted in this slide shown at HIMSS 2018. Graphic courtesy of Karan Mansukhani.

How image sharing through a health information exchange benefits patients while saving time and money is depicted in this slide shown at HIMSS 2018. Graphic courtesy of Karan Mansukhani.

Feature | Information Technology | June 05, 2018 | By Greg Freiherr
A regional image exchange system is saving lives and reducing radiology costs in Maryland by improving the efficiency
Using Imaging Analytics for Radiology, VCU Health in Richmond, Va., has developed a dashboard to view turnaround time analysis. This functionality allows drill down for each technologist and radiologist and looks at the different steps of the imaging cycle.

Using Imaging Analytics for Radiology, VCU Health in Richmond, Va., has developed a dashboard to view turnaround time analysis. This functionality allows drill down for each technologist and radiologist and looks at the different steps of the imaging cycle.

Sponsored Content | Case Study | Information Technology | June 05, 2018
Sharon Gibbs, director of the radiology department at VCU Health in Richmond, Va., aims to provide quality, timely and...
PACS and the Road to Reconstruction
Feature | PACS | June 05, 2018 | By Dave Whitney and Jef Williams
The PACS — picture archiving and communication systems — have been in existence for more than 45 years. One of the...
Overlay Init