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UCLA Health Moves Forward to Connect Patients to Services—and to their Data

July 25, 2017
by Mark Hagland
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Michael Pfeffer, M.D. shares his perspectives on organizational advances, as a physician CIO

Healthcare IT leaders are moving forward in a number of directions at UCLA Health, the four-hospital, 2,000-physician integrated health system in Los Angeles. As the organization advances in its work on data-sharing, on the leveraging of data analytics to support accountable care and population health work, and on patient/healthcare consumer engagement, the healthcare IT team at UCLA Health is moving forward under the leadership of Michael Pfeffer, M.D., the organization’s vice chancellor and CIO. Dr. Pfeffer, who has been in his current position—which oversees the IT support both of the patient care organization and of the research organization, in the integrated health system—for three years, continues to practice part-time as a hospitalist.

Dr. Pfeffer recently spoke with Healthcare Informatics Editor-in-Chief Mark Hagland, and shared his perspectives on the various initiatives he’s helping to lead, as well as on his work as a CIO who continues to practice as a physician. Below are excerpts from their interview.

What has been the overall thrust of your work in the past three years?

Most CIOs will say that they’re involved in many, many different projects to support the operation—EHR [electronic health record] infrastructure upgrade, cybersecurity, clinician workflow redesign, and other areas. I’m also responsible for the school of medicine, so I’m looking at areas that support research as well.


Michael Pfeffer, M.D.

What would you say have been the biggest breakthroughs in the last year, in your area?

I’d say we’ve been doing a lot of really good work on the patient-facing side, including the patient portal for our ambulatory and inpatient sides; we’ve done a lot of work with the use of cloud in terms of analytics, to allow our business analysts to create really nice visualizations in terms of data sets, and also around data governance. We’re about to do a major upgrade on our EHR platform. Also, a year now, we redid our entire laboratory system, bringing it over to the Epic Beaker system. And we’re an Epic shop overall.

Looking at the managed care/healthcare market in the L.A. Basin/Southern California, how would you paint a brief portrait of that market?

Well, I think the L.A. market is fairly unique in that there are a lot of players in the market, and a lot of insurers in the market, both, and that’s unusual. So we’re lucky in that there isn’t a single dominant insurer. That makes it exciting and challenging at the same time. In addition to all the changes going on at the policy and payment level in the federal government, that makes it quite a challenge to predict what’s going to happen. But all in all, all of the healthcare providers and insurers in the market are looking to take the best care of our patients no matter where they end up. So making sure we can exchange information among providers in real time, will be extremely important. And there’s anecdotal data showing that when you have records available, you don’t repeat as many tests or order as many procedures, when you have that information. So that’s what it’s all about, really.

That to me sounds like health information exchange or health data exchange, in the broadest sense. And how is that area working out for your organization?

Yes, that’s correct; and there actually have been some very exciting things going on in our market, in that area. Most of our exchanges occur with fellow Epic providers, and we use Care Everywhere [the Care Everywhere Network sponsored by the Verona, Wis.-based Epic Systems Corporation] for that. Epic-to-non-Epic is more of a challenge, but we’re making headway. We’ve signed up for Carequality, and we’re beginning to exchange records seamlessly between our site and other sites that don’t have Epic. And we’re also waiting for the CommonWell platform, which is basically Cerner’s version of CareEverywhere, and that would really connect the people in the L.A. Basin, no matter where they are.

How many sites or organizations are involved in all of those data and information exchanges?

In terms of Epic-to-Epic, we’ve exchanged patient records with organizations in all 50 states. In calendar year 2016, we did about 3.75 million record exchanges, Epic-to-Epic. In terms of Epic-to-non-Epic exchanges through Carequality, we’ve exchanged about 2,500 records with 21 organizations so far. That’s been after about six months so far.

And through CommonWell?

Care Everywhere is part of Carequality, and CommonWell is going to join Carequality—whose membership already includes Epic, eClinicalWorks, NextGen, athenahealth, etc.—CommonWell is going to join that large collaborative And Epic has been a really progressive player in the market. And being part of Carequality is very important, and exciting, and eliminates the need for health information exchanges, which have been struggling.

