Health IT Infrastructure Enables Clinical Decision Support within Workflow

“Infrastructure enables innovation” –Mignon Clyburn, FCC Commissioner 

I like this quote by Mignon Clyburn that Rob Havasy used in his presentation at the New England HIMSS National Health IT Week event last evening in Boston. People often balk at the effort and expense required for large infrastructure projects (remember, I’m from Boston and lived through the Big Dig!). Nonetheless, a strong reliable infrastructure is essential to establishing the basis for a vibrant and innovative ecosystem. 

Since attending my first national HIMSS meeting in 2010, this has been my consistent refrain: we need to establish foundational health IT infrastructure so that we can move on to disseminating information more efficiently and enabling advanced analytics. Large scale outcomes analysis and population health management simply aren’t feasible without a basic layer of data organization and management provided by open standards and interoperable systems. 

Much has been achieved in establishing the core record-keeping infrastructure. Currently, we’re making good progress in establishing interoperability standards for basic data exchange. Still, we need to go further than simple data exchange; the data that are exchanged have to be executable if we want to build real-time clinical decision support applications. In other words, we need a higher level of data interoperability that includes sufficient metadata to enable real-time integration into analytics systems for population health management analysis, diagnostic support systems, and the like.

CDS hooks

One of the initiatives in the health IT standards domain that I find promising is the CDS (clinical decision support) Hooks effort spearheaded by Josh Mandel, MD, a health informatics researcher at Harvard Medical School & Boston Children’s Hospital[1]. CDS Hooks works within the SMART on FHIR ecosystem to send notifications of information sources that may be of value to the user in real time. Users don’t have to know in advance that resources are available; instead relevant resources are presented within the user’s workflow for them to consult at their option.

For the most part, CDS resources have been important reference sources for academic and medical researchers, but their usage by practicing clinicians has remained limited. To move from being “nice to have” reference sources to truly achieving the goal of “making the right decisions as easy as possible to come by, and as easy as possible to execute”[2], clinical decision support tools need to be embedded in the workflow of the clinician, patient, or other decision maker.  There are still a lot of interoperability issues to work out, but I plan to watch the development in CDS Hooks and encourage publishers of evidence-based databases and other resources to explore intently how they can connect their resources to the SMART on FHIR ecosystem.

Delivering the right information to the person at the right time in the right format via the right channel (the 5 rights of clinical decision support) enables better decisions and supports improved information flows to all stakeholders, including patients. Advancements in core health IT infrastructure and improved interoperability standards will help make these 5 rights an everyday practice. That’s why #IHeartHIT.


[1] This interview with Josh in Healthcare Informatics provides a useful introduction to CDS Hooks:

[2] Jonathan Teich, MD quoted in, June 14, 2006.


CMS Hospital Star Ratings Offer Incremental Step Forward in Transparency

Would you consult a Michelin Guide if you were looking for the closest pizza place? No. But for people who are seeking a “once in a lifetime” dining experience on their special vacation, finding the right 3-star Michelin restaurant may be just what they want.

Michelin has a storied history and promotes their strict system for evaluating restaurants via their publishing & promotional efforts. Still, most consumers who are not familiar with Michelin’s methodology would probably guess that a 3-star rating isn’t so wonderful, compared to 4 and 5-star ratings doled out by so many other restaurant reviewers.[1]

My point is: when it comes to ratings, it is critical to know what universe is being rated and the methodology used to calculate the ratings.

On that score, the CMS Quality Star Ratings for hospitals offer an incremental step forward in improving the value of the Hospital Compare data to consumers. If nothing else, the Quality Star Ratings generate attention, which can lead to further research that uncovers richer information on which to base decisions.

Value of Ratings

Ratings and rankings of products and services will always be imperfect. So, why are ratings so popular? In part, because they fill an information gap for data that either aren’t available or aren’t easy to summarize because of their complexity. In essence, ratings are a signal of comparative quality and often a proxy for missing data.

Measuring and comparing quality among healthcare provider organizations presents an especially thorny problem as described by Andy Oram in a 2-part series on measuring quality[2].  One pertinent extract from part 2 for which I provided some input:

We are still searching for measures that we can rely on to prove quality–and as I have already indicated, there may be too many different “qualities” to find ironclad measures. McCallum offers the optimistic view that the US is just beginning to collect the outcomes data that will hopefully give us robust quality measures.

