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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.

Medical Record Duplicates and Overlays Impact the HIM Workflow

Posted on February 10, 2016 I Written By

Erin Head is the Director of Health Information Management (HIM) and Quality for an acute care hospital in Titusville, FL. She is a renowned speaker on a variety of healthcare and social media topics and currently serves as CCHIIM Commissioner for AHIMA. She is heavily involved in many HIM and HIT initiatives such as information governance, health data analytics, and ICD-10 advocacy. She is active on social media on Twitter @ErinHead_HIM and LinkedIn. Subscribe to Erin's latest HIM Scene posts here.

HIM professionals are responsible for many different tasks throughout the day and the highest priority is typically on ensuring the accuracy and integrity of the medical record. There are many obstacles that can threaten the integrity of medical records including accidentally creating duplicate medical record numbers or overlaying patient information in the Master Patient Index (MPI). These issues can be costly not only in productive man hours but in potential patient care delays and HIPAA violations. Monitoring these duplicates and overlays is something that must be done daily to keep records accurate and HIPAA compliant.

I was recently interviewed by John Trader for a podcast on this subject. We discussed the downstream affects of patient duplicates and overlays and how this impacts the HIM professionals’ daily workflow.

Check out this 1 minute clip from the podcast to get a taste of our discussion:

If you want to hear more, you can download the full podcast. Thanks John Trader for having me on your podcast.

If you’d like to receive future HIM posts by Erin in your inbox, you can subscribe to future HIM Scene posts here.