Are you participating in any accountable care organizations (ACOs) yet?

Yes, we’re in the MSSP [Medicare Shared Savings Program] with CMS [the federal Centers for Medicare and Medicaid Services].

Can you share your thoughts and perspectives on aligning data and leveraging analytics, for your ACO development work?

I think a lot of this is going to start to align with MACRA [the Medicare Access and CHIP Reauthorization Act of 2015, which has mandated physician participation in quality outcomes measurement and value-based purchasing] and the different advanced care management tracks within MACRA. Participating in MSSP qualifies you for different tracks for MACRA, including with ACI, advancing care information, which is the old meaningful use [and is now an element in the requirements under the MIPS program—the Merit-based Incentive Payment System—within the MACRA law]. We’re seeing that align. So I think things will hopefully get easier in that space, in terms of a more standardized way of reporting quality and value emerging. It’s been challenging, certainly, to align all of that for different payers and different programs. Hopefully, we’ll start to see more alignment.

What we’re hearing from all of the healthcare IT leaders we speak to is that a lot of work needs to be done to customize analytics solutions; that there are no “off-the-shelf” solutions that can simply be plugged in. And creating the interoperability or interfacing with the EHRs remains a challenge. What are your thoughts on that?

Yes, I absolutely agree. The data sets are incredibly complex. You really need to acquire the data scientists to help you find the data and figure out where it has to go. Here’s one typical example of the complexity involved: there is actually no value that you can pull out of the EHR that represents length of stay; instead, you have to create that value as a calculation, based on different time stamps. And determining how to calculate that correctly is something that requires data scientists. So it’s more than simply asking what your length of stay f or heart failure is. You have to determine what heart failure is. And then you have to determine what you consider length of stay, before you can even put that into a tool for population health work.

So it’s a lot more challenging than simply bolting something on. We’ve never had success simply trying to plug things in. But we are making a lot of headway. So if you have a very good data governance process, you can define what length of stay is for conditions, and you can code that to pull out the correct variable from the EHR. And then people can use that for different kinds of platforms. And as we build up our data governance and data model, it’s going to become a lot easier to build platforms to manage risk and manage populations, so that’s really where we’re focused. We want to move towards a self-service analytics model that has a robust data governance behind it, so that when we develop programs, we can feel comfortable that we’re using embedded data variables that are accurate.

Let’s talk a bit about your perspectives as a physician CIO. Do you still have time to practice clinically?

I do. In fact, I’m on service this week; I’m a hospitalist with an internal medicine background. I do about five or six weeks a year on hospital service. And I have a phenomenal team for backup, during the times I’m on service as a hospitalist.

What do you think physicians bring to the role, what do you bring?

That’s a great question. I’ve thought a lot about this. I have a lot of colleagues, obviously, who aren’t MDs. And I think basically, when you look at the leadership of the IT organization around the CIO, you basically find the people who are experts in the areas that you’re not, and bring them on board, right? And when I look across my team, I come with a clinical background, but I don’t come with the level of technological background that others have. So I need to make sure I have a really strong team with that background—which I do—to counter that gap. So what I’m saying is that it’s more about the team than the CIO. The CIO has to take into account the strategies the organization’s working with, and the team’s knowledge. And they have to be humble and ask a lot of questions and be willing to learn—and that may not necessarily be the strongest strength of MDs [chuckles]. But I get to use what my team develops, and that helps me also to relate to one of our customer bases, which is clinicians. I think that a CIO who is not an MD who has really strong clinical leadership under them, will have that covered as well. So I think it’s important to understand what you have in terms of strengths.

And you have a CMIO reporting to you?

Yes, I have a CMIO and CNIO both reporting to me.

How does that work? Is it better, being a physician CIO, with a CMIO reporting to you? Does it help both positions?