CMS Hospital Quality Star Ratings

What is the overall objective of the CMS Star ratings? In essence, the star ratings serve to condense the information in the Hospital Compare database and improve the usefulness of that data by making it faster and easier for consumers to assess quality of hospitals in a comparable manner. The hospital star ratings also complement other Star Rating initiatives from CMS that cover nursing homes, dialysis facilities, home health care ratings and health plan finder ratings.

The composite star rating for hospitals is based on 7 quality categories:

1. Mortality


2. Safety of Care


3. Readmission


4. Patient Experience


5. Effectiveness of Care


6. Timeliness of Care


7. Efficient Use of Medical Imaging



Categories were chosen to align with CMS Hospital Value-Based Purchasing (HBVP) program. The right-hand column lists the weights that were assigned each category in calculating the composite rating. Note, the methodology document describes how the weightings were calculated in more detail and should be consulted by those who really want to dig into the details. (See the Fact Sheet from CMS for a description of the ratings and a link to the methodology report:

The composite ratings and the underlying measures remain limited to values that are currently measured by HEDIS, HCAHPS surveys and other quality initiatives. As I mentioned in Andy Oram’s article, measuring outcomes in a meaningful and comparable way is still in early stage. In the future, clinical outcomes measures will improve and the ability to measure “effectiveness of care”, for instance, will improve and that category will likely be weighted more heavily (it is currently weighted at only 4% of the composite rating).

Limitations of CMS Ratings = Opportunities for Data Publishers

Back in 2011, after a lively presentation by then US CTO Todd Park (all of his presentations are lively!) on the topic of Data Liberación, I wrote:

Park spent some time describing and and how they can act as a resource for entrepreneurs. I loved his analogy between and NOAA data. He told an anecdote of how someone once told him that NOAA is unnecessary because one can find the same data in a more user-friendly application on  What the commenter didn’t realize is that NOAA data form the backbone of The federal government provides the data gathering, normalizing, and updating functions and then makes the data available to others who can overlay, combine, segment, analyze, integrate and distribute the data in any variety of mashed-up and improved formats.

The tradition of building data businesses on the foundation of federal, state, and local government data is strong. Savvy data publishing entrepreneurs have been digging deeply into government sources of data and providing new applications based on the data for centuries and new data products and services continue to emerge.[3]

The door remains open to enterprising data companies that are willing to do the hard work of aggregating and integrating data from multiple sources and presenting the aggregated data clearly for consumers. In most cases, a single source of information isn’t sufficient to guide consumer decisions. Proximity and referrals will remain key determinants of choice of hospitals for consumers.  Furthermore, choice is restricted by whether providers are included a patient’s health plan network.

So, from my perspective, the new CMS Hospital Quality Star Ratings represent a step forward in the supply of source data and ratings methodologies that healthcare data publishers can leverage to publish and promote value-added quality guides and other transparency tools for healthcare consumers.

To close, I’ll quote the final paragraph from Oram’s article:

When organizations claim to use quality measures for accountable care, ratings, or other purposes, they should have their eyes open about the validity of the validation measures, and how applicable they are. Better data collection and analysis over time should allow more refined and useful quality measures. We can celebrate each advance in the choices we have for measures and their meanings.




[1] Priceonomics recently posted a good article on the Michelin Guides:  Accessed 8/2/2016.

[2] Part II of Oram’s 2-part series focuses on assessing and measuring healthcare quality:, accessed 8/2/16.

[3] Leveraging the Liberated Data, Health Content Advisors blog, Accessed 8/2/16.


Scholarly Publishing's Napster Moment: Are Paywalls or Poor Ux Driving Users to Pirated Content?

Even for journals to which the university has access, Sci-Hub is becoming the go-to resource, says Gil Forsyth, another GWU physics Ph.D. student. “If I do a search on Google Scholar and there’s no immediate PDF link, I have to click through to ‘Check Access through GWU’ and then it’s hit or miss,” he says. “If I put [the paper’s title or DOI] into Sci-Hub, it will just work.”[1]

Sci-Hub is a Napster-like site that aggregates pirated articles from scholarly journals and provides free access worldwide. With media attention from the NY Times and others, the site has garnered a lot of attention recently & has raised the profile of the Open Access movement.

