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How One HIE Tackled the Challenge of Improving Patient Record Matching

August 17, 2016
by Heather Landi
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SDHC, a not-for-profit HIE, officially evolved from the San Diego Beacon Community, and now connects 25 different clinics and health systems across the San Diego region.
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Six years ago, San Diego Health Connect (SDHC) began as a local health information technology project and has since grown into a regional health information exchange (HIE) that connects San Diego’s three largest health systems and enables the exchange of 3.2 million patients’ electronic medical records (EMRs).

As the HIE has expanded, SDHC leaders have worked to improve the exchange and the quality of the data that’s available through it. That work has come with its share of challenges, and through the use of third-party data quality and data integration technology tools, SDHC has been able to overcome many of these hurdles.

SDHC, a not-for-profit HIE, officially evolved from the San Diego Beacon Community, the largest of the 17 Beacon Community projects that received a total of $250 million in three-year grants from the Health and Human Services Office of the National Coordinator for Health Information Technology (ONC). In April 2010, UC San Diego received a $15.3 million Beacon cooperative agreement from ONC. The San Diego Beacon Community was tasked with building and strengthening local health information technology infrastructure and implementing new approaches for making measurable improvements in the cost and quality of healthcare.

The regional health information exchange was one of the initial projects of that Beacon community, and in 2013, UC San Diego transferred operational and oversight responsibility for the HIE to SDHC. The Beacon grant gave San Diego healthcare organizations a jumpstart for implementing HIE to improve healthcare quality and efficiency, and according to SDHC executive director Dan Chavez, the HIE is further ahead than most HIEs in its development and technological sophistication.

Dan Chavez

The community-wide HIE now  enables the exchange of electronic medical records for 3.2 million patients between 25 different clinics and hospital systems throughout San Diego and Imperial counties, including UC-San Diego Medical Center, Scripps Health, Sharp HealthCare, Kaiser Permanente, Rady Children’s Hospital-San Diego, the U.S. Department of Veteran Services and the County of San Diego Health and Human Services. San Diego is the fifth most populous county in the United States, with three military facilities, 18 federally recognized Indian reservations, 19 acute care hospitals, four non-acute, rehab hospitals, 115 clinics and 9,000 physicians.

SDHC provides healthcare providers with medical records exchange, direct secure messaging and alerts, public health reporting capabilities as well as the EMS Hub, which transmits pre-hospital data from EMS vehicles en route to the hospital.

Throughout the SDHC’s roll out and adoption, the organization’s leaders have faced a significant obstacle that is a common challenge for HIEs—accurate patient identity matching. SDHC is a federated model and does not house medical records, as the clinical data is housed at each of the participating facilities. The HIE uses a master patient index (MPI) as a record locator service to manage the identifying information for 3.2 million people across the San Diego region and to ensure that the records belong to the correct patients. The HIE facilitates 7.5 million transactions a month between the 25 provider institutions.

Using the matching capabilities in the MPI tool, when patient records do not match they end up in an “exception queue.” Due to stringent matching criteria, SDHC’s MPI matching algorithm had, by 2015, excluded 187,000 patient records because of unresolved patient identification, Chavez says. And, each new provider joining SDHC led to more backlog, due to data quality and differences in governance, he says. The HIE also was using a manual data stewardship process. So, the task of addressing the backlog of 187,000 records in the “exception queue” would take eight years for two full-time employees.

Accurate patient identification is not only a data management and data quality issue, it’s also a patient safety issue. As reported earlier this year by Healthcare Informatics, ECRI Institute ranked patient identification errors as second on its list of top 10 patient safety concerns. ECRI Institute analysts discovered that patient identification errors "were not only frequent, but serious.”

In order to develop a better patient matching progress, SDHC convened a working group of 41 HIE members from 13 organizations. As a result of that working group’s efforts, in May 2015, SDHC began a pilot project with health IT startup Verato, a Software-as-a-Service provider that developed a cloud-based patient matching solution.

Accurately identifying people, essentially matching the right record to the right record, is a pervasive problem in healthcare as well as other industries like retail, according to Brent Williams, founder and chief technology officer at Verato.

