Author Archives: Charlotte Davis

Market Impact of EMA decision on GBCAs

Walking a Gadolinium Tightrope of Perception & Bottom Line

The recommendation by the European Medicines Agency (EMA) on 10 March that market authorisation for four linear gadolinium contrast agents (GBCAs) be suspended shocked the radiology community, but very little has been said about this decision’s effect on businesses.

Supply of the agents in question is significant business for Bayer HealthCare Pharmaceuticals (Magnevist), GE Healthcare (Omniscan), Bracco (MultiHance), and Guerbet (Optimark), and Europe’s one of their largest and most mature marketplaces. So, what will be the market repercussions?

Fight or flight? It’s not all black and white

The information offered with the EMA announcement provides a few clues about how the market will react. However, it’s clear that a swift reversal of the recommendation and soon-expected EMA suspension is unlikely.

This is the opening extract of Steve’s regular monthly market column for AuntMinnie Europe.  

To read the full article, please click here.

(Access to the article may require free membership to AuntMinnie Europe – it’s full of great content and insight so well worth signing up!) 

Deep Learning in Ultrasound – Ready to be Embedded?

Applying Deep Learning to Ultrasound – Is the Technology Ready to be Embedded?

Written by Simon Harris

Much like at last year’s RSNA conference, deep learning was one of the key themes at ECR 2017. Several speakers at the scientific sessions presented promising research results for the application of deep learning in specific use-cases. In one of the professional challenges sessions, Dr. Angel Alberich-Bayarri from QUIBIM suggested that convolutional neural networks (CNNs) may already be old news, with generative adversarial nets (GANs), a new architecture for unsupervised neural networks, showing promise for medical imaging applications. GANs may be a solution to one of the major challenges with developing deep learning algorithms – the need for large training data sets.

On the exhibition floor, there were fewer companies showing machine learning solutions than at RSNA (there were at least 20 at RSNA but less than 10 at ECR) and in our conversations with vendors it was evident that expectations were more measured, with less marketing hype. Several of the better known deep learning start-ups were notable by their absence, including Enlitic and Zebra Medical, as was IBM Watson Health.

Samsung chose ECR to make a big push for its S-Detect™ deep learning feature, which is currently available as an option on its RS80A premium ultrasound system. S-Detect™ for Breast makes recommendations about whether a breast abnormality is benign or cancerous. It is commercially available in parts of Europe, the Middle East and Korea and is pending FDA approval in the US. S-Detect™ for Thyroid uses deep learning algorithms to detect and classify suspicious thyroid lesions semi-automatically based on Thyroid Image Reporting and Data System (TI-RADS) scores. With both applications, S-Detect™ produces a report to show the characteristics of the lesion, including composition, echogenecity, orientation, shape, etc., along with the risk of malignancy, e.g. “high suspicion”.

ContextVision, the leading independent vendor of ultrasound image enhancement software, showcased its latest research in artificial intelligence at ECR.  Its prototype VEPiO (Virtual Expert Personal Image Optimizer), which is built on the company’s Virtual Expert artificial intelligence platform, can automatically optimize ultrasound images for individual patients. VEPiO aims to improve diagnostic accuracy and reduce scan times, particularly for more challenging patients, by making automated setting adjustments to obtain the optimal image quality. The company is also exploring the use of deep learning to optimise image quality, for organ-specific segmentation and for decision-support functionalities.

Ultrasound OEMs must decide whether deep learning technology is ready to be embedded into their systems, or to take a “wait and see” approach. Although many research papers have found that deep learning can produce good results in specific medical imaging applications, often at or near the performance of experienced radiologists, these are usually based on relatively small datasets and/or small reader studies. It remains to be seen if deep learning will perform as expected in routine clinical use. Although Samsung has taken an early lead and is the first of the major ultrasound vendors to embed deep learning, it carefully positions S-Detect™ for Breast as a decision support tool for “the beginner or non-breast radiologist”.

OEMs must also decide whether to establish an in-house deep learning capability or to partner with a specialist. Deep learning engineers are a scarce and expensive resource and most mid-tier ultrasound OEMs will struggle to attract and retain talent. Instead we expect they will partner with independent software vendors, such as ContextVision. For the major OEMs, we expect to see a combination of build, buy and partner strategies. Most of the major modality OEMs have, to varying extents, established in-house R&D efforts for machine learning and with over 50 start-ups developing artificial intelligence solutions for medical imaging, there’s certainly no shortage of options for acquisitions and partnerships.

Another limiting factor is the additional processing power, typically GPUs, required for embedded deep learning algorithms. Ultrasound is a fiercely contended and price sensitive market and OEMs will be reluctant to add additional hardware cost. Initially we expect deep learning to be an optional feature on premium systems only, such as with the Samsung example, but as is often the case in ultrasound, features that start out on premium systems typically cascade to less expensive high-end and mid-range systems over time.

With deep learning technology progressing at a rapid pace, and ultrasound OEMs constantly on the look-out for the next “big thing” to differentiate their products, it seems inevitable that deep learning will increasingly be embedded in ultrasound systems, both as workflow tools to help with productivity and decision support tools to improve clinical outcomes.  It’s no longer a question of will it happen, but when will it happen, and the OEMs that wait too long will get left behind in the AI race.

 

Related Reports

Machine Learning in Medical Imaging – 2017 Edition” provides a data-centric and global outlook on the current and projected uptake of machine learning in medical imaging. The report blends primary data collected from in-depth interviews with healthcare professionals and technology vendors, to provide a balanced and objective view of the market. If you would like further information please contact Simon.Harris@signifyresearch.net.