As detailed in this overview of Open Access by Peter Suber, one of the leading advocates of Open Access (OA), two key defining characteristics of OA are:

1)      OA removes price barriers (subscriptions, licensing fees, pay-per-view fees) and 

2)      OA removes permission barriers (most copyright and licensing restrictions).

In essence, the OA movement adheres to the belief that scientific research findings, especially those funded with public funds, should be available to all without fees for the benefit of scientific advancement.

However, there’s an interesting article in Science Magazine this week that raises the point that ease of use may be an equally important driver of the use of Sci-Hub for accessing articles published in scholarly journals:

Millennials (and others who might describe themselves as digital natives[2]) are accustomed to quick and easy search functionality to find just about anything they are looking for.  Furthermore, once something is identified online, the digital natives expect to be able to gain quick access to the full object, whether it is a full-text article, physical book, or a consumer good. Think of it as the Google Apple Facebook Amazon mindset.

The fact that usage of Sci-Hub includes a base of users who likely have pre-paid access to a base of content far greater than what is included in Sci-Hub underscores how important it is to make content easily accessible with user interfaces that match – or nearly match – what is available via search engines and consumer sites.

Upfront barriers to access—multiple log-ins and passwords, restrictions on mobile usage, and even lack of awareness that access is available—are fatal errors. If your intended audience doesn’t know you exist or gives up on using your service because it is too difficult to figure out how to log in, then the delivery channel mechanism in your business model is broken.

In my view, the interest in using pirated sites is an indictment on the design and technical capabilities of the publishing platform companies that serve scholarly publishers. There are other aspects of the scholarly publishing business models that need updates (including pricing), but turning pre-paid users away at the front door needs to be fixed first.



[2] Note, I want to start a new category for those of us who have been early adopters and digital enthusiasts our entire adult lives—no matter how old we are now. Our wisdom and perennial enthusiasm has value, too.


At HIMSS16, Massachusetts Leads Health IT into Next Stage of Data Analytics and Value-Based Care

Massachusetts is known for pioneering healthcare reform programs that led national efforts and we continue to demonstrate leadership in advancing quality improvements in healthcare delivery.  At the recent annual HIMSS16 conference in Las Vegas, where approximately 42,000 health IT vendors and customers convened to exchange the latest information on health IT and analytics innovations, it was clear that Massachusetts is in the pole position to retain the lead in developing the next generation of health IT and analytics solutions.

Healthcare analytics depend on a reliable foundation for data collection and data management. With database infrastructure that serves 2/3 of the US population via its healthcare provider clients, InterSystems has played a key role in establishing the health IT foundation. Although they have generally operated behind-the-scenes, InterSystems is moving into a more visible role as they offer solutions for care coordination and advanced data analytics. I expect more people in healthcare will know their name in the future.

InterSystems booth at HIMSS16

GE, IBM and Xerox are extremely well-known corporate names that are recognized in the healthcare sector. These storied corporate brands have demonstrated a history of innovation and reinvention that they are applying to an array of data management, analytics, and connected health initiatives. With decades of experience in enterprise computing and cultures that are skilled at integrating acquisitions to build best-of-breed solutions, these corporate giants will likely remain leading names in healthcare for the foreseeable future.

There are far too many product and corporate development announcements made at HIMSS to attempt a recap, even if it were limited to companies with strong ties to Massachusetts. However, the announcement of the $2.6 billion acquisition of Truven Health Analytics by IBM Watson is one that captured a lot of attention. Furthermore, I heard from more than a few experienced health IT professionals who would jump at the opportunity to join IBM’s expanding team at its new Watson Health headquarters near Kendall Square.

In healthcare, financial incentives and regulatory requirements factor into most major business and clinical decisions.  Telehealth is a great example. The technology has been available for some time, but regulations held back the supply of doctors available to practice across state lines. More important, the lack of a clear path for reimbursement constrained interest from clinicians. With the advent of recognition of the value of telehealth by payers, Boston-based American Well has been able to expand its portfolio of services to include multiway video, a mobile SDK, and the Telemed Tablet that facilitates specialist consultations via mobile teleconferencing.

Securing access to protected health information is another area where the right technology can overcome barriers to efficient workflow. Lexington-based Imprivata, a leading provider of health IT solutions for single sign-on and secure communications, is known for its clever and informative presentations at HIMSS which attract a large audience to its booth every year and didn’t disappoint this year.

