Healthcare providers are seeing great potential in portable and miniature devices that enable the measurement of vital health data in acute and non-acute environments.
This article appears in the July/August issue of HealthLeaders magazine.
Thanks to mobile technology, the line between acute and nonacute care is blurring, reaping benefits for providers and patients.
Using technology ranging from newly miniaturized vital signs monitors to FDA-approved portable devices for measuring asthma symptoms, providers are seeing improved outcomes today—and great potential as the mobile monitoring trend just starts up its adoption curve.
Away from the ICUs, on the regular nursing floors, patients in postacute care can benefit from portable monitors such as Sotera Wireless' ViSi Mobile, according to Lisa Graydon, chief nursing officer of five Salt Lake City–area hospitals of Intermountain Healthcare: Intermountain Medical Center, LDS Hospital, the Orthopedic Specialty Hospital, Riverton Hospital, and Alta View Hospital.
ViSi Mobile, which straps to a patient's wrist, monitors and displays ECG, heart-pulse rate, respiratory rate, blood pressure, blood oxygenation level, and skin temperature. "Those patients are much more mobile," Graydon says. "We expect them walking in the halls. If we can monitor them, their vital signs, more closely, wirelessly, or in some way not invasive to them, then we could probably provide a safer environment, and we're all about patient safety at Intermountain."
To evaluate ViSi Mobile, Graydon and nurse administrators from two of the five hospitals—the 460-bed Intermountain Medical Center and the 200-bed LDS Hospital—selected a floor in each facility with patients recovering from orthopedic surgery. To formalize its study of the device, Intermountain went through its institutional review board, Graydon says.
Out of that came a three-phase trial approach. In phase one, Intermountain nurses and patients simply wore the ViSi Mobile device during rounds. "The patients got to wear it just for a little while to see how comfortable this is," Graydon says. "We didn't monitor anything. We didn't use the data. We just wanted to see if it was comfortable, and then we took a survey to see how people felt about it."
Then, in April 2013, Intermountain began getting patients' consent to begin having them wear the devices. About 20 patients in each facility agreed to be monitored, Graydon says. At first, the number of alarms being generated by the ViSi Mobile devices due to sensitivity to vital sign changes was a nuisance. Sotera Wireless took the initial data collected, deidentified it, and ran it through a software simulator to troubleshoot the device's software to reduce the number of nuisance alarms.
Monitors in ICUs are troubling to patients, as well, so it's critical that false alarms be minimized so as not to disturb patients trying to relax or sleep. As the testing progresses, nursing staff are becoming more confident that the device is issuing alarms only when patents really need attention, Graydon says. "It's a great technology that we're just learning about," she says.
"The nursing staff is excited about this new technology that gives them more information about their patient without requiring them to do more work, or adding some sort of data collection along with it," Graydon says. "Nurses are here to take care of people, not to take care of equipment. It's a great way to keep your patients safe and know what's going on at a distance, if you will."
A benefit of using ViSi Mobile in a postorthopedic surgical setting is to monitor patients' oxygen saturation while they are being administered opioid medications for pain, because such medicine suppresses the respiratory system. Continuous mobile monitoring can spot trends in respiration or blood pressure over a 24- to 48-hour period that intermittent vital sign collection can miss, Graydon says.
In phase 3 of the trial, now in the planning stages, data from ViSi Mobile devices will flow directly into Intermountain's electronic medical records, Graydon says. "I think this type of monitoring could become a standard of care," she says.
Three categories of mobile monitoring are emerging in healthcare and wellness, according to John Mattison, MD, CMIO of Kaiser Permanente, which serves more than 9 million members and employs more than 16,000 physicians.
Mattison says the first category encompasses super-athletes and warriors. Special military forces are intensively tracking their personnel's vital signs with mobile technology in cases where the health of the soldier is vital to completing the mission. Athletes are trying to squeeze "every last erg of energy" out for highly competitive events. "In five years, it will be standard practice for even high school athletes to be wearing this stuff periodically to ensure they don't have any risk indicators for sudden death or adverse consequences," Mattison says.
Category 2 is patients recovering from a hospital discharge or serious illness, Mattison says. Category 3 is "the rest of us," where mobile devices can play a "powerful role" in the initiation and reinforcement of healthy behaviors, he says.
"As the price comes down and the data science grows, it's going to become more and more routine," Mattison says. "The problem is, we don't have a lot of data to know where the thresholds are.
"Until we calibrate all of these devices and all those streaming data for different contexts, we're going to have a lot of false alarms."
There was even a Mayo Clinic study a few years ago that found that monitored patients had higher mortality than unmonitored patients, Mattison says. "What happens when you put a monitoring device on someone who's ill and you don't give them any encouragement that this is going to help them?" asks Mattison. "They are constantly aware that they're sick. What it does is it raises anxiety levels and fear, and fear raises your cortisone or it raises your adrenaline, and both of those are known to be acute phase stress reactants. That increases your mortality. That's been known for 50 years."
The solution, Mattison says, is to convert mobile monitors from "worry devices" to "reassuring and supportive and healthy devices for that category of people."
Kaiser is about to begin testing the AliveCor, an FDA-approved case for the iPhone that lets the phone collect ECG data by resting the case's electronics on the fingers of each hand. "There's a very high percentage of people with atrial fibrillation who go for quite a period of time before it's diagnosed simply because if it's intermittent, it might not be detected at those rare moments when they're actually in a clinician's office," Mattison says. "[If] we can detect atrial fibrillation earlier, we can prevent a significant number of catastrophic events by diagnosing and anticoagulating those folks as appropriate."
The clinical need exists and efforts to develop and deliver the technology continue.
"Real-time data delivered to patients and physicians is going to be an essential component to providing 21st century care and achieving the goals of the triple aim," says Rich Roth, vice president of strategic innovation at Dignity Health, one of the nation's five largest health systems, an 18-state network of nearly 10,000 physicians and 56,000 employees with more than 300 care centers. "While it may take a few routes, and we need to make sure to address the digital divide effectively, it's hard to imagine it not being a standard of care in the next three to five years."
According to Roth, accelerating that progress will be a $1 billion Center for Medicare & Medicaid Innovation initiative announced in May 2013. CMS is seeking proposals for models that are designed to rapidly reduce Medicare, Medicaid, or Children's Health Insurance Program costs in outpatient or postacute settings.
"It's a great opportunity to improve quality and ensure that patient preference and patient choice in the postacute care realm is preserved, but that you can add in these efficiencies that allow for better care coordination," Roth says.
Dignity Health "has a very purposeful strategy" for mobility technology, working with three to five companies at any given time, Roth says. One example is AirStrip OB, which offers an app that runs on iPads and enables nurses to share heart rhythm waveforms collected by traditional ICU monitoring equipment with obstetricians who call up those waveforms in the AirStrip OB app running remotely on their iPads.
This takes the place of trying to describe the waveform over a phone call, which, Roth says, is "like describing a sunset to somebody." The AirStrip OB app instead ensures that "caregivers can make appropriate and right decisions at a very critical moment with all the information that they need to ensure the health and safety of the mother and the child," Roth says.
So far, Dignity Health has monitored 15,000 babies with the AirStrip OB app. As part of the Hospital Engagement Network, a joint effort with the Centers for Medicare & Medicaid Services and CMMI, Dignity Health has put in significant processes incorporating AirStrip OB to lower costs and save lives.
"The country has got to make these great improvements in quality and safety," Roth says. "We've got to figure out ways to take advantage of technology as a healthcare system to improve our own operations, become more efficient, and ultimately achieve the clinical goals and the cost-reduction goals that the system needs to achieve."
Mobile monitoring of asthma symptoms is another technology being tested now at Dignity Health. Patients use an inhaler paired with the Asthmapolis sensor device, which records the type and amount of medication dispensed, as well as date, time, and GPS-enabled location of the self-treatment. "If patients are using their inhaler too often, or not using it, we can ping them and get them into the clinic and adjust their medication or help with patient education so they can better self-manage," Roth says.
