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#HIMSS16: Some Questions I Plan To Ask

Posted on February 1, 2016 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

As most readers know, health IT’s biggest annual event is just around the corner, and the interwebz are heating up with discussions about what #HIMSS16 will bring. The show, which will take place in Las Vegas from February 29 to March 4, offers a ludicrously rich opportunity to learn about new HIT developments — and to mingle with more than 40,000 of the industry’s best and brightest (You may want to check out the session Healthcare Scene is taking part in and the New Media Meetup).

While you can learn virtually anything healthcare IT related at HIMSS, it helps to have an idea of what you want to take away from the big event. In that spirit, I’d like to offer some questions that I plan to ask, as follows:

  • How do you plan to support the shift to value-based healthcare over the next 12 months? The move to value-based payment is inevitable now, be it via ACOs or Medicare incentive programs under the Medicare Access and CHIP Reauthorization Act. But succeeding with value-based payment is no easy task. And one of the biggest challenges is building a health IT infrastructure that supports data use to manage the cost of care. So how do health systems and practices plan to meet this technical challenge, and what vendor solutions are they considering? And how do key vendors — especially those providing widely-used EMRs — expect to help?
  • What factors are you considering when you upgrade your EMR? Signs increasingly suggest that this may be the year of the forklift upgrade for many hospitals and health systems. Those that have already invested in massiveware EMRs like Cerner and Epic may be set, but others are ripping out their existing systems (notably McKesson). While in previous years the obvious blue-chip choice was Epic, it seems that some health systems are going with other big-iron vendors based on factors like usability and lower long-term cost of ownership. So, given these trends, how are health systems’ HIT buying decisions shaping up this year, and why?
  • How much progress can we realistically expect to make with leveraging population health technology over the next 12 months? I’m sure that when I travel the exhibit hall at HIMSS16, vendor banners will be peppered with references to their population health tools. In the past, when I’ve asked concrete questions about how they could actually impact population health management, vendor reps got vague quickly. Health system leaders, for their part, generally admit that PHM is still more a goal than a concrete plan.  My question: Is there likely to be any measurable progress in leveraging population health tech this year? If so, what can be done, and how will it help?
  • How much impact will mobile health have on health organizations this year? Mobile health is at a fascinating moment in its evolution. Most health systems are experimenting with rolling out their own apps, and some are working to integrate those apps with their enterprise infrastructure. But to date, it seems that few (if any) mobile health efforts have made a real impact on key areas like management of chronic conditions, wellness promotion and clinical quality improvement. Will 2016 be the year mobile health begins to deliver large-scale, tangible health results? If so, what do vendors and health leaders see as the most promising mHealth models?

Of course, these questions reflect my interests and prejudices. What are some of the questions that you hope to answer when you go to Vegas?

Is Cerner Edging Up On Epic?

Posted on January 7, 2016 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

At Verona, Wisc.-based Epic Systems, growth is a way of life. In fact, the EMR vendor now boasts a workforce of 9,400, which is estimated to be an increase of 1,400 staffers over the past year.

Not only that, Epic is confident enough to build cute. Its Campus 4, dubbed the “Wizards Academy Campus,” is designed to resemble the fictional Hogwarts school of Harry Potter fame — or if you’re academically-minded, England’s Oxford University. When completed this summer, Campus 4 will add 1,508 offices and 2,000 parking spaces to the Epic headquarters.

I could go on with details of the Disneyland Epic is making of its HQ, but you get the picture. Epic leaders are confident that they’re only going to expand their business, and they want to make sure the endless streams of young eggheads they recruit are impressed when they visit. My guess is that the Epic campus is being designed as a, well, campus speaks to the idea of seeing the company as a home. When I was 25, unique surroundings would have worked on me!

In any event, if I was running the place, I’d be pretty confident too. After all, if its own stats are correct, Epic software is either being used by or installed at 360 healthcare organizations in 10 countries. The EMR giant also reports that its platform manages records for 180 million Americans, or about 55 percent of the entire U.S. population. It also reported generating a not-so-shabby $1.8 billion in revenues for 2014.