PHM & Telehealth at St. Joseph Health

The Signify Innovator Series: Patient Portals, PHM & Telehealth at St. Joseph Health

The Signify Innovator Series: Read how pioneers in the provider community are driving innovation through the use of leading edge technology.

Download our interview with Dr. Michael Marino, DO, MBA who is Chief, IS Operations/ Clinical Systems at St. Joseph Health. Dr Marino discusses how St. Joseph’s has innovated on patient engagement, risk stratification and remote patient monitoring.

Click here to download the interview

Funding Analysis of Companies Developing Machine Learning Solutions for MI

Funding Analysis of Companies Developing Machine Learning Solutions for Medical Imaging

There are over 50 start-up companies developing artificial intelligence solutions for medical imaging. Combined, these companies have raised over $100 million in funding. This short report from Signify Research shows the trends in capital funding for these companies and highlights how funding breaks down by company, by region and by clinical application.

Click here to download the report

Key Observations from ECR 2017

Key Observations from ECR 2017:

  • Is Radiology Losing Grip on Imaging IT Decision-Making?
  • Applying Deep Learning to Ultrasound – Is the Technology Ready to be Embedded?
  • Canon + Toshiba + Vital + Olea = Serious Competitor, but do they have a missing link?

Is Radiology Losing Grip on Imaging IT Decision-Making?

Written by Steve Holloway

In stark contrast to the recent RSNA show in North America, imaging IT and vendor neutral archives (VNA) were far less evident at ECR. Of course, the traditional radiology PACS vendors were there alongside the well-known names in advanced visualisation, but you had to hunt hard for any independent VNA vendors. Even on the major vendors’ booths, imaging IT was far from prominent, hidden away behind the latest modality hardware systems.

Is this a result of limited space at the smaller exhibition, or a reflection of the state of imaging IT maturity in Europe?

For much of Europe today, radiology IT still means PACS and RIS, be it at the radiology department-level, or increasingly “super PACS” at the hospital-network or regional level (such as Spain, Ireland and Scotland). In some cases, VNA has been used to bring disparate PACS systems together between hospital clusters, but for the most part it has remained heavily driven by DICOM radiology and cardiology image management and archiving. If we consider Europe’s largest five markets (Germany, France, UK, Italy, Spain) only the UK and Spain are starting to show any real development towards integrating non-DICOM content into VNA. For the remainder, there are very few examples of collaboration outside of the core DICOM applications, with most limited to academic or university hospitals.

Perhaps more telling was the lack of attendance from two of the largest VNA vendors globally: IBM Merge and Lexmark Healthcare (recently acquired by Kofax). Both are predominantly active in the North American market, but also have customers in Europe. Their lack of exhibition attendance might suggest they don’t yet see enough enterprise VNA opportunity in Europe.
Alternatively, there could be another factor – that enterprise IT adoption (including multi-application VNA) will be decided not by imaging specialists (such as radiologists and cardiologists) but by Chief Information Officers (CIOs), as we’ve seen more recently in North America. While this could have a positive impact in driving enterprise IT strategy and connecting disparate parts of health organisations together, it could also have negative connotations for radiologists; less choice of radiology software, overarching clinical IT decision-making and Electronic Health Record (EHR) vendors with greater customer influence.

Today, radiology IT decision-making remains very much in the hands of radiology departments for most of Europe, but it might not stay there for too much longer.

 

Applying Deep Learning to Ultrasound – Is the Technology Ready to be Embedded?

Written by Simon Harris

Much like at last year’s RSNA conference, deep learning was one of the key themes at ECR 2017. Several speakers at the scientific sessions presented promising research results for the application of deep learning in specific use-cases. In one of the professional challenges sessions, Dr. Angel Alberich-Bayarri from QUIBIM suggested that convolutional neural networks (CNNs) may already be old news, with generative adversarial nets (GANs), a new architecture for unsupervised neural networks, showing promise for medical imaging applications. GANs may be a solution to one of the major challenges with developing deep learning algorithms – the need for large training data sets.

On the exhibition floor, there were fewer companies showing machine learning solutions than at RSNA (there were at least 20 at RSNA but less than 10 at ECR) and in our conversations with vendors it was evident that expectations were more measured, with less marketing hype. Several of the better known deep learning start-ups were notable by their absence, including Enlitic and Zebra Medical, as was IBM Watson Health.

Samsung chose ECR to make a big push for its S-Detect™ deep learning feature, which is currently available as an option on its RS80A premium ultrasound system. S-Detect™ for Breast makes recommendations about whether a breast abnormality is benign or cancerous. It is commercially available in parts of Europe, the Middle East and Korea and is pending FDA approval in the US. S-Detect™ for Thyroid uses deep learning algorithms to detect and classify suspicious thyroid lesions semi-automatically based on Thyroid Image Reporting and Data System (TI-RADS) scores. With both applications, S-Detect™ produces a report to show the characteristics of the lesion, including composition, echogenecity, orientation, shape, etc., along with the risk of malignancy, e.g. “high suspicion”.

ContextVision, the leading independent vendor of ultrasound image enhancement software, showcased its latest research in artificial intelligence at ECR.  Its prototype VEPiO (Virtual Expert Personal Image Optimizer), which is built on the company’s Virtual Expert artificial intelligence platform, can automatically optimize ultrasound images for individual patients. VEPiO aims to improve diagnostic accuracy and reduce scan times, particularly for more challenging patients, by making automated setting adjustments to obtain the optimal image quality. The company is also exploring the use of deep learning to optimise image quality, for organ-specific segmentation and for decision-support functionalities.