The cost of controlled asthma conditions versus uncontrolled asthma is a difference of $3,000 per Dignity Health member per year, and early stage data of the trial has been significant enough to prompt Dignity Health to expand the technology's use in the greater Sacramento, Calif. area, Roth says.
"If you can interject something with mobility that allows for simplicity, and really just does the work to support the patient, rather than making the patient do 10,000 other things that are just not intuitive to them, I think there's a real win there that really gets at the promise of what mobility will offer," Roth says.
One last example of mobile health saving lives is at Health Quest, an alliance of three hospitals in the Hudson Valley region of New York. In the past year, Health Quest has seen a steady decline of 20% to 30% in the time required to open arteries for emergency patients, says Daniel O'Dea, MD, Health Quest director of cardiovascular services.
In part, Health Quest achieved this by deploying the AirStrip system to ambulances within its service area, O'Dea says. EKGs, taken by paramedics and transmitted to the AirStrip app, "can be looked at by the emergency room doctors even before the patient arrives at the hospital," O'Dea says. "This allows us then to activate the team before the patient arrives at the hospital. So while the patient is coming to the hospital, the team is also coming to the hospital, so those two things occur in parallel rather than in series."
As for postacute and home monitoring, O'Dea says the technology has a role to play, even if the monitoring itself has the potential downside of unnerving patients, as Mattison described.
"If you have a reminder that you do have a chronic disease that needs to be managed on an ongoing basis, such as heart failure, where there are specific things that you need to do to take care of yourself—you need to weigh yourself, you need to watch your fluid intake, you need to watch your salt intake—it's easy for patients, once they leave the acute care center and go into the home setting, to forget and to revert to their old ways and go back to eating the same things that they always ate and doing the same things they always did," O'Dea says.
"If there's something around us reminding you that you do have a chronic illness, that may actually increase adherence to medications, diet. Things like that that are going to have a positive effect, so you have to weigh the two of them, and you have to know your patient, really, to understand that."
Reprint HLR070813-6
This article appears in the July/August issue of HealthLeaders magazine.
Health data from medical devices and electronic health records remains frustratingly siloed beyond the reach of individuals and analytical tools. Anna McCollister-Slipp, co-founder of a real-time analytics platform, is working to change that.
Anna McCollister-Slipp
Patients want it. Innovators want it. Providers want it. What is it? Data, liberated from electronic health records, and medical devices. Not to mention millions of records and documents still trapped in paper form.
Getting this data into a form where it can be browsed, analyzed, and applied to a thousand new theories about disease and treatment is no small feat. Doing it while the healthcare system as we know it is being reinvented is even more challenging.
When talented individuals bring their passion to more than one of these callings, they can really make an impact. One such individual is Anna McCollister-Slipp. First, she's an innovator. McCollister-Slipp is co-founder of Galileo Analytics, whose Galileo Cosmos visual data exploration and real-time analytics platform was used in a March 2013 demonstration by the American Society of Clinical Oncology (ASCO) to visually explore complex data in ASCO's CancerLinQ prototype.
But McCollister-Slipp has a special stake in this work. She's also a type 1 diabetes patient, with complications.
"I did everything and more than what you're supposed to do, but it still doesn't work very well, so I'm an outlier in many respects," McCollister-Slipp tells me. "There's a lot that you could learn from these big sets of EHR or registry data that people aren't able to access, because somebody has ownership over it. They're afraid that somebody else might publish something from the data set that they've collected, that they might want to. It might occur to them to study and publish on one day, so they don't release it to others to be able to access and to analyze.
As a result, McCollister-Slipp says, "we've got this rich repository of data all over the place that only a few select folks have access to, and it frustrates me incredibly. There's so much that we need to learn in terms of generating better evidence for diabetes, especially type 1 diabetes, and the real experts can't access the data, because it's being held up in these data silos."
Every data point in those data silos started with a patient, and while it remains important to protect patient identity, it is just as important to make that data appropriately available to those who would analyze and theorize and play with the data in unimagined ways in order to identify new patterns or correlations that today's healthcare system, with its antiquated system of clinical trials, cannot unlock fast enough.
McCollister-Slipp is not content to merely advocate for these changes, or even merely to develop innovative new analytics tools. She also epitomizes the movement of "quantified self" patients who measure every possible health data point they can to help manage their diseases.
McCollister-Slipp has four medical devices on her around the clock. Two are literally attached to her body. One is a continuous glucose monitor, and another is an insulin pump. A third is a SymlinPen, a biologic-in-a-pen she uses to control glucose at mealtime. The last one is a second glucose monitor, which provides auxiliary readings.
Still, McCollister-Slipp cannot see relevant patterns in the data from the combined data outputs of all these devices – because they are not available for analysis outside of each one's closed data system.
"You still have to hand-write most of the stuff," she says. "It's beyond absurd."
McCollister-Slipp also has chronic kidney disease, and must monitor her blood pressure with a wireless blood pressure monitor. She also has a body analysis scale which tells her about her bone mass as a portion of her body, as well as her level of hydration. Finally, she has a fitness tracker device, to keep tabs on her activity level as she hits the gym or heads out for a walk.
"All of that is very relevant information for what I need to do in terms of my day-to-day, hour-by-hour treatment of type 1 diabetes," McCollister-Slipp says. "But none of the data can be collected and integrated into one place. So you've got all of this critical data just at the patient level. It would be very helpful as I determine what insulin I need to take, how I need to adjust my medication to stay healthy. But I can't do it unless I sit down with or manually enter it into a spreadsheet and do Excel stuff."
So, McCollister-Slipp is not terribly impressed by mere talk of empowering people's chronic disease care for themselves. "The technology and the people who have control of the technology from the device manufacturers to the current way that we regulate things at FDA, it's just not making it possible for that to happen," she says.
"It's a nice thing to say from a podium when you're a physician or a public health person who's talking about the need to manage chronic disease, but nobody is really pushing for this to change. And that's one of the things that's motivated me to get involved in this stuff."
Recently, McCollister-Slipp found a receptive audience at the national level. This spring, ONC's Health IT Policy Committee formed a Food and Drug Administration Safety Innovation Act (FDASIA) Workgroup specifically to look into ways to get mobile medical applications to work together with the rest of the healthcare system. And they had the good sense to appoint McCollister-Slipp to that workgroup.
It's lack of political will that's keeping the necessary data sharing from happening, she says—company politics and marketplace politics.
The timing is crucial, since there is still an opportunity to establish requirements in Meaningful Use Stage 3 to demand an end to these data silos when those regulations are written in 2014.
"I'm trying to get other people within the diabetes community and other disease communities and groups to join with me," she says. "If we're ever going to have a learning health system, if we're ever going to be able to do real outcomes research for diseases like type 1 diabetes, we need this data to be collected into the EHR. Outcomes for type 1 diabetes are horrible."
The entire notion of a learning health system is worth a column of its own. Meanwhile, I wish McCollister-Slipp all the best on her self-described crusade. Meanwhile, be sure to check out ASCO's CancerLinq, which has implications across all of disease management.
If you think that moving to electronic health records will eliminate mistaken identity in healthcare, you are mistaken.
This article appears in the June 2013 issue of HealthLeaders magazine.
The change from fee-for-service to coordinated care is challenging providers to solve a longstanding need to identify patients more precisely to avoid waste, fraud, and substandard care.
For years, the healthcare industry has recognized the problem of errors related to improper patient identification. If you were to think that moving to electronic health records would eliminate mistaken identity in medicine, you would be, well, mistaken, according to a variety of healthcare executives interviewed for this story.
The reasons are many, but mainly boil down to incompatibilities between different vendors' EHR technology and the variety of identifiers generated by the other technological systems in use in hospitals and that come from many sources—everywhere from insurance companies to subsystems dedicated to labs or other diagnostics—and that have evolved in isolation from each other over the past 40 years.
