Medical Imaging Depends on IoT for Automation and Operational Analytics

Medical Imaging Depends on IoT for Automation and Operational Analytics

This piece was originally published in the April 2018 issue of electroindustry.

Henri “Rik” Primo, Director, Strategic Relationships, Digital Health Services, Siemens Healthineers and Mr. Primo is a member of the NEMA Internet of Things Council.

Over the past decade, healthcare providers such as hospitals, outpatient clinics, imaging centers, and physician groups have been merging and consolidating to prepare for increases in the size of the covered population and other expected difficulties with care delivery. There is a consensus that healthcare costs are too high and healthcare delivery practices need improvement.[1]

One proposed healthcare business model focuses on fee-for-value versus the traditional fee-for-service model. By consolidating different healthcare providers through mergers or acquisitions in an integrated delivery network (IDN), opportunities exist to realize cost savings through economies of scale and implement quality improvement programs across the IDN.

Automating Medical Imaging

While the IDN model is a holistic strategy for healthcare organizations, outcomes are based on the sum of all the parts. Radiology is one of these parts, i.e., the imaging service line (ISL).

In an IDN, the individual radiology departments in the different hospital locations ideally follow the same standardized workflow processes. Staff can easily move—physically and virtually—between locations without site-specific workflow training. Patients may schedule their appointments at locations convenient to them.

ISL fleet management is the art of centrally managing utilization of all imaging equipment in the IDN’s different facilities. HIPAA-enabled and designed with cybersecurity provisions, Siemens developed an Internet of Things (IoT) standards-based analytical system. It collects operational data for the entire scanner fleet in an IDN, including patients’ exposure levels to ionizing radiation doses as well as usage information such as computed tomography (CT) scans per day.

Automated analytical reporting shows service line managers (SLMs) where workflows need optimization, e.g., when a certain scanner has lower productivity than the rest of the fleet.

In the IoT, machines can communicate which each other without human interaction. DICOM, the Digital Imaging and Communications in Medicine global information technology standard developed by NEMA, ensures the interoperability to produce and process medical images.[2] In this example, the imaging modality, a computer tomography (CT) scanner sends DICOM images from the patient automatically to the radiologist’s diagnostic reading applications over the intranet as soon as the scan is completed. The diagnostic reading applications then send a DICOM message back to the scanner that the image transfer was successful and the next patient can be scanned.

Simultaneously, the DICOM 3.0–formatted CT images are automatically anonymized, encrypted, and transmitted over the IoT to a cloud-based analytic application.

Information about the image scan is derived from DICOM metadata and is used by the application to auto-analyze operational imaging equipment parameters. The results are then automatically forwarded to a dashboard on the SLM’s fixed or mobile display device. The SLM doesn’t need to manually query the information.

The ionizing radiation dose dashboard shown in Figure 1 allows the SLM to monitor institutional-specific dose reference levels as well as nationally defined targets. Any CT scanner in the IDN’s multisite hospitals operating outside of these levels can be identified in almost real time and corrective action taken.

The dashboard provides easy access to ISL scores and trends. From a daily overview of system scores to the detailed analysis of utilization trends, it allows seamless access to ISL performance and the number of patients examined on a specific scanner. This helps the SLM improve ISL productivity and efficiency.

Utilizing such IoT technology and cloud-based applications enables IDNs to improve quality of care and lower costs by automation and resource optimization.

[1] https://www.ama-assn.org/practice-management/physician-payment-delivery-models

[2] NEMA holds the copyright to DICOM. It is also known as NEMA PS3 and ISO 12052:2017.


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