A HIMSS17 Conversation about Data, Workflow, and Actionability with David Freeman, Quest Diagnostics

[This post is part of a series I am writing as a HIMSS17 Social Media Ambassador (four years in a row!) in the run up to HIMSS17, in Orlando, February 19-23. Stop by and meet me at the first ever HIMSS Makerspace, booth 7785 in the Innovation Zone!]

Actionable data. What is it? Why does healthcare need it? What is its connection to workflow? Inquiring minds want to know!

(The lunch bag and apple? Inspired by
Quest Diagnostics Lunch & Learn panel, which I moderated
on the Monday of the HIMSS17 conference.)

Are you one such inquiring mind? If so, you are in luck. This blog post is a series of questions and answers from David Freeman, of Quest Diagnostics, about these topics, and more. I’ll be tweeting links to the individual Q/As during HIMSS17. I hope you’ll weigh in an add a comment to this post (I’ll tweet it!). Or respond to any of the tweets. My comments are in italics, questions in bold.

1. Let’s set the stage: who are you and what do you do for who?

I am general manager for Information Ventures at Quest Diagnostics, an exciting effort that leverages our valuable lab data, along with data from partners, to derive insights which drive better outcomes. Through collaborations with progressive healthcare-solutions companies and our own clinical and technology expertise, we are committed to providing insights that are actionable; not just for physicians and patients, but for therapy developers, health plans and health systems. Quest has a long history as a trusted healthcare provider, yet we are now so much more than lab testing. We are also an insights company, and we’re now actively engaged in innovative collaborations and new technology development that turns those insights into actions that help patients, caregivers, health systems and health plans across the entire ecosystem align to improve care quality, value and satisfaction.

My role in all of this is to forge partnerships that can benefit from Quest’s vast collection of data and analytics assets. These partnerships span everything from population health to precision medicine and value-based care. One notable example is IBM Watson, where we’re helping advance precision medicine by combining cognitive computing with genomic tumor sequencing. It’s exciting to be involved with an initiative aimed at leap-frogging conventional genomic services as a better way to target oncology treatments.

On the technology side, we’re leading in health information technology (HIT) too. We’re at HIMSS because we now play an important role in helping health insurers, health systems and providers use data and analytics to improve care, lower cost and better manage populations. QuestQuanum, our suite of internally developed technology solutions, brings forward our expertise generating insights from data, including our own industry-leading dataset of more than 20 billion test results, as well as connectivity with nearly 600 EHR platforms and half the physicians and hospitals in the U.S. Our origin story, unlike some in HIT, started within healthcare, and we believe that puts us in a unique position to drive meaningful change.

[CW]Very cool! By-the-way, when I was an EHR CMIO/Junior Programmer, I cut my teeth on building our very first lab interface to Quest. I have fond memories of how smoothly that went! (Great workflow!)

2. Define data. Define workflow. How should they work together? What are some obstacles to doing so?

Data represents potential, but in its most common form – raw and unorganized – it can do very little. Everything on a patient’s record, from a single lab test to an HCC code, does have value, but in isolation those data points can offer limited insights. If a physician at the point of care had hours to pore over data, she’d likely discover useful trends, but the scale would still be limited. Today, there are experts tasked with mining data for trends and insights, but pulling insights and making them actionable at the point of care is still a great challenge. Harnessing big data is a big job but we believe tremendous value will be unlocked by shifting from retrospective analysis to near real-time analytics.

Workflow is what enables physicians and others at the point of care to ensure the highest quality in the most efficient manner. Critical, highly-considered steps are required for each patient visit, and deviation from this process leads to costly disruption, which can impact quality and affect outcomes. For this reason, not all technology is well-received in a healthcare setting – if it fails to consider highly structured workflows and tight interdependencies it will have limited utility, no matter how innovative it may seem.

