Considerations for Success - Patient Matching

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Considerations for Success - Patient Matching

September 21, 2018

Patient matching compares data sources from different health IT systems, doctors’ offices, and hospitals to decipher if they belong to the same patient. The process recovers data from health records and identifies commonalities based on personal traits, such as demographics, to find a “match.”  Patient matching improves patient safety and clinical care by establishing continuity of care among patients with multiple records at one provider or across various providers. The patient matching process allows organizations to develop a complete record of the patient’s health history and medical care.

Our August Technology & Analytics Workgroup Meeting included executives from 4Medica and the Nebraska Health Information Initiative (NeHII) who suggested the following considerations for success when developing a patient matching solution:

  • Is your enterprise-wide duplication rate below two percent?
  • Does your current Master Patient Index solve all of your identity matching and resolution problems – across all data sources and locations within your organization?
  • Do you feel that you are spending too many resources (money and human capital) to continuously clean up identities in your data sources?
  • Do you currently use unlimited historical and clinical data enrichment available to help with more precise matching?
  • Is your organization at risk by having duplicate identities?

Patient matching has raised fears about false matching, privacy, and consent. According to a survey from Black Book Research, around 33% of all denied claims are linked with inaccurate patient identification, which costs the average hospital $1.5 million and the U.S. healthcare system $6 billion annually. Implementing the appropriate patient matching steps will help your organization better serve patients, while saving money.

To build a 360-degree view of a patient:

  • Share data transparently
  • Promote informed patient-centric care coordination
  • Segregate and identify clinical information from each data source to ensure most up to date information for a patient in real-time.

Press release on the patient matching collaboration between NeHII and 4Medica.