Imaging Exam Acquisition and Quality Control (QC) Workflow in Today’s Consolidated Enterprise – Part 1 of 2

As existing healthcare provider organizations merge and affiliate to create Consolidated Enterprises, image acquisition workflows are often found to be different across the various facilities. Often, the different facilities that comprise the Consolidated Enterprise had different procedures and standard of practice for image acquisition and Quality Control (QC), along with different information and imaging systems.

Standardizing and harmonizing enterprise-wide policies, especially for imaging exam QC, can have significant benefits. A failure to standardize these workflows in a Consolidated Enterprise may result in inconsistent or inaccurate imaging records, which can lead to reading and viewing workflow challenges. These are compounded with a shared imaging system, such as an enterprise PACS or VNA, and can result in delays in care and patient safety risks.

There are generally two areas worth evaluating for optimization:

  • Technologist imaging exam acquisition workflow (Tech Workflow)
  • Imaging record Quality Control workflow (QC Workflow)

Here, we will explore Tech Workflow. QC Workflow will be covered in a subsequent post.

Throughout this discussion the term Radiology Information System (RIS) is used, which can be a standalone system or a module of an EMR.

Tech Workflow

The use of DICOM Modality Worklist (DMWL) for the management of image acquisition is well-understood and broadly adopted. However, the process of marking an exam as “complete” (or “closed”) following acquisition is less standardized and varies across different vendors and healthcare enterprises. The subsequent QC and diagnostic reading workflows rely on the “completion” of the exam before they can begin. For example, an exam that is never marked as “complete” may not appear on a Radiologist Reading Worklist, and an imaging exam that is marked as “complete” when it isn’t will be available for Radiologists to read with only a partial set of images.

Imaging Technologists typically interact with the following applications on a daily-basis.

Tech WF Screens

  • Modality Console – a comprehensive set of tools, attached to the modality, to perform image acquisition activities (such as DMWL queries, exam protocoling, post-processing, etc.).
  • Radiology Information System (RIS) – a specific view into the enterprise RIS application, allowing Technologists to look up patient/procedure information, a set of tools to document the acquisition and mark exam as “complete”, etc.
  • Image Manager/Archive (IM/A) QC – a comprehensive set of imaging exam Quality Control (QC) tools, provided by the Image Manager/Archive (IM/A), such as PACS or VNA, or a dedicated application, to make any necessary corrections to ensure the quality of acquired imaging exam records.

As stated above, there is significant variability among healthcare providers with respect to instituting Tech Workflow policies and procedures. The following diagram illustrates the steps involved in a common Tech Workflow.

Tech WF Flow

Notes:

  • In some cases, Technologists validate the quality of the image and confirm that the number of images in the IM/A is correct for multiple studies at a time instead of each one independently due to the high-volume of exams being acquired.
  • An ability to assess the quality of the imaging exam and correct it (if needed) in a quick and user-friendly manner is critical for an efficient exam completion workflow.

PACS-driven Reading Workflow

In this scenario, the PACS Client provides a Reading Worklist and it is typically responsible for launching (in-context, through a desktop integration) the Report Creator application. There are several methods used across provider organizations to communicate study complete status updates to the PACS.

Method Benefit Challenge
Time out – this is the most typical approach, which considers a study to be complete after a defined period of time has passed (for example, five minutes) since the receipt (by PACS) of the last DICOM object from the modality.
  • Easy to implement
If the time-out is too long, the creation of the corresponding Reading Worklist item will be delayed. Alternatively, a short time-out may result in a Radiologist reporting an incomplete study, which requires follow-up review and potentially an addendum to the report once the missing images are stored to PACS.
HL7 ORM – some organizations release HL7 ORM messages to the Report Creator only after the order status is updated (to study complete) in the RIS.
  • Easy to implement
  • Prevents reporting of incomplete exams (although relies on Technologists to validate the completeness of the study structure in the PACS)
There are scenarios where PACS has received DICOM studies, but their statuses in the RIS application has not yet been updated (for example, as can happen with mobile modalities). The Reading Worklist is unaware of the HL7 message flow between the RIS and the Report Creator and, therefore, allows the Radiologist to start reviewing cases. However, these cases have no corresponding procedure information in the Report Creator. When the Radiologists tries to launch the reporting application in the context of the current study, the Report Creator is unable to comply.
DICOM MPPS – Once an exam is complete, a DICOM MPPS N-Set message (issued by the modality) informs the PACS (and/or RIS) about the structure of the study and the fact that it is completed (along with other useful exam information).
  • Prevents reporting of incomplete exams
  • Automatic confirmation of the structure of the study

 

