Article – Hospital Hookups: Implications for Imaging IT

This article interviews several people in the trenches, and on the front lines, of imaging IT planning, integration and management in today’s Consolidated Enterprise.

Critical to success are:

  • Imaging and clinical informatics knowledge (how to get all those MRNs to link, how to manage orders and results across facilities)
  • Solution flexibility/scalability (having systems that can expand, as needed, at reasonable cost…even temporarily during a data migration)
  • Viable financial models (shared cost allocations based on volumes)
  • Policy development (for assigning user permissions and setting data quality and retention targets)
  • Human resource planning (what roles and skills are needed post-consolidation)
  • Partnerships with suppliers (to ensure that system expansion and data consolidation will succeed at predictable costs)

Organizations that prepare for consolidation and invest effort in these areas will survive—and even thrive—in the never ending healthcare provider merger and acquisition race.

Enterprise Imaging Industry State-of-the-Art

Based on discussions with colleagues and our clients, Enterprise Imaging is becoming an integral part of U.S. Hospital IT Consolidated Clinical Record strategies.

HIMSS-SIIM Enterprise Imaging Workgroup‘s current working definition of Enterprise Imaging is as following:

  • Diagnostic Imaging – Encompassing traditional diagnostic imaging disciplines such as Radiology and Cardiology
  • Procedural Imaging – Including images that are acquired for diagnosis or clinical documentation purposes (such as visible light photos, point-of-care ultrasound)
  • Evidence Imaging – Including images and/or videos that are acquired for clinical documentation purposes (for example, scope videos, computer aided detection)
  • Image-based Clinical Reports – Documentation that includes or entirely consists of images (for example, Pulmonary Functional Test (PFT) report, multi-media pathology report)

Despite the attention from vendors, industry focus, and provider demand, this market space is still in its early stages of development. There are two main reasons: 1) the scope of the problem domain is still being defined; and 2) the vendor community is still working out the best practices and optimal technical approaches.

Moreover, the number of the departments that generate Enterprise Imaging content and that have their own departmental workflows is quite large.

This results in significant confusion on the provider side who are left to navigate a myriad of perspectives expressed by the imaging informatics industry. There are on-going initiatives that are currently working on demystifying the field of Enterprise Imaging. For example, the recent SIIM Webinar delivered by Dr. Towbin from Cincinnati Children’s, provides a very thorough analysis of the problem domain.

In conversations with vendors and providers, we have compiled several observations that might benefit the imaging informatics community.

The Right Approach

In the SIIM 2015 Opening General Session presentation, Don Dennison presented the following slide titled “Enterprise Image Management: Making the Right Choice”

EI

With the various systems in place to manage patient record data, there is often debate as to which enterprise system is best suited to offer Enterprise Imaging services.

At the moment, there is no obvious answer to the question presented by the slide. Besides the technical capabilities of the systems, the provider’s internal IT capabilities, capacity and policies can significantly influence the decision. At some organizations, where the Imaging Informatics Team plays a prominent IT role, the choice could be the VNA, while at others, where the Enterprise IT team takes the lead, the EMR or ECM is often chosen.

The Right Functionality

During RSNA 2015, we conducted a study to identify the state-of-the-art of Enterprise Imaging technology, including methods of acquisition, management, and distribution of non-DICOM images. The following table summarizes our findings.

 