When data-driven insights meet workflow in a stepwise fashion – inserted when and how it’s needed, meaningful actions can be taken. It’s our mission to understand how that data can be most useful and present it in a form that works for the user. If the goal is better lab utilization – right test, right patient, right time – then we will present that data in a clear and useful manner so it can inform an action, perhaps, for example, not ordering a test that has already been ordered. We can also present that data to the patient, giving them a unique view so that they can better advocate for their care. In the end, it’s about removing the primary obstacles to deriving value from data – analytics and access in near real-time and at scale.

[CW]”Synergy” is an interaction between two areas or activities to produce an effect greater than the sum of their individual effects.

3. Is it possible to have good data but bad workflow? How does Quest exploit synergies between data and workflow?

It is indeed possible to have good data and bad workflow. In fact, much of the data captured at the point of care is good; it is just not actionable. Making that data actionable involves many important steps, from combining and cleaning datasets to analytics and subsequent application to unique workflows. You cannot pay attention to some of these steps and ignore others.

What makes Quest’s approach different from others is how we apply rigor borrowed from two worlds: the healthcare setting and the IT setting. This marries data analytics and workflow in ways that accelerate adoption and utility. Whether the customer is focused on revenue cycle management, lab utilization or quality metrics, we’re able to provide an HIT-enabled report that fits within a rigid workflow that must account for myriad dependencies. There is no one-size-fits all approach because no two health plans, health systems or individual practices are alike.

QuestQuanum puts us in a unique position to connect patients, providers, payers and ACOs with actionable insights based on lab, clinical, quality, claims and other health data. This reflects a new way of thinking about Quest and our broader ability to harness insights and technology to deliver better healthcare. Our national connectivity, big data, technology and clinical expertise uniquely position us to provide the kinds of technology solutions that will improve quality, lower costs, engage patients and optimize financial performance. In effect, we are aligning data with workflow so that stakeholders across the ecosystem – from plans to patients – can tap into the value most useful to them whenever and however they need it.

[CW]I’m looking at something Quest calls “Data Diagnostics™ Quality Reports.” Specifically I am looking at the sections, “Current Status” (No Current Action Required, Action Required) and “Clinician and/or Facility” (“Contact information for the clinicians or facilities most recently involved with the specific measure for the patient”).

4. My workflow “Spidysense” is tingling! Is there a workflow angle here?

You’re correct, Data Diagnostics reports are designed to ensure that all data are actionable for physicians in the workflow, as they meet with patients. If they see “Action Required,” the physician can take that action immediately, inside the EHR, without needing to navigate to another application and log in.

In certain circumstances, a physician may need to consult with another clinician or facility, but even that step can be executed from within the EHR. Presenting the specialist’s contact information at this point in the workflow ensures that proper steps can be taken to verify recent procedures, HCC codes and other information vital to the current exchange with the patient. Once again, providing this information later in the “process” reduces the likelihood that it will have value for the existing physician/patient engagement. Providing it during the visit is transformative and supports maximizing that patient-provider encounter. For example, if a patient has been brought in as part of a population health initiative (all diabetic patients who haven’t had an A1C test in the last 3 months), Data Diagnostics will provide a list of all the open quality gaps that can now be closed during that encounter.

Data Diagnostics reports simply bring more information and insights into an existing workflow. That data, pulled from Quest’s 20 billion lab results and Inovalon’s clinical datasets representing more than 139 million unique patients and then analyzed and presented with existing claims and EHR data, are valuable. But the fact that all that data are aligned with workflows in near real time is transformative because it means that this can happen on-demand. This needn’t be a prolonged data mining exercise to prepare for each patient, but instead it brings insights to physicians at the moment of decision – when it’s needed most.

[CW]Some sterling qualities of healthcare workflow technology include: Actionability: Stuff happens automatically, or almost automatically. Transparency: While stuff is happening, you can easily see what has been accomplished versus what is not, and why. Flexibility: Workflows can be easily modified and improved.