  • The adoption of DICOM Modality Performed Procedure Step (MPPS) is still limited in most enterprises, even though some modalities, RIS, and PACS support it.
  • Somewhat complex to implement (requires integration and testing between each modality and the MPPS server) coupled with a lack of understanding as to the benefits of this approach in many healthcare provider organizations.
  • Some modality vendors charge an additional fee for a license to enable MPPS integration.
  • Can be disconnected from the “completion” of the exam in RIS (i.e. can ensure the Report Creator’s readiness), provided only the PACS receives and processes the MPPS messages.
DICOM Storage Commitment – Once the exam is complete, a series of DICOM messages (N-Action, N-Event-Report) between modalities and PACS can determine whether a complete study was stored to PACS.
  • Prevents reporting of incomplete exams
  • Automatic confirmation of the structure of the study
  • Although most PACS and many modalities support this DICOM transaction, it is not widely implemented by healthcare providers.
  • Somewhat complex to implement (requires integration and testing between each modality and the PACS server) coupled with a lack of understanding as to the benefits of this approach in many healthcare provider organizations.
  • Can be disconnected from the “completion” of the exam in RIS (i.e. can ensure the Report Creator’s readiness).

RIS-driven Reading Workflow

In this scenario, the RIS provides the Reading Worklist and it is implicitly aware of the status of the exam (assuming the same system is used by Techs and Rads). It creates the worklist item that corresponds to the exam once it reaches the “complete” status. As the Reading Worklist launches both the Report Creator and the Diagnostic Viewer (PACS Client) applications, it does not face the informatics challenges inherent to the PACS-driven Reading Workflow described above.

Enterprise-wide Reading Workflow (Dedicated, Standalone Application)

Some organizations use an enterprise-wide Reading Worklist that is a separate application from the PACS and RIS to orchestrate enterprise-wide diagnostic reading (and other imaging related) tasks across all their Radiologists using fine-grained task-allocation rules. Similar to the RIS-driven Reading Workflow, the worklist launches both the Report Creator and the Diagnostic Viewer applications once a worklist item is selected.

To prevent the complexity of the PACS-driven Reading Workflow described above, some organizations choose to release an HL7 ORM message from the RIS application to the worklist only when the status of the corresponding exam in that system is updated. Alternatively, organizations that choose to send all ORM messages to the worklist application as soon as procedures are scheduled, need to deal with ensuring that the PACS has a complete study prior to allowing it to be reported.

So, what?

It is important for healthcare provider organizations to understand the relationship between the Tech Workflow and the Reading Worklist approach they adopt. If a RIS-driven approach is not chosen, then there should be a clear integration strategy in place to ensure that studies are not reported too soon or missed.

Article – MU No More…Meet MACRA, MIPS and APMs

The death of Meaningful Use (MU) will not be mourned by many physicians.

While the overall program drove adoption of electronic medical record (EMR) systems, which is necessary for information accessibility, the measures required to be reported upon were viewed by many as misguided and not a reflection of the actual practice of medicine.

Also, many of the EMR systems implemented were criticized as being hard to use with limited capabilities to allow information interoperability with other systems.

Regardless of one’s views of MU, CMS is moving on.

With a keen focus on patient outcomes, CMS is looking to new models for reimbursement, such as the Medicare Access and CHIP Reauthorization Act (MACRA) legislation, introduced last year.

CMS is also intent on addressing the lack of interoperable patient record information.

“We’re deadly serious about interoperability. Technology companies that look for ways to practice data blocking in opposition to new regulations will find that it will not be tolerated.”

Andy Slavitt, acting administrator of the Centers for Medicare & Medicaid Services

The MACRA site provides an overview of Merit-Based Incentive Payment System (MIPS) and Alternative Payment Models (APMs), which are sure to be popular acronyms to fill the void created by the decline of the use of MU in discussions.

Here is another article on Slavitt’s comments. And another article by HIMSS.

My previous posts on healthcare payment reform are herehere and here.

Article: Major Insurance Company will no longer cover Breast Tomosynthesis Exams

Per this article, citing lack of clinical evidence and radiation dose concerns, Cigna will no longer cover Breast Tomosynthesis exams, which generate 3D image sets, as of 15-Feb-2016.

Digital Breast Tomosynthesis (DBT) exams are often praised for their superior ability to provide effective imaging when diagnosing women with dense breasts.

Somewhat of a challenge for IT systems and staff due to the significant size of their data sets compared to the traditional 2D mammogram exams, adoption of DBT modalities has been rapid lately due to the generally accepted diagnostic benefits.

I can’t imagine that this lack of coverage will last.

For those wanting a description of the different between 2D (Mammogram) and 3D (Tomosynthesis) breast imaging, this article provides an overview in plain language.

Here is an RSNA article on the state-of-the-art for Breast Tomosynthesis.

And here is an article on the merits of Breast Tomosynthesis over traditional Mammography for detecting cancer.

And another on reducing recall rates.