The problem, Williams says, is that identity data is a collection of attributes which often change over time. For instance, names, addresses, phone numbers, email and marital status can change over time. In addition, there’s also ambiguity with names, such as hyphenated names, nicknames and twins. There can also be spelling errors and homonym errors and data governance issues, such as formatting and data quality. So, one person can be represented by old, incorrect or incomplete data, resulting in different identities across provider systems. The matching capabilities in MPI tools typically result in a 70 percent match rate given typical error rates in identity data, Williams says, and the other 30 percent of unmatched identities must be manually resolved, as the case at SDHC. Or, the identities are falsely categorized as non-matches which prevents the information from reaching a patient’s care providers during the care visit.

Verato launched its technology in 2012 to try to solve this problem and the core of the technology is a specially programmed reference database, Carbon, that’s provided as a service to hospitals and government agencies to reconcile identities faster.

During the pilot project, SDHC employed Verato’s technology and was able to resolve 75 percent of the 187,000 mismatched records, thereby eliminating 75 percent of the manual effort that would have been required to match the 187,000 records in the exception queue. Of the 45,000 in the exception queue not matched, 95 percent were pediatrics patients. In addition, during the pilot project, SDHC was able to boost its patient match rates as the technology platform identified an additional 126,000 patient matches that the MPI algorithms had originally missed. In total, SDHC increased the number of patient record matches in its MPI by 110 percent, Williams says.

Of new matches that were identified during the pilot, 20 percent had at least one critical error, either conflicting birthdates, a difference in last name or a different address. According to Williams, the software utilizes a referential matching engine. “MPI matching, or probabilistic matching, can’t see through different or bad identity data. Referential matching works despite different or bad identify data,” he says.

Due to the success of the pilot program, SDHC has implemented the technology platform, and according to Chavez, it will be used to augment the MPI database through an automated data management feature aimed at detecting matches missed by the standard MPI process.

The combination of high quality data and stringent patient matching standards enables SDHC member providers to have access to a complete picture of a patient’s health information, Chavez says.

“SDHC’s mission is to facilitate the exchange of medical records throughout our region so doctors can provide better patient care, decrease the number of duplicate tests and procedures, and decrease costs,” he says. “Foundational to exchanging records is the ability to match various records that belong to the same patient, and this technology can increase our match rates without sacrificing SDHC’s stringent data governance standards.”

Chavez says the value of the HIE to San Diego health systems includes improving care coordination, improving Meaningful Use compliance and reducing preventable admissions. For physicians, the HIE helps to strengthen provider engagement and reduce costs, and for community clinics, it improves access to relevant patient information and speeds up the referral process. At the same time, the HIE also enables automated real-time public health reporting.

Moving forward, SDHC continues to expand its services and capabilities. California Healthcare Foundation recently awarded SDHC a grant to pilot, implement and maintain a Physician Orders for Life-Sustaining Treatment (POLST) eRegistry in San Diego. San Diego will be the pilot geography to work with a group of diverse local providers to make the POLST forms accessible by a wide variety of disparate organizations and functions, Chavez says. POLST is a standardized medical order form that indicates which specific treatments, such as a ventilator or feeding tube, a seriously ill patient does or does not want. Unlike a health care directive, a POLST form is signed by the patient and physician and is intended to serve as medical orders that move with the patient across settings of care. 




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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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HIE 2.0: CORHIO’s Leaders Map a Pathway to Advanced Data-Sharing Success in Colorado

November 7, 2018
by Mark Hagland, Editor-in-Chief
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CORHIO’s leaders have been involved in intensive work to improve data quality, while expanding data-sharing more broadly

The leader of CORHIO, one of the most progressive health information exchange (HIE) organizations in the country, continue to innovate forward across a broad range of areas. The Denver-based CORHIO already connects 65 hospitals across Colorado—virtually all of the inpatient community and academic facilities in the state—and connects around 5,000 physicians statewide as well.

As the organization’s website notes, “CORHIO empowers people, providers and communities by providing the information they need to improve health. Our advanced health information exchange (HIE) technology, data analytics tools and expert consulting help healthcare providers access information that saves lives, streamlines care coordination, reduces costs, and improves clinical outcomes for millions of people.”

Recently, CORHIO’s leaders, including Morgan Honea, the HIE’s president and CEO, and Mark Carlson, its director of product management, have been pushing ahead to connect providers across the state both more broadly and more deeply—extending out into the behavioral health sphere as well as facilitating the sharing of more granular data across Colorado, through data normalization work. Honea and Carlson spoke recently with Healthcare Informatics Editor-in-Chief Mark Hagland regarding their current initiatives. Below are excerpts from that interview.