But a little-noticed report issued by analyst firm KLAS last year raises questions as to whether the Epic steamroller can maintain its momentum. According to the report, which admittedly came out about a year ago, “the competition between Epic and Cerner is closer than it has been in years past as customers determine their future purchasing plans,” analysts wrote.

According to KLAS researchers, potential EMR buyers are largely legacy customers deciding how to upgrade. These potential customers are giving both Cerner and Epic a serous look, with the remainder split between Meditech and McKesson upgrades.

The KLAS summary doesn’t spell out exactly why researchers believe hospital leaders are beginning to take Cerner as seriously as Epic, but some common sense possibilities occur to me:

The price:  I’m not suggesting that Cerner comes cheap, but it’s become clear over the years that even very solvent institutions are struggling to pay for Epic technology. For example, when traditionally flush-with-cash Brigham and Women’s Hospital undershoots its expected surplus by $53 million due (at least in part) to its Epic install, it’s gotta mean something.

Budget overruns: More often than not, it seems that Epic rollouts end up costing a great deal more than expected. For example, when New York City-based Health and Hospital Corp. signed up to implement Epic in 2013, the deal weighed in at $302 million. Since then, the budget has climbed to $764 million, and overall costs could hit $1.4 billion. If I were still on the fence I’d find numbers like those more than a little concerning. And they’re far from unique.

Scarce specialists:  By the company’s own design, Epic specialists are hard to find. (Getting Epic certified seems to take an act of Congress.) It must be quite nerve-wracking to cut a deal with Epic knowing that Epic itself calls the shots on getting qualified help. No doubt this contributes to the high cost of Epic as well.

Despite its control of the U.S. market, Epic seems pretty sure that it has nowhere to go but up. But that’s what Microsoft thought before Google took hold. If that comparison bears any weight, the company that will lap up Epic’s business and reverse its hold on the U.S. market probably already exists. It may not be Cerner, but Epic will face meaningful competition sometime soon.

Uncovering Hidden Hospital Resources: Hospital IQ Shows that the First Resource is Data

Posted on January 4, 2016 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://radar.oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

We’ve become accustomed to the results that data mining have produced in fields ranging from retail to archeology to climate change. According to Rich Krueger, CEO of HospitalIQ, the health care industry is also ripe with data that could be doing a lot more for strategic operations and care.

Many companies (perhaps even too many) already offer analytics for grouping patients into risk pools and predicting the most unwanted events, such as readmissions within 30 days of a hospital discharge. According to Krueger, Hospital IQ is the first company offering analytics to improve operations. From a policy standpoint, the service has three benefits:

  • Improving operations can significantly lower the cost of providing health care, and the savings can be passed on to payers and consumers.
  • Better operational efficiency means better outcomes. For instance, if the ER is staffed properly and the hospital has enough staff resources to meet each patient’s needs, they will get the right treatment faster. This means patients will recover sooner and spend less time in the hospital.
  • Hospital IQ’s service is an intriguing example of the creative use of clinical data, inspiring further exploration of data analysis in health care.

One of the essential problems addressed by Hospital IQ is unexpected peaks in demand, which strains emergency rooms, ICUs and inpatient units, and ultimately can contribute to poor patient outcomes. The mirror images of this problem are unexpected troughs in usage, where staff is underutilized and costing the healthcare system.

“There’s no reason for surprise,” says Krueger. While it is difficult to predict demand for any given day, it is possible to forecast upper and lower boundaries for demand in a given week. Hospital staff often have an intuitive sense of this. Krueger says with his software, they can mine clinical data to make these forecasts based on actual live data.

There are firms who make sensors that can tell you when a bed is occupied, when someone has come to clean the room or visit a patient, and so forth. The interesting thing about Hospital IQ is that it does its work without needing to install any special equipment or IT builds. Its inputs are the everyday bits of data that every hospital already collects and stores in their electronic record systems: when someone enters the ED, when they are seen, where they are transferred, when surgery started and ended. The more at-risk patients in telemetry beds generate information that is also used for analytics.

