Combating Patient Identification Errors 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.

The Need for Integrating Data

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:

  • Recognize patients at each point of contact
  • Accurately track patient records across disparate clinical and ambulatory systems
  • Receive and consolidate data from outside sources
  • Associate clinical results with the correct patient
  • Identify a patient’s care team and recognize overlaps
  • Prevent duplicate or unnecessary tests and procedures
  • Provide superior service to patients who visit multiple facilities within the enterprise
  • Lower costs due to inefficient processes
  • Utilize data for analytics

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).

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. Further, it is becoming increasingly important as organizations seek to improve care coordination and safety, eliminate waste and inefficiency, engage patients as consumers and incentivize providers to achieve better outcomes.

MDM Technology Benefits

Master data management (MDM) technology is becoming a critical component of any organization that manages patient and provider data, including hospitals, ACOs, HIEs and payers to list a few. Specifically, an enterprise-wide master patient index (EMPI) based on MDM technology reduces the occurrence of duplicate patient records by increasing the likelihood that patients with previous encounters are identified. According to an April 2106 Emergency Care Research Institute report, , patient identification errors were the second biggest concern following health IT configurations and organizational workflow that do not support each other.

Achieving accurate patient identification is also vital to ensuring that the information presented by and entered into the electronic health record (EHR) is associated with the correct person.

However, processes related to patient identification are complex and require careful planning and attention to avoid errors. The patient or consumer identity must be accurate and linked to the entire health history in order to support the immediate care or wellness event. Once established, the patient or consumer documentation must be linked to other points to create patient-centered care and wellness.

While the majority of U.S. hospitals have some form of EHRs, they don’t tend to communicate with each other. As a recent U.S. News & World Report pointed out, six years after health reform mandated EHRs, the dream has yet to materialize as some 94 percent of U.S. hospitals do have at least rudimentary EHRs, up from just 9 percent in 2008 but they generally don’t communicate with each other – at least not yet.

More particularly, MDM helps healthcare providers create a healthy EMPI by:

  • Employing a probabilistic matching algorithm that uses patient’s first and last names, date of birth, gender, and other attributes, such as SSN, zip code or telephone number.
  • Having policies and procedures that can identify and prevent duplicate patient records and integrate unintentional duplicate records into one complete record.
  • Creating organizational policies that address how to ensure correct patient identification of information from external sources, such as external labs, pharmacies or healthcare providers, and how to monitor compliance with those policies.
  • Updating policies on patient identification related to the master patient index as best practices change.

Better data governance is also a necessary component to reducing duplicate patient records and improving the process for patient matching, according to a new study published in the online journal for the AHIMA Foundation.

“Severe patient-care issues can occur and resources are wasted when systems are inundated with duplicate records,” wrote AHIMA. “Patient safety is a major concern for many organizations, yet it is necessary to increase awareness of the safety, legal, financial, and compliance concerns created by duplicate and overlaid medical records.”

Leveraging MDM technology, hospitals and health systems can enable patient safety, interoperability and analytics through data quality. By identifying and matching duplicate patient records, healthcare institutions can prevent future redundancy by enabling patient safety, patient engagement and a rich analytic and data exchange capability. More importantly, MDM technology can help healthcare institutions to overcome traditional data challenges, solve traditional data and interoperability errors, and apply the data needed for analytics in order to improve patient care and outcomes.

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