Imprivata booth at HIMSS16

The overarching theme of my coverage of HIMSS16 has been how health IT has entered a more mature phase, where basic IT capabilities are a required part of doing business and more advanced solutions are in the spotlight. New value-based care and payment models depend on a higher degree of care coordination and need to involve patients in care decisions. Massachusetts has many early-stage and more “mature” health IT companies that offer solutions for secure communications, data exchange, population health analytics, and patient decision tools that all contribute to a more efficient connected care continuum. Other notable MassTLC member companies that are playing a role in transforming healthcare & were represented at HIMSS16 run the gamut from start-up PatientPing, not-for-profit government systems engineering and analysis company Mitre, and big data analytics company, Optum Labs and athenahealth, whose CEO, Jonathan Bush, always manages to capture the spotlight at HIMSS.

HIMSS is not just a conference; it is an event that combines education sessions, keynote addresses, exhibit hall demonstrations, and social events. Health IT companies from Massachusetts also stood as sponsors of some of the “must-attend” social events, too. Here’s a picture of the author at HIStalkapalooza, posing with Elvis and Pat Rioux, who works for Elsevier in the Boston area. Elsevier and athenahealth are both sponsors of HIStalkapalooza.


Janice McCallum, “Elvis”, and Pat Rioux at HIStalkapalooza, HIMSS16

This article first appeared in the MassTLC blog: This is an updated version and is republished here with permission. 


Parsing the Progress of Health IT at HIMSS16

Since my first HIMSS conference in 2010, my consistent theme has centered on how health IT will get more interesting as it matures. My rationale: the types of problems we can solve become more complex and impactful as more core data become accessible for analysis.

That’s the focus on one of my articles in the HIMSS16 newsfeed, Identifying Signs of Maturity in Health IT at HIMSS16. One sign of maturity includes an increasing volume of partnerships and merger & acquisition (M&A) activity, especially among established firms. I’d like to thank IBM for announcing its acquisition of Truven Health Analytics prior to HIMSS16; that relieves me of relaying that information during the conference! At $2.6 billion, I expect this acquisition to be one of the biggest announced for the health IT and analytics community for the whole quarter and I look forward to learning more about the combined entity next week.

Another sign of maturity can be found in terminology changes. I’ve already seen indications that some specific categories in health IT will be rolled up into larger categories. For instance, the distinction between the EMR and the EHR categories is blurring.[1] Over time, more amorphous categories such as clinical decision support will likely get subsumed into larger categories like clinical intelligence. And, before long, we won’t need a dedicated area to showcase interoperability at HIMSS; instead, we will be able to talk about all the things we can do because of the underlying interoperability between previously distinct systems.

Moving From Meaningful to Valuable Uses of Health Data

With the foundation for ‘meaningful use’ of basic EHR data nearly complete, we can move forward to developing analytic solutions that depend on a solid foundation of process and outcomes measures. We’re making progress understanding the relationships between outcomes and interventions, but in this segment, we’re at very early stages of maturity. However, the shift to a value-based payment system will accelerate developments in outcomes measurement and analysis.

Where to Find Me at HIMSS16

My schedule for HIMSS16 is a mish-mash of 1:1 meetings, press briefings, receptions, keynotes and education session with a few minutes here & there left open to wander the exhibit hall.

A few notable sessions & events where I hope to run into friends and colleagues follow:


  • Opening keynotes on Monday, March 1 at 5 pm.
  • HIStalkapalooza Monday evening
  • #HealthITChicks meetup, Tuesday, March 1 at 10 am, HIMSS Spot
  • #TheWalkingGallery meetup, Tuesday, March 1 at 1:30 pm, Xerox booth #8005
  • New England HIMSS reception, Tuesday, March 1 at 4:30 pm, Elsevier booth #3039
  • Social Media Ambassador meetup, Wednesday, March 2, HIMSS Spot


I look forward to a super-charged week at HIMSS16. I’ll try to live up to the new “Health IT Maturity Champion” moniker that HIMSS Media has coined for me (or maybe not!).


[1] The HIMSS Analytics team tipped me off to some terminology changes that are likely to occur soon. See my article on HIMSS Analytics LOGIC here: