Digital Health Management: Hype vs Reality Webinar #SPMLearning

Who remembers the Quantified Self movement? I recall attending meetups of the QS community years ago and considered the quantified self group central to consumer adoption of digital health technologies—through advocacy and example.

Today, we don’t hear the term ‘quantified self’ as often, but a recent Rock Health survey indicates that the young ‘worried well’ between the ages of 18-35 with incomes greater than $75,000 remain the dominant users of digital health technologies. In comparison, those who might benefit most from monitoring vital signs to identify changes in health condition are not heavy users of digital health tools.


Why haven’t we made more progress in directing digital health technologies to the populations most in need? The Society for Participatory Medicine’s Learning Exchange webinar on September 11 with guest speakers who are leaders in advancing the adoption of digital health technologies that improve patient outcomes will help answer that question.

We are fortunate to have a stellar panel of speakers to provide context on where we have hit roadblocks and where we have made the most progress in serving targeted populations.  Joining S4PM members Vera Rulon, Sarah Krüg and me will be:

Patient Perspective
Donna Cryer, JD

President  & CEO, Global Liver Institute

Digital Health Experts:

Joe Kvedar, MD

VP, Connected Health, Partners Healthcare

Lygeia Ricciardi, EdM

President, Clear Voice Consulting

Former Director, Office of Consumer e-Health, ONC, HHS

We will have time for questions from the audience, so please come prepared with questions or information you’d like to share.

The Learning Exchange webinars (#SPMLearning) are sponsored by Accenture and Vocera; registration is free. Register for the Sept 11, 2018 Digital Management Hype vs. Reality webinar at 1 pm here:


Engaging Physicians Through Intelligent Workflow

Part I of my HIMSS17 commentary described how patient engagement applications have evolved into value-added patient workflow solutions. In this part II, the focus is on the emergence of an ecosystem that delivers integrated workflow solutions for physicians.

Ecosystems don’t arrive ready-made. As much as we wanted healthcare to vault over the development cycle that other industries followed in establishing enterprise resource planning (ERP) systems and other productivity platforms, we’ve found that healthcare has had to follow a similar path that begins with a fragmented group of limited-purpose billing, clinical, administrative, and patient-facing software systems and progresses toward platforms that connect information from multiple sources to enable more efficient workflow.

Once the foundational ecosystem is sufficiently established, value-added analytics can flourish and systems can be further tuned to improve utility, usability, and efficiency. Have we achieved success in delivering workflow systems that delight rather than deter physicians yet? Not quite, but at HIMSS17 there were good signs of progress in the foundational infrastructure, the building blocks and the interfaces that constitute a viable ecosystem.

Technology has delivered some amazing tools for mining insights from massive datasets by applying data science and cognitive computing methods. IBM Watson stands out in this area and IBM Watson Health was definitely in the spotlight at HIMSS17, given the opening keynote by IBM’s CEO, Ginni Rometty.  But, we need to remain aware of the importance of a strong data foundation for the advanced applications. Data need to meet minimum levels of accuracy, normalization, timeliness and breadth.  And, let’s not forget security and access control.


Can AI help the future of health? Here’s @janicemccallum’s take on the matter 

Debating Physician Engagement

A highlight for me at HIMSS17 was a brief debate with fellow social media ambassador Rasu Shrestha, MD, MBA, Chief Innovation Officer at UPMC. Our topic was “Physician Engagement” and the conversation quickly turned toward better design of products for physicians so that the product enhances productivity, with interfaces that delight rather than frustrate.  The example of EHR development, which is viewed in retrospect as including too little input from intended users and almost no vision on how digital records could interact with other digital systems to dramatically improve productivity, sits in everyone’s mind as the wrong way to develop health IT software.


We weren’t able to solve the issue of the ideal product development process for health IT systems in our seven minute session (although I’d love to spend more time on this topic). However, the following takeaways relate well to other hot topics at HIMSS17.

Physicians as detectives

Rasu described the work of physicians as similar to detectives who search for clues and put the pieces together to come up with the best solution. EHRs and other installed health IT systems weren’t designed to solve this core functional need of physicians. Early clinical decision support (CDS) systems have existed alongside EHR/EMRs, but have only recently begun to be integrated into workflow.