It’s phenomenal, actually, both [individuals] are. And we do different jobs; when I was the CMIO, I was really focusing on synching systems and working through clinician workflow and providing real-time alerts and clinical decision support. I don’t do that job anymore; I’m much more focused on the broad running of the organization. So I support my CMIO and CNIO in their efforts; it’s all working out very well.

And you speak the same language, as fellow clinicians, of course—that must be helpful.

Yes, I agree, that’s very helpful.

What are a few of the big things coming up in the next few years for you and your team?

A lot is around analytics and precision medicine; about how to use artificial intelligence, and about how to use NLP [natural language processing] to extract key information from unstructured data, and to support research. And on the technology side of the envelope, continuing to push the envelope in terms of providing excellent products for our clinicians to use. And on the patient-facing side of the world, we’ll be focusing on providing excellent portals and providing information for patients online, and providing patient-facing apps.

We want to keep engaging our patients. We have a patient-focused technology council, so we get to show them the technologies that we’re working on, and ask for their advice and feedback. We have about 10 patient representatives on that. They meet quarterly and it’s been in existence since April 2015.

All CIOs are facing a tsunami of things that have to be done, these days. Are you optimistic, going forward, when you look at all that needs to be done at UCLA Health?

Yes, I am. I think that this is an incredibly exciting time, actually; there’s no better time to be a CIO. We have incredible challenges, but the information needs have never been more important. So we definitely have a seat at the table now. And patients have never been considered a customer of IT, but more than ever, patients are interacting with our information. So we’ve really had to shift our thinking to be more patient-focused, population-focused, analytics-focused. It’s incredibly exciting; every day, I come to work and there are five or six new challenges to work on.

 


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Across the Care Continuum, Improving Patient Matching Capabilities Has Become Paramount

December 13, 2018
by Rajiv Leventhal, Managing Editor
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Combining its internally developed “common key” service with a big data MPI platform, MiHIN is uniquely identifying patients at a much higher rate than ever before

Patient matching—the ability to accurately link all of a patient’s health data within and across health systems—has been a challenge for the healthcare industry for decades, and the lack of a nationwide patient matching strategy remains one of the largest unresolved issues in the safe and secure electronic exchange of medical data.

In a 2014 report about the issue, the Office of the National Coordinator for Health Information Technology (ONC) found the best error rate among healthcare providers is around 7 percent, though the error rate is typically closer to 10 to 20 percent within healthcare entities, and this rises to 50 to 60 percent when entities exchange information with each other.

And for health information exchanges (HIEs), the issue is often compounded as they specifically face a significant challenge with matching and linking patient identities because of the diversity and independence of the institutions they serve.

To this end, the Michigan Health Information Network (MiHIN)—a state-designated entity that facilitates information sharing among the state's numerous HIEs and hundreds of thousands of providers—has embarked on a major project: standardizing patient matching across all these different entities in the state.

Specifically, MiHIN officials said in an August announcement that the HIN uses the big data MPI (master patient index) from California-based clinical data exchange company 4medica, along with a private patient attribute or “common key” that links individuals and their health information across systems and organizations. The combined solution enables MiHIN to match patient identities in real time, officials noted.

Shelley Mannino-Marosi, MiHIN's senior director of state and national programs, says in a recent interview that in the early stages, MiHIN’s leaders were entirely determined to only aim for exact matching. “At MiHIN, and in Michigan, our goal is to get the right information about the right patient to the right care team member or provider at the point of care in near real time,” she says.

To help reach that goal, Mannino-Marosi points to one of MiHIN’s core services, its active care relationship service, or ACRS, which enables organizations to submit data files which record the care team relationships attributing a particular patient with health professionals at that organization. As Mannino-Marosi explains, this service enables a provider or payer to “declare” a patient, so that if something happens to him or her, such as a hospital admission, ACRS can be searched to see what providers or health plans have declared that relationship with the patient, leading to that stakeholder getting a notification.

