Author Archives: Charlotte Davis

North American PHM Market Worth $8B in 2021

North American PHM Market Worth $8B in 2021

Written by Alex Green

  • North American Population Health Management (PHM) market projected to grow at a CAGR of 16.6% from $3.7B in 2016 to $8.0B in 2021.
  • Lives managed by PHM solutions will increase from 135 million at the end of 2016 to 245 million at the end of 2021 (Note: one life can be managed by more than one organisation, e.g. a payer and a provider, and would be counted twice in this scenario).
  • Analysis and commentary taken from the Signify Research North American Population Health Management IT Market Report

Analysis

Data from Signify Research’s report “Population Health Management IT – North America – 2017” shows that the North American PHM market is forecasts to grow at a CAGR of 16.6% from $3.6B in 2016 to $8.0B in 2021. Over this period, the number of lives managed by PHM solutions is projected to increase from 135 million at the end of 2016 to 245 million at the end of 2021. Solutions will be implemented by a range of organisations such as providers/ACOs, payers, government organisations and employers, in some cases leading to individual lives being managed by more than one entity. The provider/ACO vertical is projected to represent the largest market in terms of both managed lives and platform revenues, with the acute sector driving the lion’s share of the provider market.

Defining Population Health Management

Before digging into the main factors will drive this growth, it’s important first to define what’s included in a PHM solution and in our analysis.

In recent years, a standard structure has evolved in terms of the required components of a population health management platform, and this is a structure that most vendors now adhere to, or are at least working towards, in terms of solutions offered. The structure comprises seven core functional modules:

  • A solution to pool and normalise data from multiple sources so that it can be interrogated as one – data aggregation
  • A solution to interrogate the normalised data to obtain meaning – health analytics
  • A solution that allows the analytics to then be used to drive strategy. Normally by segmenting the population into groups based on health conditions being managed, costs and behaviours – risk stratification
  • A solution that allows standard evidence-based care plans and workflows to be developed for specific segments of the population depending on the conditions they are managing, their risk and their likely behaviours – care management
  • A solution that allows the specific work flows and care plans to be executed across different health care continuums and care teams – care coordination
  • A solution that allows simple, secure electronic communication with patients for messaging, education, data collection, etc. – patient engagement
  • A solution that allows for the impact of each work flow and care plan strategy to be measured and fed back into the overall management system – performance management

It’s the market for platforms that support these functions, and the associated implementation and support/maintenance services, that Signify Research has included within its definition of the PHM market and within its projection of an $8.0B market in 2021.

Factors Driving Growth

The factors positively affecting the uptake of PHM solutions in North America are focused heavily on US legislation and attempts to modernise health care provision, such as.

  • Elements of the Affordable Care Act that are expected to remain in place
  • The move from fee-for-service to value-based care
  • Providers taking on risk and the rollout of ACOs
  • MACRA

The figure below and the following summary explanation outlines the development of these main themes.

Leading up to 2010 – Poor health outcomes and spiralling health care spending in the US contributed to the development of the Affordable Care Act (ACA).

2011-2015 – To implement ACA, the CMS establishes ACOs and shared savings programs. This encourages providers to better manage their entire population’s health. ACOs receive a share of the financial savings they make from the move to new models of care, assuming quality targets are met. PHM solutions are a key enabler in achieving and measuring these quality and financial targets. Key elements of the ACA that PHM solutions address include supporting wellness services, reducing hospital readmission rates and developing community-based care transition programs.

2016-2019 – MACRA/MIPS targets are established to encourage non-ACO providers to accelerate the move to value-based care. For example:

  • MIPS ‘quality measures’ include targets focused on areas such as improving screening rates and controlling blood pressure of those with hypertension.
  • MIPS ‘improvement activity measures’ include targets related to the increased use of care plans for chronic condition management (e.g. diabetes management) and the increased use of longitudinal care management for high risk patients, such as those recently discharged from hospital.
  • MIPS ‘advancing care measures’ include targets focused on attaining better patient engagement and better care transitions.

PHM platforms provide a range of management tools that have been designed to aid providers and other health care organisations in developing their services in order they improve and report on these measures.

As a note of caution, significant changes to the ACA from the Trump Administration over the period 2017 and 2018 could impact the transition to value-based care. However, the assumption within our market forecasts is that the underlying drivers remain in place.

Beyond 2020 – As the transition to a value-based care model progresses, the triple goal of improved outcomes, improved value for money and improved health of populations starts to be realised. PHM platforms remain a fundamental tool in driving continued quality and financial performance.

New Market Report from Signify Research

The market data presented above is taken from Signify Research’s just published report on the North American PHM market. The report is a component of the Signify Research “PHM & Telehealth Market Intelligence Service”. Vendors tracked include Aetna, Allscripts, AthenaHealth, AxisPoint Health, Caradigm, Cerner, Conifer Health, eClinicalWorks, Enli, Epic, Evolent, HealthCatalyst, Humana/Transcend Insights, IBM Watson Health, McKesson, Medecision, Meditech, NextGen, Optum, Orion Health, Premier Inc., Verscend, ZeOemga and others. The report provides quarterly market estimates for 2015 & 2016, and annual forecasts by vertical, function, service type, platform delivery and country to 2021.

For further information about purchasing this report please click here or contact Alex.Green@signifyresearch.net.

Partnerships are King for Machine Learning in Radiology

Partnerships are King for Machine Learning in Radiology

Written by Simon Harris

For companies developing machine learning solutions for radiology, strategic collaborations and partnerships with healthcare providers are king. Not only do they provide vendors with academic and clinical domain expertise, but they also give access to annotated imaging data to train and validate machine learning algorithms – one of the biggest challenges for most algorithm developers. By working closely with providers, vendors can identify the greatest pain-points for physicians, be it workflow-related or part of the clinical decision-making process, and hence the areas where machine learning can add the greatest value.

To that end, leading medical imaging companies are forging strategic partnerships with health providers to collaborate on machine learning projects, as shown in our graphical analysis below.

GE Healthcare Partners with Partners

One of the most recent was last week’s announcement from GE Healthcare and Partners HealthCare that they have entered a 10-year collaboration to develop artificial intelligence and deep learning solutions. Partners is a Boston-based, not-for-profit health care system that was founded in 1994 by Massachusetts General Hospital and Brigham and Women’s Hospital. Key points from the announcement are as follows:

The collaboration aims to implement AI into every aspect of a patient’s journey through the healthcare system – from admittance through discharge – and spans multiple medical specialties, including radiology, pathology, genomics and population health.

  • The initial focus of the relationship will be on the development of applications aimed at improving clinician productivity and patient outcomes in diagnostic imaging.
  • Early applications will address cases like determining the prognostic impact of stroke, identifying fractures in the emergency room, tracking how tumours grow or shrink after the administration of novel therapies, and indicating the likelihood of cancer on ultrasound scans.
  • GE and Partners will co-develop an open platform to enable them and third party developers to rapidly prototype, validate and share applications with hospitals and clinics around the world.