Hospital IQ uses mature business analytics tools such as queuing theory that have been popularized for decades since the age of W. Edwards Deming. Even though EHRs differ, Krueger has discovered that it’s not hard to retrieve the necessary data from them. “You tell us where the data is and we’ll get it.”

The service also provides dashboards designed for different types of staff, and tools for data analysis. For instance, a manager can quickly see how often patients are sent to the ICU not because they need ICU care but because all other beds are full. While this doesn’t compromise patient safety, it’s an unnecessary cost and also reduces patient satisfaction because ICUs generally have a more restricted visiting policy. This situation becomes more problematic when a patient arrives through the ED with a real need for an ICU bed and the unit is full (Figure 1). Hospitals can look at trends over time to optimize staffing and even out the load by scheduling elective interventions at non-peak times. There’s a potentially tremendous impact on patient safety, length of stay, and mortality.

solutions-patient-safety-and-quality
Figure 1: Chart showing placements into the ICU. “Misplaced here” are patients that don’t belong in the ICU, whereas “Misplaced elsewhere” are patients that should have gone to the ICU but were sent somewhere else such as the PACU.

Taken to another level of sophistication, analytics can be used for long-term planning. For instance, if you are increasing access to a service, hospitals can forecast the additional number of beds, operating rooms, and staff the service will need based on historic demand and projected growth.. Hospitals can set a policy such as a maximum wait of three hours for a bed and see the resources necessary to meet that goal. Figure 2 shows an example of a graph being tweaked to look at different possible futures.

solutions-capacity-planning
Figure 2: Simulation using historical demand data showing the relationship between bed counts and average wait time for a patient to get a bed.

Hospital IQ is a fairly young company whose customers cover a wide range of hospitals: from safety net hospitals to academic institutions, large and small. It also works across large systems with multiple institutions, aiding in such tasks as consolidating multiple hospitals’ services into one hospital.

My hope for Hospital IQ is that it will open up its system with an API that allows hospitals and third parties to design new services. It seems to offer new insights that were hidden before, and we can only guess where other contributors can take it as well.

Time For A Health Tracking Car?

Posted on December 30, 2015 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

Several years ago, I attended a conference on advanced health technologies in DC. One of the speakers was Dr. Jay Sanders, president and CEO of The Global Telemedicine Group. And he had some intriguing things to say — especially given that no one had heard of a healthcare app yet and connected health was barely a vision.

One of Dr. Sanders’ recommendations was that automobile seat belts should integrate sensors that tracked your heart rhythm. After all, he noted, many of us spend hours a day behind the wheel, often under stressful conditions — so why not see how your heart is doing along the way? After all, some dangerous arrhythmias don’t show up at the moment you’re getting a checkup.

Flash forward to late 2015, and it seems Dr. Sanders’ ideas are finally being taken seriously. In fact, Ford Motor Co. and the Henry Ford Health System are co-sponsoring a contest offering $10,000 in prize money to employees creating smartphone apps linking healthcare with vehicles. While this doesn’t (necessarily) call for sensors to be embedded in seat belts, who knows what employees will propose?

To inspire potential entrants, the Connected Health Challenge sponsors have suggested a few ideas for possible designs, including in-vehicle monitoring and warnings and records access from the road. Other suggestions included appointment check-ins and technology allowing health data to be transmitted to providers. The contest kicks off on January 20th.

In some ways, this isn’t a huge surprise. After all, connected vehicles are already a very hot sector in the automotive business. According to research firm Parks Associates, there will be 41 million active Internet connections in U.S. vehicles by the end of this year.

At present, according to Parks, the connect car applications consumers are most interested in include mapping/navigation, information about vehicle performance, Bluetooth technology and remote control of vehicles using mobile phones. But that could change quickly if someone finds a way to interest the well-off users of wearables in car-based health tracking. (A possible direction for Fitbit, perhaps?)