Ultrasound OEMs must decide whether deep learning technology is ready to be embedded into their systems, or to take a “wait and see” approach. Although many research papers have found that deep learning can produce good results in specific medical imaging applications, often at or near the performance of experienced radiologists, these are usually based on relatively small datasets and/or small reader studies. It remains to be seen if deep learning will perform as expected in routine clinical use. Although Samsung has taken an early lead and is the first of the major ultrasound vendors to embed deep learning, it carefully positions S-Detect™ for Breast as a decision support tool for “the beginner or non-breast radiologist”.

OEMs must also decide whether to establish an in-house deep learning capability or to partner with a specialist. Deep learning engineers are a scarce and expensive resource and most mid-tier ultrasound OEMs will struggle to attract and retain talent. Instead we expect they will partner with independent software vendors, such as ContextVision. For the major OEMs, we expect to see a combination of build, buy and partner strategies. Most of the major modality OEMs have, to varying extents, established in-house R&D efforts for machine learning and with over 50 start-ups developing artificial intelligence solutions for medical imaging, there’s certainly no shortage of options for acquisitions and partnerships.

Another limiting factor is the additional processing power, typically GPUs, required for embedded deep learning algorithms. Ultrasound is a fiercely contended and price sensitive market and OEMs will be reluctant to add additional hardware cost. Initially we expect deep learning to be an optional feature on premium systems only, such as with the Samsung example, but as is often the case in ultrasound, features that start out on premium systems typically cascade to less expensive high-end and mid-range systems over time.

With deep learning technology progressing at a rapid pace, and ultrasound OEMs constantly on the look-out for the next “big thing” to differentiate their products, it seems inevitable that deep learning will increasingly be embedded in ultrasound systems, both as workflow tools to help with productivity and decision support tools to improve clinical outcomes.  It’s no longer a question of will it happen, but when will it happen, and the OEMs that wait too long will get left behind in the AI race.

 

Canon + Toshiba + Vital + Olea = Serious Competitor, but do they have a missing link?

Written by Steve Holloway

Following the announcement of the completed acquisition of Toshiba Medical Systems by Canon, co-branding for the new firm was proudly displayed at the exhibition. For other exhibitors at the show, it was an ominous sign. Here’s a few reasons why:

Canon DR fills a hole in the Toshiba X-ray portfolio: Toshiba Medical Europe has a solid presence in the European X-ray market, but only in the interventional and fluoroscopy X-ray segments, two saturated and mature markets. Most growth in the European X-ray market in the last five years has come from Flat Panel Detector (FPD) digital radiography for both fixed and mobile systems. This is a market where Canon has a strong reputation for FPD panel technology and smaller equipment sales through their acquisition of Delft DI. Combining the two offerings with Toshiba’s strong CT, MRI and ultrasound offerings will allow the combined entity to target large imaging equipment bundle deals with a full complement of systems.

Strong focus on R&D and innovation: Both Canon and Toshiba Medical are well-known and respected for technically strong products, especially in their core application sectors. While it will take some time for the two firms to integrate R&D and manufacturing capability, the combined brand will no doubt continue to be viewed as a leading vendor for technical capability and image quality, putting them in a good position to challenge the “big three” (Philips Healthcare, Siemens Healthineers and GE Healthcare) for top spot in European imaging hardware.

Back on the acquisition trail: Perhaps the biggest challenge for the combined entity will not be imaging hardware-related, but software-related. While the Vital and Olea Medical products are highly-regarded for advanced imaging and visualisation, the combined offering will be missing a central software platform for managing imaging content and workflow.

While not yet essential in Europe, the importance of clinical content management and enterprise imaging is increasing. What’s more, all major competitors have established imaging IT platforms (Philips Healthcare Intellispace platform, Siemens syngo and Digital Ecosystem, GE Healthcare Centricity platform and Healthcloud). Even mid-size vendors such as AGFA Healthcare (Orbis) and Carestream (Vue) have a significant installed base in Europe.

Vital Images (a subsidiary of Toshiba Medical Systems) more recently started to expand its capability to include workflow tools and VNA in their Vitrea product line, but do not yet have the scale of installed base or feature-set to match other major competitors. Without such a platform, the new Canon-Toshiba venture may still find it hard to compete in large hospital networks and regional tenders requiring both hardware and software capability.

So, while the new vendor will increasingly be able to compete in Europe, it will need to make more acquisitions to boost its clinical software offerings to challenge for top-spot in Europe in the long-term.

 

New Service from Signify Research: Clinical Content Management IT – 2017
This and other issues will be explored in full in Signify Research’s upcoming intelligence service ‘Clinical Content Management IT – World, with first delieverable due in February 2017. For further details please click here or contact simon.harris@signifyresearch.net

HIMSS 2017 Post Show Report

HIMSS 2017: Post Show Report

HIMSS is a world leading event which brings together 40,000+ health IT professionals, clinicians, executives and vendors from around the world.  During the event, leading edge technology was showcased by the healthcare IT industry.  The show report contains three insights covering Clinical IT, Population Health Management market and an in-depth interview with St. Joseph Health.

Click here to download the report.

Signify Research Analyst Insights from ECR Today 2017

Our Daily Insights from 2017 ECR Show Paper

Written by Steve Holloway

As well as attending the ECR show in Vienna last week, Signify Research analysts also provided a daily column for the Congress Newspaper – ECR Today.