Strategic Partnerships for Machine Learning Radiology

GE Healthcare, IBM Watson Health, Siemens Healthineers and Philips Healthcare

Note: blue linear lines indicate vendor partners and green leader lines indicate clinical partners
Source: Company annoucements

 

GE Healthcare has existing partnerships with Boston Children’s Hospital, to develop solutions that interpret paediatric brain images faster and more accurately, and with UC San Francisco’s Center for Digital Health Innovation. The partnership with UCSF aims to develop a library of deep learning algorithms, with an initial focus on algorithms that expedite differential diagnosis in acute situations such as trauma.

GE Healthcare also has partnerships with several image analysis vendors, including Arterys and imbio, whose solutions are made available on GE Health Cloud. The solutions developed by GE and its clinical partners will also be available on GE Health Cloud, creating a large library of image analysis applications.

Watson Health Medical Imaging Collaborative Now at 24 Members

IBM Watson Health is also implementing a partnership strategy and in June 2016 it announced the Watson Health Medical Imaging Collaborative. The initiative launched with 16 members, including health systems, academic medical centres, ambulatory radiology providers and imaging technology companies, and has since expanded to 24 organisations. The first application from the collaborative is IBM Watson Imaging Clinical Review, which helps hospitals to identify patients that may have aortic stenosis. Sentara Heart Hospital contributed data from 3,000 heart echo-cardiology studies, 60% of which were used, to train Watson in the development of IBM Watson Imaging Clinical Review. The collaborative is also developing solutions for diseases of the eye, brain and other heart-related conditions such as myocardial infarctions, valve disorders, cardiomyopathy and deep vein thrombosis.

IBM Watson Health is also courting partnerships with image analysis vendors for Watson Platform for Health (formerly Watson Health Core), its healthcare data platform-as-a-service offering, powered by Watson Health Cloud, which features a mix of IBM Watson Health and third-party applications. One of the first third party radiology products is an application from MedyMatch that detects intracranial bleeds from CT scans.

Siemens Launches Digital Ecosystem

Siemens Healthineers announced its new digital healthcare platform, Digital Ecosystem, at HIMSS 2017 and has partnered with several third-party software developers, including Arterys, HeartFlow and SyntheticMR. In January this year, Siemens and Biogen announced an agreement to jointly develop new MRI tools for quantifying key markers of multiple sclerosis disease activity and progression, including new T2 lesions and atrophy.

Siemens has announced relatively few machine learning partnerships with health providers. At RSNA 2016 it presented a prototype developed with Essen University Hospital to improve the diagnostic accuracy of a non-expert radiologist in differentiating between usual interstitial pneumonia (UIP) and non-UIP on thoracic CT. Siemens is also a partner in the ‘Data Intelligence for Clinical Solutions’ project, funded by the Federal Ministry for Economic Affairs and Energy (BMWi), which aims to develop artificial intelligence solutions that provide physicians with differential diagnoses based on available patient data. The clinical partners in the project are Charité hospital in Berlin and Erlangen University Hospital.

Philips Focuses on its In-house AI Capability

Philips Healthcare has several long-term, strategic partnerships with health providers, typically based on a managed services business model. Examples include Westchester Medical Center Health (US), Heart Hospital Tampere (Finland) and Karolinska Hospital (Sweden). However, these partnerships typically do not have specific projects on machine learning. One exception is a deal signed in March this year with Phoenix Children’s Hospital for a 15-year agreement relating to imaging, patient monitoring and clinical informatics, which will explore the use of machine learning in paediatric care.

Similarly, Philips has relatively few partnerships with image analysis software vendors and to date has not pursued the ‘open imaging ecosystem’ approach of GE (Health Cloud), IBM (Health Core) and Siemens (Digital Ecosystem). Instead, Philips appears to be more focused on developing its in-house artificial intelligence capability. At RSNA 2016 it introduced Illumeo, which uses data and contextual awareness to help optimise radiologist workflow. Illumeo adapts the user interface by offering tool sets and measurements driven by the understanding of the clinical context. The software provides the radiologist with the most relevant case-related information from various sources in a single view and generates dynamic reports that can include 3D images or image quantification data.

Not the Only Game in Town

This article has focused on the partnership activities of a handful of the leading medical imaging companies. There is also considerable partnership activity from mid-tier imaging companies looking to add machine learning to their repertoire and the growing number of start-up companies in this field. Moreover, open platforms are available from other vendors, e.g. NTT DATA Unified Clinical Archive, and it is likely than new ones will come on stream in the coming years. Specialist image analysis platforms are also available, such as those from medimsight and McCoy Medical, although these are perhaps better suited to clinical research than mainstream clinical practice.

More Partnerships Still Needed

One of the most commonly cited shortcomings of machine learning in radiology is the limited number of commercially available products. Most vendors offer only a handful of solutions, which are typically focused on a specific application area, e.g. breast, lung or cardiology, which limits the utility of machine learning for most radiologists. Generalist radiologists require a comprehensive “analytical tool kit” with a broad portfolio of algorithms. It’s a daunting task for a single company to create such a library of algorithms, comprising tens and potentially hundreds of analytical tools. Instead, the radiology industry must continue to collaborate for radiologists, and ultimately patients, to fully benefit from the rapid developments in the field of machine learning.

Investment Analysis for Telehealth Companies

Investment Analysis for Telehealth Companies

Since 2013, more than 80 telehealth companies have secured external capital funding. Combined, these companies have raised $2.9 billion in venture and private equity 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 telehealth solution type.

Click here to download the report

Investment Analysis for Diagnostic Ultrasound Companies

Investment Analysis for Diagnostic Ultrasound Companies

Since 2010, 29 diagnostic ultrasound companies have secured external capital funding. Combined, these companies have raised $560 million in venture and private equity 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

PHM 2016 Market Share Analysis

EHR & Payer/Provider-owned Vendors Take 55% of PHM Market

Written by Alex Green

  • Signify Research analysis and commentary from the North American Population Health Management IT Market Report
  • In 2016 55% of the North American PHM market was accounted for by EHR vendors and payer/provider-owned vendors
  • The remaining 45% was made up of a long list of vendors, with the market remaining highly fragmented
  • Optum was the market leader in terms of revenue share in 2016. It was followed by IBM Watson Health, Allscripts, Cerner and Conifer Health.

Analysis

Data from Signify Research’s report “Population Health Management IT – North America – 2017” shows that in 2016, 55% of the North American PHM market was accounted for by EHR vendors and payer/provider-owned vendors. This was split further into 30% of the market being taken by payer/provider-owned vendors and 25% of the market taken by EHR vendors.