Ordinarily, I’d have some doubts about Henry Ford Health System employees’ ability to grasp this market. But as I’ve reported elsewhere on Healthcare Scene, Henry Ford takes employee innovation very seriously.

For example, last year HFHS awarded a total of $10,000 in prizes to employees who submitted the best ideas for clinical applications of wearable technology. Not only that, the health system offers employees a 50% share of future revenues generated by their product ideas which reach the marketplace.

Now, it’s probably worth bearing in mind that the wearables industry is far more mature than the market for connected health apps in automobiles. (In fact, as far as I can tell, it’s still effectively zero.) Employees who participate in the challenge will be swinging at a far less-defined target, with less chance of seeing their ideas be adopted by the automotive industry.

Still, it’s interesting to see Ford Motor Co. and HFHS team up on this effort. I think something intriguing will come of it.

FDA Limitations Could Endanger Growth Of mHealth

Posted on December 28, 2015 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

mHealth technology has virtually unlimited potential. But until the FDA begins putting its stamp of approval on mHealth tools, many providers won’t take them seriously. And that could be a big problem for mHealth’s future.

Unfortunately, early signs seem to suggest that the FDA is in over its head when it comes to regulating mHealth. According to speakers at a recent FDA Law Institute conference, it could be years before the agency even has a solid idea of how to proceed, Bloomberg reports.

Jeffrey Shapiro, a member of the Washington, D.C. law firm of Hyman Phelps & McNamara P.C., told the conference the FDA just isn’t equipped to handle the flood of new mHealth approaches. “Experience has shown that the FDA’s almost 40-year-old regulatory framework is a bad fit for much of today’s health IT with its networked ecosystems, rapid iterative improvement, deep collaboration between providers and end-users and focus on clinical decision support rather than direct diagnosis or treatment,” he told the audience.

The FDA dismisses the notion that it’s not prepared to regulate mHealth technologies. Bakul Patel, the agency’s associate director for digital health, told Reuters that the agency is planning to fill three new senior health scientist positions focused on digital health soon. That’s an encouraging step, though given that there are more than 165,000 health apps on the market, probably an inadequate one.

Sure, few of those app developers will apply for FDA approval. And the agency only plans to demand approval for technologies that are designed to be used as an accessory to a regulated medical devices, or transform a mobile platform into a regulated medical device. mHealth devices it has already approved include Airstrip Remote Patient Monitoring, the AliveCor Heart Monitor for iPhone and McKesson Cardiology’s ECG Mobile.

On the other hand, if Shapiro is right, the FDA could become a bottleneck which could severely stunt the growth of the U.S. mHealth industry. If nothing else, mHealth developers who seek FDA approval could be faced with a particularly prolonged approval process. While vendors wait for approval, they can keep innovating, but if their proposed blockbuster product is in limbo, it won’t be easy for them to stay solvent.

Not only that, if the FDA doesn’t have the institutional experience to reasonably evaluate such technologies, the calls it makes as to what is safe and efficacious may be off base. After all, apps and remote monitoring tools don’t bear much resemblance to traditional medical devices.

In theory, upstart mHealth companies which don’t have the resources to go through the FDA approval process can just proceed with their rollout. After all, the agency’s guidelines for requiring its approval are reasonably narrow.

But in reality, it seems unlikely that providers will adopt mHealth devices and apps wholesale until they get the FDA stamp of approval.  Whether they geniunely consider non-approved devices to be too lightweight for use, or fear being sued for using questionable technology, providers seem unlikely to integrate mHealth technology into their daily practice without the agency’s green light.

Given these concerns, we’d best hope that the FDA doesn’t begin requiring its approval for EMRs. Or at the very least, we should be glad that it didn’t jump in early. Who knows where EMR infrastructure would be if vendors had had to play patty-cake with the FDA from day one?

How Much Patient Data Do We Truly Need?

Posted on November 23, 2015 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

As the demands placed on healthcare data increase, the drive to manage it effectively has of course grown as well. This has led to the collection of mammoth quantities of data — one trade group estimates that U.S. hospitals will manage 665 terabytes of data during 2015 alone — but not necessarily better information.

