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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.

Two Competing Challenges: Integration and Innovation

Posted on February 23, 2015 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.

In my other post about BIDMC’s webOMR acquisition by Athenahealth, I found this old post from John Halamka about the best of breed healthcare IT application approach and the all in one integrated EHR approach. In that post, I was really struck by the way John Halamka describes the challenge of balancing innovation and integration:

Innovation:

Epic eases the burden of demand management. Every day, clinicians ask me for innovations because they know our self-built, cloud hosted, mobile friendly core clinical systems are limited only by our imagination. Further, they know that we integrate department specific niche applications very well, so best of breed or best of suite is still a possibility. Demand for automation is infinite but supply is always limited. My governance committees balance requests with scope, time, and resources. It takes a great deal of effort and political capital. With Epic, demand is more easily managed by noting that desired features and functions depend on Epic’s release schedule. It’s not under IT control.

Integration:

Most significantly, the industry pendulum has swung from best of breed/deep clinical functionality to the need for integration. Certainly Epic has many features and overall is a good product. It has few competitors, although Meditech and Cerner may provide a lower total cost of ownership which can be a deciding factor for some customers. There are niche products that provide superior features for a department or specific workflow. However, many hospital senior managers see that Accountable Care/global capitated risk depends upon maintaining continuous wellness not treating episodic illness, so a fully integrated record for all aspects of a patient care at all sites seems desirable. In my experience, hospitals are now willing to give up functionality so that they can achieve the integration they believe is needed for care management and population health.

These comments also say something significant about IT governance as well. It’s a challenging balance. Although, it also illustrates why a well done EHR API is so powerful. It allows a large organization to have deep integration into an EHR while not having to sacrifice the ability to innovate. Too bad APIs are Hard and so many EHR vendors haven’t executed on them. We’ll see if FHIR can get us at least part of the way there.

How do you approach innovation and integration in your hospital? What’s the right balance?