"You have to be able to identify the patient across all the venues of care in order to be able to do analytics on the information to make sure that … the care is being delivered, and people are getting the care, and that they're getting only the care that they need in a cost-effective manner," says Frank Richards, CIO of Geisinger Health System, a system that serves more than 2.6 million residents throughout 44 counties in central and northeastern Pennsylvania.
Patient identification is a fundamental building block of the emerging accountable care organization trend, according to Bill Spooner, CIO of Sharp HealthCare, which operates four acute care and three specialty care hospitals with an approximate total of 2,000 licensed beds in the San Diego region.
"The important thing is to be able to get accurately identified patients into your database and to be able to link them out to your transaction systems so everybody knows who they are so you can effectively engage in care management," Spooner says.
The United States in particular faces a hurdle that other developed countries do not: By law, the U.S. Department of Health and Human Services is prohibited from establishing a national patient identifier.
Providers are coping in several ways. Technology exists to flag suspected duplicate identities with varying degrees of certainty. Some are turning to technology offered by suppliers of their electronic health records.
Other providers are relying upon technology that has been employed by payers for years. And for those systems that can make the technological jump, patients are now being positively identified during every visit using smart cards with photo IDs attached, or even by biometric means, such as fingerprint, palm, or retinal scans.
Duplicate-detecting algorithmic technology is generally known as enterprise master patient index technology. "It's all matching on information that you have on the patient, so name, address, telephone number, cell phone number," Richards says. "There are algorithms that run that give you a score of how sure the system is that this is the same person coming from multiple different institutions."
Geisinger is a textbook example of why, in the EHR age, EMPI is still in use. "Epic's master patient index works very well in the Epic world, which is in our case pretty big," Richards says. "We have about 9,500 users on any given day using the Epic system. We have their inpatient/outpatient, many of their specialty modules—ED, OR. We probably run 12 or 15 of their software modules here, and they have very good master patient index for all those. It will track multiple medical record numbers from different sources."
But when Geisinger first installed Epic, it didn't reconcile Epic medical record numbers effectively with other external systems in use, not only within its provider system but now increasingly with its health information exchange. "So let's say that we purchase a hospital that has another billing system or another lab system or something," Richards says. "Epic, at least as we installed it originally, was not capable of taking calls from an external system, reconciling the numbers in its database, and interacting with that system," Richards says.
So, for the past 15 years and continuing today at a cost of $1 million a year, Geisinger maintains an EMPI separate from Epic to reconcile the non-Epic patient identifiers.
"We'd need an army of people to check every one of these, so it's well worth it," Richards says. "So once I've identified that person A from hospital X is the same person from Geisinger, I'll then capture their identifier, their medical record number, from hospital X and so I'll have that forever, and so the next time I don't have to match on all of these parameters. I know that this person coming from this organization has this patient identifier. Over time, it gets more efficient."
Not all hospitals have been able to make the kind of investment Geisinger has. "Right now, the current matching strategy [for] when somebody's not within the system is using their other identifiers: their name, their date of birth, their Social Security number, a variety of things," says Bala Hota, CIO and CMIO of Chicago-based Cook County Health and Hospitals System, with a 464-bed main hospital and a variety of clinics. "But what do you do if the patient doesn't have a Social Security number? Or if there's some problem with the data that you receive? In a public hospital system, that's often the case, and so then you're forced to do some other matching on the data elements."
While Cook County H&HS has "really good matching" about 70% of the time, he says that still leaves the other 30%. "You have to have manual matching. You have to have an inbox almost for somebody to do a match. There's a lot of work there," Hota says.
So he is turning to Cerner Corp., which supplies Cook County H&HS' EHR. "We've looked primarily at the system that's integrated with the Cerner electronic record, and they have this self-registration kiosk that they offer," Hota says. "The advantage is it's fully integrated into our existing electronic record and so we won't have to worry about designing and implementing a project to integrate some external system."
Payer-assembled data forms the cornerstone of the patient ID efforts of Salem Health, a two-hospital system with more than 450 acute care beds based in Oregon's Willamette Valley.
The insurance industry has previously struggled with the question "Was the Mary Smith who has BlueCross the same Mary Smith that has Aetna Medicare?" says Cort Garrison, MD, MBA, CIO of Salem Health. "They have some matching algorithms, as well as somewhat of a common database that we think covers about 70% to 80% of our population."
Salem Health plans to leverage this insurance industry work to bring up a communitywide central repository as part of its coordinated care organization, the state of Oregon's equivalent of an accountable care organization.
Since Oregon's 15 CCOs just organized starting August 1, 2012, they are "fairly new structures," and implementation of the patient ID system is depending on state Medicaid funding that is still pending, Garrison says. But an "agnostic" patient ID system must be built, because "no one EMR is a single source of truth in this community. Our Epic system has the inpatient and some of the outpatient stuff," but other record systems hold other patient data.
"We have basically three disparate EMRs that are prevalent in our community that we need to integrate for transformation purposes." Vendor-supplied EMPI technology alone is insufficient, Garrison says. "We could get there by using that technology alone, but I think we can get there faster by using a different source," he says.
A number of providers have turned to smart cards to solve the patient ID problem.
"It looks like a credit card, but it actually has a memory chip in the card," says Lawrence Carbonaro, director of patient access, purchasing, and HIM at Memorial Hospital, a 25-bed critical access hospital in North Conway, N.H. "You also have the patient's photo on the card, so when a patient presents anywhere [in the hospital], they have to have the card." A card swipe opens up the correct patient's EHR. "We have not had instances of anybody with a card where we've misidentified them by pulling the wrong medical record," Carbonaro says.
If patients forget their card, they can still register once they provide answers to pertinent questions. When it was installed in 2009, accompanied by smoother workflow processes, Memorial Hospital was about to reduce its headcount by 6.5 full-time equivalents, Carbonaro says.
Larger systems are also opting for smart cards. The Nashville-based Vanguard Health Systems operates in cities such as San Antonio, Chicago, Detroit, Boston, and Phoenix. A few of the company's markets are using LifeMedID, the same smart card technology Memorial Hospital uses, with plans to expand to other markets.
Since deploying the smart cards a year ago, nearly 22,000 patients in ambulatory service settings between the two Texas cities of San Antonio and New Braunfels use it, while Vanguard builds a new hospital in town, reaping the benefits of less overhead needed for ID matching, says Roderick Bell III, CIO of Resolute Health, a clinical integrated health and wellness enterprise owned by Vanguard that currently has a network of 150 physicians.
"I've been working with Life-MedID for maybe a year and a half, and I haven't had one duplicate record," Bell says. "I haven't had one patient identity theft, and I'm here in south Texas, where that happens a lot."
Vanguard is integrating LifeMedID technology with its EHR with the help of Allscripts, the EHR vendor, Bell says. "They love the idea that there's a card that will allow them their one-source solution, their Sunrise solution, meaning that there's one record in ambulatory, there's one record in acute care, throughout home health—everything is on one record. This card takes that to another level," he says.
At the March HIMSS conference, Allscripts, Cerner, and others announced the CommonWell Alliance, a consortium of EHR vendors devoted to standardizing patient ID as part of improving healthcare interoperability. All the providers and vendors interviewed for this story see CommonWell's efforts as accelerating their own efforts to eliminate patient ID discrepancies across providers and EHR vendors, and thus accelerate the movement to accountable care.
"We certainly do a lot of work on all of those products, so it's probably not such a bad strategy," says Beth Just, MBA, president and CEO of Just Associates Inc., a Centennial, Colo., consulting firm that has helped hundreds of healthcare providers implement master patient indexes for nearly 20 years.
For now, the industry lacks a universal solution. For instance, Geisinger tested adding a patient photo to be kept on file some years ago, but patient resistance was so great, the company chose to abandon the experiment, Richards says.
