Imaging Informatics as part of M&A

Recently I read this report titled “M&A—To What End?” written by The Advisory Board Company. Although it was published in 2014, it provides good insight into the ongoing merger and acquisition (M&A) activity in the U.S. healthcare market.

There are several observations that I think are worthwhile sharing.

The motivation behind M&A

Historically, the most common reasons cited for M&A activity are: 1) the consolidated provider’s ability to demand higher prices for delivered services; and 2) the consolidated provider’s ability to secure larger referral volume. The following study by Jamie Robinson of the University of California provides empirical evidence for the first above-mentioned reason.


Therefore, it was quite interesting to read the following statement and the associated chart in the Advisory Group report:

“These benefits of scale are increasingly hard to come by as the health care industry evolves and matures. Still, we see boards and management teams, from the smallest private practices and community hospitals to the largest for-profit chains, continuing to narrowly focus on scale as the primary motivation for M&A. They are asking each other, and asking us: “How big is big enough?” But these days, “How big is big enough?” is a worthy but insufficient question. Size alone, and size’s legacy benefits, will not be enough for health systems to grow profitably. 


Cost-savings Opportunities

The report claims that the perceived economies of scale—that should deliver cost-savings to the merged organizations—exist, but it is very hard to capture them due to “… institutional inertia, pressure from stakeholders, and the sheer magnitude of the task…”.

The following chart is particularly interesting. It ranks different cost-savings opportunities pursued by the merged organization.


As you can see, Radiology Services represent the first clinical domain which is targeted by the merged organizations once the back-office’s economies of scale are achieved.

I find this particular ranking to be sensible. In contrast to other clinical domains, the imaging informatics industry has very mature and standardized clinical IT solutions that can scale to serve merged organizations and provide quick wins during post-merger clinical and IT integration.

Our clients are frequently growing their Radiology services through M&A and affiliation activities. The current state-of-the-art of the imaging informatics market, such as the implementation of VNA and Enterprise Viewer solutions, coupled with existing Image Sharing methods, enables them to abstract the complexities of multiple PACS systems (across multiple joined organizations) to realize both consolidated IT and clinical benefits.

As always, comments, opinions, and insights are welcomed.

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.

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.


“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.”

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.

What can Enterprise Imaging Learn from Radiology?

Radiology Information Interoperability for Productivity and Quality

In the early days of Radiology, data entry errors by Radiology Technologists (aka Techs) were common. Their attention was on the patient and the operation of the modality, not the clerical task of typing in data, after all. To address this, something called a DICOM Modality Worklist (aka DMWL) was developed and adopted.

Essentially, this took the textual patient and imaging procedure order information entered into the HIS or RIS (i.e. the order placer), and sent it to some system as an HL7 ORM message (an order). The structured patient/order information was then provided to modalities using the DICOM protocol (because this is the language they speak). DMWL could be provided by the RIS or PACS or some form of broker system that spoke both HL7 and DICOM.

This allowed trained clerical workers (or physicians), combined with software that validated the data entered (where it could), to pass the information to the modality workstation where it could be mapped into DICOM objects, without having to ask Techs to enter this info. The productivity and information quality gains were significant.

It is worth noting that the order provides other value than just eliminating duplicate data entry. It represents a work instruction, and it is used in scheduling and billing. Where image acquisition is not scheduled or billed for, orders are typically not created.

Enter Enterprise Imaging

As we enter the era of Enterprise Imaging, there are lots of lessons that we can learn from the solved problems in areas like Radiology.

For example, when capturing a photo in a Wound Care clinic, it has to be associated with the correct patient (obviously), but there is likely other pertinent info that should be captured, such as the anatomical region imaged and any observations by the physician.

In Enterprise Imaging, orders are often not placed. In many areas, the imaging is often not the primary task, but one that used to support clinical work.

If orders are not placed, how can we at least provide the benefit of passing textual patient data to the image capture device or application to reliably associate patient (and perhaps encounter or procedure) data?

Even if orders are placed, most of the devices and applications used in Enterprise Imaging cannot accept an HL7 message and do not speak DICOM. Some form of broker would likely be required yet again.