Image / Video Acquisition
Ability to capture from mobile devices The majority of current vendors opted for native applications to provide better user experience and tighter security controls. Still, image capture is the prevailing capability, with video acquisition capabilities lagging behind. Some vendors offer integration with leading EMRs’ mobile applications.
Ability to capture from visible light cameras The ability to manually (i.e. file browse, drag & drop, etc.) upload both videos and images is a commodity. Automatic ingestion, on other hand, varies significantly from vendor to vendor. Most vendors offer proprietary integration frameworks, but their comprehensiveness and real-life integration experience is very different from one to another.
Ability to capture from different scopes Most of the vendors leverage third party hardware devices to integrate with digital or analog video sources real-time.
Acquisition Workflow
Order-based Workflow DICOM Modality Worklist (DMWL) SCU support, as well as the ability to generate or receive order information, are available in most vendor’s applications.
Context-based launch of the capture application is also a well understood and supported functionality.
Many of the vendors mimic an order-based workflow (i.e. create the Accession Number) for the acquisitions that are not scheduled. The main challenge with this approach is to determine the correct method to feed the created information back to the EMR (e.g. often called an “unsolicited result”, which may not be supported at the site).
Encounter-based Workflow Some vendors, originating from the Diagnostic Imaging space, struggle with native Encounter-based workflow support.
On many occasions, departmental visit/encounter information, supplied in HL7 messages from the EMR, is sufficient to build specific acquisition worklists for different service lines.
Scenarios where information services are not available Most of the vendors offer the ability to manually create patient and procedure information. The difference lies in whether all or just a sub-set of capturing methods (e.g. mobile vs. desktop) support that functionality.
Patient identity management Standards-based methods to discover or receive patient information is widely supported, while the support for proprietary methods to connect to patient information sources varies from vendor to vendor.
Ability to Edit Images/Videos
Editing Tools Most of the vendors rely on an installed Windows OS client application to edit (e.g. crop) acquired images or videos as part of the manual upload process (e.g. drag & drop). Selected vendors also allow static image editing only (i.e. no video) during the mobile capture.
Images An ability to associate different types of metadata (including notes) is supported by the majority of the vendors. Also, basic manipulation of the acquired images such as image deletion, markups and annotation, which are stored as overlay objects associated with the acquired images is common.
Only selected vendors are capable of calibrating images on-the-fly by using recognizable objects of known size embedded in the image.
Videos A flexible and comprehensive ability to associate different types of metadata (including notes and keywords) is supported by the majority of the vendors.
Most of the vendors have very limited (if at all) video editing and capturing capabilities and rely on third party providers.
Viewer
Current state The solutions typically consist of the following viewers:

  • Mobile capture
  • Desktop image/video upload
  • Desktop image/video editor
  • Zero-footprint (ZFP) EMR viewer with very limited, if at all, editing capabilities
Privacy and Security
Current state Most of the vendors offer a range of methods to ensure PHI protection such as:

  • Information deletion/encryption from the device
  • Strong Authentication and Authorization methods
  • Auditing
Reporting
Current state The most prevalent approach is to rely on an external system, such as the EMR or specialty-specific reporting application, to create and manage reports.
Record Management
Current state Most of the vendors opt for managing image and videos in their native format, while converting the content on-the-fly for standards-based communication with external systems.

Conclusion

It seems that Enterprise Imaging is going to rapidly evolve and we are eager to see how our clients, and providers in general, will benefit from these changes.

Working on an Enterprise Imaging project? Leave us a comment with your thoughts, or contact us.

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 – 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.

Report – Fifth Annual Study on Medical Identity Theft

Here is a report on the theft of medical identity data. Worth a read.

Excerpts…

“Since last year’s study, medical identity theft incidents increased 21.7 percent. “

“Sixty-five percent of medical identity theft victims in our study had to pay an average of $13,500 to resolve the crime.”

“…victims learn about the theft of their credentials more than three months following the crime and 30 percent do not know when they became a victim. Of those respondents (54 percent) who found an error in their Explanation of Benefits (EOB), about half did not know whom to report the claim to”

“Forty-five percent of respondents say medical identity theft affected their reputation mainly because of embarrassment due to disclosure of sensitive personal health conditions (89 percent of respondents). Nineteen percent of respondents believe the theft caused them to miss out on career opportunities. Three percent say it resulted in the loss of employment.”

“…79 percent of respondents say it is important for healthcare providers to ensure the privacy of their health records. Forty-eight percent say they would consider changing healthcare providers if their medical records were lost or stolen.”

“Twenty-five percent of medical identity theft victims in this study knowingly permitted a family member or friend to use their personal identification to obtain medical services and products and 24 percent say a member of the family took their credentials without their consent.”

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.

Why should you work here? No EMR!

This article has some great observations and sound bites, including the mention of a hospital promoting the lack of an EMR in their employee recruiting ad as a reason to work there.

Health IT is often touted by IT professionals (myself included) as necessary for the digitization, consolidation, aggregation, integration, access, and exchange of a patient’s information.

The article describes how the introduction of an anti-social third party—a computer with an EMR on it—affects the physician-patient relationship.

It also talks about the current state-of-the-art for user experience design within EMR systems.