Some healthcare systems, such as Cook County H&HS, are considering employing enterprise data warehouse technology to help eliminate duplicate patient IDs. Emerging health information exchanges, many of which are employing EMPI technology, also provide a possible solution.
For instance, Resolute Health's Bell was encouraged recently when Allscripts acquired dbMotion, which Resolute was already planning on using as its health information exchange. dbMotion, coupled with LifeMedID, could provide a more comprehensive patient ID solution, as Resolute moves to stand up its private health information exchange and integrate with state HIEs in Texas and share patient information with competing hospitals.
Providers are just beginning to explore biometric methods of identification. "One system that has been presented by Cerner is a palm vein scan, where the patient actually can go and do a self-registration," Hota says. Cook County H&HS hopes to begin pilot testing of such a system soon, he says.
Just notes that there is, as yet, no silver bullet, no one-size-fits-all solution for the patient ID matching problem.
"If you can't uniquely identify your patients within whatever data you're analyzing, you're going to misread and therefore make executive decisions that are not spot-on," Just says. "And you make some big strategic mistakes because of that."
Reprint HLR0613-6
This article appears in the June issue of HealthLeaders magazine.
Until recently, MU has had a bipartisan aura about it. But now the desire for a delayed deadline for Stage 2 is growing among healthcare providers and technology vendors. Could this be the moment that MU becomes another partisan issue in Washington?
July has been full of FUD—fear, uncertainty, and doubt—for electronic health record technology.
Committees in both the House of Representatives and the Senate have heard officials make the case for providers to get more time to comply with Stage 2, beyond the current September 30, 2014 deadline.
In a statement, the organization of healthcare CIOs said the additional 12-months for meeting Stage 2 "will give providers the opportunity to optimize their EHR technology and achieve the benefits of Stage 1 and Stage 2; it will give vendors the time needed to prepare, develop and deliver needed technology to correspond with Stage 3; and it will give policymakers time to assess and evaluate programmatic trends needed to craft thoughtful Stage 3 rules."
Farzad Mostashari, MD, National Coordinator for Health IT, defended the existing Meaningful Use timetable, but found few allies outside the Department of Health and Human Services, other than the Bipartisan Policy Center and assorted patients' rights groups, for whom the coordinated care and quality controls that Stage 2 will hard code cannot arrive fast enough.
"A pause would stall progress," Mostashari told the Senate Finance Committee. "We need to give Stage 2 a chance."
But clearly the public has grown weary of hearing Mostashari and other officials proclaim how many incentive dollars have been handed out implementing Stage 1. And his beginning-of-year pledge to make 2013 the year of interoperability isn't panning out so far.
Ever since President Bush pledged to bring an EHR to every American by the year 2014, Meaningful Use has had a bipartisan aura about it. Could this be the moment that it becomes yet another partisan issue in Washington?
If the existing Meaningful Use deadlines and eventual outcome milestones get extended, critics of the Obama administration get to point to yet more healthcare dollars spent on Obama's watch with too little to show for it.
If Meaningful Use doesn't get extended, hasty implementations could lead to a series of embarrassing headlines and, in a worst-case scenario, HIT-triggered preventable patient deaths.
My pessimism arises from the continuing politicization of everything in Washington, and a fear that the Obama administration is taking an inflexible position on Meaningful Use for political purposes, a fear that arises out of recognizing that IT transitions of this magnitude take a long time.
Last week, I outlined the complexity of the health insurance exchange data integration effort. It is arguable that the HIX challenge is relatively simple compared to what is being asked of Meaningful Use, particularly if one is looking for solid returns on the investment, returns that can only be quantified with certainty after the outcomes-oriented goals of Meaningful Use are realized.
Originally, outcomes were to be achieved at the conclusion of Stage 3 of Meaningful Use. Given that we haven't yet defined exactly what is going to be in Stage 3, much less begun building it into our IT systems, it is clear that we won't be looking at measurable outcomes for several years to come.
Shouldn't we all agree to allow Meaningful Use to move forward beyond the Obama administration before we see measurable outcomes, or will the program end up dismantled like so many earlier attempts to fix healthcare?
Can the political process and the American people hold its breath that long? Should we expect technology to fix healthcare, and not nearly as fast as the next iPhone will arrive?
Somewhere down the road, Meaningful Use is going to reap dividends. If the program were going swimmingly right now, the Obama administration could take all the credit for having it implemented in ACA. Instead, it could continue into a new administration which would then likely reap the political benefits of its success, assuming that the ROI of Meaningful Use appears by 2020.
Another assumption is that the existing healthcare system doesn't collapse into a heap in the meantime.
"EHRs are like a utility. You've got to have one," says one healthcare IT consultant I know. But so far, we haven't been able to measure its return on investment in a consistent, predictable way.
This is like no utility ever built in the history of technology. Quality metrics are proving to be a tough thing to standardize across EHRs and providers. "Any decision to delay Stage 2 should establish clear expectations on [quality] standards harmonization," says Bill Spooner, CIO of Sharp HealthCare.
In fact, you could argue that incentive programs have institutionalized at the federal level proprietary EHR systems with currently inconsistent and half-baked quality measures. The question now is how do we make sure that when the last of the funding for Meaningful Use has run out—not that far off in the future—that we have truly open technology managing this country's healthcare information technology?
Where will the leadership come from to make that happen? ONC has been a cheerleader for the process, but it's not working out the way it had hoped.
The HIMSS organization doesn't want to alienate its main vendors too badly, and yet, those vendors are dealing with enormous pressures. Software consultant Frank Poggio points out that ONC has continued to update some Stage 2 software compliance test suites as recently as this month, and those weren't just fixing typographical errors. Does such tinkering at this late date help vendors meet their deadlines, or just make the existing deadlines look more unrealistic?
CHIME's visionaries are trying to integrate all this technology, and they speak with a clear voice for you, the customers.
If leadership does not appear, at the end of this $26 billion experiment, we won't be too much further down the line than we are now.
If the next administration is Republican, and manages to roll back part or all of Obamacare, and in the process can put its own stamp on Meaningful Use, rearranging or recasting the program, then that administration, which potentially has until 2024 to get the program right, could claim the political payoff and continue to heap scorn on predecessors in a time-honored political tradition.
I would like to think politics isn't behind some of the thinking going on behind delay, or behind rushing to implement prematurely. With the move toward accountable care—a move only made possible at scale through ubiquitous deployment of EHRs—it's clear we are on a journey, but nowhere near its end.
Last week, a doctor who should know told me it would take a decade from today to realize a true return on investment on the move to electronic health records. An insurer I spoke with last week assured me that its ACO partners have five years to prove their value, and only a handful are in year two.
So, setting politics aside for the moment, let me close with a few hopeful signs:
This month HIMSS launched its Health IT Value Suite, which categorizes money-saving and quality-improving health IT stories, a first step toward an evidence-based repository of healthcare IT best practices.
The HIMSS Electronic Health Record Association now has an EHR Code of Conduct.
190 million e-prescriptions have been filled so far. How many medical errors were avoided due to lack of indecipherable handwriting? How many dollars and lives has that saved?
Despite the sequester, CMS and ONC have continued to hold many online meetings to educate providers about their current efforts, and to continue preparatory work on Stage 3 of Meaningful Use.
There are hundreds of knowledgeable committee participants at the ONC policy and standards committee and subcommittee levels. Without a doubt, they are dedicated to tackling the tough technology issues that lie between where we are today and the outcomes we desire from Meaningful Use.
They also see the coming wave of ubiquitous medical sensors and are working hard to integrate them with our health records. The tone of these meetings is refreshingly collegial, in welcome contrast to the rancorous debate found in the political realm.
Every week in this column, I find someone improving quality or lowering cost in a small way through technology. But if you've ever read Nicholas Carr's Pulitzer-nominated book, The Big Switch, you'll know that electric motors provided a lot of value to individual businesses long before there was an electric grid. We're at that point now with healthcare IT. We've paid for most of the motors, and are hoping that the grid to move information from healthcare business to healthcare business will inevitably follow.