Those that fell into the payer/provider-owned category included companies such as Optum, Conifer Health Solutions, Transcend Insights, Aetna and Medecision. Optum and Conifer Health being the two that commanded the highest share of the market within this category. The EHR vendor list included Allscripts, Cerner, eClinicalWorks, McKesson, Epic, MEDITECH, NextGen Healthcare and athenahealth. Allscripts and Cerner being the two in this group with the highest market share in 2016.

Beyond these two groups, the market remained highly fragmented. Large health IT/technology generalists such as IBM Watson Health, Philips (including Wellcentive) and GE Healthcare (including Caradigm) accounted for approximately 10% of the market between them. IBM Watson Health, via its acquisitions of Truven Health, Phytel and Explorys, had the greatest share within this group.

The supplier base also consisted of a long list of specialists that have portfolios highly focused on PHM and related markets. Of note within this group were Orion Health, Evolent Health, Verscend, Health Catalyst, Enli, ZeOmega and SCIO Health Analytics.

Opportunities Going Forward

As the PHM market develops, both the EHR and payer/provider-owned vendors are expected to have somewhat of an advantage over others. The EHR vendors have an existing installed base of provider customers using their EHR technology that they can leverage as their PHM businesses are developed. However, historically there has been some criticism of EHR vendor PHM solutions. In particular, this related to the sophistication of features offered and the breadth of the datasets used during the data aggregation/risk stratification process. The EHR vendors’ initial patient engagement platform deployments, often designed around a tick box process of supporting meaningful use targets, also reinforced this criticism. The combined result was a perception that EHR vendors’ PHM solutions were simple “bolt-ons” to existing EHR offerings.

This has been addressed to some extent in more recent years. Many EHR vendors have acquired leading PHM vendors (e.g. Allscripts acquisition of dbMotion and Jardogs) to bolster their offerings and have also invested significantly in PHM platform feature-set development. This has resulted in a closing of the gap with the more specialist companies. Many EHR vendors now have business plans that have PHM at the core creating high levels of investment in portfolio development. For example, Cerner has stated it has targets where PHM will drive 20% of its total business by 2025, up from 5% in 2016.

The payer/provider-owned companies also have an advantage in that they have a captive market with their payer/provider owners. For example, Conifer Health is estimated to have generated approximately 80% of its 2015 and 2016 revenues from its two owners, Tenet Health and Catholic Health Initiatives. Optum generates a significant proportion of its revenues from its payer-owner UnitedHealth Group. However, payer/provider-owned companies will need to implement strategies to expand beyond their owner companies if they wish to maintain their positions in the PHM market, a process that is already well underway. For example, Optum’s purchase of Humedica and the subsequent development of its provider-focused Optum One solution, has enabled it to grow its business beyond UnitedHealth Group, and other payers, and develop a strong provider-focused PHM business.

Ability to Scale Business

For those vendors not in the EHR vendor or payer/provider-owned groups there is still a great opportunity to drive success and build share in the PHM market. However, as the market starts to mature it is forecast to consolidate in terms of the number of suppliers addressing the market.

Companies such as Philips Healthcare, GE Healthcare and IBM Watson Health have the scale and, for most, the legacy customer base to drive success in the PHM market. Both IBM Watson Health and Philips have gained PHM market share via acquisition. GE Healthcare is well positioned, through its ownership of Caradigm, to address the acute/enterprise-focused PHM market. To date, GE Healthcare has not yet leveraged its Centricity ambulatory EHR customer base. However, it will start to address this during 2017 as its ambulatory PHM offering (Project Northstar) is commercialised.

Of the specialists, vendors such as Orion Health, Health Catalyst and Evolent Health have gained significant market share which they can leverage to support product innovation in order to grow their PHM businesses. Assuming though that profitable business models can be maintained and/or established (with some doing better than others on this front).

Further consolidation within the PHM industry is expected over the coming years and some of the smaller specialist vendors are expected to disappear, either through mergers, acquisitions or market exit. That being said, Signify Research does see opportunities for the more innovative amongst the smaller vendors to succeed. Particularly those that have developed strengths in specific areas (e.g. patient engagement platforms or analytics) and have the potential to partner with the larger vendors looking to address the full PHM platform market.

Market Shares in 2016

The dominance of the EHR vendors and payer/provider-owned vendors is illustrated well in terms of overall market shares in 2016. Optum was estimated to be the overall leader, with a share of 12%. This was followed by IBM Watson Health taking an estimated 9% of the market. Allscripts, Cerner and Conifer Health followed with estimated shares of 6%, 5% and 5% respectively. Evolent Health is estimated to have gained the most in terms of share during 2016, partly owing to organic growth, but also boosted via its acquisition of Valence Health. Speculation has been abundant in recent weeks regarding a potential merger between Evolent Health and the Advisory Board (which already owns part of Evolent). Should this merger take place the company is well positioned to break into the top five ranking illustrated below.

New Market Report from Signify Research

The market data presented above is taken from Signify Research’s just published report on the North American PHM market. The report is a component of the Signify Research “PHM & Telehealth Market Intelligence Service”. Vendors tracked include Aetna, Allscripts, AthenaHealth, AxisPoint Health, Caradigm, Cerner, Conifer Health, eClinicalWorks, Enli, Epic, Evolent, HealthCatalyst, Humana/Transcend Insights, IBM Watson Health, McKesson, Medecision, Meditech, NextGen, Optum, Orion Health, Premier Inc., Verscend, ZeOemga and others. The report provides quarterly market estimates for 2015 & 2016, and annual forecasts by vertical, function, service type, platform delivery and country to 2021.

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

Hyland Software Snaps Up Lexmark Perceptive

Hyland Software Snaps Up Lexmark Perceptive

Written by Steve Holloway

  • Thoma Bravo (private equity owner of Hyland Software) has agreed terms to acquire the Lexmark International Enterprise Software business (Kofax and ReadSoft business)
  • Hyland Software itself will then acquire the Lexmark Perceptive Software business. This includes the Perceptive Intelligent Capture, Acuo VNA, PACSGEAR and Enterprise Medical Image Viewing (originally Claron Technology)  product lines
  • The deal is expected to close in Q3 2017 for an estimated $1.5B, with Hyland Perceptive deal to follow.

Here’s our analysis of the deal, likely outcomes and what this will mean for the imaging IT and clinical ECM market:

Powerhouse of Health Data Management?

Focusing on the Lexmark Perceptive Software deal, the main attraction for Hyland will be gaining a share in the imaging IT archiving and management market. Lexmark Perceptive is one of the top three vendors by revenue globally in this market, driven predominantly by its past acquisitions of Acuo (VNA) and PACSGEAR (image exchange  and connectivity solutions), along with multiple others in viewing and workflow technology. Hyland OnBase originally launched its own VNA product competing against the Lexmark Perceptive Acuo VNA in early 2015, though it only holds a small base of customers today.