You’ve been expanding some of your core data-sharing capabilities of late, correct?

Mark Carlson: Yes; we certainly do have some activity and infrastructure that we’ve been building out. I’ll focus in on clinical and population health first. One area we had identified a couple of years ago in terms of being able to generate information for population health, at the state level, or in partnership with ACOs, came about as the state pushed forward an initiative called “regional care collaboratives” with ACOs. As part of that initiative, we did work on packaging and bundling notifications around ED visits and hospitalizations and discharges, for providers, as well as helping smaller physician practices in that area. And we’ve been looking at expanding out that concept around clinical indicators, initially focusing on labs.

We have 65 hospitals sending data into CORHIO, and we had 30-plus representations as to how a hemoglobin a1c might be represented, in terms of vocabulary and coding. So we used NLP [natural language processing] to help us with that, to help move forward in disease management in areas like diabetes. We’ve also focused on another use case with our Department of Health in Colorado, around an influenza use case, where we’re able to flag a positive influenza use test and track for an inpatient admit that occurs within 48 hours, to map the cost of care as well as the ability to access supporting resources that hopefully would avert an inpatient admission.

That’s what we’re working on—normalization across general labs and clinical metrics; and as we expand our data types, we’re expanding towards social determinants, as well as labs that extend beyond the general labs.

Morgan Honea: I agree with everything that Mark said. I would just add that this is, really, in my opinion, kind of a second evolution around the interoperability question. We’ve got a tremendous HIE with tremendous participation here in Colorado. The important fact is that, after laying the infrastructure for a statewide HIE, it next becomes imperative move into normalization across data sources, so that you’re not changing vocabularies or nomenclature.

That sounds like “HIE 2.0,” in terms of the advanced work, doesn’t it?

Carlson: That’ll work.

What’s next or top priority now for providers?

Honea: Our top priority is to continue to expand the type of data available in the HIE. In that context, we’re facing up to the incredible challenge of continuing to integrate behavioral data into the system. We’re also working with state agencies, to make sure that folks are getting the best care coordination for the best outcomes possible. And probably the highest demand from our clients is fewer queries and more push notifications and types of functionality, greater integration into EHRs [electronic health records] and other population health-type tools, with really clean, neatly packaged data, which is where this conversation becomes more important, because as Mark said, with hemoglobin a1c, things get very messy as the volume of the data grows, if you’re constantly having to clean up the data. So providing the data in interoperable, easily usable ways, is a top priority.

Carlson: And you have to follow the money in terms of reimbursable events and other value-based areas. So as we improve our inbound CCDA-type activities, we want to improve the quality of submission at the level of formatting as well as presence of charted measures, as being able to format and report those out, from practices, including around broader performance measures.

With regard to the capture and sharing of data, are you making any use of artificial intelligence? And where is that going?

Carlson: One of our core initiatives is, how do we become more situationally aware? I’ve looked at FHIR as a path forward, in that context Whereas the CCDA is a blunt-force instrument, FHIR provides the opportunity to be a lot more precise in packaging and bundling data. For example, we’ve been working on a use case for an anesthesiology group. They want to see problems, meds, last treatments, discharge summary, they don’t want to see everything. FHIR helps us to bundle and package data, and then via an API connection, they can receive more precise information that meets their needs, rather than via all-encompassing data. More targeted, based on clinical needs.

Honea: The ability to get down the discrete data level, understand the data points and bundle and share them, is where I think things are going. A CCDA is a big, narrative summary of an encounter, and doesn’t get down to that level of granularity.

Carlson: In the media right now, there’s been a lot of discussion around where the next steps of IBM Watson should be. And we’ve had this discussion with a lot of vendors in the past, where we’ve been introduced to some very compelling functionality; but then some wonderfully designed tools absolutely choke on some of the variability of the nomenclature in the data. And that prevents us from getting to advancing the Quadruple Aim. Those learnings and market information that we’ve gathered over time, indicated our absolute need to partner with organizations that have a foundation for creating mappings that are clinically valid and reliable and backed with the expertise behind it. That can help us get to the population health insights that you’re referencing when you mention AI.

