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Hospital Patient Identification Still A Major Problem

Posted on April 18, 2018 I Written By

Anne Zieger is veteran healthcare branding and communications expert with more than 25 years of industry experience. and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also worked extensively healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

A new survey suggests that problems with duplicate patient records and patient identification are still costing hospitals a tremendous amount of money.

The survey, which was conducted by Black Book Research, collected responses from 1,392 health technology managers using enterprise master patient index technology. Researchers asked them what gaps, challenges and successes they’d seen in patient identification processes from Q3 2017 to Q1 2018.

Survey respondents reported that 33% of denied claims were due to inaccurate patient identification. Ultimately, inaccurate patient identification cost an average hospital $1.5 million last year. It also concluded that the average cost of duplicate records was $1,950 per patient per inpatient stay and more than $800 per ED visit.

In addition, researchers found that hospitals with over 150 beds took an average of more than 5 months to clean up their data. This included process improvements focused on data validity checking, normalization and data cleansing.

Having the right tools in place seemed to help. Hospitals said that before they rolled out enterprise master patient index solutions, an average of 18% of their records were duplicates, and that match rates when sharing data with other organizations averaged 24%.

Meanwhile, hospitals with EMPI support in place since 2016 reported that patient records were identified correctly during 93% of registrations and 85% of externally shared records among non-networked provider.

Not surprisingly, though, this research doesn’t tell the whole story. While using EMPI tools makes sense, the healthcare industry should hardly stop there, according to Gartner Group analyst Wes Rishel.

“We simply need innovators that have the vision to apply proven identity matching to the healthcare industry – as well as the gumption and stubbornness necessary to thrive in a crowded and often slow-moving healthcare IT market,” he wrote.

Wishel argues that to improve patient matching, it’s time to start cross-correlating demographic data from patients with demographic data from third-party sources, such as public records, credit agencies or telephone companies, what makes this data particularly helpful is that it includes not just current and correct attributes for person, but also out-of-date and incorrect attributes like previous addresses, maiden names and typos.

Ultimately, these “referential matching” approaches will significantly outperform existing probabilistic models, Wishel argues.

It’s really shocking that so many healthcare organizations don’t have an EMPI solution in place. This is especially true as cloud EMPI has made EMPI solutions available to organizations of all sizes. EMPI is needed for the financial reasons mentioned above, but also from a patient care and patient safety perspective as well.

Understanding Cloud EMPI with Shaz Ahmad from NextGate

Posted on March 21, 2018 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

Readers of this blog have no need for me to explain the importance of an effective EMPI (Enterprise Master Patient Index) in their organization. Ensuring the right identity of your patients in disparate systems is essential to effectively running a healthcare organization from both a financial and a patient safety perspective.

While every healthcare organization knows they need EMPI, many aren’t as familiar with the new cloud EMPI options that are available on the market today. In order to shed some light on cloud EMPI, I sat down with Shaz Ahmad, VP Cloud Operations and Delivery at NextGate at HIMSS 2018 to look at the advantages and disadvantages of moving to the cloud for your EMPI. Plus, we dive into topics like the cost of cloud EMPI and security concerns some might have with a cloud EMPI solution.

If you’re looking at moving your EMPI to the cloud or wondering if you should, take a minute to watch this interview to learn more about what it means to move your EMPI to the cloud.

What’s your organization’s approach to EMPI? Are you already using cloud EMPI? Are you considering a move to the cloud? What’s keeping you from moving there? We look forward to hearing your thoughts and perspectives in the comments.

EMPI is so important in healthcare and I really like how cloud EMPI can solve a challenging problem in a simple, cost effective way for many healthcare organizations and healthcare IT vendors.

Note: NextGate is a sponsor of Healthcare Scene.

Breaking Bad: Why Poor Patient Identification is Rooted in Integration, Interoperability

Posted on December 20, 2017 I Written By

The following is a guest blog post by Dan Cidon, Chief Technology Officer, NextGate.

The difficulty surrounding accurate patient ID matching is sourced in interoperability and integration.