The countdown is on and the make-or-break technology backbone of the government's health insurance exchange is shrouded in questions about security and privacy. One health insurance vendor calls the scenario "a nightmare."
Don't let me give you the impression that technology doesn't have its down side.
It's too complicated. It takes too long to implement. Too often, training is an afterthought. The workforce usually isn't ready for sudden changes. Make the technology too constricting, and clever users will find a way around it, or they'll simply ignore it and go about their business in spite of carefully thought out laws and guidelines.
Recently, I talked with Morgan Hege, who runs an online insurance agency known as HealthInsurancePlus. I asked him how his business is going given the opening up of the health insurance exchanges this fall. He didn't mince words.
"It's a nightmare, because we're waiting on the government, and that's never a good thing," Hege told me.
In the crush of last week's news cycle, reassurances by the Centers for Medicare & Medicaid Services that the individual health information exchange will open on time on Oct. 1, 2013, were drowned out by other stories.
After some digging, I was able to find a YouTube recording of the July 17 House Committee on Oversight & Government Reform hearing on "Evaluating Privacy, Security, and Fraud Concerns", where this reassurance was given. As of Monday, fewer than 300 people had viewed even part of the three-hour YouTube video. [It may be viewed here: Part I and Part II.]
It's a fascinating but painful glimpse into the inner workings and politics of Obamacare's individual health insurance mandate. Whether it also represents a level of FUD (fear, uncertainty and doubt) being generated purely for the political purpose of undermining the Patient Protection and Affordable Care Act, is a tougher call.
Part of the answer is that certain anti-PPACA interests may be playing upon the fears of the segment of the American public that does not understand computer systems, or the methods of protecting personally identifiable information. This sector of the population is instead inundated by fears of "big brother" and the many reported privacy breaches already present in our society.
In California, Hege used to be able to quote prospects a rate on health insurance simply by asking for their age. No more. As of Oct. 1, potential members must also provide his Web site with their social security number, income information, tax filing status, and more.
"The idea is we're going to ping the IRS with that information to then get a number back as to what their rebate is, based off of if they're eligible for a rebate first," Hege says. The amount of the rebate will be based off of what their tax filing status was last year.
The rebate could disappear, however, if the applicant ends up earning more money than projected in the current tax year. A job promotion "could push them out to where they don't have the rebate any longer, and then when they file their taxes at the end of the year, and they're expecting a return, they won't get a [rebate] anymore."
Few people are aware of this aspect of Obamacare, and fewer still are aware that a massive information technology integration effort is underway across the systems of the Internal Revenue Service, the Department of Health and Human Services, and the Department of Homeland Security, to make the back end of this system work as the PPACA intended.
This IT effort dwarfs many previous governmental and non-governmental interoperability efforts, yet the PPACA states must be up and running by Oct. 1, 2013, when state-run and federal-run health insurance exchanges open for business, initially primarily through healthcare.gov.
As yet, private health insurance providers such as HealthInsurancePlus are, for now, locked out of the development process. Somehow, just 70 days from now, it will all be different. Exchanges are planning bronze, silver, and gold plans, but won't be able to reveal final rates until October, Hege says.
Even more confusingly, employers with groups of 50 or more employees don't have to offer insurance to those employees until January 1, 2015. That deadline was extended, in part because of employer concerns about the complexity of the data reporting requirement.
"It is unlikely to be perfect out of the gate," says Rep. Jackie Speier (D-CA), in what was the understatement of last Wednesday's hearing.
The make-or-break technology of health insurance exchange has to be CMS's Federal Services Data Hub, which was never actually formally described in PPACA. Instead, the Hub arose out of PPACA's language requiring the exchange of information between IRS (for income verification, filing status, number of dependents), DHS (for citizenship verification), and HHS, which will compute rebates due Americans on their health insurance premiums, and communicate that information back to the IRS.
Got that?
Well, talk that kind of talk about aggregating that much information about any one American, and you are going to run into every sort of privacy concern you can imagine, even in this day of Facebook and generally acknowledged big-data surveillance by the NSA, credit bureaus, and the like.
It's easy to imagine that IRS/CMS/DHS/HHS information sitting in a single, massive database somewhere in the federal government's computers. Yet, that's not how the system is architected, say federal officials.
Instead, the Data Hub acts more like a giant router, whisking queries between computer systems to minimize the copying and aggregation of personally-identifiable information (PII) and the potential for its abuse.
At Wednesday's hearing, a number of members of Congress did not seem reassured by these safeguards, and raised a host of other questions that seem to require some fancy footwork to be answered by Oct. 1.
For instance, if an employer offers an employee health insurance through its own plan, how are the state and federal exchanges able to know if an employee has refused that offer of insurance?
CMS Administrator Marilyn Tavenner made no friends at the hearing by not having a good answer for that question. Instead she suggested that HHS will work with Equifax, the consumer credit reporting agency, which is being considered to verify, for the federal government, such employer offers to employees through a process yet to be defined.
Congressman Pat Meehan (R-PA) noted that one-third of privacy breaches originate with employees; in effect, they're inside jobs. Then he noted that the state of California plans on hiring 22,000 "navigators" to assist consumers purchasing health insurance. "I fear our government is about to embark on an overwhelming task," Meehan warned.
Tavenner and other officials from the IRS, the General Accounting Office, and CMS kept their cool even when the Republican questioning came to resemble, in Speier's words, a "witch hunt." During too many opportunities, a substantive discussion was put on hold while members of Congress revisited the IRS' recent misadventures in non-healthcare related areas.
Still, I didn't come away with much confidence that the system will work as intended on day one. You don't just stand up a Data Hub of this size and scope with millions of fields of tax data securely flowing back and forth between two massive federal agencies who've never done such a thing before, without problems.
Then add the fact that 15 states will be operating their own health insurance exchanges and exchanging such information with the IRS, HHS and DHS, all simultaneously with expected response times of 5 to 8 seconds, and there are bound to be errors, and probably data breaches.
Hege and many House Republicans point out with alarm the law's requirement for employees to report changes in their income within 30 days, to allow appropriate adjustments in health insurance refunds from the IRS. Federal officials note that those requirements will be relaxed, that such adjustments could be rectified finally at tax time without penalty. Fraud concerns, though not brushed aside, were mostly left to be addressed another day. It just adds to the formidable complexity of what we all acknowledge was a formidably complex law.
Obamacare will have many do-or-die moments, and October 1 is surely one of them. Sequestration continues to sap budgets at IRS and HHS. If the health insurance exchange system gets up and going on Oct. 1, from a system integration and agency coordination point of view, it will surely be something of a miracle.
Medication adherence is a multifaceted challenge that's getting a shot in the arm from technology developers. Glowing pill bottle caps connected to the Internet and a digital library of pill images with detailed data on drug interactions are just the beginning.
If a picture is worth a thousand words, how much could a picture of a patient's medications be worth?
Technology developers have not been idle. Vitality's GlowCaps, available since 2008, have made medication reminders a function of programming a pill bottle's cap to glow, and presages the coming age of the Internet of Things, when many objects of everyday living will periodically remind us what they are there for. It's definitely a space worth watching.
But the challenge of medication adherence is multifaceted. It's not just which medication is the right one to take. It's also knowing whether the patient took too much or too little, or if the medication is interacting with some other medication the patient is taking. As a result, other innovative solutions are proliferating.
One such solution is MedSnap, which premiered at HIMSS. MedSnap visually identifies prescription meds and comes along at a pivotal time.
In June, by a 5-4 decision, the U.S. Supreme Court threw out a $21 million jury verdict involving a woman who suffered skin burns after she took a pill to relieve shoulder pain. A majority of the justices said the FDA had approved the drug, sulindac, for sale, and that federal approval trumps a state's consumer protection laws.