ACR: CMS Delays Clinical Decision Support (CDS) Implementation Requirement

ACR post (30-Oct-2015) is here.

Highlight…

…CMS states that they anticipate including further discussion and adopting policies regarding claims-based reporting requirements in the CY 2017 and CY 2018 rulemaking cycles. Therefore, they do not intend to require that ordering professionals meet this requirement by January 1, 2017

Article – First Look at Stage 3: CMS Sticks to Its Guns on APIs, Patient Engagement

Here is a good summary on what is new in Meaningful Use Stage 3 Rules.

This excerpt caught my eye:

As far as timing goes, CMS said it disagrees that the API functionality cannot be implemented successfully by 2018 “as the technology is already in widespread use in other industries and API functions already exist in the health IT industry.”

All of this should be a boon for the FHIR (Fast Healthcare Interoperability Resources) standard development community and the Argonaut Project, working on API-related standards, as well as for the broader community of mobile app and personal health record developers. With barriers to patient access to their data coming down, patients will finally be able to create their own portals, separate from any health system and share that data with whomever they want.

This is good news for everyone.

If we truly want so solve issues that require access to information where and how we need it, we must provide interoperability. This means not only the data needs to available be in a format that is understood and supported by common applications, it means the method of discovering and accessing that data needs to be understood and supported, as well.

FHIR® (clinical data) is built on the right web technologies and design methods, as is DICOMweb™ (imaging data). With these APIs, we can discover and access the necessary patient information and make it available in any care setting we need.

And these APIs will create the foundation of data liquidity to spark an explosion of innovation of applications—including traditional departmental and enterprise ones, but also web and mobile ones.

Without clearly defined, supported and accessible APIs, we (healthcare) had no hope of achieving the kind of system-wide change required. We have no more excuses now.

Article – The Healing Power of Your Own Medical Records

This NYT article tells the story of a very bright young man that took control over has health data and probably saved his own life. Few of us have the knowledge to do what he did, but most would agree that having the choice to access our health data is the right approach.

I suspect that as long as the risk of uninformed patients misusing the information they access and the risk of unauthorized access of protected health information outweigh the demand for access to the information, progress will be limited. How do we balance freedom of information and data liquidity with effective access controls and reasonable assignment of liability?

Previously, I blogged about my thoughts on patient privacy and its use as an excuse for an non-interoperable patient record.

Meaningful Use Stage 3 Rule and Imaging

At 3 pm ET on March 20, 2015, CMS released the Meaningful Use Stage 3 proposed rule to “specify the meaningful use criteria that eligible professionals (EPs), eligible hospitals, and critical access hospitals (CAHs) must meet in order to qualify for Medicare and Medicaid electronic health record (EHR) incentive payments and avoid downward payment adjustments under Medicare for Stage 3 of the EHR Incentive Programs.”

Here is a useful overview of MU Stage 3 (not just about imaging). And here is another MU Stage 3 overview. And here is an infographic.

A quick search for any mention of “imaging” (there are no instances of the word “images” in the 301 page PDF document; I checked), and here are the main excerpts.

Page 78

In alignment with the HHS National Quality Strategy goals, providers are encouraged to implement CDS related to quality measurement and improvement goals on the following areas:

Appropriateness of diagnostic orders or procedures such as labs, diagnostic imaging, genetic testing, pharmacogenetic and pharmacogenomic test result support or other diagnostic testing.

Page 81

Objective 4: Computerized Provider Order Entry

Proposed Objective: Use computerized provider order entry (CPOE) for medication, laboratory, and diagnostic imaging orders directly entered by any licensed healthcare professional, credentialed medical assistant, or a medical staff member credentialed to and performing the equivalent duties of a credentialed medical assistant; who can enter orders into the medical record per state, local, and professional guidelines.

Page 82

We propose to continue our policy from the Stage 2 final rule that the orders to be included in this objective are medication, laboratory, and radiology orders as such orders are commonly included in CPOE implementation and offer opportunity to maximize efficiencies for providers. However, for Stage 3, we are proposing to expand the objective to include diagnostic imaging, which is a broader category including other imaging tests such as ultrasound, magnetic resonance, and computed tomography in addition to traditional radiology. This change addresses the needs of specialists and allows for a wider variety of clinical orders relevant to particular specialists to be included for purposes of measurement.

Page 85

We also propose to maintain for Stage 3 the Stage 2 description of “radiologic services” as any imaging service that uses electronic product radiation (77 FR 53986). Even though we are proposing to expand the CPOE objective from radiology orders to all diagnostic imaging orders, this description would still apply for radiology services within the expanded objective.

Proposed Measures: An EP, eligible hospital or CAH must meet all three measures.