5. Tell me about how Quest helps achieve actionability, transparency, and flexibility.

Our technology is designed for high-actionability, visibility and flexibility, so it certainly fits what you outline as the “sterling qualities” you’d like to see. We aren’t workflow technology, however; instead, we offer a technology suite that is built to turn healthcare data into insights and align with established workflows, so it will be embraced and adopted. So, I guess you could add a fourth quality: utility – people use it because it has a demonstrable impact on efficiency, performance and, most important, patient outcomes.

When you break down Quanum, you see our focus on turning data into insights that drives specific actions. Whether that’s to order or not order a test, or whether there are specific actions that could lead to increasing quality scores or more accurate diagnostic coding, we drive to engage around the action itself. The ability to see what’s happening, what you call transparency, is also built into our offering. We think of this as visibility – the ability to see more data related to the patient and have confidence that it’s updated with sufficient frequency so that it improves decision-making.

The last piece is flexibility – there must be a focus on adjusting to changing workflows as the system learns and adapts. We certainly enable that. New diagnostics tests reach the market regularly, quality metrics change and the models that govern value-based care are in constant flux. As that happens, however, our technology can adapt, making it possible to have a workflow that is always ready to insert data where it can matter most; chiefly as a single point of truth that aligns health plans, health systems, practices and clinicians around the singular goal of delivering the best care to individuals based on their needs.

[CW]I read Quest’s recent white paper, Finding a Faster Path to Value-Based Care. Data is obviously incredibly relevant to value-based care.

6. How and why is workflow also relevant to value-based care?

Value-based care is predicated on the notion that all steps in the care delivery continuum are optimized. How this happens, and with what sets of data, depends on the relationship between the health plan and the health systems and all constituents involved, from the quality manager and practice manager to the physician and his or her patient. Value-based care relies on data, but that data must be actionable and be fully aligned with how work is done – in its flow.

If data exists but cannot make its way from a quality manager to the point of care, then it’s outside the workflow and may not have an impact. Likewise, if the data used at the point of care isn’t aligned with specific goals for quality, population health or other objectives, the exercise is more about optics than real alignment for change. The only way to make an impact is to align data to specific value-based care models that can be tracked and tweaked within a feedback loop.

Our study, Finding a Faster Path to Value-based Care, produced some interesting insights, but none more so than the misalignment between plans and physicians. This doesn’t mean the objectives aren’t in sync but rather that they don’t always see the problems the same way. When that happens, the data may not address the most pressing issues and, even more importantly, the insights don’t make it to the workflow level where real impact is possible. Once we bridge this chasm, we can create alignment about what’s really happening at the point of care – what’s really happening in the workflow – and that’s when real value-based care is achievable.

[CW]This next question requires a bit of personal background; I beg your patience.

Many years ago I was an accounting student with an interest in science. A wild and crazy idea occurred to me: declare myself a premed-accounting major! But I had to do my research first. I went to the library and looked through books on health policy and health IT (not many yet, at the time). I found a chapter about integrating clinical and financial information systems. It was like wandering in the wilderness and finding a compass. Of course! Clinical systems generate benefit. Financial systems calculate cost (among other things). The only way to maximize healthcare’s benefit/cost ratio (AKA “value”) is to integrate clinical and financial systems (including payer systems).

7. Given that Quest’s Data Diagnostics faces both providers and health plans, what is Quest’s vision for integrating and optimizing health information to maximize healthcare value?

Data Diagnostics and the entire Quanum site is about integrating and optimizing health information to drive value for patients. Your idea to combine pre-med and accounting wasn’t that crazy after all. You were just ahead of your time. At a basic level, value-based care is the logical marriage of clinical systems with financial accountability, including all the complexities involved with risk, reimbursement and other changing policies. Our partnerships and technologies are designed to bring data into that complex equation, not to the benefit or advantage of one party, but in a way that aligns all parties around common goals.