The assumption that we need to capture most, if not all, of a patient’s care history digitally is clearly driving this data accumulation process. As care moves into the digital realm, the volume of data generated by the healthcare industry is climbing 48% percent per year, according to one estimate. I can only assume that the rate of increase will grow as providers incorporate data feeds from mHealth apps, remote monitoring devices and wearables, the integration of which is not far in the future.

The thing is, most of the healthcare big data discussions I’ve followed assume that providers must manage, winnow and leverage all of this data. Few, if any, influencers seem to be considering the possibility that we need to set limits on what we manage, much less developing criteria for screening out needless data points.

As we all know, all data is not made equal.  One conversation I had with a physician in the back in the early 1990s makes the point perfectly. At the time, I asked him whether he felt it would be helpful to put a patient’s entire medical history online someday, a distant but still imaginable possibility at the time. “I don’t know what we should keep,” he said. “But I know I don’t need to know what a patient’s temperature was 20 years ago.”

On the other hand, providers may not have access to all of the data they need either. According to research by EMC, while healthcare organizations typically import 3 years of legacy data into a new EMR, many other pertinent records are not available. Given the persistence of paper, poor integration of clinical systems and other challenges, only 25% of relevant data may be readily available, the vendor reports.

Because this problem (arguably) gets too little attention, providers grappling with it are being forced to to set their own standards. Should hospitals and clinics expand that three years of legacy data integration to five years? 10 years? The patient’s entire lifetime? And how should institutions make such a decision? To my knowledge, there’s still no clear-cut way to make such decisions.

But developing best practices for data integration is critical. Given the costs of managing needless patient data — which may include sub-optimal outcomes due to data fog — it’s critical to develop some guidelines for setting limits on clinical data accumulation. While failing to collect relevant patient data has consequences, turning big data into astronomically big data does as well.

By all means, let’s keep our eye on how to leverage new patient-centric data sources like wearable health  trackers. It seems clear that such data has a role in stepping up patient care, at least once we understand what part of it is wheat and which part chaff.

That being said, continuing to amass data at exponential rates is unsustainable and ultimately, harmful. Sometimes, setting limits is the only way that you can be sure that what remains is valuable.

Connected Health Conference Tops Itself–But How Broad is Adoption? Part 1 of 3

Posted on November 5, 2015 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://radar.oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

Along the teeming circuit of health care conferences that Boston enjoys year-round, a special place is occupied by the Connected Health Conference sponsored by Massachusetts giant Partners HealthCare. For 12 years this conference, shepherded by the spirited Joseph Kvedar, has shown Boston and the rest of the world what can be accomplished by the integration of data, technology, and clinical empathy.

But people I talked to at the conference were asking: where’s change visible in the health care field? Why aren’t we seeing these great things adopted throughout the country to support value-based care? The much-vaunted Accountable Care Organization model is failing to thrive, interoperability continues to elude medical sites, and consequently, health care costs are “eating” American’s incomes.

The way forward may have been shown by the two final keynotes of the conference, delivered by executives at Massachusetts General Hospital (one of the central institutions in Partners HealthCare and a destination for patients around the world).

Chief Clinical Officer Gregg Meyer referred to “punctuated evolution” to suggest that the health care field is at an “inflection point” where change is starting to happen fast. What makes this change hard is that two major initiatives separate most health care institutions from the fee-for-value world we want. One initiative focuses on organizational change and payment regimes, whereas the other involves wrenching changes to technology that track, record, and analyze what doctors and patients are doing.

I believe the reason many ACOs and other fee-for-value systems are failing (or at least not showing cost improvements) is that they took on the organizational change before they were ready with the technological parts. According to Meyer, Massachusetts General Hospital took on the technological change first, years before a payment system was offered that reimburses them for it.

Many speakers at the conference pointed to recent payment changes, such as Medicare Advantage, that promote fee-for-value. Programs along those lines in Massachusetts have shown modest headway against costs.