Proposed Measure 1: More than 80 percent of medication orders created by the EP or authorized providers of the eligible hospital’s or CAH’s inpatient or emergency department (POS 21 or 23) during the EHR reporting period are recorded using computerized provider order entry;

Proposed Measure 2: More than 60 percent of laboratory orders created by the EP or authorized providers of the eligible hospital’s or CAH’s inpatient or emergency department (POS 21 or 23) during the EHR reporting period are recorded using computerized provider order entry; and

Proposed Measure 3: More than 60 percent of diagnostic imaging orders created by the EP or authorized providers of the eligible hospital’s or CAH’s inpatient or emergency department (POS 21 or 23) during the EHR reporting period are recorded using computerized provider order entry.

Page 86

Based on our review of attestation data from Stages 1 and 2 demonstrating provider performance on the CPOE measures, we propose to increase the threshold for medication orders to 80 percent and to increase the threshold for diagnostic imaging orders and laboratory orders to 60 percent. Median performance for Stage 1 on medication orders is 95 percent for EPs and 93 percent for eligible hospitals and CAHs. Stage 2 median performance on laboratory and radiology orders is 80 percent and 83 percent for eligible hospitals and CAHs and 100 percent for EPs for both measures. We believe it is reasonable to expect the actual use of CPOE for medication orders to increase from 60 percent in Stage 2 to 80 percent in Stage 3 and the actual use of CPOE for diagnostic imaging and laboratory orders to increase from 30 percent in Stage 2 to 60 percent in Stage 3. We note that despite the expansion of the category for radiology orders to diagnostic imaging orders, we do not anticipate a negative impact on the ability of providers to meet the higher threshold as the adoption of the expanded functionality does not require additional workflow implementation and allows for inclusion of a wider range of orders already being captured by many providers. Therefore, for medication orders we propose the threshold at 80 percent and for diagnostic imaging and laboratory orders we propose the threshold at 60 percent for Stage 3.

Page 88

Proposed Measure 3

To calculate the percentage, CMS and ONC have worked together to define the following for this measure :

Denominator: Number of diagnostic imaging orders created by the EP or authorized providers in the eligible hospital’s or CAH’s inpatient or emergency department (POS 21 or 23) during the EHR reporting period.

Numerator: The number of orders in the denominator recorded using CPOE.
Threshold: The resulting percentage must be more than 60 percent in order for an EP, eligible hospital, or CAH to meet this measure.

Exclusion: Any EP who writes fewer than 100 diagnostic imaging orders during the EHR reporting period.

Page 221

A table lists the estimated time burden to attest for the CPOE rule (Measure 3 for Imaging), as 10 minutes for an EP and also 10 minutes for a hospital.

Article – Imaging Shift to Hospital Outpatient Facilities Concerns Radiologists

Following my post on consumer choice in imaging services, in which I asked how do we use quality—and not just cost—to help consumers make choices, I found some observations in this article on the shift of imaging being done in imaging centers to outpatient facilities to be quite interesting.

For example…

“groups at imaging centers may struggle to upgrade or get new equipment, which could affect image quality and interpretation”

So, how do I, as an imaging consumer know which provider has modern, safe, calibrated equipment, operated by qualified and skilled operators when making my choice of where to get imaging done?

I don’t ask my dry cleaner about what equipment they use, or when it was last serviced, or how much experience the person in the back doing the work has. Nor to I ask these questions about my car wash.

I often make choices in dry cleaning and cash washing based on cost, but more so convenience.

But this is my health and it is my body going through that device, not my clothes or my car.

I wonder how many people will simply trust that a friendly receptionist, flowers and nice magazines in the waiting room at a facility near where I work means quality and safe imaging. If I have a good experience during my imaging appointment, but they miss important findings due to low quality images (or lack of sub-specialty knowledge/training), how will I know?

Unlike a spot that doesn’t come out of my shirt or a still dirty section of my car, the consequences can be severe.

Putting the Power of Choice in the Hands of Healthcare Consumers

As reported in this Healthcare Informatics article, The Health Care Cost Institute, a non-profit organization based in Washington D.C., is making data on healthcare costs from 40 million insure individuals available for use by consumers to help them understand pricing information for common health conditions and services.

As I have blogged about in the past, providing the consumer, referring physicians and employers with tools to help them make choices about where to get affordable and market competitive healthcare services will be a growing trend.

Of course, to measure the value of something based purely on the cost assumes the product or service is a commodity. In the world of medical imaging, this is not the case.

Should an imaging service provider that has 15 year old equipment, no radiation dose tracking or optimization program, no sub-specialized Radiologists, and no peer review program (for quality assurance and ongoing learning) be paid the same for a procedure as a service that has all of these things (and more)?

Unless there is some consideration of quality in calculating the value of the money spent on a service, like medical imaging, then prices will be driven down to a commodity level and there will be no funds available to invest in the tools and resources required to provide quality. The math of economics is pretty unemotional about this stuff.