With this decision, the Supreme Court established that patients badly injured by a generic drug cannot sue the manufacturer.
So, more than ever, pity the poor emergency room physician, confronted by an incoming patient with a baggie full of pills, many of them generics, barely identified or distinguishable from each other.
Meanwhile, families may be taking home bags of medicines from pharmacies, and storing them together in a common place. Confusion is bound to result, and probably does.
Enter technology. MedSnap is an app for the iPhone 4S or 5 that identifies sets of pills in a single snapshot, checks against the patient's drug regimen, flags drug/drug and drug/disease interactions, and in the process improves a vast and growing collection of crowdsourced knowledge about the shape, imprints and textures of medications to improve future identification.
Initially aimed at emergency room and home health care personnel, MedSnap holds the potential for such an app to live on every smartphone, ultimately to be used by patients themselves.
It is possible to truly geek out on the cleverness of this system. The app takes great care to get a good picture. The MedSnap system includes a specially-printed card upon which users place the medications. This card offers proper measurement and corrects for color variations in the surrounding light. Just to be sure, the app requires the camera's flash also be used to reduce color variation. Fortunately, more and more smartphones are coming equipped with flash, and before too long it will probably be a standard feature on some tablets.
Because of slight variations between pills manufactured in the same batch, the app then asks the user to verify its findings, a momentary process I liken to the "are you sure" prompts one receives before deleting a file. "We find pills that have no imprints," says MedSnap CEO Patrick Hymel MD. "We find pills that have partial imprints that are slightly different in color. For all these reasons, the user needs to click each pill and sign off."
For pills that MedSnap knows, it correctly identifies them 97 percent of the time, which approaches the accuracy of appearance to which the pills themselves are manufactured, Hymel says. "Capsules might be 50 millimeters in length, but then you'll find some that are 60. You can look at six Adderall [pills] – this happened last week – and four of them will be dark gray. Two of them will be light gray. They're both gray. Which one is accurate? So there are limits to the specifications that you can depend on."
MedSnap ended an extended beta test period this spring, after being tested at Auburn School of Pharmacy, the Samford School of Pharmacy, and other similar institutions, involving more than 300 pharmacists. When the app discovers a pill it doesn't recognize, it asks the user if they want to donate images of the unknown pill to the MedSnap library, then adds it to the growing knowledge base.
App pricing is based on the number of admissions at a particular facility, and initial deployments have come in hospital emergency departments, home nursing, and pre-op departments, then eventually make its way into outpatient clinics, where it will be licensed on a per-physician basis, says Hymel.
One early MedSnap adopter is no stranger to me: Cullman Regional Medical Center. "The culture of our hospital is to utilize the latest technology to help us with better patient outcomes," says Cullman president Jim Weidner. Cullman was familiar with MedMined, a previous company Hymel ran, so was receptive to the new idea.
From its first use of the product, Cullman had convincing evidence that MedSnap could be useful, as it was able to distinguish an antipsychotic medication from a similar-looking common antibiotic, Weidner says.
Since then, Cullman has deployed MedSnap with its home health nurses as well as when patients present at the emergency department with bags full of their medications, Weidner says.
"It's improved accuracy, it's improved efficiency, it has improved quality in the way of identification of contraindications, and, what we hope to have it morph into is to actually have our patients have the application on their iPhones so that on a daily basis the patient can do their own MedSnap," Weidner says. The app would then be able to notify physicians or the hospital that the patient is not following what has been prescribed.
Hymel, whose own father struggled with a challenging regimen of medications while being treated for cancer, sees the power of technology to change a culture where patients were expected to recite what medications they are on, to one of where the patient simply brings in what they are taking and presents that history visually – a visual intervention, if you will.
"There have been studies that more than 50 percent of medication histories are wrong in some way," Hymel says. "[Patients are] taking too many of one or not enough of another. They've swapped their husband's pills with their pills in their medication organizer, so all of these little bugs in the system that are very easy for patients to make mistakes on become apparent when you say 'show me'."
Not everyone will have an iPhone 4S with a flash (or equivalent) in the immediate future, so the industry will continue to have a variety of different technological approaches to medication adherence. Some of them will be evolutions of the classic pill organizer.
Two such examples are MedMinder and SentiCare. There are others. We're likely to see many such technological solutions contend for a permanent place in healthcare. But with so many lives at stake, and costs waiting to be cut like so much low-hanging fruit, the time is now for exploring what options exist.
Aetna is rounding out its mobile strategy by selecting more than 20 Web-based healthcare applications for its own CarePass wellness app, which pulls data from various sources and presents visualizations of progress toward goals.
Most patients think of their health insurance company as a source of never-ending paperwork and denied claims. Aetna, through technology, is working to bust that stereotype.
The insurer's latest move is to effectively become a curator of mobile and Web-based healthcare apps, rounding out the company's mobile strategy, which already includes iTriage, the popular mobile phone app the company acquired last year.
Aetna's CarePass app
Aetna CEO Mark Bertolini spearheaded the development of a wellness app called CarePass to make buying healthcare as convenient as going to a store, scanning a bar code, finding the best price online, and having it shipped to his home.
By the way, this practice, known as "showrooming," drives retailers crazy. Likewise, some doctors will be a bit agitated by Aetna's new app, for it draws together the new crop of wellness apps, but doesn't yet advance interoperability of those apps with electronic medical records.
But if healthcare providers are going to engage patients, they have to assume different roles: curator, coach, cheerleader, and concierge. CarePass pulls data out of different wellness apps and visualizes consumers' progress towards a goal, and so doing aspires to solidify Aetna's brand in new ways.
The 20-plus apps Aetna has picked touch more than 100 million consumers today. Some of the numbers for each app are staggering. MapMyFitness has 30 million users. RunKeeper has 25 million. Aetna's scrambling to get in front of a parade already under way.
Each of these apps already has its own community, its own social network, and its own structure of peer support. Aetna pulled in another virtuous cycle by incorporating consumer-entered data from healthy eating apps such as FatSecret or Lose It! CarePass then generates custom discounts in local supermarkets, powered by Zipongo, yet another app tapped for CarePass prominence.
Aetna vice president Martha Wofford heads the CarePass initiative.
If CarePass is the Aetna wellness app, iTriage remains its health app—the place Aetna sends its members (or non-members) for symptom checking and doctor referrals. But starting later this year, the lines between the two will start to blur. At that point, CarePass will begin to connect with some of the mobile apps that strive to help people manage, and remember to take, their medications, says Aetna vice president Martha Wofford, who heads the CarePass initiative.
"It's obviously a difficult space," Wofford says. "I don't think any of the solutions are super-strong yet, but again it's an important part of the whole process for many consumers."
There's still a lot of friction in the digital practice of wellness. People generally can't be bothered with entering their calories or food choices. Passive devices such as FitBit (supported by CarePass) take over some of the work. The most important new device in the home is probably the Withings scale (also supported by CarePass) which captures that all-important regular weight reading and uploads it to the Withings servers and from there on to Aetna.
But once you wander into medication adherence and the like, you're entering the FDA's territory. That's why we'll be hearing more and more about the connection between devices, apps, and patient safety. Just recently, it was noted that Apple continues to crack down on medication dosage apps listed in its App Store.
So Aetna, other insurance companies, and providers aren't the only ones trying to curate health apps—app vendors are getting into the act as well.
At some point, however, CarePass, iTriage, and consumer wellness devices start to become part of a complete healthcare picture, but without some of the traditional guidelines that the FDA has imposed upon medical devices. Part of the challenge is that various transient readings from devices can be indicators of more serious conditions, and yet there are no guidelines that the apps being fed data by these devices aren't summarizing or averaging such data. If such summarizing or averaging does occur, telltale signs of undetected disease might be missed.
Wofford realizes the challenges ahead, and in fact, notes that CarePass comes with a set of disclaimers about not allowing it to act as a substitute for a doctor's care.