Early on in the process, MiHIN’s staff would search the service and compare the demographics on an incoming ADT (admission, discharge, transfer) notification with the data that was stored in ACRS. “And we would look for an exact match only. We were very cautious in wanting to be extremely accurate and ensure we weren’t sending the incorrect information to the wrong place,” Mannino-Marosi says.

But over time, MiHIN’s leaders realized that there was a need to be more probabilistic. For example, Mannino-Marosi offers that if a patient’s first name is Bill and his doctor has already declared a relationship with this person as William, with the same date of birth, address and social security number, a computer can easily determine that Bill and William are in fact the same person. But with MiHIN’s early-stage patient matching system, the stakeholder who declared that patient would not receive this alert since the demographic information was not an exact match.

So what MiHIN did next was develop its in-house common key service that assigns a “key” or “ID” attribute to each patient. This information was funneled to the centralized MPI from 4medica, and then the common key, or attribute, is given back to the participating organization so that it could be stored in its system to add to any subsequent information, or to strengthen the matching that’s being done in ACRS. Essentially, explains Mannino-Marosi, “the common key becomes a shared attribute that MiHIN’s participating organizations could use to talk to the HIN or to one another.”

When used in action, 4medica’s big data MPI and the common key service can now determine with certainty that even if there’s just a bit of a difference in demographic information, the inbound ADT message is in fact talking about the same patient that the doctor cares about, Mannino-Marosi attests. Gregg Church, president of 4medica, adds, “It’s a guaranteed match even though the demographic change is in there, as we know it’s the same person based on everything that’s being looked at and scored against on the historical information.”

Notably, Mannino-Marosi contends that the common key service acts as a “gatekeeper” to the MPI and won’t automatically add information for patients when they don’t meet a certain threshold for the quality of the data. She explains that if the common key service queries the MPI and knows with certainty that a given patient is in the system, that unique attribute can be used. And at the same time, if the service knows that the person is brand new, he or she is assigned a new key and added to the MPI.

But where things can get tricky is the “middle zone” where it’s too close to call and the computer, as configured, isn’t 100 percent confident. “In that case, we will not assign a common key and will [instead] provide an error message back to the organization,” says Mannino-Marosi. That way, the cleanup of the data is also shared across the state, so the burden of data stewardship is spread out and everyone benefits from the data cleansing activities—as opposed to the person being added to the MPI and potentially pulling redundant information, she adds.

When it comes to evaluating the results of this system, Mannino-Marosi points out that some patient matching companies will boast about 100 percent or near 100 percent matching, but the criteria they are using to match is a grey area. For MiHIN, she notes, one key measure is how many unique identities they have been able to assess in Michigan. “Over a year-and-a-half, we have been able to uniquely identify nearly 8 million of the 9 million Michigan residents, and that number is of course growing,” she says.

Beyond that, another massively important metric to measure is if MiHIN can send more information to more care team members as a result of the service. “If I have three members of our care team but just one is notified, that doesn’t achieve our mission to ensure we’re getting the right information where it needs to go so that a singular patient’s care can be coordinated cost effectively and quickly,” Mannino-Marosi says. But by using the common key service with the 4Medica MPI, MiHIN has been able to send out well over a million more ADT notifications per week. “That’s very significant,” she asserts.

It’s important to note that the common key service from MiHIN is unique to Michigan, and other organizations that do not develop their own unique identifiers are using patient matching solutions—such as 4medica’s big data MPI—in a more conventional manner.

One such entity is the Nebraska Health Information Initiative (NeHII), a statewide HIE that is using the solution to assign unique patient identifiers to patient identities and to match incoming patient data to the right master patient record. According to Jamie Bland, NeHII’s CEO, because her HIE is a qualified clinical data registry for quality reporting purposes, it needed a robust solution that would be able to match patients across various complex data sets. The goal at NeHII, Bland says, “is to grow a true population health repository that matches patients. We can do better population health management and that starts with the identity matching aspect of data management.”

Currently, NeHII collects data from nearly 70 different hospital sources, and more than 200 sources in total across the state and region, says Bland. And because different hospital electronic health records (EHRs) have different matching algorithms for how they match patients, the level of complexity meant that the HIE needed to prioritize identity matching as it continued to grow in the diversity of data it was collecting.  