While the Lexmark-Perceptive Software business is smaller by revenue compared to the Enterprise Software deal (Kofax-ReadSoft), it does have strategic importance for Hyland. To date, barring Lexmark Perceptive , there is no other vendor that has the in-house capability to provide large-scale clinical content management and archiving technology (e.g. VNA, image exchange , workflow tools and enterprise viewing), alongside enterprise content management (ECM) for clinical, administrative and financial information management and storage. Instead, each market has remained distinct; ECM vendors have catered for non-clinical administrative and finance data, usually partnering with EMR vendors, while imaging IT vendors, health care technology vendors and a small group of independent companies have catered for clinical data management and imaging.

Therefore, the new Hyland-Lexmark-Perceptive partnership offers a potential edge over the other major clinical and non-clinical enterprise IT giants, such as IBM, GE Healthcare and EMC, by offering a complete content application layer for management of all health care related data.

Not Without Risk

While the strategic move from Hyland is clear, the operational juggling required to make it happen will be an arduous task with many challenges. The Lexmark Perceptive business was created by combining nine different businesses, which have been pieced together, with limited success, over the last five years. The acquisition of Lexmark Perceptive in November 2016 by a Chinese investment consortium also resulted in many key personnel from the original business jumping ship to competitors.

The approach of each partner in this deal has also been markedly different to date. Lexmark Perceptive has been most successful in winning large enterprise deals requiring complex customised solutions. Albeit with little evidence of a coherent strategy combining the clinical archiving business together with the Perceptive ECM business line. In contrast, Hyland has a strong reputation as an ECM vendor, catering mostly to Epic Systems EMR customers, which has been leveraged to expand into clinical content with its OnBase VNA. Hyland also has little experience in interfacing and replacing legacy clinical IT systems.

From a geographical perspective, both businesses have some commonality, with a vast proportion of their installed base being in the US. Lexmark Perceptive has also branched out internationally in the UK, Nordics and Asia Pacific region, though opportunities for large enterprise clinical content management deals are less common. Hyland has an almost exclusive US-based customer list, again driven mostly from providing ECM to support customers with an Epic Systems EMR. From a non-US perspective, adoption of large enterprise EMR akin to that seen in the US in the last five years, is weak. Instead, these markets are heavily dominated by health care technology firms for clinical data management and the large multinational ECM businesses. Consequently, non-US market penetration for the combined Hyland-Lexmark-Perceptive business will be a significant challenge given current experience and capability.

The Bigger Picture

Vendors from both the clinical and non-clinical data management market sectors will be watching the outcome of this deal closely. To date there has been little appetite, or market-available solutions, for health care providers to fully integrate data management capabilities across clinical and non-clinical segments.

However, interoperability has been a hot topic in health care IT for the past few years, in improving interfacing of systems both within and between provider networks. This has been further exacerbated by new focus on population health management and the emerging use of artificial intelligence in health care, both of which require providers to develop a more federated and accessible approach to management and storage of health care data.

If the expected combined clinical and non-clinical solution from the new Hyland-Lexmark-Perceptive provides significant commercial success, there is no doubt the wider market will react, ramping up merger and acquisition activity, especially from non-clinical enterprise ECM vendors looking for clinical data management expertise. Moreover, it would also start a ding-dong battle  for market leadership of “content application” platforms that will act as the supporting layer to all health care providers’ software. Watch this space.

20% of North American PHM Market is “Captive”

20% of North American PHM Market is “Captive”

Written by Alex Green

  • Signify Research preliminary analysis and commentary on the North American Population Health Management IT Market, which includes data for the quarter ending December 2016
  • 20% of North American PHM market in 2016 is accounted for by vendors supplying their own owners with solutions
  • Optum, Healthagen, Medicity, ActiveHealth Management, Transcend Insights, Conifer Health, Medecision – all have owners who are also customers

Analysis

According to preliminary data from Signify Research’s report “Population Health Management IT – North America – 2017”, 20% of the North American PHM market is effectively locked out to competition as it is served by vendors supplying their owners with PHM solutions – i.e. it’s a captive market.

Many of the leading vendors of PHM software solutions are owned by major payer or provider organisations, who then purchase PHM products and services from their subsidiaries. In some circumstances these payers or providers were initially responsible for developing the PHM solutions offered and once successful, commercialised the products by establishing new operating companies or brands. There are also several examples of payers or providers acquiring vendors that had already developed successful PHM solutions and then ultimately becoming customers of these acquired companies.

The leading vendors that are driving this captive 20%, along with an overview of their businesses, are outlined below.

Optum

Optum, the market leader in terms of PHM IT revenues in North America, is owned by US payer UnitedHealthcare and is one of the companies that makes up the largest share of the captive market.

United is Optum’s largest customer across its entire portfolio. In 2016 Optum Insight, Optum’s health care technology business segment, generated more than 50% of its $9B sales via internal business. Specific to PHM, in 2016 United was a major customer for Optum’s payer-centric PHM solutions, such as Optum Impact Intelligence, Optum Impact Pro and Optum Symmetry.

Optum has also started to bolster its non-UnitedHealthcare business; in particular it has increased the share of its business that is driven by providers as opposed to payers. Its acquisition of Humedica in 2013 and the subsequent launch of its provider-focused PHM solution Optum One being the main enabler. As sales of this solution have ramped up, the share of the overall Optum PHM business generated by UnitedHealthcare has started to fall.

Conifer Health Solutions

From a leading payer-owned example to a leading provider-owned example – Conifer Health Solutions offers a broad range of provider-focused PHM solutions via its ConiferCore portfolio of products. It is estimated to have commanded a top five market share position in North America in 2016 (based on Signify Research preliminary market estimates).

Conifer Health Solutions is the principal operating subsidiary of Conifer, which is majority owned by the US health provider Tenet Healthcare. Further, US provider Catholic Health Initiatives (CHI) also holds a 23.8% ownership position in Conifer Health Solutions.

Tenet alone accounted for 37% of Conifer’s sales (all products) in 2016. Across both Tenet and CHI, the figure was between 75% and 80% in 2015 and 2016. These figures relate to business across all Conifer’s products, but its PHM business is also very much focused around Conifer Health’s two owners.

Healthagen

US payer Aetna has developed a broad PHM portfolio via several acquisitions over recent years. In 2005 Aetna acquired ActiveHealth Management for a reported $400M. ActiveHealth Management provided medical management and data analytics solutions at the time. In 2011, it completed the acquisition of Medicity, a provider of Health Information Exchange (HIE) solutions for $500M.  Finally, in 2011, Aetna acquired Healthagen, at the time best known for developing the mobile symptom checking app iTriage. In 2013 Aetna consolidated all its PHM- products obtained via these acquisitions under the Healthagen brand.