Zynx Health, which was a pioneer in workflow software for creating order sets, is celebrating its 20thanniversary.  They now work more closely with EHR vendors to integrate CDS and care plans into core workflow.[1]

It’s encouraging to see that in both consumer-facing apps and provider-focused health IT products the cluttered and disjointed landscape of health IT products and mobile apps is coalescing into a connected health IT ecosystem. But, it didn’t happen overnight. All the buzzwords from previous HIMSS conferences, including standards, interoperability, meaningful use of EHRs, data warehousing, data security, privacy, population health management, patient engagement, big data/data analytics, cloud computing and APIs have served as building blocks to get us to where we are today. AI and virtual reality systems may be awe-inspiring, but a sustainable ecosystem still needs a solid foundation built on best practices in data management, security and infrastructure.

Furthermore, the drudge work that Rasu describes in seeking clues from multiple systems and sources that often present repetitive navigation challenges is precisely the type of task suited to healthbots, as I described in my pre-HIMSS17 Industry Perspective article. Let’s offload the annoying, time-consuming drudge work to bots that perform these tasks better than humans and allow the physicians, researchers and other clinicians to focus on improving outcomes and providing better care.

[1] Note that Zynx Health’s sister company, FDB, known for its drug database, has introduced FDB Prizm, a master database for medical devices.

This article was orginally published by HIMSS on March 28, 2017 and can be found here:



Patient Engagement Tools Mature into Workflow Solutions

In this part I of my HIMSS17 commentary, I describe how the array of patient engagement offerings at this year’s annual conference has matured to include many connected workflow solutions that benefit both providers and patients & their families: 

It has taken a long time for common standards and a sufficient installed base of EHR software to be adopted to create the necessary conditions for a connected health ecosystem. But there’s good news: based on advances reported at HIMSS17, all signs indicate that we are turning the corner toward the next phase where advanced analytic and productivity applications can be built upon the basic infrastructure layer. It’s still not plug and play, but enterprise-wide systems like customer relationship management (CRM) platforms for the healthcare sector are providing the backbone, along with APIs that supply the connective tissue to related apps, for a sustainable connected healthcare ecosystem.

At HIMSS17, one pleasant surprise was witnessing the progress that has been made on the patient engagement workflow front. Prior to HIMSS17, I was quoted as saying “Without fully including patients in their own health care decisions, patient engagement programs are nothing more than paternalistic compliance programs”. That statement garnered a lot of attention on social media and led to requests for meetings with several companies that offer a new generation of patient engagement tools that far outshine the first generation of prescription adherence apps and rudimentary patient portals.

HealthGrid, for example, has created a CRM platform, CareNarrative, which helps providers communicate with patients at appropriate times and offers solutions for ambulatory care, acute care and post-acute care. CareNotify is HealthGrid’s consumer-facing platform that enables patients and their family members/care team to access real-time information on inpatient care, discharge instructions, as well as education materials. CareNotify can be used to request appointments, complete check-in, fill in surveys and more.

Geisinger Health System also has found that a CRM platform is the best way to connect and manage patient-related data to engage patients on a personalized basis. Geisinger is working with Salesforce and Accenture to develop a custom CRM that can tailor care plans to individuals. This article in MobiHealthNews provides more detail on how the team at Geisinger has maintained a patient-centric mindset with a focus on improving outcomes.

In my discussions with Chanin Wendling, AVP Informatics and Jonathan Slotkin, MD, Medical Director, Division of Applied Research & Clinical Informatics at Geisinger, they further described use cases where an entire community will be served by its CRM by connecting to related organizations and retail health outlets across the community, as is being done in a pilot program in Scranton, PA. The Scranton pilot provides a glimpse into how social determinants of health (SDOH) could be incorporated into a CRM system to create a community-wide population health management system.

It is also worth mentioning that telemedicine services can be integrated into a CRM-based patient engagement system. Salesforce, the leading worldwide CRM vendor, offers a telemedicine capability through its own-branded HealthCloud patient relationship management solution.

B.well approaches patient engagement from a different angle. Kristen Valdes, founder and CEO of b.well, brings her experience working in the health plan segment to bear on improving the patient experience. B.well’s patient engagement platform for health plans, employers and brokers offers a single solution for providing patients and their care team access to care management and wellness tools, with an emphasis on understanding benefits and costs. At the same time, the platform serves as a population health management service that incorporates cost information for the payers that offer b.well.

The examples above represent just a fraction of the enhanced patient engagement solutions that were on display at HIMSS17. Although questions remain about control, access and security of patient relationship management platforms, integrated workflow systems serve a vital function in creating a health ecosystem that can help connect providers, patients, health plans and over time, the larger communities.

Growth in patient relationship management platforms has benefited from standards and IT advances that were developed for the provider market, as well as innovations in the consumer sector, (smartphones and mobile access, in particular). Part II of my HIMSS17 commentary will focus on workflow developments that enhance physician engagement.

For the original article, please see:


MA-based Social Media Ambassadors Meet OnPage at HIMSS17


Janice McCallum & Judit Sharon, CEO, OnPage at HIMSS17

Matthew Fisher and I, both HIMSS17 Social Media Ambassadors, met with OnPage, a Waltham, MA-based secure messaging company at the HIMSS annual conference. We decided to post a combined blog, reporting from our different perspectives: Matt as a healthcare lawyer with expertise in HIPAA and security; me as a healthcare market strategist and analyst. 

In my pre-HIMSS17 industry perspective article, I wrote how the core IT infrastructure at provider organizations needs a level of enhanced communications services that connects data from EHR and other database systems to build workflow solutions. OnPage represents a good example of the type of enhanced communications service I envisioned.

Judit Sharon, CEO, described how OnPage was a BlackBerry-based secure messaging service that evolved into a cloud-based escalation scheduling service that connects to available on-call physicians.

New opportunities for OnPage arose when telemedicine and other remote care services became more widely used. By providing a fast and reliable means of connecting telemedicine patients to the right clinicians, OnPage has uncovered a winning workflow solution. See this case study on Sage NeuroHospital Management Group for more details.

Matt Fisher & Orlee Berlove, Marketing Director, OnPage at HIMSS17

Matt’s discussions included greater emphasis on privacy and security issues. OnPage recognized fairly quickly that demonstrating satisfaction of HIPAA requirements would be critical to driving adoption. To this end, OnPage determined applicable standards and implemented those requirements into its product.

The ability to securely connect multiple devices is a serious issue within healthcare. Finding tools that can be used on multiple devices is important, especially if those tools can segregate data, since accessed documents automatically saved to a phone is an often overlooked security issue.  A tool like OnPage, which can seamlessly fit into workflow and meet regulatory requirements, is one worth investigating.

To me, OnPage is representative of the evolution of health IT devices and apps from single-purpose tools to workflow productivity services. Matt emphasizes that extra care needs to be taken to protect the security of patient data when new communications services enable the quick and easy flow of information across internal and external networks. 


#HIMSS17 Perspective: Connected Healthbots Will Wake Up Clinical Decision Support

This article was first published on the HIMSS Conference site on January 29, 2017:

The computer “woke up once it got connected to other people”.Anil Dash

On a recent Krista Tippett’s OnBeing broadcast, Anil Dash talked about how for the first half of his life the computer was an island that wasn’t plugged into anything. But the computer “woke up once it got connected to other people” via the Internet. He jokes that young people he now mentors find it hard to understand the use of a computer that doesn’t communicate with other computers and they wonder what computer users did with those early machines: stare at the screen?

Those of us who follow the development of EHRs and their effect on the doctor-patient relationship don’t think there’s anything funny about a computer that doesn’t communicate with other computers. Unfortunately, in the health IT community, we’re still pondering what we could do ‘if only’ data could flow more freely between computers.

But, it requires more than just creating a communications network between the boxes to wake up computers and use them to their fullest; it requires transmitting data that can be programmed or executed. My colleague at the InfoCommerce Group, Russell Perkins, who has been producing conferences on the theme of Data Content for over a decade, has long spoken of the power of “data that can do stuff.” HIMSS prefers the hashtag #PutData2Work. The sentiment is the same: we need data that are interoperable and can be communicated efficiently across networks so that important information can be consulted at the point of need and integrated with other data to support health care decisions.

Stocks versus Flows

I view it as a stock versus flow problem. The major EHR vendors focus on creating record-keeping systems; they don’t specialize in the communications layer that moves information from one place to another. Their reluctance to develop—or even enable— inter-organization communication is similar to the reaction of the computer hardware and software vendors when faced with the Internet in the mid-90s. These vendors underestimated the changes that would occur once users were allowed to communicate and exchange data across a wide network of computers. It took a major external development effort to invent the Web. In health IT, we don’t have to reinvent the Internet or the Web; they already exist. But, based on events to-date, we should look to a new class of vendors that understand data science and APIs to introduce enhanced communications and cross-institution data analysis. The legacy EMR/EHR vendors that market record-keeping systems either don’t have the skills, imagination or urgency to extend their field of competency into data exchange.

Enter the Bots

Technology continues to make it easier and faster to find information. Early search engines required training courses to master the interfaces. Then Google came along and offered a simple interface that sat atop algorithms that aimed to present the most relevant results first.

Now, we’ve entered a new phase, where the search box itself is being replaced by bots that surface relevant information without requiring a search query. For example, with my Google Pixel phone, all I have to do is ask Google Assistant to find me direct flights from point A to point B and I’ll receive verbal information about the length of the flights, along with search results for specific flights that I can click on. If I’ve previously searched for flights to that destination, Google will remember the dates I chose and use them as the starting point. Once I’ve booked the flight, I can easily retrieve the information with a quick request to Google. Note, this is an incremental step that focuses on advances in the chat interface and builds upon data extraction and presentation tools that Google has been developing for years.

Through cognitive computing advances, consumer chatbots like Google Assistant, Amazon Alexa, and Apple’s Siri have matured to a point where bots can learn what is important to a user and continuously hone its ability to personalize its services. The popularity of these consumer chatbots is paving the way toward adoption by other segments; telemedicine interfaces are a good example.


I define healthbots as special purpose bots that perform automated context-specific information retrieval and analysis services via voice, text, or other natural language interface.

One of the more obvious areas where healthbots could improve efficiency in health IT is in EHR interfaces. Bots are ideal for navigating through complicated structured databases. Healthbots could speed up the process of finding the right location for both data entry and data retrieval and they could perform countless advanced operations, specialized for each use case.

Still, to achieve higher-value implementations, healthbots need to operate across broader collections of data than what is stored in a single healthcare provider’s EHR system. With the massive amounts of data being produced by medical and life science researchers, devices, sensors and health data analytics services, healthbots will need to work in tandem with APIs to enable the degree of information flows needed to take clinical decision support solutions to the next level, where data from multiple sources can be interpreted in context and delivered within the clinician’s or patient’s workflow.

What to Watch at HIMSS17

Each year that I’ve attended HIMSS since 2010, I’ve sought out signs of progress in integrating evidence-based medical information into the clinician’s workflow. Good progress has been made in appending links to relevant content at the point-of-need within patient records (via Infobuttons & more recently CDS Hooks), but there’s still a long way to go before we see a clinical decision support resource that pulls together relevant data on a topic from diverse collections of data and includes collaborative features that help construct a learning system based on collective experience. The biggest limiting factor has been business models for licensing or sharing data across competing publishers and my hope is that APIs will continue to advance in how they manage business terms for data licensing or sharing.

This year at HIMSS17, I’ll be seeking out companies that produce healthbots, as well as those that provide APIs that embed business rules for exchanging data. APIs are a critical piece of the solution needed to wake up data stored in siloed repositories so that healthbots can reinvent the way we communicate with broader collections of health data.

It’s important to recognize that siloed repositories exist across the entire health information landscape, not just in EHR/EMR systems. Medical and life science research information is scattered across many public and private publishing and research organizations. Publishers and information services companies try to aggregate and synthesize results of new research, but there’s no single source for such a complex and constantly-changing set of data, especially considering the number of potential use cases for the data.

We need a solution that allows collaboration across the many sources of data to create learning systems in healthcare. Medical publishers that are implementing APIs to their data silos will definitely catch my attention at HIMSS17.