Bland says that the idea is to marry clinical data, along with claims data and PDMP (prescription drug monitoring program) data so that a population health utility is created. “That’s the last mile of interoperability,” she says. “We are here as a public service to assist in improving identity matching across the state so that we can build a population health infrastructure to make that a solid suite of applications that’s available through the HIE.”


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Becoming a Data-Driven Ecosystem: How San Diego County is Moving the Needle

December 11, 2018
by Rajiv Leventhal, Managing Editor
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Collaboration around information sharing and integration is serving as the foundation for a person-centered healthcare environment in San Diego

“Living well" would be an accurate way to describe the experiences of tourists who visit San Diego, often for its miles of white-sand beaches and amazing weather. But behind the scenes, too, city healthcare leaders have been working hard on their own version of living well.

Indeed, a strategic vision known as “Live Well San Diego”—the city’s 10-year plan to focus on building better health, living safely and thriving—has provided a foundational base for how healthcare in San Diego should be imagined. Essentially, the strategy aligns the efforts of individuals, organizations and government to help all 3.3 million San Diego County residents live well, the region’s health officials say.

As Nick Yphantides, M.D., the chief medical officer for San Diego County’s medical care services division, puts it in a recent sit-down interview with Healthcare Informatics, “It’s not just about healthcare delivery, but it’s about the context and environment in which that delivery occurs.” Expanding on that, Yphantides notes that the key components for Live Well San Diego are indeed health, safety, and thriving, and within these larger buckets are critical care considerations such as: economic development, vitality, social economic factors, social determinants of health, preparedness and security, and finally, being proactive in one’s care.

So far, through the Live Well San Diego initiative, the city has created more than 8,000 healthcare jobs over a five-year span and more than 1.2 million square feet of additional hospital space, according to a 2017 report on Southern California’s growing healthcare industry.

From here, the attention has turned to improving the data sharing infrastructure in the city, a significant patient care challenge that is not unique to San Diego, but nonetheless critical to the evolution of any healthcare market that is progressing toward a value-based care future. To this end, toward the end of 2016, ConnectWellSD, a county-wide effort to put Live Well San Diego into action, was launched with the aim to improve access to county health services, serving as a “one-stop-shop” for customer navigation. Officials note that while still in the early stages of development, ConnectWellSD will implement new technologies that will allow users to perform functions such as looking up a customer file, making and managing referrals, or sharing case notes.

Carrie Hoff, ConnectWellSD’s deputy director, says the impetus behind the web portal’s launching was the need to pull disparate data together to have a fuller view of how the individual is being serviced, in compliance with privacy and confidentiality. “Rounding up that picture sets ourselves up to collaborate across disciplines in a more streamlined way,” Hoff says.

Moving forward, with the ultimate goal of “whole-person centricity” in mind, San Diego health officials envision a future in which ConnectWellSD, along with San Diego Health Connect (SDHC)—the metro area’s regional health information exchange (HIE)—and the area’s “2-1-1 agency,” which houses San Diego’s local community information exchange (CIE), all work in cohesion to create a longitudinal record that promotes a proactive, holistic, person-centered system of care.

Yet as it stands today, “From a data ecosystem perspective, San Diego is still a work in progress,” Yphantides acknowledges. “But we’re looking to really be a data-driven, quantified, and outcome-based environment,” he says.

To this end, SDHC is an information-sharing network that’s widely considering one of the most advanced in the country. Once federally funded, SDHC is now sustained by its hospital and other patient care organization participants, and according to a recent newsletter, in total, the HIE has contracted with 19 hospitals, 17 FQHCs (federally qualified health centers), three health plans and two public health agencies.