Even so, MGH has made only some early steps in health IT. Some doctors allow virtual visits, but it’s not done strategically and most providers don’t understand that such visits could reduce their workloads in the long run. Chief Health Information Officer O’Neil Britton said that the Epic EHR they installed still can’t accept streaming data. But he vaunted MGH’s growing use of genomics, wearables, video information delivery, and telehealth. The use of video was praised frequently at the conference for bringing information to people when they need it and reducing office visits that are costly and inconvenient for everyone.

The next section of this article will contrast techno-optimists with techno-skeptics and mention some advances reported at the conference.

I Have Seen The Portal, And It Is Handy

Posted on July 14, 2015 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

After writing about EMRs/EHRs and portals for many years, I’ve finally begun using an enterprise-class portal to guide my own care. Here’s some of my impressions as an “inside” (EMR researcher) and “outside” (not employed as a provider) user of this tool. My conclusion is that it’s pretty handy, though it’s still rather difficult to leverage what I’ve learned despite being relatively sophisticated.

First, some background. I get most of my care from northern Virginia-based Inova Health System, including inpatient, primary care, imaging and specialist care. Inova has invested in a honking Epic installation which links the majority of these sites together (though I’ve been informed that its imaging facilities still aren’t hooked up to core medical record. D’oh!) After my last visit with an Inova doctor, I decided to register and use its Epic portal.

Epic’s MyChart has a robust, seemingly quite secure process for registering and accessing information, requiring the use of a long alphanumeric code along with unique personal data to establish an account. When I had trouble reading the code and couldn’t register, telephone-based tech support solved the problem quickly.  (Getting nearsighted as I move from middle- to old-aged!)

Using MyChart, I found it easy to access lab results, my drug list and an overview of health issues. In a plus for both me and the health system, it also includes access to a more organized record of charges and balances due than I’ve been able to put together in many years.

When I looked into extracting and sharing the records, I found myself connected to Lucy, an Epic PHR module. In case you’ve never heard of it (I hadn’t) here’s Epic’s description:

Lucy is a PHR that is not connected to any facility’s electronic medical record system. It stays with patients wherever they receive care and allows them to organize their medical information in one place that is readily accessible. Patients can enter health data directly into Lucy, pull in MyChart data or upload standards-compliant Continuity of Care Documents from other facilities.

As great as the possibility of integrating outside records sounds, that’s where I ran into my first snag. When I attempted to hook up with the portal for DC-based Sibley Memorial Hospital — a Johns Hopkins facility — and integrate the records from its Epic system into the Inova’s Lucy PHR, I was unable to do so since I hadn’t connected within 48 hours of a recent discharge. When I tried to remedy the situation, an employee from the hospital’s Health Information Management department gave me an unhelpful kiss-off, telling me that there was no way to issue a second security code. I was told she had to speak to her office manager; I told her access to my medical record was not up for a vote, and irritated, terminated the call.

Another snag came when I tried to respond to information I’d found in my chart summary. When I noted that one of my tests fell outside the standard range provided by the lab, I called the medical group to ask why I’d been told all tests were normal. After a long wait, I was put on the line with a physician who knew nothing about my case and promptly brushed off my concerns. I appreciate that the group found somebody to talk to me, but if I wasn’t a persistent lady, I’d be reluctant to speak up in the future given this level of disinterest.

All told, using the portal is a big step up from my previous experiences interacting with my providers, and I know it will be empowering for someone like myself. That being said, it seems clear that even in this day and age, even a sophisticated integrated health system isn’t geared to respond to the questions patients may have about their data.

For one thing, even if the Lucy portal delivers as promised, it’s clear that integrating data from varied institutions isn’t a task for the faint of heart. HIM departments still seem to house many staffers who are trained to be clerks, not supporters of digital health. That will have to change.

Also, hospitals and medical practices must train employees to enthusiastically, cheerfully support patients who want to leverage their health record data. They may also want to create a central call center, staffed by clinicians, to engage with patients who are raising questions related to their health data. Otherwise, it seems unlikely that they’ll bother to use it.