To read our insights on major themes from the show and how these relate to the European markets for ultrasound, MRI, CT, radiology IT and digital X-ray, please click on the links below for digital version of the daily paper – we’re on page 18 in each.

A step closer to Doc Mccoy’s favourite toy? (page 18)
01/03/2017 https://www.myesr.org/media/1384

Does breast MRI hold future for mammography market? (page 18)
02/03/2017 https://www.myesr.org/media/1389

Gap widening between CT innovation and installation (page 18)
03/03/2017 https://www.myesr.org/media/1499

The great enabler: artificial intelligence in radiology (page 18)
04/03/2017 https://www.myesr.org/media/1583

Where next for digital X-ray? (page 18)
05/03/2017 https://www.myesr.org/media/1653

These stories will also be run online at www.auntminnieeurope.com the week following the conference, starting Wednesday 8th March 2017.

New Service from Signify Research: Clinical Content Management IT – 2017
This and other issues will be explored in full in Signify Research’s upcoming intelligence service ‘Clinical Content Management IT – World, with first delieverable due in February 2017. For further details please click here or contact steve.holloway@signifyresearch.net

HIMSS 2017: PHM Market Observations

HIMSS 2017: Population Health Management Market Observations

Written by Alex Green

With Population Health Management (PHM) plastered across the majority of exhibitors’ stands at HIMSS last week, it’s hard not to be cynical about the subject and consign it to the list of many other transient themes. However, if you delve underneath the hype there were several serious and well defined solutions on show. Whilst no single vendor yet offers a complete solution, both in terms of technology and services, vendors now have a relatively clear and consistent definition for what needs to be offered to address PHM. One message I thought particularly hit the mark was from Health Catalyst. Their message; PHM is a verb not a noun, and solutions should be designed with this in mind. This certainly resonated and is a message several other vendors would do well to take on board.
Here are our top five PHM market observations from the show:

EHR Vendors Catching Up Fast

EHR vendors have struggled to keep pace with some of the specialist vendors in the PHM market. This has led to companies such as Wellcentive (now part of Philips), IBM (via its ownership of Truven Health, Phytel and Explorys) and Optum taking market leading positions. This is despite the EHR vendors having a significant installed base of customers which should have provided rich pickings for their PHM solutions. Providers and other customer groups have often reported that the PHM solutions offered by EHR vendors are limited in functionality compared to those offered by the specialists. In many cases the solutions are often simple bolt-ons to the EHR offerings, developed largely only to address Meaningful Use, rather than solutions that will drive change as health systems increasingly take on risk.

However, the tide does appear to be turning. Via acquisitions and product development a number of the EHR vendors appear to have caught up and are starting to leverage the advantage that a large installed base of provider customers brings. This was evident from the solutions on show at HIMSS and also if considering the 2016 financial results from a number of the EHR vendors that were announced in the run up to HIMSS. For example, Cerner, reporting $234 million of PHM business in 2016 and Allscripts, reporting $235 million PHM business for the same year. Both are good illustrations that PHM is starting to have positive financial outcomes for some (although not yet all) of the EHR vendors.

Analytics Moving Beyond Claims and Clinical Data

A key focus of many of the PHM and analytics vendors during the show was that PHM platforms require analytics solutions that go well beyond simple claims and clinical data when developing risk stratification. Pooling data from other sources, such a demographic data, social determinants of health, patient generated heath data, geographic information sources and other unstructured sources is now viewed as essential by many (although there is still work to do to convince some physicians). Using this data to develop patient personas will enable providers and payers when implementing stratification processes to better target and communicate with different patient types.

Admittedly, the requirement to aggregate non-clinical/claims data has been the general message for some time, but I certainly witnessed an increased emphasis on this during my meetings last week. This is perhaps a sign that the companies that weren’t doing this well have started to get their act together. This is one part of the PHM market where specialist analytics solution providers still have an advantage to some extent on some of the broader solution providers and some of the EHR vendors. Companies such as SCIO, Lexis Nexis and Health Catalyst certainly exhibited some solutions around this that were particularly compelling.

All or Nothing

Rolling out one element of PHM does not mean you have a PHM solution. From vendor and provider discussions during HIMSS it was clear that in many cases solutions had been rolled out that utilised just one or two elements of PHM. This may be a data analytics or data aggregation tool, or a patient engagement platform.  Stand-alone these components are not addressing the PHM need and will not give the provider the outcomes that are required as they make the transition to value-based care or to taking on risk. Only a complete solution that brings in data aggregation, analytics, risk stratification, care management, care coordination and patient engagement with a results feedback loop will allow providers to obtain the full benefits they’re looking for from PHM. Furthermore, the technology is just the first step; organisational adjustments and infrastructure changes are essential in ensuring that the technology investment pays dividends. My discussions from HIMSS illustrated that in many cases providers and other customer groups that are dipping their toes in PHM are heading for failure as they are not embracing the whole system approach that is required. This does not mean that a vendor needs to offer a complete solution, there is certainly room for best of breed specialists for certain elements of PHM. Rather, the providers need to be taking a whole system approach.

