Combating Patient Identification Efforts With Master Data Management

Combating Patient Identification Efforts With Master Data Management

Combating Patient Identification Efforts With Master Data Management
From patients and providers to claims and lab results, healthcare organizations are inundated with data. The need for healthcare professionals to understand the whole picture is crucial not only to patient safety and quality of care but also to reducing costs, aiding analytics, streamlining workflow and adhering to regulatory compliance.

Throughout the 21st century, the healthcare industry has fought to regain the culture of innovation and invention that so defined it during the early part of the 20th century, during which dramatic advancements were made to improve the quality of patient care on all levels. The patient, rather than systems and departments, is now the center of every healthcare ecosystem, from clinical research and pharmaceutical manufacturing to integrated delivery networks, regional and governmental exchanges and insurers.  This dramatic change from previous years seeks to improve care coordination, eliminate waste and inefficiency, and engage patients as consumers and providers to be incentivized for better outcomes.

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However, integrating all of this data is challenging because it resides in many different departments and legacy systems with varying degrees of completeness and accuracy. Patient identification and patient matching have long plagued the healthcare continuum and the complexity is increasing as the United States moves to a patient-centered wellness approach.

This has created a need to better understand the individual as a patient, citizen, consumer, subscriber, and beneficiary. This shift is driving basic, advanced, and predictive analytics for which linked records must be created and/or used. Yet, the ability to access and transform the numerous data stores related to health, society, cost, providers, etc. to create a trusted single source of information has been elusive. In fact, without a single view of a patient, healthcare enterprises struggle to:

Consistently identifying each patient at every point of care is imperative to increasing care collaboration and ensuring patient safety. Nevertheless, duplicate patient records are a common problem in healthcare and can cause harm, as they often leave clinicians with an incomplete picture of the patient. This is also true when two different patients’ records are co-mingled. In fact, more than half of health IT management professionals regularly work on fixing problems with patient matching and duplicate patient records, according to a recent survey from the American Health Information Management Association (AHIMA).

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Today, the patient, rather than systems and departments, is the center of every healthcare ecosystem. Accurate patient information is critical from clinical research and pharmaceutical manufacturing to integrated delivery networks, regional and governmental exchanges and insurers.

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