Although Aetna is estimated to drive some internal business for Healthagen, unlike the previous two examples of Optum and Conifer, the internal business generated from Aetna is estimated to be relatively small.

Transcend Insights

A similar picture exists for Transcend Insights. As with the Healthagen brand, the Transcend Insights brand reflects the PHM offerings of another major US payer, namely Humana (until recently, itself in merger discussions with Aetna).

Transcend Insights was formed in March 2015 after Humana brought the businesses of its subsidiaries Certify Data Systems, Anvita Health and nLiven Systems together under one brand.

The combined entity is a top 10 vendor in terms of 2016 PHM market share and it addresses the PHM market via its HealthLogix portfolio. Humana is estimated to have been a significant customer for Transcend Insight’s PHM products in 2016.

Other Examples

Several other companies also contribute towards this 20% figure, such as Medecision which is owned by one of its largest clients, US payer Health Care Services Corporation (HCSC).

There are also examples of provider/payer-owned vendors where the owner relationship isn’t defined as customer/client. For example, Evolent Health, which addresses the PHM market via its Identifi portfolio, is part-owned by Pittsburgh-based provider UPMC. However, much of Evolent’s portfolio is based on IP developed by UPMC. In this set up, Evolent acts as a reseller of UPMC technology, rather than a supplier to UPMC.

That said, Evolent does contribute toward this captive market in other ways. Since February 2016 one of its top three customers, Passport Health Plan, owns a sizable share in Evolent. Passport Health drove 20% Evolent’s overall business in 2016.

Premier Inc, is also technically part-owned by its customers but the business is very different to the other vendors discussed in this section. It has been a publicly-traded company since its IPO in September 2013; however, at the end of 2016 64% of the company equity was held by its members which comprised its customers. This includes 3,750 hospitals/130,000 providers making the company technically a provider-owned business. However, unlike the others listed in this section it is not owned by one provider, but many, and the vendor/client relationships are very different to the other examples. For this reason, Premier’s business has not been included in the 20% captive market figure.

Steady Decline in ‘Captive’ Share of the Market

The share of the market represented by companies selling to their owners (or in some cases owned subsidiaries) is forecast to fall over the coming years. For the companies involved, although their internal business is forecast to grow, the share of business generated by external customers is forecast to grow faster. This, coupled with the growing PHM businesses of other vendors that don’t have internal customers, results in the captive share of the market falling to less than 10% by 2021.

New Market Report from Signify Research Publishing Soon

The market data presented above are the preliminary estimates and forecasts from Signify Research’s upcoming report on the North American PHM market which will be published in April. The report is a component of the Signify Research “PHM & Telehealth Market Intelligence Service”. Vendors tracked include Aetna, Allscripts, AthenaHealth, AxisPoint Health, Caradigm, Cerner, Conifer Health, eClinicalWorks, Enli, Epic, Evolent, HealthCatalyst, Humana/Transcend Insights, IBM Watson Health, McKesson, Medecision, Meditech, NextGen, Optum, Orion Health, Premier Inc., Verscend, ZeOmega and others. The report provides quarterly market estimates for 2015 & 2016, and annual forecasts by vertical, function, service type, platform delivery and country to 2021.

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

5 Key Issues for Cloud Adoption in Clinical IT

5 Key Issues for Cloud Adoption in Clinical IT

Written by Steve Holloway

Hype surrounding cloud solutions for clinical IT has ramped up in the last two years, buoyed by user demand for more flexible data access and connectivity. However, global market adoption of cloud technology for clinical IT to date has been relatively slow, despite the increased marketing efforts of healthcare technology vendors and the growing presence of cloud technology platform vendors in healthcare, such as Microsoft (Azure) and Amazon (AWS).

So why is market penetration so low when cloud IT is big business in other sectors? And what are the key factors in cloud adoption for healthcare?

1. Each provider implementation is unique

No two clinical IT implementations are the same and no single software solution can address every provider’s needs. Scale, complexity of existing infrastructure, variety of user groups and interfaces and differing needs for mobility and connectivity all impact the effectiveness of clinical IT implementations. Therefore, the one-size-fits-all approach rarely works.

This complexity also impacts IT architecture selection: some provider organisations already own and maintain extensive IT data warehouses, so are unwilling to use third-party solutions when they can host their own private cloud. Others have complicated legacy networks of disparate clinical IT solutions across multiple locations, requiring flexile, multi-faceted cloud IT solutions. Smaller providers have limited resources for IT administration and so require full third-party managed service cloud solutions.

This variance of need makes it very difficult for providers and vendors alike. For providers, it is challenging to find case study examples of past implementations with similar profiles to learn from, especially as cloud IT is relatively new for healthcare. For vendors, it’s difficult to know which market segments and regions to target and which product lines to “cloud-enable”, without spending extensive time understanding the nuances of their customers’ unique needs, not to mention the dizzying amount of red-tape from local, regional, national and international regulations (see number 3).

2. Providers often misconceive cloud is less expensive

Whether fully hosted or hybrid architecture, it is rare for cloud IT implementations to be less expensive than on-premise solutions, though this is a common misconception amongst buyers.

Some cloud solutions are offered with a subscription-based managed service pricing model which can be misunderstood as less expensive relative to an up-front purchasing model. However, cloud solutions for clinical IT can be up to a third more expensive, depending of course on the unique needs of the provider. The complexity of most providers’ health networks and multi-faceted interfacing also adds significant financial risk to new implementations, for providers and vendors alike.

The relative infancy of cloud implementation also means there are few long-term case studies outlining the cost benefits of cloud for clinical IT. Vendors should be doing more to partner with early-adopters to better profile the wider benefits that cloud IT enables (mobile and remote access, workflow efficiency, reduction in IT administration). In doing so, providers will be able to better understand if a true return on investment (ROI) is possible.

3. Security and legislation is a moving target

Barely a day goes by without news headlines announcing the unsolicited release of sensitive patient health data, be it from malicious hacking or accidental release. Cybersecurity has therefore become a leading issue and challenge for healthcare providers, both to satisfy patients and adhere to the increasingly complex array of cybersecurity and compliance legislation. For larger providers with regional, national or international footprints, this is even more challenging, as each has its own “flavour” of regulation and each is evolving as legislators catch-up with new types of cyber threat.

This creates a challenging environment for selling cloud IT products, even if they are proven to be more secure than the provider’s current on-premise architecture. Large health providers are particularly sensitive to patient data security, as a major breach could be costly both from a financial and legal perspective, not to mention losing patient trust.