Consumerisation of Healthcare

The modern healthcare consumer in the US is used to having choices. In banking, retail, travel, and most other areas, product or service information is abundant and decisions are made quickly, based on price, convenience, reputation and quality.  Increasingly, consumers are approaching healthcare with a similar attitude. They want to be able to compare the quality of the service they’ll receive, view feedback from other service users, manage appointments online, understand the cost implications of medical procedures, contribute their heath data to the decision-making process and be able to easily communicate electronically with providers. HIMSS demonstrated that technology vendors are now starting to take this on board and are developing patient engagement solutions that address the marketing needs of providers operating in an environment where their customers are increasingly fickle, demanding and where brand loyalty carries a lot less weight. Influence Health has been a long-time player in this space with solutions that have typically been used for marketing purposes. The company is now integrating its solutions with clinical patient engagement functionality to meet this need. SalesForce continued its high profile showing at HIMSS, adding weight to the argument that good CRM is increasingly essential in this more consumer centric healthcare environment. EHR vendors are also developing solutions that better address the marketing needs of providers. For example, Allscripts has a compelling 2017 development plan for its FollowMyHealth solution that will go a long way to addressing the needs of providers that want to execute sophisticated marketing strategies.

It’s Getting Harder to Differentiate

As I toured the booths last week, the constant theme I heard from the vendors was how only they had the right data aggregation tools that blended claims and clinical data from multiple EHR with social determinants of health. How only their analytics solutions gave in-depth actionable solutions for patient stratification. How only their portal went further than meaningful use to offer a truly compelling patient experience. Finally, how only their implementation team could offer the provider support needed to really take advantage of PHM. Unfortunately, the reasons given as to why they were different were more than often than not, very similar. I am being slightly facetious here as there were some that could provide good evidence of solid differentiators. However, most solution providers are now clear on what is needed to offer a comprehensive well-constructed PHM solution, including support services. And although each vendor is at a different point in terms of how far along they are to having a solution that addresses all facets well, they are all moving ever closer. This will ultimately result in differentiation becoming increasingly difficult.

New Market Report from Signify Research Publishing Soon

A full analysis of the population health market will be provided in Signify Research’s upcoming market reports ‘Population Health Management – North America Market Report 2017’, publishing in 1Q 2017, and ‘Population Health Management – EMEA, Asia & Latin America Market Report 2017’, publishing in 2Q 2017. For further details please click here or contact Alex.Green@signifyresearch.net.

The Signify Innovator Series: St. Joseph Health

The Signify Innovator Series: Technology Innovation within St. Joseph Health

Interview conducted by Alex Green

As part of our Innovator Series, Signify Research was able to meet up with Dr. Michael Marino, DO, MBA who is Chief, IS Operations/Clinical Systems, at St. Joseph Health, an Integrated Healthcare Delivery System. I spoke with Dr. Marino about how St. Joseph’s was pioneering the use of technology for patient engagement, population health management and telehealth.

Key takeaways

  • St. Joseph’s has rolled out a sophisticated patient engagement solution from Hart (www.hart.com) that goes well beyond Meaningful Use requirements
  • The provider is also using a risk stratification tool from Verscend (www.verscend.com) that aids maximizing the benefits from the patient engagement outreach
  • It is also working with Jvion (www.jvion.com) and Clearsense (www.clearsense.com) to integrate data on social determinants of health into the stratification process
  • St. Joseph’s experience in using solutions from the large EHR vendors to address patient engagement, population health and telehealth has been disappointing to date
  • Medtronic (www.medtronic.com) has been used to pilot a number of remote patient monitoring telehealth initiatives and St. Joseph’s has a partnership with MDLive (https://welcome.mdlive.com/) to enable the roll out of telemedicine video consultation services

Can you tell me about how St. Joseph’s has been leading the way in terms of its use of innovative technology?

A good place to start is how we’ve been developing the use of patient portals as they relate to patient engagement.  Initially Meaningful Use ushered in patient portals but the requirements were set so low that the major EHR vendors developed solutions that had very limited use. Providers only had to put in place a simple portal and sign people up, but there were no requirements to ensure that the portal was useful and that people were using it. This will change with Meaningful Use 3, but in the meantime we’ve been developing our portal so that it actually has benefits for patients and is used regularly.

A basic portal where a patient can only look at their discharge instructions for example, isn’t going be a portal that a patient will want to interact with regularly. In order to make portals more sticky and of use to a greater share of the population, St. Joseph’s partnered with a development company that had a fair amount of experience in the more of the social elements of healthcare. It was a start-up company called Hart (www.hart.com). What Hart offered was an app that allowed patients to aggregate their daily activities with their medical information.

What we’re seeing in the locations we’ve rolled this solution out is if you add the social components of wellness; such as step tracking, sleep tracking, adding challenges within friendship or other social groups, on the same portal that patients can get their annual cholesterol check booked, then the overall use of the portal increases massively.

Once patients are used to using the portal for the wellness tracking functionality, they then start to use it for other things such as online scheduling of appointments, reviewing discharge instructions, booking and holding their place in a queue in the urgent care unit without having to physically turn up and wait in a room. The results have been pretty dramatic. In some of our employee centred clinics where we’ve rolled out the Hart system patients are now typically hitting the portal once a week, whereas before it may have been once per year. The Hart app functionality is integrated into our legacy EHR solution so the data from both can be aggregated.

Why didn’t you use your EHR provider’s portal solution?

We use Meditech’s EHR solution across all of our hospitals. At the time we made the assessment, Meditech had its standard portal that had been designed to hit meaningful use. However, it was three shades of blue. It didn’t offer much beyond the standard meaningful use requirements. For example, you could download a CCDA or you could see your discharge notes, but you couldn’t feedback into it. St. Joseph’s want to embrace where the trends are going with wellness and the Meditech solution just did not meet that need.