Do you think you’ll be able to incorporate some social determinants of health data into what you’re sharing?

Honea: That’s an area where I’m spending some of my time now. I have no doubt that we’ll run into the same challenges with local code sets and varying terminologies with that type of data that we’ve had with clinical data. I don’t see that that process is strictly limited to hospital and clinic data; I think it will go across all sorts of systems; and when we share from one program to another and one type of data system to another, we’ll face the same types of challenges and requirements for data standardization. So we’ll probably rinse and repeat every time we go out and get another data point.

Carlson: We are working with United Way 211, understanding how their community resources and curated content and partnerships are working, and getting insights from diabetic prevention programs and food banks—the data quality is as variable as some of the source organizations involved. I think this opens up a whole new opportunity for whole-person care, but it will pose some of the types of data normalization and use challenges as clinical data.

How do you see the next few years evolving forward at CORHIO?

Carlson: We’ve touched on a lot of priorities—ECQM work… our learnings in various areas. It’s a big lift to ingest the CCDA documents and get consistency at the data level. Our partner organizations continue to work with us and with Wolters Kluwer, to work on various types of data together. When we spoke at the HIMSS Conference earlier this year, Morgan and I talked a lot about data normalization work and about data visualization, and about being able to visualize risk across counties and the state, to identify pockets of need. And in that context, the social determinants data will help us understand where the food deserts are, and where high levels of chronic diabetics live. We have a number of mountain and rural communities that are fairly isolated, so our opportunities to impact that, are large, but so are the needs, and thus, we need to address data quality issues.

Honea: I agree with everything that Mark said. We’ve got this never-ending effort to include programmatic elements, site-specific elements, into the HIE, every kind of element—that work will never end. But I’m also continually focused on the question of how we as a state, with only 5 million people, can identify ways to leverage the infrastructure built with significant investment at the federal, state, and local levels, to advance our overall HIE efforts as a state, and minimize the risk of continually building new silos of data that will just require new efforts in the same fashion? How do we improve coordination when folks are moving across different geographies or service areas, without rebuilding existing infrastructure? How do we partner with communities to get the biggest bang for our buck? That requires a lot of planning and coordination and collaboration.

Carlson: For HIEs to provide value, Morgan and I often say, it’s data versus documents. Document exchange has a very valuable place in the broader landscape, but where the HIEs are differentiating themselves is at local-level attention and relationships and meeting community needs, and where we can operate at the data level to provide the insights to drive patient care quality forward.




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Seven HIEs Now Connected to Military Health System

November 1, 2018
by Heather Landi, Associate Editor
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Seven physician-led health information exchanges (HIEs) are now connected to the Military Health System (MHS), enabling MHS providers to have access to patients’ electronic health records to support clinical decision making at the point of care.

The Kansas Health Information Network (KHIN), the eHealth Exchange, and KAMMCO, a provider of insurance and health care technology services for physicians and other health care professionals, assisted in facilitating the connection.

With this new development, medical records can be shared across the world as military personnel and their families transition between multiple locations, stateside or overseas. Military hospitals and clinics now can quickly and securely access patients' personal health information 24/7 and have access from the physician-led HIEs in Kansas, Connecticut, New Jersey, South Carolina, Georgia, Missouri and Louisiana.

“This represents the growing capabilities of HIEs to share records in all locations from which a patient has received care,” Laura McCrary, executive director of KHIN, said in a statement.

“MHS cares for 9.4 million beneficiaries, delivering care globally in military hospitals and clinics and providing coordinated, integrated care through civilian networks," Kimberly Heermann-Do, Health Information Exchange Office Lead in the EHR Modernization Program Management Office, said. Heermann-Do added, “Through HIEs, records are available securely from the private sector if the HIE is onboarded to the MHS. Having access to records for patients across the KAMMCO network will assist MHS providers with clinical decisions.”

“The Medical Society of New Jersey (MSNJ) has a long history of supporting the healthcare needs of our active duty military in New Jersey. Sharing clinical information from our physician practices with MHS through OneHealth New Jersey furthers our support in this important area,” Larry Downs, MSNJ CEO, said in a statement. “With a large joint base located in New Jersey our physician members provide care to many active duty military and their families.” MSNJ is one of seven medical societies who partner with KAMMCO in the delivery of a physician-led health information exchange platform.

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