While many strategies exist to overcome these issues, vendors must fundamentally build customer-confidence in their adherence to the most up-to-date legislation and security protocols, provide certified examples and statistics on their cybersecurity record and be willing to work long-term with their customers on transitioning to cloud. Risk-averse providers are more willing to adopt cloud IT in a step-wise approach, such as off-loading second copy data and disaster recovery back-up in a hybrid cloud architecture as a first phase trial. Once the benefits from a financial, administration and security perspective have been proven, they will be more willing to expand cloud technology implementation.

4. Enterprise EMR is not an adoption precursor, but it helps

From a global perspective, adoption of cloud technology for clinical IT is relatively low compared to other industry sectors. It has however, been closely linked to markets where enterprise EMR implementation has been significant, such as the USA, the Nordics, the Netherlands and Singapore. There is no technical reason for this trend – cloud technology can in theory be deployed in any market with the necessary base infrastructure.

Instead, it is more to do with the impact made by digitalising core patient information with enterprise EMR. The mere existence of a basic centralised EMR spurs greater administrative and clinical focus on improving interoperability and connectivity of health data, both within network and intra-network. Moreover, EMR has commonly provided the initial interconnectivity of patient and data to drive momentum for implementation of value-based care models. As many of these models exploit and demand patient-payer-provider interconnectivity across a variety of access nodes, cloud technology adoption consequently increases.

5. Health data is the new currency

The value of health data is also changing, especially due to recent market development and focus on predictive analytics and artificial intelligence. While the question of who should “own” patient data is a complex and ethical one that far outstrips the remit of this piece, the increasing importance of patient data as a commodity to fuel new healthcare IT solutions, such as risk stratification analytics for phm or new care management workflows, is quickly becoming evident to provider, vendors and patients-alike.

Hybrid or hosted cloud technology solutions can be viewed by some providers as “losing control” or “ownership” of their data, despite the many contractual safeguards available. This view has also intensified with the advent of artificial intelligence, as providers also see the mid-term revenue potential of licensing use of their data to train machine learning algorithms.

While this is still a relatively new development, providers, healthtech vendors and cloud IT platform vendors are already acutely aware of the potential commercial gains to be made from pooling patient data, making adoption of cloud technology even more complicated.

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 April 2017. For further details please click here or contact steve.holloway@signifyresearch.net

Target Applications for Machine Learning in Medical Imaging

Target Applications for Machine Learning in Medical Imaging

Written by Simon Harris

Rapid advancements in machine learning, most notably deep learning techniques, are fuelling renewed growth for medical image analysis software tools. We estimate that the global market1 for these products will be worth nearly $300 million this year and will more than double in size by 2021.  But which clinical applications are driving this growth?

Breast is Best

Breast imaging was the largest category in 2016, accounting for just over one-quarter of the total market. The breast imaging market mainly comprises computer-aided detection (CADe) solutions, such as iCAD’s SecondLook and Hologic’s ImageChecker, for the US breast cancer screening market, along with quantitative image analysis software for diagnosis applications, such as Invivo’s DynaCAD Breast and QLAB Suite from Philips Healthcare.

The market for image analysis tools in breast imaging is forecast to grow at a slower rate than the other applications, as the well-established CADe market in the US is now saturated. The main growth drivers will be:

  • CADe upgrades as imaging centres replace 2D mammography systems with digital breast tomosynthesis
  • Wider acceptance of CADe outside of the US
  • The increasing use of ultrasound (with CADe) in breast cancer screening
  • Uptake of new solutions such as breast density analysis software and decision support tools (e.g. MammoRisk from Statlife)

Cardiology Still Pumping

The cardiology market for image analysis software solely comprises quantitative imaging tools2, which are typically sold as applications for advanced visualisation platforms. These tools provide automatic calculation of various cardiovascular metrics, such as stroke volume, ejection fraction and arterial calcification. Growth will be driven by an accelerated pace of innovation from the use of deep learning algorithms and the resulting introduction of innovative solutions that address unmet market needs. In the mid-term, growth will be boosted by the introduction of decision support tools that provide predictive analytics for risk stratification and computer-aided diagnosis (CADx) systems that facilitate early detection of cardiovascular disease. For example, healthbit’s heartcare™ uses machine learning algorithms to predict congestive heart failure based on cardiac MRI scans.

Deep Breathing

Lung cancer is the leading cause of cancer-related death worldwide, and in response, many countries have introduced lung cancer screening programmes. This is driving demand for CADe solutions, although a lack of reimbursement prohibits more widespread uptake. Early generation CADe solutions based on shallow machine learning suffered from high false positive rates. Deep learning solutions promise improved detection accuracy, which should increase the usability of lung CADe and accelerate demand.

There is also a sizeable and growing market for quantitative image analysis tools for pulmonology applications, that provide characteristics of abnormalities such as size, texture, location, rate of growth, etc. These imaging biomarkers may be useful for predicting prognosis and therapeutic response. As was the case for breast imaging and cardiology, there is also an emerging market for pulmonology decision support tools that combine quantitative imaging with other patient information to provide a data rich, longitudinal history of the patient’s care. An example is the QIDS platform from HealthMyne.

A Head Start in Neurology

Brain scans are the most common type of MRI procedure and accounted for around one-quarter of the 34 million MRI exams performed in the US last year. There is already an established market for quantitative imaging software in neurology, primarily for tools that provide visualisation and quantification of blood perfusion in the brain. Additional growth will come from research into the use of imaging biomarkers for the diagnosis and management of neurological disorders, such as Alzheimer’s disease, multiple sclerosis and Parkinson’s disease.

Growth will be boosted by the introduction of CADe solutions to detect intracranial haemorrhage (ICH) from head CT scans. vRAD and MedyMatch have developed real-time ICH detection tools and both are expected to fully commercialise their solutions in 2017, pending regulatory approval. Teleradiology companies are expected to be the early adopters, particularly in the US as most CT scans ordered by emergency department are interpreted by teleradiologists.

Best of the Rest

The gastroenterology and urology markets for image analysis software were estimated to be similar in size and are forecast to grow at similar CAGRs over the coming years. The gastroenterology market comprises a mix of quantitative tools for analysis of the colon, pancreas and liver and CADe solutions for the detection of colorectal cancer, the third leading cause of cancer death in the US. Colonoscopy remains the gold standard in colon cancer screening, but CT colonography (CTC) is gaining acceptance. However, a lack of reimbursement (CMS does not pay for the use of CTC in colon screening) has hampered the uptake of CTC. The urology market solely comprises quantitative imaging tools, primarily for prostate analysis.

Footnotes

1 The image analysis software market comprises computer-aided detection (CADe) systems, quantitative image analysis tools, decision support tools and computer-aided diagnosis (CADx) systems. A full list of the products included is available on request.
 2 The quantitative image analysis tools category includes all software products that provide automatic quantification of anatomical features, not just those that use machine learning. Products that use other image analysis techniques, such as a statistical model-based approach, are also included.

