Point-of-Care Ultrasound (POCUS) Workflow Challenges and Solutions

Point-of-care ultrasound (POCUS) is imaging performed and interpreted by the treating clinician at the moment of care. This can include diagnostic assessment, procedural guidance, and serial monitoring across emergency medicine, critical care, anesthesia, cardiology, vascular access, obstetrics, and hospital medicine, performed by clinicians for whom imaging is one tool among many in a patient encounter that may last only a few minutes. These clinicians are not familiar with the procedural steps governing radiology workflows because they focus on clinical practice within their area of specialization. Scheduling, ordering, protocoling, worklists, and formal diagnostic reports fall outside their scope of practice. The ultrasound scan informs a decision at the bedside, and that decision is frequently made before the study has been named, ordered, or archived.

Enterprise imaging platforms already ingest, archive, and distribute studies from a wide range of devices, departments, and vendors; adding another ultrasound source is not the hard part. The challenge is the sequence of events. Traditional imaging workflows assume an order precedes the exam, and bedside POCUS typically has no order at the moment of acquisition. Almost every downstream problem for POCUS programs traces back to that gap: hand-keyed demographics, studies stranded on device storage, unverified and orphaned exams in the Vendor Neutral Archive (VNA), and no dependable path to documentation, quality review, or credentialing evidence.

Why Traditional Order-Based Imaging Workflows Break Down for POCUS

Traditional radiology workflows follow a structured, order-based process:

• A provider places an imaging order
• Scheduling staff schedule the exam, with edits or protocoling by the radiology department as needed.
• A technologist acquires the images
• A radiologist interprets the study
• The reporting system delivers finalized results to the EHR

This workflow assumes imaging occurs under centralized control, with predefined orders and scheduled acquisition. The critical detail is that the order binds the acquired images to the patient and the procedure: it populates the DICOM Modality Worklist, and the modality receives the identity, accession number, and procedure context from that worklist at the point of acquisition. Everything downstream: PACS, VNA storage, result generation, inherits that metadata. The order always precedes the image.

Bedside imaging breaks that sequence. POCUS is just-in-time imaging, designed to address a clinical question at the time of care. Requiring clinicians to stop and generate a formal imaging order before scanning introduces workflow friction that conflicts with bedside operational realities. When organizations attempt to standardize POCUS practice, that pre-ordering requirement runs directly counter to the speed and immediacy that make POCUS valuable in the first place.

As a result, organizations often encounter fragmented POCUS workflows where “ghost studies” are common:

• Remain stored locally on ultrasound devices
• Never route into PACS or VNA infrastructure
• Lack standardized patient metadata
• Fail reconciliation workflows
• Never become part of the enterprise imaging record

Downstream challenges can involve:

• Image retention
• Patient matching
• Auditability
• Billing reconciliation
• Quality review
• Longitudinal imaging accessibility
• Governance compliance

The challenge with POCUS is not image acquisition, but rather integrating encounter-driven imaging into governed enterprise imaging workflows without disrupting bedside care delivery.

Common Technical Challenges in Enterprise POCUS Environments

Inconsistent Patient and Study Metadata
POCUS environments frequently rely on manual demographic entry directly at the modality, often creating downstream interoperability and reconciliation challenges involving:

• Duplicate patient records
• Incorrect MRNs
• Inconsistent accession numbers
• Orphaned studies
• Metadata normalization failures

Poor metadata quality impacts PACS indexing, archive integrity, reporting workflows, analytics, and enterprise imaging governance.

Disconnected Ultrasound Devices
Most POCUS devices operate independently, cut off from the rest of the imaging environment. Without centralized workflow orchestration, the same problems tend to show up everywhere:

• Images sit in local storage instead of getting where they need to go
• Exams have to be exported by hand, one at a time
• Storage fragments across devices instead of consolidating
• Routing looks completely different from one department to the next

Most organizations don’t have a reliable way to route, reconcile, and archive bedside ultrasound studies across the enterprise.

EHR and Reporting Integration Gaps
Many POCUS implementations lack integrated reporting workflows between ultrasound devices, enterprise imaging systems, and the EHR.
Common gaps include:

• Imaging without associated documentation
• Documentation without associated imaging
• Manual transcription workflows
• Disconnected worksheet results
• Incomplete patient encounter records

These issues reduce accessibility, traceability, and operational efficiency across the enterprise.

Multi-Vendor Device Interoperability
Enterprise POCUS programs rarely standardize on a single vendor platform.
Organizations often support devices from multiple manufacturers across departments, creating challenges involving:

• Different DICOM implementations
• Proprietary worksheet formats
• Variable network capabilities
• Inconsistent metadata structures
• Difficulty in study attribution to the correct provider

Vendor-neutral interoperability becomes essential for scalable enterprise deployment.

Governance and Operational Oversight
Enterprise POCUS governance programs increasingly require:

• Centralized image retention
• Workflow traceability
• Quality review processes
• Metadata standardization
• Audit logging
• Cross-site accessibility

Without centralized workflow management, operational oversight becomes fragmented across departments and device silos.