Is the data that’s obtained from the patients wellness monitoring used when you stratify how to  manage that patient and the population as a whole?

This is where the big opportunity is. However, the difficulty we’re having is that there is no good evidence as to how to react to this data. So you have patients tracking their steps, but from a clinical point of view you there is no evidence as to what the appropriate amount of steps is. There are benchmarks that say 7,000 steps, 10,000 steps, etc. but in reality, these are just arbitrary numbers that do not relate to a patient’s existing physical condition. If you’re 6’ 2” and weigh 200 lbs and consuming 3,500 calories per day, how much you should actually be walking? There is a similar issue with sleep. A lot of people are really interested in tracking their sleep. But what can you do with the information? The science hasn’t caught up with the consumer yet on just what are the right amounts to be targeting. This is where we could potentially be supported more by the solution vendors.

How will you expand how the portal will be used going forward?

The most important element is still how you manage people to do the right thing. For example, it’s flu season, have you remembered to get your flu shot? For a diabetes patients how can we use the portal to ensure they are having an A1C every six months? We have these kind of reminder services in place now, but have just not yet rolled it out. This is the kind of thing that’s really going to change healthcare. Historically healthcare has been much more about me sitting in my doctor’s office and you coming to me with a problem. I’ll do a great job of interacting with you but once you go away, that’s where the interaction ends. The portal and patient engagement will change this approach.

At St. Joseph’s we have a comprehensive set of disease registries which we use to reach out to people using a manual process.  For example, doctors use the drug registry to monitor if a patient has had their basic metabolic panel to have their potassium checked.  In the current process a letter will be sent out to remind the patient if this has not occurred. However, what we’re now starting to do is using the portal and patient engagement tools to transition this to a computer driven process, to remind people via email, text, etc. With a computer-based system there is a lot more opportunity to keep nudging patients, ultimately driving better adherence and compliance, particularly if there is a simple call to action that can also then be followed electronically. Paper-based systems are a lot more arduous. We’re using Hart for this again. It’s ready to go and we’re just getting a critical mass of people signed up before we launch.

Do you have in place any solutions that build in risk stratification so that you know where to focus?

As well as the standard registries that allow us to put people into cohorts, we’re using a platform from Verisk Health, now Verscend (www.verscend.com). Their solution allows us to score patients, put them into cohorts and stratify how these cohorts are managed. We then have nurse navigator teams that actively manage the cohorts based on the information from Verisk’s platform. The fact that St. Joseph’s, and California in general, has been in the risk business for some time means that this isn’t that new. PHM is just an extension of this traditional function of managing risk.

However, the portal and patient engagement tools now mean they can be better managed when discharged and we’re no longer relying on the doctors just stating “Here’s your paperwork, have a nice day, see your doctor in two weeks”.

How important is non-clinical data in this risk stratification process, for example social determinants of health?

Very. On the hospital side, we have two pilots where this is key. For the two pilots we’re working with two different analytics companies that allow us to feed in data, such as social determinants of health, into the decision making and risk stratification process. The two analytics companies are Jvion (www.jvion.com) and Clearsense (www.clearsense.com).

Jvion is made up of a team of former Google engineers that have been collecting data for around a decade, and now have a huge database of population information such as what’s the average income level on my street, how many people are in each household and what are the demographics of those individuals. St. Joseph’s is marrying that up with our EHR data. The example I like to use is if I have a knee replacement, I go back to a very nice household where my wife is a doctor. If a different person has a knee replacement, for example a mechanic, who lives by themselves, in a house with lots of stairs, doesn’t have a support network, doesn’t have easy access to transport, then he needs a different level of post-care support. Both of us could look the same clinically. 55 year old males, 6’ 2”, a little over 200lbs. However, based on this data alone you could end up driving interventions where they’re not needed. The patient that lives alone, dropped out of high school, may not have understood his discharge instructions well, probably does need a home visit whereas I may not. The Jvion platform allows us to feed in other non-clinical information into the decision-making process. Information that can flesh out this picture can be of huge value as we try to maximise the use of our resources.

How do you address the issue that you don’t always have a complete longitudinal view of the patient’s healthcare interactions?

We have care management and coordination tools that we’ve used in the past, such as the solution from Allscripts. It’s not great and it doesn’t integrate well, even into Allscripts platform. I don’t think anybody does this well and that’s certainly a challenge for the vendors to improve their solutions in this area. Vendors will tell you their solution is great and is up to the challenge but they’re not there yet.

We were also an early adopter of Explorys’ platform, now part of IBM. We still have their tools but the difficulty we’d have is that once you get out of the IT conversation and into the operations discussion, the vendors always want you to go after their new shiny tool. Explorys was a perfect example. We’ve had Explorys for four or five years, we run the data, we have all these great registries that have been built within Explorys, but unless it perfectly matches our operations workflow it’s not helpful.

What programs do you have in place around remote patient monitoring?

We’ve been using remote patient monitoring platforms that support the use of blood pressure monitors, weight scales, pulse oximeter and blood glucose monitors, for three and a half years. Initially we developed the solution with Hart; however, after a while they decided this wasn’t an area they specifically wanted to focus on and so now we’re transitioning to the Medtronic (www.medtronic.com) platform.

To date we’ve rolled out our remote patient monitoring solution to a relatively small cohort of a couple of hundred patients. This did significantly reduce readmission in that group and was very successful. Information from the remote monitoring was rapidly getting out to nurse teams and cases were escalated to doctors when needed so that action could be taken to stop readmissions before they occurred. The difficulty we’re having related to the question of when do we stop remote monitoring? Should we monitor three months, six months or should the monitoring continue all the way through the remainder of the patient’s life. We always try to do things that are evidence based. When you go to the literature for evidence around remote patient monitoring best practice, there is very little advice.