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.

How to Sell Machine Learning Algorithms to Healthcare Providers

How to Sell Machine Learning Algorithms to Healthcare Providers

Written by Simon Harris

One of the greatest commercial challenges for developers of medical image analysis algorithms is how to take their products to market. Most independent software vendors (ISVs) of image analysis solutions only offer a handful of algorithms for specific use-cases, e.g. coronary calcium scoring, bone age prediction, detection of lung nodules, etc. However, most generalist radiologists require a comprehensive “analytical tool kit” with a broad portfolio of algorithms that can detect a wide range of conditions for multiple body sites and across multiple modalities. Locating, evaluating and sourcing image analysis algorithms on a piecemeal basis from multiple vendors will be a cumbersome and time consuming process for healthcare providers. Not to mention the challenges associated with integrating the algorithms with the providers’ existing healthcare IT infrastructure. Whilst this may be a viable option for the larger academic hospitals and IDNs, most providers will not have the necessary resources for this and instead will prefer to deal with a small number of vendors, and ideally a single supplier.

There are several routes to market for image analysis ISVs, as follows:

  1. Develop an in-house image analysis workstation or platform (proprietary or open)
  2. Partner with established imaging IT companies, e.g. PACS, viewer and advanced visualisation companies
  3. Partner with modality companies
  4. Partner with healthcare ecosystem (open platform) providers
  5. Partner with companies who provide vendor agnostic image analysis platforms

The advantages and disadvantages of each, as viewed through the lens of algorithm developers, are presented below.

1. Develop an in-house image analysis platform

Examples: iCAD PowerLook Advanced Mammography Platform (AMP), RADLogics AlphaPoint™, HealthMyne QIDS
Advantages: A viable option for specific clinical applications, e.g. breast and lung cancer screening. Solutions can be highly customised for specific customer types, e.g. breast imaging specialists. Full control of the development roadmap.
Disadvantages: Limited choice of algorithms for general radiology. High product development, marketing and sales costs.

2. Partner with established imaging IT companies

Examples: Most of the major PACS and advanced visualisation companies offer clinical applications from third party vendors, alongside their in-house applications. For example, GE offers over 50 clinical applications for its AW advanced visualisation platform, some of which are licensed from third party developers.
Advantages: Access to an established customer base. Tight integration with partner’s imaging IT platform. Partnering with a well-known brand may add credibility by association. Leverage the partner’s sales and marketing efforts.
Disadvantages: The imaging IT market is fragmented – being tied to a specific vendor(s) gives access to only a fraction of the total available market. The Imaging IT market is evolving from departmental PACS to enterprise imaging solutions, creating uncertainty and complexity in the marketplace.

3. Partner with modality companies

Examples: Arterys has a non-exclusive, co-marketing agreement with GE Healthcare, whereby Arterys 4D Flow is available via the ViosWorks application for GE MRI scanners.
Advantages: Access to an established customer base. Credibility by association. Leverage partner’s sales and marketing efforts. Access to “raw data” direct from the modality may improve accuracy of algorithms.
Disadvantages: Doesn’t give access to the total market, although the modality markets are more consolidated than Imaging IT. For example, the MRI market is largely controlled by an oligopoly of 5 companies – Siemens, GE, Philips, Toshiba and Hitachi. Long sales cycles. Modality companies are likely to embed a small number of algorithms rather than a full suite, which will limit the available market.

4) Partner with healthcare ecosystem (open platform) providers

Examples: GE Health Cloud (features applications from Arterys, Pie Medical Imaging and imbio, to name a few), IBM Watson Health Core (recently added an application from MedyMatch that detects intracranial bleeds on CT scans), NTT DATA Unified Clinical Archive (offers analytical solutions from imbio, Zebra Medical Vision and AnatomyWorks), Siemens Healthineers Digital Ecosystem (announced at HIMSS 2017 with Arterys, SyntheticMR and a handful of others having already agreed to provide applications).
Advantages: Widest choice of algorithms. Major focus of investment by the major healthcare technology vendors (GE plans to invest $500m over the next three years in its Health Cloud platform). Access to the platform developer’s installed base of customers. Credibility by association. Leverage the platform developer’s sales and marketing efforts.
Disadvantages: Some resistance from healthcare providers to cloud-based platforms, often due to data compliance requirements. Ecosystem platforms are a relatively new and unproven concept in medical imaging and currently there are relatively few healthcare providers using them.

5) Partner with companies who provide dedicated, vendor agnostic image analysis platforms

Examples: Medimsight offers a cloud-based computer-aided diagnosis marketplace for biomarker quantification. The platform features 39 applications, including algorithms from LAIMBIO, FMRIB (Oxford Centre for Functional MRI of the Brain) and Martinos Center for Biomedical Imaging.  Blackford Analysis offers a vendor-neutral pre-processing (VNP) platform that acts as a broker for pre-processing algorithmic solutions from third party developers, to enable integration with existing clinician workflows. McCoy Medical is a distribution partner / sales channel for companies who make algorithms and analytics.
Advantages: Support with integration reduces the need for PACS back-end engineering. A highly focused marketplace for image analysis solutions.
Disadvantages: The developers of dedicated, vendor agnostic image analysis platforms are small companies with limited resources and few customers. Strong competition from healthcare ecosystem providers (see 4 above).

The Signify View

In the short-term we expect image analysis ISVs to focus on developing their own platforms and to seek partnerships with established imaging IT vendors. However, with the major healthcare technology vendors investing heavily in their healthcare ecosystem platforms, these new “clinical application marketplaces” look set to be an increasingly important sales channel in the coming years. The single platform model greatly simplifies purchasing and workflow integration for healthcare providers and gives radiologists access to the widest selection of algorithms to build their “analytical tool kits”.

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.

Is $500M Enough? GE Healthcare’s Investment in Digital Health

Is $500M Enough? The Signify View on GE Healthcare’s Investment in Digital Health

Written by Steve Holloway

  • Late last week, the CEO of GE Healthcare announced a plan to invest $500M in the division.
  • Investment will take place over the next 3 years.
  • It will be used to recruit 5,000 software engineers, data analysts and imaging analysts.
  • Some funding may also be used to fuel acquisition of data analytics firm(s).
  • Focus to develop Health Cloud platform (announced November 2015) and hundreds of clinical software applications.
  • Platform will be driven by GE’s Predix operating system.
  • Germany highlighted as a key target market for GE.

The recent announcement from GE Healthcare on plans to invest $500M on 5,000 software engineers and potential acquisition of a software analytics firm is no great surprise but excellent PR. The firm announced in late 2015 their “Health Cloud” platform to great fanfare, but little progress has been evident to date. However, GE has been making it very clear publicly that it plans to transition the industrial conglomerate into a “digital” firm, fueled by its Predix industrial platform.