"What we'll implement is the ability to a consumer to at a summary level to share information back with their doctor, to say, look, you told me to get in a healthier lifestyle, and here's the data to show it," Wofford says. "That's fine, but as we get into more clinical uses of data into the workflow, that's where I think you end up crossing that line into more of the FDA space. We'll have decisions to make in the future about how far do you go."
At the moment, Aetna is more focused on empowering consumers to bring their data together to track and trend that information. But caring for a condition is clearly the next step. "I think you're right about understanding that there's a continuum here, where we currently are, versus what the opportunities are."
One thing that Aetna cannot do is curate more than a few dozen apps, which leaves another 40,000 or so mobile health apps outside their reach or recommendation. As far as assurance that the few dozen apps are good apps, Wofford admits that popularity is one determinant. Startup apps such as Zipongo may slip in as well, but they must have a national footprint to play in CarePass, she adds.
To promote CarePass, Aetna just launched a Web site, whatsyourhealthy.com, which it is promoting on TV and other media, even billboards. Wofford won't give specific numbers, but it's clear Aetna hopes to reach many of the 100 million consumers I mentioned earlier.
All around the Internet, opportunities beckon to providers and payers. It remains to be seen just how successful traditionally dominant healthcare players will fare. But these are platform plays, so don't bet against the big players. Healthcare will be the same kind of one-stop shopping, or impulse experience as showrooming has become in retail stores. Expect the unexpected.
OutcomesMiner, a software application codeveloped by Deloitte and Intermountain, leverages 40 years of clinical data to help analysts glean the "clinical nuances" of comorbidities and various treatment outcomes. How does it work and who will use it?
Can healthcare's Big Data become less of a mountain to be sifted through by experts, and more like a utility to hook up, like water, power or cable TV? We're about to start finding out. Analytics applied to Big Data offers tantalizing possibilities for improved healthcare, but the complexity is enormous.
I spoke last week with Brett Davis, general manager of Deloitte Health Informatics (DHI), following the release of OutcomesMiner, a service that leverages 40 years of clinical data from Salt Lake City–based Intermountain Healthcare to help analysts throughout healthcare glean insights about the relationship between combinations of comorbidities and various treatment outcomes.
HealthLeaders: Where does this fit in the analytics tool universe?
Brett Davis: In a lot of ways, I wouldn't actually think of it as an analytics tool. One of the big things that we and Intermountain coming together are trying to solve is that the secondary use of healthcare data to understand what works for whom, why and in what context and at what cost, is not really a software problem. There's tons of great analytical software and tools out there, but the challenge is bringing together a combination of insights from health systems and firms that have longitudinal clinical data, combining it with analytical tools that provide nuanced understanding of outcomes in subpopulations, and then actually applying that to clinical change and transformation. That's not going to be solved by software alone or data integration tools alone, and so that's why Intermountain Healthcare and Deloitte really came together with our alliance … with this platform, OutcomesMiner, being the first result. OutcomesMiner is a tool at one level, in that there is software, but it's software meeting analytical and clinical insights from the 40-plus years of experience Intermountain has in becoming a data-driven organization—which … led to them being able to prove that you can take variation out of care and increase quality while at the same time reducing costs.
HealthLeaders: Is this a service that Deloitte is just delivering to customers, so there's nothing a customer need install? Do they have to set up a new data warehouse or anything like that?
Davis: There's really two dimensions to it, depending on the client need. There is a full cloud-based subscription service, where a health system who may be doing comparative effectiveness research on real-world data can access the tool and not implement anything on-site, [They can] glean insights through the tool into Intermountain data in an ethical, secure way, but health systems and even pharma companies also want to do comparative analytics with their own data that they may have. In that case, they can feed the tool, the platform, through an existing warehouse that they may have, or they may ask Deloitte to help them with putting a warehouse in place to feed the OutcomesMiner platform so they can look at their own clinical variation. Traditional benchmarking at system levels is interesting to potentially diagnose that your CHF population or your asthmatic population is not performing as well relative to your peers, but if you're going to start taking on more risk in managing populations, you really need to be able to get granular. You need to start getting down into what I call "clinical nuance," and understand that it might be CHF patients who have these other two comorbidities—psychosis, hypertension, and diabetes—are on these two drugs, etc. Existing platforms and tools on the market don't give you that level of clinical nuance to be able to actually go beyond this and start to identify the sub-stratified populations that you really need to be going after.
HealthLeaders: Are these predictive models, or is that overstating what this is doing? Are you predicting outcomes? Are you modeling outcomes?
Davis: It may be taking a step too far to truly call it predictive, in that we're giving the answer. It's giving you the insights, though, of where to look. With observational data, you always have got to be careful [not] to overstate causality and the associations. It gives you associations between outcomes and the multiple comorbidities to go investigate in the right areas; to use the overused analogy, of making sure that if you drop your keys in the dark, you've got a flashlight that you can search and find the right spots. It's kind of that analogy to do the diagnosis and make sure you're targeting the areas that are going to have high impact to addressing cost issues while not impacting quality.
HealthLeaders: How has this been proven out? What is the evidence you have so far that this combination of insight and services makes a difference?
Davis: We're early in the journey, so we don't have client results that we're talking about yet publicly, but we do have validation from the Intermountain clinical and informatics community, working closely with the Homer Warner Center there, which is a 60-plus person informatics center that were codevelopers in the platform.
HealthLeaders: Is there a double-blinded format that protects PHI [personal health information]? How does that work?
Davis: No PHI data ever makes it into any IT environment where PHI information could be potentially revealed. There's a double-blinded format where there's a blinding step that's done by Intermountain before Deloitte or our platform gets involved, and there's a second double-blinded key—so it's sort of like the old nuclear days where you needed two keys to reidentify, to provide extra protection to make sure that there's never any exposure of PHI through the platform.
HealthLeaders: What kind of customers is this appropriate for? Are we talking about customers who have a large IT staff, who have no IT staff, somewhere in between? Give me a feel for that. It might be analysts, not necessarily IT people per se. Analytics people, data people, quants, or whatever.
Davis: The platform and the mission of our venture together with Intermountain is really to scale the insights that come from the secondary use of data to drive clinical practice improvements. Because if you look across the market broadly, the level of investment that, say, an Intermountain or a Partners Healthcare or UPMC can put behind building out large staffs around analytics is limited, and if you look at the skills out there, even if they had the capital and resources, the skills of people who can actually do this kind of work are extremely limited. It's a very competitive field, so to recruit the kinds of data scientists and informatics folks who can actually do this stuff—and then you put on top of that the fact that most health systems just invested tens of millions or hundreds of millions of dollars in their EMR journey—going in and investing in a big complicated analytics environment, it's just not going to happen. The solution was really designed to democratize healthcare analytics, and bring these insights and learnings to the broader market for those systems that haven't [become] a data-driven organization. A lot of these health systems are flying blind in terms of really being able to understand the nuances of what's going on inside their comorbid populations. This solution is really designed to avoid having to go and invest in a big complex IT project for three or four years before getting value.
HealthLeaders: Does the fact that you've announced it at the Drug Information Association's 2013 Annual Meeting mean that you're going to see a dominant customer base of pharmaceutical companies, or did that just happen to be the convenient place to launch it? What's the mix of customers likely to be on this?
Davis: It's hard to predict exact customer mix, but there's absolutely demand in the pharmaceutical/biotech and medical device space, because they're facing similar pressures to prove value and compare effectiveness in their products. Going forward, and maybe not as widely known, some pharma are already entering into their equivalent of ACO-like contracts, where instead of just getting reimbursed based on pill volumes, they actually are engaging in helping to make sure that their therapies, diagnostics, etc. actually are creating the value that they say they will. So on the pharma/med device/biotech side, there's absolutely a market for insights from real-world longitudinal data. Similarly, where we're seeing demand on the health systems side is really around systems that are starting down the journey of moving to value-based care, whether that be in the context of formal ACOs (the CMS shared savings program), or whether that is via the context of just trying to become more clinically integrated, recognizing that management of complex, comorbid populations is going to be a differentiator and a necessity in the coming years. We're seeing demand on both sides.