In terms of rolling out further, we are looking to expand this cohort. There are two things holding it back, the evidence on when to stop and then potentially restart, and then the issue of how this is paid for and the return on investment.

So what’s your vision for how technology and innovation will be used going forward in St. Joseph’s?

One area where we’re planning on innovating relates to telemedicine. We currently have a partnership with MDLive (https://welcome.mdlive.com/) where we’re increasingly rolling out video visits to patients. We’ve already rolled it out at multiple sites and are working through all our ambulatory sites up to this Spring.

Some patients want old fashioned care with the same doctor and limited use of technology. Others, often with less complicated care requirements, don’t care who they see. If the issue is relatively uncomplicated many want a video visit that’s quick and convenient. At the same time if a patient needs to see a real person they want the tools to quickly figure out when and where to get treated. They want to do this electronically just like when booking a flight or a restaurant.

On the other end of the spectrum, where people truly have lots of health problems, it’s understanding their risk, helping them manage their way through the system, giving them tools so they can track their medicine online and easily access their paperwork. This is where a comprehensive patient portal is crucial.

The minute you tell someone they’re going home from the hospital, that’s the last thing they hear. Immediately the patient starts to think about the logistics of other parts of their life. Picking up the dog, collecting groceries, visiting family, etc. they miss the instructions the doctor is giving on changing the bandage, picking up prescriptions, planning a return appointment with the physician, seeing their regular doctor. With a good portal, that the patient is used to using, you can send this information and build in reminders so that instructions are followed. This is really where we’re focusing our efforts going forward.

About St. Joseph Health

St. Joseph Health (SJH) is a value-based healthcare delivery system that serves residents throughout Northern and Southern California, West Texas and Eastern New Mexico. SJH provides a full range of care facilities including 16 acute care hospitals, home health agencies, hospice care, outpatient services, skilled nursing facilities, community clinics and physician groups. For more information visit www.stjhs.org.

For further details please click here or contact Alex.Green@signifyresearch.net.

HIMSS 2017: Clinical IT Show Report

HIMSS 2017: Clinical IT Show Report

Written by Steve Holloway

After a hectic week of meetings, booth tours and press briefings, here’s The Signify View on the key takeaways from the HIMSS 2017 meet for Imaging IT and Clinical Content Management (CCM) IT stakeholders:

Emergence of Agnostic Clinical Enterprise (ACE) Platforms

While the shift has been gradual, it’s clear that the world’s largest imaging IT vendors are making a bid to “lock-in” their customer base to broader, enterprise clinical IT platforms. Siemens Healthineers announced its “Digital Ecosytem” model at the show, following similar recent announcements from Philips Healthcare (“Intellispace” platform) and GE Healthcare (“Health Cloud”). The move is hardly surprising – enterprise EHR vendors have done little to establish any real expertise in best-of-breed clinical IT or imaging IT software to date. Therefore the “the big three” are leveraging their clinical expertise and modality hardware footprint to expand the breadth of their clinical IT offerings, including analytics, dashboarding, integrated workflow and even population health and telehealth capability. These new solutions, that Signify Research has termed Agnostic Clinical Enterprise (ACE) platforms, look set to be the foundation for future cross-discipline implementations.

In adopting the ACE platform model, there are many benefits for provider and vendor alike. The single ACE platform model allows the vendor to become embedded in the providers’ core clinical workflow and care management, while also putting themselves in prime position to win long-term, managed service deals, including imaging hardware, clinical care device supply and lucrative professional services.

For providers, the ACE platform model offers a single vendor to deal with for clinical IT (“one-throat-to-choke”) and a partner to share the risk of previously capital-intensive procurement. Moreover, the ACE platform model will, over time, use the core platform vendor as a contractor. If the provider wants to bring in a new technology or software for a specific clinical function, the ACE platform vendor will have responsibility to sub-contract and integrate the new module into their platform. This will lead to greater choice for the provider in each clinical discipline.

It is still early days for the ACE platform approach as was evident from the solutions on show. The few ecosystems being touted are essentially proprietary ecosystems, available only to current customers of the vendor’s software, integrated with a few select partners. The benefit of choice for providers therefore remains very limited. Little has also been discussed on how the new clinical ecosystem will interact with the incumbent EHR platforms – any sign of encroachment into acute EHR and the focus on interoperability will soon be lost. Furthermore, the clinical IT market is awash with mid-size and small vendors each with a market role to play. For mid-size vendors with partial imaging modality business, such as AGFA Healthcare, Carestream Healthcare and Fujifilm Medical, a strategic decision will need to be made, whether to build their own ACE platform ecosystem, or specialise in a clinical area and look for platform partners. Smaller vendors, such as those with best-of-breed clinical capability will probably sub-contract into ACE platform ecosystems, or ultimately be acquired. For the smaller, more generalist vendors, they may well soon see their addressable market shrinking.

FHIR gains momentum but blockchain the missing link?

Interoperability was certainly on the agenda at HIMSS, albeit dwarfed by the big themes of cybersecurity, artificial intelligence and US health legislation uncertainty. Adoption of the new Fast Interoperability for Health (FHIR) standard was evident in some new solutions on show, but was patchy and far from mainstream – unsurprising considering FHIR is far from a well- defined and established standard today.