Take Data Diagnostics. Harvard Pilgrim considers the solution a benefit to its members, as they believe it will result over time in lower premiums for better care, but the benefit also accrues to physicians by lifting the burden of adhering to multiple, complex quality requirements. Likewise, it helps practice managers who own quality scoring and risk management adherence. The idea is that one large and expanding set of data, informed by powerful patient-specific analytics, can mutually benefit many across the ecosystem, engaging everyone in the common pursuit of higher value without a disproportionate amount of effort falling to one player – it’s the data and analytics that do the heavy lifting in near real-time.

[CW]Quest started as a clinical laboratory and reporting company. Lab results represent a large majority of patient healthcare information. They significantly influence clinical decision making. Lab results were among the first examples of successful healthcare interoperability. (Our Quest interface was our first EHR interface to a remote clinical data source.) One could argue clinical laboratory reporting is a natural place to pivot from toward more comprehensive sharing of clinical information among those who need access.

8. I’m interested in your thoughts on the evolution of healthcare interoperability and workflow integration in healthcare.

Quest recognized some time ago that surviving and thriving in a heterogeneous healthcare IT landscape required a sustained investment in interoperability. Lab data fills a unique role in healthcare as it provides a common quantitative framework for assessing a patient’s health status, which is why it’s ubiquitously used in diagnostic decision making. To facilitate that universal ability to order lab tests and receive test results from any provider’s information system, Quest has systematically created bi-directional interfaces to the point where we can receive test orders and return results from more than 650 EHRs, reaching more than half of the physicians and hospitals in the U.S. This is an enormously powerful pipeline where actionable information can be requested and received, within the workflow, in near real time.

Interoperability is mistakenly seen as a technology objective alone. The opportunity is much greater, however; value-based care depends on actionability, visibility and flexibility, as you pointed out in an earlier question. This means that it’s not simply about putting data into larger lakes for analysis, but also tailoring that information to drive engagement at and across all levels. And not just inside a hospital, but across health plans, health systems and practices. Data are a driver, and we can help with that, but the real change comes when workflows begin to adapt and show some semblance of interoperability.

Solutions like Data Diagnostics aren’t just focused on performance across a single health plan or health system, but instead as a more system-wide driver of value alignment. Yes, this is a much larger vision, but if access is the missing piece for many across the larger ecosystem, anything we can do to foster greater interoperability beyond clinical laboratory reporting is worth our collective energy and investment.

[CW]As you know, I track emerging workflow technologies everywhere in (and outside of) healthcare. Over the years, I’ve watched report generation systems evolve into report workflow management systems. Further, reports are less-and-less about mere reporting and more-and-more about enabling users to easily trigger actions based on, and even from within, interactive reports.

9. Where do you see Quest’s Data Diagnostics in an evolution from data toward workflow?

I hope I’ve made my point that Quest is focused on enabling users across the healthcare ecosystem to more effectively meet objectives for value-based care. In this sense, we see our role as much more than report generation or workflow management. There are systems that focus solely on that, but we’re not one of them.

QuestQuanum isn’t about an evolution from data to workflow, but instead about make data more actionable and ensuring it aligns with established workflows. Until recently, data was stuck in silos and, even when liberated from those silos, it wasn’t made actionable and directed at known issues that prevented us from crossing the value-based care tipping point. This is particularly true because there is a fundamental difference in providing retrospective data as opposed to providing predictive analytics – allowing providers to receive information that is actionable before a gap in care develops, for instance. Data Diagnostics is unique because it sets out to do just that.

While Data Diagnostics reports don’t provide diagnoses, and are not intended to second-guess or verify a clinical diagnosis, they do help health plans, health systems, clinicians and others across the ecosystem collaborate to manage the transition to value-based care and population health models (specifically those serving Medicare Advantage, managed Medicaid or commercial Qualified Health Plan patients). It’s not about compliance or checking boxes, but instead about meaningful changes that connect actions at the point of care with priorities that even transcend those of a single provider, system or payer. As a healthcare provider for decades, we’re proud to play a role in turning insights generated from data into actions that can be applied across workflows. By doing this, we can improve patient outcomes and clearly demonstrate the value we all deliver each day.

[CW]I think you have likely gathered I’m a workflow geek. Around seven years ago I set out to systematically use social media to connect with other workflow geeks. Most of the folks who follow me (11,300+, https://twitter.com/wareFLO) have more than an average interest in healthcare workflow and using health IT to improve that workflow. We’re very inclusive. We continually popularize workflow thinking and aim to grow our club.

10. Imagine you are the keynote speaker at our first Healthcare Workflow Conference. What would be the opening lines of your keynote address?

Each of you sits at the center of the most complex and costly system every developed: modern healthcare. You are part of a set of shifting interdependencies upon which lives literally depend. To make truly fundamental advances in the cost and quality of healthcare, insights will need to move from outside of the workflow to within workflows. This means that the what, how and when of healthcare analytics has to evolve.

[CW]Thank you David! I love talking about healthcare workflow and how health IT can truly improve it. I can tell you do too!

11. Where can folks attending HIMSS17 find out more about Quest’s healthcare data-driven workflow strategy. Any relevant events to attend?

Quest Diagnostics is hosting a lunch-and-learn panel at HIMSS titled, “Extending EMR Value—Technologies for Making Data More Actionable.” Our panelists, Lidia Fonseca, Quest’s Senior Vice President and CIO, and Kenneth Mandl, MD, MPH, Harvard Medical School & Boston Children’s Hospital, Chair SMART Advisory Committee, will share best practices for using data to drive decisions that improve financial performance and patient outcomes. The panel will also explore health IT solutions that extend EMR value, why they’re important and which investments to make now. The lunch-and-learn is Monday, Feb. 20th at 1pm in Room 203C. Attendees can also visit Quest at Booth #4451 to learn more about our HIT initiatives.

Have a great HIMSS17!

I will! Thank you for answering all of my geeky healthcare data/workflow questions so well!

Wonderful Video Chat About Microservices in Healthcare, With Real Code Examples!

[This post is part of a series I am writing as a HIMSS17 Social Media Ambassador (four years in a row!) in the run up to HIMSS17, in Orlando, February 19-23. Stop by and meet me at the first ever HIMSS Makerspace, booth 7785 in the Innovation Zone!]

Youtube Archive of Firetalk Event

Learn about microservices in healthcare from the co-developer of the first programming language specifically for creating microservices, @JolieLang! A recent Firetalk (19 viewers, 71 messages) got into actual programming code! For general background about microservices in healthcare, read my From APIs to Microservices: Workflow Orchestration and Choreography Across Healthcare Organizations. There’s also an excellent 5-minute Youtube explanation of microservices. You’ll see the obvious connection from microservices to workflow and workflow tech, since a microservices are like tasks in workflow management system. They need to be orchestrated to create complete workflows. Furthermore, since Jolie microservices are intrinsically distributed, as soon as you write them, one can imagine building health IT applications with workflows orchestrated across multiple health IT organizational silos. I’d love to network with anyone I can interest in Jolie at HIMSS17. You can contact me through my Twitter account @wareFLO or this blog’s Contact Me page.

The code Claudio Guidi refers to was written by Balint Maschio. It’s a toy, but executable, program illustrating how microservices written in Jolie might serve medical images. Claudio spent about twenty minutes discussing the Balint’s code, most of the time in the orchestrator service file named server.ol. Claudio is very good about systematically referring to line numbers in the Jolie code. When he does so, just scroll down to inspect the code while continuing to listen to Claudio. Server.ol refers to other services, which you can get to via the Github link. He briefly discusses OrchestratorInterface.iol, so I’ve appended that code below as well.




For my own experiments writing Jolie microservices, see the postscript to my more general post about microservices in healthcare.

See you at HIMSS17! By the way, I have my own booth this year. I’m running the first makerspace at a HIMSS conference. It’s Booth 7785 in the Innovation Zone.

@wareFLO On Periscope!