OutcomesMiner is intended to help hospitals and clinics determine better medical treatments based on clinical data and patient characteristics.
The first fruits of the alliance between Deloitte and Intermountain Healthcare emerged this week with the launch of OutcomesMiner, an analytics tool designed to give researchers, and pharmaceutical and medical device companies data-driven insight needed to conduct comparative effectiveness research and bring new therapies to market more rapidly.
Leveraging electronic medical records data, OutcomesMiner helps population health analysts understand associated outcomes for treatments and filter for sub-populations using phenotypic characteristics and specific medical associations.
The tool draws upon Intermountain's vast repository of electronic health records in supporting analysis around patient and product outcomes under a double-blinded format designed to protect the privacy of personal health information.
OutcomesMiner also enables users to conduct follow-on studies to support comparative effectiveness research programs, new product planning activities, health economic and outcomes research and observational insights that support safety analytics and commercial decision making.
In addition to the benefits for life sciences companies, OutcomesMiner can help hospitals and clinics determine better treatments based on clinical data and patient characteristics.
The two companies made the announcement at the Drug Information Association's 2013 Annual Meeting.
"The life sciences and healthcare industry is entering a new era in which success is tied to demonstrating value for reimbursement with an increased focus on safety and clinical effectiveness," said Brett Davis, general manager of Deloitte Health Informatics (DHI). "OutcomesMiner can help our clients thrive under this new paradigm by providing the insights they need based on rigorous real-world evidence."
Asif Dhar, M.D., chief medical officer and managing director of DHI, said, "With OutcomesMiner, we aspire to create a solution that is transformative, one that can support the health system as it undergoes fundamental change based on insights generated from EHR data. Tackling the issues vexing today's health system requires new approaches based on the smart use of data."
Marc Probst, chief information officer of Intermountain, said users of OutcomesMiner will be able to form "research communities" that develop additional insights related to comparative effectiveness and evidence-based medicine. "OutcomesMiner can do more than provide insights in a one-off manner," said Probst. "It can also be the catalyst that brings key players together in further exploring new approaches to healthcare based on data."
Researchers and a journalist were able to re-identify, without much fuss, the de-identified medical records of scores of patients, thought to have been protected by HIPAA. Here's how they did it.
Patients concerned about privacy have more than flimsy hospital gowns to worry about. Their medical data may be showing.
First, a visual aid. Click on the map and take a look at where much medical information is flowing today.
This map, constructed by some of the nation's leading privacy experts, is an apt illustration for a big problem. In theory, all the healthcare providers on this map are complying with HIPAA, the Health Insurance Portability and Accountability Act of 1996 and its subsequent amendments.
So how come, in a year-long investigation, a few researchers and a journalist were able to re-identify, without much fuss, the de-identified medical records of 85 patients treated in Washington state in 2011?
The answer to that question is a big challenge to HIPAA and to providers in 33 states, and perhaps beyond.
The story resulting from this investigation, "States Hospital Data for Sale Puts Privacy in Jeopardy," hit Washington D.C. like a health privacy bombshell earlier this month. As I've been researching a HealthLeaders magazine story on HIPAA, it's obvious that the revelations are troubling to healthcare CIOs and other executives as well.
Here's how the investigation worked: State public health departments, eager to expand medical research, collect de-identified discharge data from hospitals. HIPAA permits this disclosure, in part because the privacy advocates who helped write HIPAA made it easy for states to pass tougher versions of the federal HIPAA law. The problem is, however, that most never did. So in 33 states, this discharge data gets sold for little or no money to all takers.
Through a Freedom of Information Act request process, the story's author, Bloomberg BusinessWeek writer Jordan Robertson discovered that the primary buyers of this data turn out to be public and private corporations not primarily known as public health researchers: Truven Health Analytics, Optuminsight/Ingenix, and WedMD, among others.
"Hospital records are very useful in enriching prescription data databases, because a prescription record will only show you what medication you're on," Robertson told an audience at the 3rd Annual Summit on the Future of Health Privacy in Washington D.C., which I attended.
"If you can link that with a hospital record, you can also learn what your original diagnosis was, which physician recommended you that particular drug, as well as all these ancillary conditions, so it turns out, and I had no idea about this, but hospital discharge data is one of the most valuable pieces of data in the medical data ecosystem," Robertson says.
No one is yet saying that these companies are the ones re-identifying patient data, but Robertson's investigation shows how easily it can be done.
Assisting Robertson in his discovery was computer scientist Latanya Sweeney, professor of government and technology in residence at Harvard University and the mastermind of the Data Map, first envisioned in 1997 and used to discover former Massachusetts governor William Weld's medical records in a redacted data set.
"Suppose you know someone went to the hospital," Sweeney said. You might know the name of the hospital, the data of admission, and maybe something about why they were there. "It's also the same kind of information that a financial institution would know about someone who said they were going to be late making credit card payments, because of a hospitalization," she said. "It's also the same kind of thing that a data mining company would know could extract from purchasing pharmacy data."
Another source of such data is news stories, so Sweeney and Robertson surveyed the NexisLexis online researcher service, and by tapping only three news sources in the state of Washington, the team was able to search for mentions of hospitalizations, and identified 81 subjects, many in news stories identified by their names, their ages and what happened to them.
Through some other searches on the public Internet, the investigation exactly identified 35 of the subjects, a 43 percent success rate. Sweeney then hired a temp who could use computers but didn't have a specific background in computer science, statistics, or medicine. The temp had two days to match the remaining 46 subjects using ordinary Internet searches, and was able to match every one of them.
When Robertson contacted subjects for comments for his story, they were astounded, and sometimes angry, that he knew their medical diagnoses and treatments from those hospitalizations, and that the system could be used in such a fashion.
"The data has a lot of value in the wrong hands, and we've chosen to publicize this, because we're trying to draw attention to it," Robertson says. "This could have been done just as easily by a private investigator or by a short-seller, if they had the wherewithal and the means to do it."
It dawned on me that while providers may do everything they're supposed to do to abide by HIPAA, loopholes like this state public health exemption, renders information accessible. And once it's on the Internet, data can live forever.
States may be lulled out of their inaction by Robertson's story. Already, Washington state has told Robertson it intends to tighten its data standards. Unless the entity requesting the information is truly a public health agency, the state will likely charge steeper fees to access the data. Already, the state of Pennsylvania, seeing increased demand from commercial data companies, increased the cost of the data sets.
But Robertson noted that the uses of secondary health data, including for marketing purposes, is projected to be in a $10 billion industry by 2020. So how likely is it that commercial interests will let higher fees slow them down?
Meanwhile, it's worth pondering just how injurious the release of this data can be to patients.
In his investigation, Robertson discovered that the records included diagnoses and procedures, diagnoses mostly, that many patients didn't even know that they had. And even worse, some of these diagnoses can really impact a patient's public reputation.
"Somebody who goes in for a broken arm from a car crash might show an addiction to heroin, or methamphetamines, or cancer, or all these other things that show up in a hospital intake," Robertson says. "There's some really sensitive stuff in there. Many of these states are releasing more data than even some of them realize."
Technology almost always is a two-edged sword. No one wants to deny researchers the data they need. The promise of big data and analytics is to do an end-run around this country's archaic clinical trial process to discover new statistical correlations between genetics, environment and disease. None of it is possible without electronic medical records and the aggregation that big data makes possible.
But we must be careful. The genie is out of the bottle, and adequate safeguards must be in place, or our health privacy will be endangered. At the end of Sweeney and Robertson's talk, one audience member asked, probably rhetorically, if her medical records could return exclusively to paper.
No one really expects that to happen. But this bombshell of a story is a warning that we must deal with all the implications of the electronic systems we are deploying.