Report – Fifth Annual Study on Medical Identity Theft

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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

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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!

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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

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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.

What can Enterprise Imaging Learn from Radiology?

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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 – Imaging Shift to Hospital Outpatient Facilities Concerns Radiologists

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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

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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.

Article – Million Dollar Murray

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This Malcolm Gladwell article has nothing directly to do with medical imaging or healthcare record integration, which I often discuss here, but does use analytics of data to identify the type of problem distribution (bell curve vs. power law) involved. And this seems to be a very important step to complete before designing a solution to a large, complex problem—such as homelessness and its impact on healthcare costs.

It was originally published 9 years ago, but all the stories and findings are still just as powerful today. And the solutions suggested are considered just as radical nearly a decade later.

I hope you find the time to read it, as I really enjoyed reading it.

The Healthcare Revenue Revolution Continues

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I continue to study how healthcare payment reform will affect services like diagnostic imaging. I blogged about it here, and here.

If you are really keen on learning about this topic, I recommend that you follow some of the links provided. Lots of info to absorb.

Now, HHS—in what is being called an ‘historic’ announcement—is making major changes towards value-based reimbursement.

Also, the trends in Revenue Cycle Management (RCM) provide insights to how the financial management leaders see things changing. This article from Healthcare IT News, titled Revenue cycle headed for a ‘new world’, reinforces the trend towards provider consolidation and predicts that RCM will be increasingly outsourced. Worth a read.

One thought I have been musing…

Will value-based reimbursement accelerate the adoption of so called Enterprise Imaging capture and integration within the EMR (using a common platform for image management and viewing)?

Up until now, the ROI on enterprise imaging has been elusive, mostly because it is compared to fee-for-service imaging, like Radiology. However, once the reimbursement model changes, and the improved correlation of images and findings across diagnostic and clinical imaging proves to contribute positively to outcomes (as I expect that it will), the capture and integration of enterprise images within the patient record may be rapidly adopted.

Article – Insurers will have to change to survive

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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.