Enterprise Information Interoperability for Enterprise Image Capture

One hope that we have is the adoption of the new HL7 FHIR standard. Based on REST-based API design methods, it is much easier to integrate with different devices (especially mobile devices) than HL7 v2.x messaging and DICOM interfaces are. Other methods used are to generate a URL from the EMR, with all the info provided in parameters, that launches the image capture application/device in context. Another method is to use HL7 messaging to populate the VNA database with patient, encounter and order/procedure information (essentially a copy of what the EMR has), and use a tool or API (perhaps the DICOMweb™ Query API, QIDO-RS) to query this system to get the necessary information.

Don’t Forget the Metadata and Supporting Information

This still leaves the issue of how to reliably and consistently capture the information that goes with the image(s)—notes, anatomy info, findings, technical exam info, observations, etc. In DICOM, when this type of information is needed, a SOP Class is defined. The header of the SOP Class object specifies where all this metadata should go. This is one of the primary principles of interoperability: a defined format and data scheme, with a clear and shared meaning.

Assuming that not all Enterprise Images will be generated in, or converted into, DICOM format, the definition of the metadata schema may be left to be defined by the implementing vendor.

In addition to the clinical and technical data, sooner or later, someone is going to be looking for operational data for use in analytics and process improvement, so it will need to be captured (on some level of detail), as well.

Consistent Terms

And, even when we have a common schema, if the terms used within the scheme are not consistent, we end up spending an enormous amount of time doing mappings or integrating terminology services (and even then, never fully addressing all cases).

To Acquire or Not to Acquire

If we think about Enterprise Imaging that is not “ordered”, what triggers the acquisition of an Enterprise Image? Is it up to the clinic or individual care provider to make the judgement? Should a published set of best practices define this? Would the EMR have logic, based on the patient’s condition or care pathway, to prompt or force the user to acquire and store the image(s)?

Enterprise Imaging Acquisition Protocols Needed?

If we consider the different ways that images can be captured (still, video), the subject in frame (cropping, zooming), lighting, etc., and the ability to capture a single image or a set of images, do we also need some form of a book of protocols to guide the person acquiring the images? Should certain images contain a ruler (or object of known size) to allow the image to be calibrated for measurements?

The Cost of Doing Nothing

If we consider the impact of not having methods to avoid data entry errors, or not having a common schema, not having common terms, and not even having a common communication protocol or best practices for acquisition workflows, what hope does Enterprise Imaging have?

Even with options for all these things, imaging and information devices are still struggling to be interoperable with departmental and enterprise applications, as described in this Healthcare IT News article, “Nurses blame interoperability woes for medical errors”.

The Future is Now(ish)

This is why the mission and output of the joint HIMSS-SIIM Enterprise Imaging workgroup (charter in PDF here) is so important. The space needs to be better defined, with acquisition workflow practices, data formats, schemas, terms, and protocols outlined.

If we simply try to copy what is done in Radiology into Enterprise Imaging, it will create too much of a burden on the people asked to capture these images, and they won’t do it, frankly. Unlike the reimbursement in Radiology, they often have little incentive to spend the extra time to capture, index and upload images to the EMR when they are focused on the patient.

But, if we ignore the benefits that come with the controls and methods we have developed and matured over the years in Radiology, we risk having to re-learn all the same lessons again. And that would be very sad (and expensive, and wasteful, and unsafe…).

Add on top of all this the increasing need to share this data across different enterprises for continuity of care and the importance of interoperable data portability/liquidity is critical.

The fundamental healthcare informatics knowledge and business analysis skills developed by imaging informatics professionals, through on-the-job experience and membership in educational/research societies like SIIM, will be important in determining the right mix of proven concepts that apply, and new methods and innovations. Without a supply of talent to foster the change, nothing will change.

In Conclusion…

When dealing with such an undefined space, people often relish the idea of “doing it right this time”. I would urge anyone involved in this space to reflect on what has been accomplished in mature fields like Radiology, as there are a lot of “right things” that we may be taking for granted. With a little modernization, we can still get continued value out of what we have already achieved.

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.