Encounter-Based Imaging Workflow (EBIW) and POCUS

The HIMSS-SIIM Enterprise Imaging Community and American Institute of Ultrasound Medicine (AIUM) identify Encounter-Based Imaging Workflow (EBIW) as the appropriate workflow for POCUS and other encounter-driven imaging environments.

EBIW supports imaging workflows in which clinicians make imaging decisions at the point of care rather than through predefined imaging orders. Instead of requiring clinicians to place an order before performing a study, EBIW enables immediate image acquisition by generating modality worklist data in advance and supplying accurate patient and study metadata at the time of imaging.

Accurate metadata supports downstream interoperability workflows, including:

• DICOM routing to PACS or VNA systems
• Patient reconciliation
• Enterprise archive integration
• EHR association and documentation workflows

1. Patient Identified at the Bedside
   Unifier pulls patient demographics from an HL7 ADT feed or FHIR query and populates a DICOM Modality Worklist (DMWL). Clinicians can then select the correct patient directly on the ultrasound system without manual demographic entry.
2. Clinician Performs the Scan
   The provider performs the ultrasound examination when and where clinically necessary, without interrupting the workflow.
3. Images: Route to PACS or VNA
   Completed studies are transmitted to Unifier and routed to the enterprise imaging archive via standards-based DICOM workflows, making them immediately accessible across the enterprise.
4. Results: Deliver to the EHR
   If worksheet data exists on the ultrasound device, Unifier transforms and routes it to downstream systems via HL7 ORU messaging or DICOM-encapsulated PDF workflows. The EHR can then associate imaging and documentation within the patient encounter and, where necessary, retroactively generate imaging order linkages.

How Dicom Systems Unifier Enables Encounter-Based Imaging Workflow

The Unifier platform removes the order from the critical path without removing it from the record.

Registration data serves as the source for the worklist. Every patient seen at a medical center is registered, and that registration already emits an HL7 ADT message from the EHR – no new workflow, no clinician action. Unifier consumes that feed and transforms each qualifying event into a POCUS-specific Modality Worklist entry, creating a unique accession number in the process. Where an organization prefers to key on scheduling rather than registration, SIU messages can work the same way.

The clinician decides that POCUS is indicated, refreshes the ultrasound device’s worklist, and selects the patient already present. The study is acquired with correct demographics, encounter context, and accession embedded in the DICOM metadata – the same metadata an order would have supplied, obtained without the clinician placing one.

To correctly present the data as part of the cohesive patient record, the order is still created; however, the Unifier triggers it only when it should. Unifier holds the HL7 order message (ORM) until the acquired study arrives from the device. Registration creates a worklist entry, but only a performed exam creates an order. Unifier then issues the ORM to the EHR carrying the accession it minted, and Epic, Cerner, and comparable systems create the order reflexively, binding it to the same accession the images already carry. The clinician never touched an order screen, but the chart, the revenue cycle, and the imaging record all benefit from this complete metadata. The workflow inverts the sequence — image first, order behind it — without breaking the identity model everything downstream depends on.

From there, the workflow is conventional. Unifier routes the completed study into PACS or VNA using standards-based DICOM, applying tag morphing and normalization to reconcile device-side variation across ultrasound manufacturers. Interpretation is documented by the performing clinician as a templated clinical note in the EHR, keeping the diagnostic record in the patient’s existing encounter documentation.

The Benefits of Dicom Systems Unifier® In Orchestrating POCUS Workflows

Worklist scoping is department-specific. Unifier filters and shapes worklist generation by facility, unit, or location from the ADT feed, so an ED device sees ED patients and an anesthesia device sees the pre-op list for the surgery department. Without this, an enterprise ADT feed produces worklists too large to use at the bedside. We work with you to ensure the correct scoping is implemented, which is what makes the model operational.

The order is gated on acquisition, not registration. Since the ORM is triggered upon study arrival rather than upon ADT, the EHR receives one order per exam performed. A department that registers two hundred patients and scans fifteen creates fifteen orders, not two hundred.

The clinician-facing workflow requires no additional steps in the EHR before imaging. The EHR-side work before the workflow is implemented may include adding POCUS orderables, as appropriate for each department, and mapping them in Unifier as valid order types.

We remain vendor-neutral at both ends. Any ultrasound device that supports DICOM Modality Worklist can be used; any PACS or VNA can receive the DICOM data, and the EHR will still receive an order record. Organizations are free to continue using their diverse fleet of POCUS devices and benefit from a streamlined, governed workflow.

Deployment follows the organization’s preference: on-premises, cloud, or hybrid, with centralized workflow governance across hospitals, ambulatory facilities, and remote care environments.

The result is an encounter-based imaging workflow that preserves the immediacy of POCUS, while producing studies that are archived, discoverable, auditable, billable, and part of the patient’s longitudinal medical record.

Connect POCUS to Your Enterprise Imaging Ecosystem

See how Dicom Systems can help your organization build scalable POCUS workflows with vendor-neutral interoperability, enterprise imaging integration, and encounter-based workflow orchestration.