With consumer health records scattered across disparate settings, something as seemingly simple as correctly identifying patients and members across various systems has become a significant challenge. Poor data reconciliation is not just an administrative headache; it’s a problem with serious consequences for patient safety, treatment outcomes, healthcare costs and the patient experience.
Consider the statistics:
When healthcare organizations struggle to reconcile accurate patient and member identities, the consequences extend across the entire healthcare system, resulting in:
Misdiagnosis and Treatment Delays
Gaps in a patient’s medical history can result in unnecessary testing, delayed diagnosis and wasted time identifying the best course of treatment.
Medication Errors
Patients may be prescribed medications that have dangerous interactions with non-documented drugs they’re already taking. Some might continue receiving treatment for conditions they no longer have due to their updated status isn’t reflected across all systems.
Identity Mix-Ups
When multiple people share the same or similar names, records can easily be attached to the wrong person. Similarly, a single person may have records scattered across multiple profiles, such as “John Smith,” “John V. Smith” and “Jon V. Smith.”
Whole person data and insights are vital to transforming the patient experience and providing better outcomes. Here are some recommendations for getting an accurate and complete view of patients and members:
Reconcile data with referential matching.
Referential matching uses the data at hand plus records from hundreds of external data sources. Unlike some matching methods that compare only records within an organization, referential matching provides a broader context that includes data sources such as clinical, laboratory and wearable device data, linking together records common to a single individual.
Ensure accuracy with unique identifiers.
Unique identifiers provide a more secure and reliable way to track patients and members across the healthcare system. These unique IDs allow you to identify duplicate records and match and merge like records. Unlike a Social Security Number identification system, which presents a risk of exposing personal information, unique IDs are designed with privacy and security in mind.
Incorporate social determinants of health data.
Understanding a patient’s lifestyle and socioeconomic circumstances allows for more personalized and effective care. By incorporating social determinants of health data into their records, organizations can address not only the medical aspects of health but also the social factors that influence outcomes.
Augment patient and member demographic profiles.
Patient and member demographic data become outdated quickly. People move, change phone numbers, get married and update email addresses. A robust solution fills in and augments profiles with information from public and proprietary sources. A solution should also use unique identifiers that don’t rely on sensitive personal information. With accurate and current demographic information, organizations can better maintain contact with patients and members, conduct outreach and coordinate care.
As healthcare becomes even more distributed across care settings and providers, the need for accurate, comprehensive patient and member data will only grow. Organizations that invest in solving this challenge will be better positioned to deliver high-quality, coordinated care in the future.
Would you like to learn more about how you can transform the patient and member experience through data and insights? Read our ebook, Solving Mistaken Identities and Reconciling Unmatched Records for an Effortless Patient Journey, and follow Sophia, a fictional patient, as she faces these challenges. Then learn how high-quality data could have made all the difference in her healthcare journey.
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