Adapting Hospital Records to the Needs of Transgender People

Posted on July 13, 2015 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://radar.oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

More than just about any other institution, hospitals and clinics have to deal with the unexpected. People with the most unusual characteristics and problems drop in all the time. But electronic records, being formal documentation, like regularity. The clash between diversity and computerization explodes into view when a transgender or gender-queer person walks in.

I have written about the strains that transgender people put on an EHR earlier as part of my family’s encounter with the medical system. Recently I got a chance to talk with a leader who has taken some of the necessary steps to fix systems: Scott MacDonald, MD, working in the health system of University of California at Davis.

A thrust to improve UC Davis’s handling of LGBT clients preceded Dr. MacDonald’s arrival. A group of staff and clinicians interested in providing better care to LGBT people decided to take steps to address the needs in that area. The institution made an ethical commitment to reducing disparities in care. The group recognized that the information in the record was deficient–they often didn’t even know who identified as LGBT.

The first step in this information gathering is training health providers to ask for the information in ways that are sensitive to patients’ feelings, and to become comfortable with it. The next step is deciding what to do with that information, and the third is figuring out how to store it in a structured way.

As MacDonald says, “The first priority is to train providers to understand why this data collection is important, explaining that they cannot care for a person whose life situation they don’t understand. Research (especially for reducing disparities) is a close second priority. An electronic means to capture the data needs to be created along with these efforts. Once the data is available in a formal, structured way, we can encourage and train clinicians to ask the pertinent questions and respond to the information sensitively.”

When MacDonald joined the organization, he brought technical expertise with working on disparities in ethnicity and language. He started two surveys: one of the patient population and another of the staff.

The patient survey showed that for the most part, patients were glad to be asked about their sexual orientation (which is different from sexual behavior, although related). They were particularly open to the question if their primary care provider was the one holding the discussion. Naturally, some expressed privacy concerns and wondered who might have access to the information once it was recorded.

Health care providers also showed a willingness to learn more about LGBT issues and be listed in the UC Davis registry as an LGBT-welcoming provider. Over time, without an explicit mandate from leadership, the information collected on the sexual preference of patients increased. UC Davis also provided resources for training in LGBT issues via a web site.

Before starting, UC Davis interviewed the clients of a local clinic specializing in gender issues, in order to flesh out their understanding of patient needs and sensitivities.

Now we get to the heart of the IT issues. Any record system used by a health care institution needs at least the following to handle transgender and gender non-conforming patients:

  • A way to list their preferred name and gender, along with the name and gender that appear on their insurance cards and other official documents. Transitions can take years, and patients often have insurance with the old name and gender long after they have made the determination to be known in a new way. Gender can also be a fluid and evolving concept for some patients.

  • Ways to record the factors that affect gender, such as what surgeries they have had for gender dysphoria and what hormones they are taking. Someone who identifies as male may still need to have a regular Pap smear. A male-to-female transgender person may have a very different normal range on a blood test from someone born female (cis-female).

UC Davis had licensed an Epic EHR, but at that time Epic had only a few suggestions to offer. For instance, they suggested adding a special flag for transgender patients, but this would be too limited a way of handling the range of gender issues encountered, and would not provide adequate clinical information. UC Davis thus launched into a series of customizations, which Epic in turn compiled into an implementation guide that has been used by other customers.

The goal at UC Davis was to make it easy for patients to enter data at in the privacy of their homes through Epic’s patient portal. The interviews at the partner clinic had showed that many were comfortable providing information this way that many were comfortable providing information this way. Besides asking for assigned sex at birth, click-buttons in the portal’s web page offer common choices for current gender identity and sexual orientation. The patient could also enter free-text comments if the predefined choices didn’t capture their identity.

The same information could be entered by clinicians as well. People viewing the record could not tell whether the gender information was entered by a clinician or directly by the patient (although on the back-end, the system preserves the provenance of the information). MacDonald said that the source of the information was ultimately the patient, so it doesn’t really matter who entered it.