The regional HIE was shown to prove its value during last year’s tragic hepatitis A outbreak in San Diego County amongst the homeless population that resulted in 592 public health cases and 20 deaths spanning over a period of a little less than one year. In an interview with Healthcare Informatics Editor-in-Chief Mark Hagland late last year, Dan Chavez, executive director of SDHC, noted that the broad reach of his HIE turned out to be quite helpful during this public health crisis.

Drilling down, per Hagland’s report, “Chavez is able to boast that 99 percent of the patients living in San Diego and next-door Imperial Counties have their patient records entered into San Diego Health Connect’s core data repository, which is facilitating 20 million messages a month, encompassing everything from ADT alerts to full C-CDA (consolidated clinical documentation architecture) transfer.”

According to Chavez, “With regard to hep A, we’ve done a wonderful job with public health reporting. I venture to say that in every one of those cases, that information was passed back and forth through the HIE, all automated, with no human intervention. As soon as we had any information through a diagnosis, we registered the case with public health, with no human intervention whatsoever. And people have no idea how important the HIE is, in that. What would that outbreak be, without HIE?”

To this point, Yphantides adds that to him, the hepatitis A crisis was actually not as much about an infectious outbreak as much as it was “inadequate access, the hygienic environment, and not having a roof over your head.” Chavez would certainly agree with Yphantides, as he noted in Hagland’s 2017 article, “We’re going through a hepatitis A outbreak, and we’re coming together to solve that. We have the fourth-largest homeless population in the U.S.—about 10,000 people—and this [crisis] is largely a result of that. We’re working hard on homelessness, and this involves the entire community.”

Indeed, while administering tens of thousands of hepatitis A vaccines—which are 90 percent effective at preventing infection—turned out to be a crucial factor in stopping the outbreak, there were plenty of other steps taken by public health officials related to the challenges described above. Per a February report in the San Diego Union-Tribune, some of these actions included “installing hand-washing stations and portable toilets in locations where the homeless congregate and regularly washing city sidewalks with a bleach solution to help make conditions more sanitary for those living on the streets.” What’s more, Family Health Centers of San Diego employees “often accompanied other workers out into the field and even used gift cards, at one point, to persuade people to get vaccinated,” according to the Union-Tribune report.

Yphantides notes that the crisis required coordinated efforts between the state, the city, and various other municipalities, crediting San Diego County for its innovative outreach efforts which he calls the “Uberization of public health,” where instead of expecting people to come to healthcare facilities, “we would come to them.” He adds that “hep A is so easily transmissible, and it would have been convenient to say that it’s a homeless issue, but based on how easily it is transmitted, it could have become a broader general population factor for us.”

Other Regional Considerations

Beyond the problem of homelessness in San Diego, which Jennifer Tuteur, M.D., the county’s deputy chief medical officer, medical care services division, attributes to an array of factors, some unique to the region, and others not: from the warm year-round weather; to the many different people who live in vastly different areas, ranging from tents to canyons to beaches and elsewhere; and to the urbanization of downtown and the building of new stadiums; there are plenty of other market challenges that healthcare leaders must find innovative solutions to.

For instance, says Yphantides, relative to some parts of the U.S., although California has made great strides in expanding insurance coverage, due to the Affordable Care Act—which lowered the state’s uninsured rate to between 5 and 7 percent—there are still core challenges in regard to access. “We’re still dealing with a fragmented system; like many parts of the U.S, we are siloed and not an optimally coordinated system, especially when it comes to ongoing challenges related to behavioral health,” he says, specifically noting issues around data sharing, the disparity of platforms, a lack of clarity from a policy perspective, and guidance on patient consent.

To this end, San Diego County leaders are looking to bridge the gap between those siloes while also looking to bridge the gap between the healthcare delivery system, having realized how important the broader ecosystem is, Yphantides adds. “But what does that look like in terms of integrating the social determinants of health? Who will be financing it, and who will be responsible for it? You have a tremendous number of payers who all have a slice of the pie,” he says.

Speaking more to the behavioral health challenges in the region, Yphantides says there are “real issues related to both psychiatric and substance abuse.” And perhaps somewhat unique to California, due to the cost of living, “we have tremendous challenges in relation to the workforce. So being able to find adequate behavioral health specialists at all levels—not just psychiatrists—is a big issue.”