Coordinated, accountable, patient-centered care is reliant on access to quality patient data. Yet, healthcare continues to be daunted by software applications and IT systems that don’t communicate or share information effectively. Health data, spread across multiple source systems and settings, breeds encumbrances in the reconciliation and de-duplication of patient records, leading to suboptimal outcomes and avoidable costs of care. For organizations held prisoner by their legacy systems, isolation and silo inefficiencies worsen as IT environments become increasingly more complex, and the growth and speed to which health data is generated magnifies.

A panoramic view of individuals across the enterprise is a critical component for value-based care and population health initiatives. Accurately identifying patients, and consistently matching them with their data, is the foundation for informed clinical decision-making, collaborative care, and healthier, happier populations. As such, the industry has seen a number of high-profile initiatives in the last few years attempting to address the issue of poor patient identification.

The premature end of CHIME’s National Patient ID Challenge last month should be a sobering industry reminder that a universal solution may never be within reach. However, the important lesson emanating in the wake of the CHIME challenge is that technology alone will not solve the problem. Ultimately, the real challenge of identity management and piecing together a longitudinal health record has to do with integration and interoperability. More specifically, it revolves around the demographics and associated identifiers dispersed across multiple systems.

Because these systems often have little reason to communicate with one another, and because they store their data through fragmented architecture, an excessive proliferation of identifiers occurs. The result is unreliable demographic information, triggering further harm in data synchronization and integrity.

Clearly, keeping these identifiers and demographics as localized silos of data is an undesirable model for healthcare that will never function properly. While secondary information such as clinical data should remain local, the core identity of a patient and basic demographics including name, gender, date of birth, address and contact information shouldn’t be in the control of any single system. This information must be externalized from these insulated applications to maintain accuracy and consistency across all connected systems within the delivery network.

However, there are long-standing and relatively simple standards in place, such as HL7 PIX/PDQ, that allow systems to feed a central demographic repository and query that repository for data. Every year, for the past eight years, NextGate has participated in the annual IHE North American Connectathon – the healthcare industry’s largest interoperability testing event. Year after year, we see hundreds of other participating vendors demonstrating that with effective standards, it is indeed possible to externalize patient identity.

In the United Kingdom, for example, there has been slow but steady success of the Patient Demographic Service – a relatively similar concept of querying a central repository for demographics and maintaining a global identifier. While implementation of such a national scale service in the U.S. is unlikely in the near-term, the concept of smaller scale regional registries is clearly an achievable goal. And every deployment of our Enterprise Master Patient Index (EMPI) is a confirmation that such systems can work and do provide value.

What is disappointing, is that very few systems in actual practice today will query the EMPI as part of the patient intake process. Many, if not most, of the systems we integrate with will only fulfill half of the bargain, namely they will feed the EMPI with demographic data and identifiers. This is because many systems have already been designed to produce this outbound communication for purposes other than the management of demographic data. When it comes to querying the EMPI for patient identity, this requires a fundamental paradigm shift for many vendors and a modest investment to enhance their software. Rather than solely relying on their limited view of patient identity, they are expected to query an outside source and integrate that data into their local repository.

This isn’t rocket science, and yet there are so few systems in production today that initiate this simple step. Worse yet, we see many healthcare providers resorting to band aids to remedy the deficiency, such as resorting to ineffective screen scraping technology to manually transfer data from the EMPI to their local systems.

With years of health IT standards in place that yield a centralized and uniform way of managing demographic data, the meager pace and progress of vendors to adopt them is troubling. It is indefensible that a modern registration system, for instance, wouldn’t have this querying capability as a default module. Yet, that is what we see in the field time and time again.

In other verticals where banking and manufacturing are leveraging standards-based exchange at a much faster pace, it really begs the question: how can healthcare accelerate this type of adoption? As we prepare for the upcoming IHE Connectathon in January, we place our own challenge to the industry to engage in an open and frank dialogue to identify what the barriers are, and how can vendors be incentivized, so patients can benefit from the free flow of accurate, real-time data from provider to provider.

Ultimately, accurate patient identification is a fundamental component to leveraging IT for the best possible outcomes. Identification of each and every individual in the enterprise helps to ensure better care coordination, informed clinical decision making, and improved quality and safety.

Dan Cidon is CTO and co-founder NextGate, a leader in healthcare identity management, managing nearly 250 million lives for health systems and HIEs in the U.S. and around the globe.