What’s important is that the gender-related information, formerly stuffed into free-form text somewhere in the record, was now stored in a structured format. This allows UC Davis to fulfill its mandate to track how it is addressing disparities in care. In the future, such information may also feed into clinical decision support tools.

The gender information is not displayed prominently, but is available to all staff who have access to patient records and seek it our for purposes of patientcare. It is protected by the usual information security measures in place at UC Davis. The information is of greatest use to the primary care provider, but is also used by in-patient nurses and special departments dealing with transgender issues.

The patient’s preferred name was easier to handle. Epic already allows records to distinguish between the official name–used for legal and insurance purposes–and the preferred name. The record offers several descriptors that explain what the preferred name is, such as a nickname or alias. To this list of descriptors, UC Davis added an option applicable to transgender patients.

The remaining missing information is the status of a patient during and after transition. A record can’t yet record birth sex in a separate field from gender identity. It can capture sex as cis-male or trans-man, but that doesn’t gracefully account for the combinatorics of birth sex, gender identity, legal sex, and so on. Transition-specific surgeries and hormone therapy can be captured as a part of surgical history and the medication list, but there is no standard way to record organ inventory. Those things are still listed in free-form text.

However, Epic is looking at ways to adapt its software at the deep level to show this diversity of status. This is something all vendors need to do, because more and more people of all ages are identifying as transgender or non-conformaing as the public gets used to the idea that this kind of identity is within the range of normal. The needs of the population are complex and urgent, so the faster we fix the records, the better will be the care we provide.

Providers Still Have Hope For HIEs

Posted on July 10, 2015 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

Sometimes, interoperability alone doesn’t cut it.  Increasingly, providers are expecting HIEs to go beyond linking up different organizations to delivering “actionable” data, according to a new report from NORC at the University of Chicago. The intriguing follow-on to the researchers’ conclusions is that HIEs aren’t obsolete, though their obsolescence seemed all but certain in the past.

The study, which was written up by Healthcare Informatics, conducted a series of site visits and 37 discussions with providers in Iowa, Mississippi, New Hampshire, Vermont, Utah and Wyoming. The researchers, who conducted their study in early 2014, hoped to understand how providers looked at HIEs generally and their state HIE program specifically. (The research was funded by ONC.)

One major lesson for the health IT types reading this article is that providers want data sharing models to reflect new care realities.  With Meaningful Use requirements and changes in payment models bearing down on providers, and triggering changes in how care is delivered, health IT-enabled data exchange needs to support new models of care.

According to the study, providers are intent on having HIEs deliver admission, discharge, and transfer alerts, interstate data exchange and data services that assist in coordinating care. While I don’t have comprehensive HIE services research to hand, maybe you do, readers. Are HIEs typically meeting these criteria? I doubt it, though I could be wrong.

That being said, providers seem to be willing to pay for HIE services if the vendor can meet their more stringent criteria.  While this may be tough to swallow for existing HIE technology sellers, it’s good news for the HIE model generally, as getting providers to pay for any form of community data exchange has been somewhat difficult historically.

Some of the biggest challenges in managing HIE connectivity identified by the study include getting good support from both HIE and EMR vendors, as well as a lack of internal staff qualified to manage data exchange, competing priorities and problems managing multiple funding streams. But vendors can work to overcome at least some of these problems.

As I noted previously, hospitals in particular have had many beliefs which have discouraged them from participating in HIEs. As one HIE leader quoted in my previous post noted, many have assumed that HIE connection costs would be in the same range as EMR adoption expenses; they’re been afraid that HIEs would not put strong enough data security in place to meet HIPAA obligations; and they assumed that HIE participation wasn’t that important.

Today, given the growing importance of sophisticated data management has come to the forefront, and most providers know that they need to have the big picture widespread data sharing can provide. Without the comprehensive data set cutting across the patient care environment — something few organizations are integrated enough to develop on their own — they’re unlikely to mount a successful population health management initiative or control costs sufficiently. So it’s interesting to see providers see a future for HIEs.