What’s more, while Yphantides acknowledges that every state probably has a similar gripe, when looking at state reimbursement rates for MediCal, the state’s Medicaid program, California ranks somewhere between 48th and 50th in terms of compensation for Medicaid care. Put all together, given the challenges related to Medicaid compensation, policy, data sharing, workforce and cost of living issues, “it all adds up with access challenges that are less than ideal,” he attests.

In the end, those interviewed for this story all attest that one of the unique regional characteristics that separates San Diego from many other regions is the constant desire to collaborate, both at an individual level and an inter-organization level. Tuteur offers that San Diego residents will often change jobs or positions, but are not very likely to leave the city outright. “That means that a lot of us have worked together, and as new people come in, that’s another thing that builds our collaboration. I may have worn [a few different] hats, but that commitment to serving the community no matter what hat we wear couldn’t be stated enough in San Diego.”

And that level of collaboration extends to the patient care organization level as well, with initiatives such as Accountable Communities for Health and Be There San Diego serving as examples of how providers on the ground—despite sometimes being in fierce competition with one another—are working to better the health of their community. “Coopetition—a hybrid being cooperation and competition—describes our environment eloquently,” says Yphantides.

Learn more about San Diego healthcare at the Southern California Health IT Summit, presented by Healthcare Informatics, slated for April 23-24, 2019 at the InterContinental San Diego.

 

 

 


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Hawaii’s HIE Leveraging Technology to Improve Patient Identification

November 8, 2018
by Heather Landi, Associate Editor
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Hawaii Health Information Exchange (HHIE), Hawaii’s state-designated HIE, is taking action to improve patient identification and the accuracy of provider data for enhanced care coordination across the state.

HHIE is working with Pasadena, Calif.-based NextGate to implement an enterprise cloud-based master patient index and provider registry software to create a sustainable statewide system of accurate patient and provider data by resolving duplicate and incomplete records.

HHIE was established in 2006 to improve statewide healthcare delivery through seamless, safe and effective health information exchange. The HIE covers more than 1.2 million patients and has more than 450 participants including Castle Medical Center, Hawaii Pacific Health, The Queen's Medical Center, and the state’s largest insurance provider, HMSA.

“Accurate, comprehensive data that flows freely across boundaries is a catalyst for informed, life-saving decision making, effective care management, and a seamless patient and provider experience,” Francis Chan, CEO of HHIE, said in a statement.

Chan adds that the technology updates will help to ensure providers have “timely and reliable access to data to deliver the high-quality level of care every patient deserves.” “We are building a scalable, trusted information network that will positively influence the health and well-being of our communities,” Chan said.

“The partnership will enable HHIE to develop internal support tools to create accurate, efficient patient identity and provider relationships to those patients to support focused coordinated care,” Ben Tutor, information technology manager of HHIE, said in a statement.

Cross-system interoperability is critical to the success of HHIE’s Health eNet Community Health Record (CHR), which has more than 1,200 users and 470 participating physician practices, pharmacies, payers and large healthcare providers that contribute to over 20 million health records statewide. Deployment of the EMPI’s Patient Matching as a Service (PMaaS) solution will support HHIE’s vision of a fully integrated, coordinated delivery network by establishing positive patient identification at every point across the continuum for a complete picture of one’s health, according to HHIE leaders.

By ensuring that each individual has only one record, participants of HHIE will be able to map a patient’s entire care journey for informed decision-making and population health management, HHIE leader say.

The provider registry will synchronize and reconcile provider data across clinical, financial and credentialing systems to enable an accurate directory and referral network of providers. Using a single provider ID, the registry aggregates and maintains up-to-date information about individual providers and provider groups, such as specialties, locations, insurance options, hospital privileges, spoken languages, and practice hours. Providers can also easily identify who else is on their patient’s care team as well as what other clinicians should receive test results, lab reports and other treatment summaries.


 

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