In contrast industry hype around blockchain was more evident and widely discussed, especially as the major EHR vendors were keen to be seen to be visibly working on interoperability. It was clear though that beneath the hype, little has happened so far. There are few working examples of blockchain in healthcare, with almost all tied into the world of financial administration and payer-provider workflow.

From a clinical IT perspective, blockchain is a long way off. It is certainly intriguing in the fact its traceability could offer a true “longitudinal” record for clinical audit, especially when applied to tracking the patient through complex, multi-provider clinical pathways. In addition, some at the show saw blockchain as a smarter way to drive interoperability and exchange of information between different health providers and vendor platforms.

That said, it is still very early days for blockchain in healthcare. Most major vendors are only starting to investigate it’s potential and scepticism remains high despite the hype. One discussion we held led to a comparison of healthcare and finance in adoption of new technology and standards – with healthcare estimated to be approximately 20 years behind finance. Blockchain in finance today is only just starting to be trialled, so for healthcare it’s reasonable to assume it’s a long way off.

Artificial Intelligence meet Workflow

There was a healthy dose of reality being eschewed from most participants with regards to artificial intelligence (AI). It seems most now understand AI will not be replacing physicians and fully diagnosing patients anytime soon so instead are focusing more on the benefits it really can provide. Interestingly, AI to date has also driven far more vendor partnerships, with major clinical IT vendors increasingly looking to work with AI specialists in targeted clinical applications.

There was also an array of AI solutions on show and almost all focused on a few key areas: workflow, efficiency, analytics, clinical audit and in some select cases, physician decision-support. Most clinical focus was on workflow analytics, with examples such as enabling customised pre-fetching of images or clinically-relevant content to add context to diagnosis. Clinical dashboard and audit was also a clear topic, with a range of solutions on show to enable providers to better monitor and predict adverse events or clinical compliance based on real-time clinical data. Automation of manual processes (quantification tools particularly) was also shown in a variety of clinical applications

However, as was evident from the findings of the recent Signify Research report on Machine Learning in Medical Imaging (published January 2017), adoption of AI for decision support and Computer Aided Diagnosis (CADx) will be a gradual process, with only a few specific clinical applications commercially available in the next five years.

Cloud Gaining Traction

Unlike many of the trends discussed above still in infancy, the adoption of cloud technology for clinical IT appears to at last be gaining traction. Vendors were reporting a far greater interest and uptake of cloud solutions, suggesting providers are overcoming concerns on data security and wanting to take advantage of the greater flexibility enabled by cloud implementations. Notably, Microsoft Azure and Amazon Web Services (AWS) were regularly discussed as making significant inroads to cloud service provision for healthcare in the last year.

That said, penetration of full third-party hosted architectures remains relatively niche and is tied closely to the scale of deployment. For small private centres and physician offices, fully hosted and Software-as-a-Service (SaaS) solutions make sense as the burden and cost of managing IT hardware, middleware, storage and maintenance are removed. For small to mid-sized hospitals, the hybrid architecture model is often more appropriate; third-party hosting is used for long-term storage, back-up and disaster recovery off-site, while primary data remains on-site. For larger hospitals and multi-provider networks, most have already invested in long-term IT infrastructure to support their networks, along with sizeable IT administration teams. Therefore, “private cloud” is most common, in which the clinical IT software is hosted on the providers’ infrastructure with a variety of in-house or third-party maintenance options.

Consequently, vendors were keen to showcase cloud and mobile-access solutions at the show, especially with regards to viewers and data management solutions (be it image archive, vendor-neutral archive or independent clinical archive solutions).

Reality Bites

Despite the broad theme of interoperability in healthcare of late, the gulf between clinical IT vendors and EHR vendors was still palpable.  Progress in some applications such as risk stratification analytics and care management (as part of population health), telehealth and clinical archiving, was on show, but mostly the worlds of clinical IT and EHR remained very much separate. Diagnostic imaging especially appeared to remain estranged from wider health IT, while it was also notable how few imaging focused symposia sessions were part of the HIMSS schedule. So, while interoperability was much hyped and the largest clinical vendors are looking to expand clinical capability, there appears to be little change yet in breaking down the barriers of clinical data interoperability in the complex mesh of vendor, provider and payer networks.

New Service from Signify Research: Clinical Content Management IT – 2017
This and other issues will be explored in full in Signify Research’s upcoming intelligence service ‘Clinical Content Management IT – World, with first delieverable due in February 2017. For further details please click here or contact simon.harris@signifyresearch.net

Signify Research joining ECR 2017

Events

1 – 5 MARCH 2017

Signify Research joining ECR 2017

The Signify Research Analyst team will be attending the 2017 European Congress of Radiology (ECR) in Vienna.

The ECR is an international meeting and one of the leading events in radiology. It is also one of the largest medical meetings in Europe and the second-largest radiological meeting in the world. We will be providing updates, news and analyst insight from the conference via Twitter, LinkedIn and www.signifyresearch.net.

We welcome and encourage the opportunity to meet vendors, providers and industry stakeholders for:

  • Discussion on specific market topics and trends
  • Briefing on our most recent market findings and data
  • Provide a vendor briefing to our analyst team on your latest products
  • An introduction to the Signify Research team and our market intelligence solutions
  • Interest in press and media collaboration
  • Participation in our  syndicated market reports, customer insights and vendor evaluation research

Please contact us at enquiries@signifyresearch.net, or find more details on our “Contact Us” page.

We look forward to seeing you in Vienna.