In an example of a near fatal medical error involving an EMR, it mentions a phenomena often known as “alert fatigue”, whereby a system provides so many alerts, they become ignored (or disabled). IT professionals may have experienced this in poorly configured system monitoring solutions.

See this article for an more in depth explanation of the problem that caused the medical error.

In talking with organizations that are in the throws of EMR adoption, they are focused on data migration, interface development, pre-canned training, roll outs, organization redesign, and cost management. There is little time for reflection on user satisfaction or efficiency. Vendors trying to sell their solutions into one of these organizations often find it difficult, as resources are scarce and the motivation to add yet another system to manage/interface is low. Budget holders are reluctant to spend money on solutions if their pending EMR promises to have similar capabilities (even if this claim is yet unproven).

When I encounter an organization that is well past their EMR implementation, they are typically looking for ways to optimize their use of the EMR. This may involve configuration changes to the EMR or changes to their workflow, but often involves the use of add-on solutions to fill gaps, or “hacks” to provide alternatives to the user interfaces provided by the EMR to their users.

The above observation on how organizations differ based on where they are in their EMR adoption, makes me think about this excerpt from the article…

“In the 1990s, Erik Brynjolfsson, a management professor at M.I.T., described “the productivity paradox” of information technology, the lag between the adoption of technology and the realization of productivity gains. Unleashing the power of computerization depends on two keys, like a safe-deposit box: the technology itself, but also changes in the work force and culture.”

I think that where Brynjolfsson is recommending  that both “keys” are considered and used in parallel—at least where EMRs are concerned—we are more often than not using them serially. First, get the EMR in as quickly as possible (to save costs and hopefully to reap the rewards promised sooner), and only after we better understand what we actually bought and have, start to figure out how to do it right.

There may be no better way, given that healthcare institutions can’t just stop and “reboot” themselves with a system and staff that is optimized. But, one can imagine that living and working in that period following an EMR implementation, and before the age of enlightened optimization, can be painful and frustrating (and even dangerous, as the article shows).

So, maybe promoting the lack of an EMR may attract those people tired or afraid of the post-EMR, pre-optimization period, as there they can be happy. For a while.

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 – Insurers will have to change to survive

I have been very interested in the changes to how Radiology revenues will be affected during the shift from volume to value based reimbursement, along with changes to healthcare business models in general. I blogged about it here.

I have also been interested in how Radiology will have to change their behaviors in this new environment of transparency and empowered consumers. I blogged about that here.

In this article, a healthcare investment firm details how insurers will have to change in order to compete for mind share among consumers (with choice).

Another very interesting point they make is about wearables. I agree that they are only used by so called Innovators (from the Innovation Adoption Lifecycle model) today.

But what if insurance companies start offering incentives in the form of reduced policy premiums for people that use them (and share the data with the insurer perhaps). This is much like having a security system on your home lowers the cost of your theft insurance, or smoke detectors lowers your fire insurance premiums. This would create a boom in the mHealth sector, and would likely improve outcomes through early detection and correcting unhealthy behaviors.

I wonder: Will providers and insurers compete for who knows the patient best?

Providers have the EMR data (for encounters with their facility), and perhaps from an HIE (if they are part of one). Insurers have info from payment transactions spanning hospitals, clinics, pharmacies and others.

Where will the data from wearables go? If the insurers are buying (by lowering premiums), I will bet that they get it more often that the provider.

Will wearables and mHealth device vendors be savvy enough to provide it to both? Will consumer-controlled PHR vendors (or information aggregation and brokering tools) have an optimized method for getting data from all a patient’s devices and apps into EMR systems? Will the provider’s EMR or HIE be open enough to receive and store the wearable’s data without manual data entry (or copy-paste)?

Will patient’s be willing to share this personal info with providers and insurers? I will bet: yes.

If I thought the data would help my outcome, and I trusted my provider, I would share it.

If it was certain to lower my premiums, I would share the info with my insurer. If the insurer reserved the right to increase premiums based on info that my wearable provided (i.e. if I sit on the couch too long, my payment goes up), I might reconsider.

Will providers supply no cost (or subsidized) wearable and mHealth devices (or apps) to patients? Will insurers and providers share this cost?

So, how can wearables help in Radiology? Other than sending out reminders on where and when to show up for the exam, and what to do (e.g. eating, etc.) prior to the procedure.