Here’s the Signify View on the announcement:

Battle Lines Drawn

The size and scale of the announcement is significant for GE Healthcare, one of the leading global healthtech firms with $18.4B of revenue in 2016. However, it is by no means the biggest move in healthcare of late.

IBM’s entry into the healthcare field, investing over $4B in Merge Healthcare ($1B) Truven Analytics ($2.6B), Explorys and Phytel (not disclosed, but estimated to exceed $400M) has been very aggressive, not to mention the serious investment IBM has made in recruiting healthcare leadership and marketing spend for its IBM Watson Health business.

Other major competitors are also making big moves. Siemens plans to take its newly branded “Healthineers” division through an IPO later this year, while Philips has re-focused the company on health and wellbeing markets, having divested its lighting division, Philips Lighting, in 2016. Other global technology giants have also been lining up the healthcare sector; Google (Deepmind), Amazon, Salesforce and NTT Data have also made a big push for healthcare market share. Therefore, GE was always going to need to invest heavily to compete.

Digital Deutschland?

The orchestrated announcement was made to a German media outlet (Handsblatt), for good reason. GE has for some time been lining up the German market. While aiming for Europe’s largest market may seem a sensible move, it will not be straightforward, especially when it comes to Healthcare IT:

  • Germany is one of the most price sensitive markets for healthcare technology in Europe; procurement prices are regularly 30-50% lower than the Western European average
  • The health IT market in Germany is highly fragmented. In Imaging IT alone there are approximately 30 local vendors and integrators working with a complex and fragmented provider network, especially in the private and administrative sectors
  • There has been little if any national or regional co-ordination of health IT in Germany to date. While the market is therefore under-penetrated for Health IT in relation to European peers, consolidation of the market to larger, more profitable enterprise networks will be challenging, bureaucratic and long-winded

In Germany, GE Healthcare does have considerable experience and past success in health IT with smaller ambulatory practice management software. This will certainly help in catering for the market, as will a sizeable installed base of imaging and clinical care hardware in Germany and surrounding markets. That said, attaining a commanding share of the multi-billion dollar German healthtech market could be far from straightforward against a mix of large incumbent multinationals (Siemens, AGFA Healthcare) and a multitude of small private vendors. Add to this economic concern and political uncertainty over the future of the European Union and GE’s strategy looks increasingly risky.

ACE Platform or Bust

GE is also not alone in its bid to position itself as a central platform provider. Philips, Siemens, NTT Data and IBM are all making a similar play. The move from these vendors 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.

For GE Healthcare, Philips Healthcare and Siemens Healthineers, 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, is a natural progression. 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 providers and vendors alike. The single ACE platform model allows the vendor to become embedded in the provider’s 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.

With its competitors also making significant moves to establish ACE platforms and aggressive investment from IT and analytics industry giants, GE’s recent announcement really only offers one question: will $500m be enough?

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 April 2017. For further details please click here or contact steve.holloway@signifyresearch.net

North American PHM Market Worth $1.01B in Q4 2016

North American PHM Market Worth $1.01B in Q4 2016

Written by Alex Green

  • Signify Research preliminary analysis and commentary on the North American Population Health Management IT Market (PHM Market), which includes data for the quarter ending December 2016
  • Q4 2016 population health management (PHM) market in North America remained buoyant despite uncertainty around US healthcare reform
  • Revenues of $1.01 billion were generated in Q4 2016, up 17% YoY and up 8% compared to previous quarter
  • PHM solution spending for FY2016 in North America was $3.7 billion, up 15% on 2015

Analysis

Signify Research’s preliminary market estimates for the Q4 2016 North American population health management (PHM) IT market (platforms and services) shows that despite the uncertainty caused by the US presidential election, and its potential ramifications for US healthcare policy, the market remained buoyant. PHM revenues for Q4 2016 in North America stood at an estimated $1.01 billion, up 17% on the same period in 2015 and up 8% on the previous quarter in 2016.

The continued growth in the fourth quarter does need to be put in context. The fall out of the presidential election result is unlikely to have had time to substantially affect sentiment to the point that immediate orders would have been impacted.  Fourth quarter has also traditionally been a seasonally strong quarter for leading vendors of PHM and related solutions.

The results are still very encouraging though. It is Signify Research’s view that the longer-term trend towards value-based care, the move to accountable care organisations (ACO) and the need to better manage health care spending in general will ultimately drive continued growth for vendors offering PHM solutions, despite legislative uncertainty.

Supplier Base Remains Fragmented

For the full year 2016, the North American PHM market was estimated to have been worth $3.7 billion, compared to $3.2 billion in 2015. The list of companies that drive these numbers remains long, and is indicative of the fact that the market, despite reaching a certain level of maturity, is still highly fragmented. However, several companies including Optum, IBM Watson Health, Cerner, Allscripts, Conifer Health and Evolent have started to take market leading positions in terms of share. Between them they are estimated to have accounted for approximately 45% of the 2016 market. Most still only command a single digit share in 2016, with a long list of vendors closely following.

Data Aggregation / Analytics / Stratification Driving Market to Date

Signify Research’s upcoming report segments the market in to three main components, data aggregation/analytics/risk stratification solutions, care coordination/management solutions and patient engagement solutions. Of the three, the data aggregation/analytics/risk stratification segment represented the largest market in 2016 and is projected to remain the largest for the report’s forecast period (2017-2021). Similarly, the provider vertical, specifically the acute provider sector, is also projected to remain the largest market channel compared with the payer, employer and other verticals.

Full Impact of Legislative Uncertainty Yet to be Felt

As indicated above, the real test of the impact of uncertainty in relation to potential changes in legislation will be in seen in market performance during the first half of 2017. Results for Q1 2017 will be eagerly awaited. Signify Research’s market update in the second half of 2017 will give an early indication on the level to which this uncertainty hits the revenues for PHM solution vendors in 2017. However, it’s our view that strong annual growth will continue in 2017, with the market projected to grow a further 16%.

New Market Report from Signify Research Publishing Soon

The market data presented above are the preliminary estimates and forecasts from Signify Research’s upcoming report on the North American PHM market which will be published in April. The report is a component of the Signify Research “PHM & Telehealth Market Intelligence Service”. Vendors tracked include Aetna, Allscripts, AthenaHealth, AxisPoint Health, Caradigm, Cerner, Conifer Health, eClinicalWorks, Enli, Epic, Evolent, HealthCatalyst, Humana/Transcend Insights, IBM Watson Health, McKesson, Medecision, Meditech, NextGen, Optum, Orion Health, Premier Inc., Verscend, ZeOmega and others. The report provides quarterly market estimates for 2015 & 2016, and annual forecasts by vertical, function, service type, platform delivery and country to 2021.

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

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.