Cost containment, preventive care and patient engagement are all the rage when it comes to value-based care. It's about helping patients lead healthy lives while also cutting costs and being cognizant of administrative and clinical efficiencies. While these are all important initiatives, it's impossible to provide value-based care effectively without the ability to link patient identities across the care continuum. Why? Patient matching enables organizations to:
- Improve patient safety
- Reduce redundant tests and services
- Prevent unnecessary hospitalizations
- Boost physician and staff productivity
Most recently, Congress validated the importance of patient matching. The U.S. House of Representatives recently repealed a ban on federal funds to adopt a unique patient identifier. Repealing the ban would allow the U.S. Department of Health and Human Services to collaborate with the private sector to identify solutions for reducing medical errors while also protecting patient privacy. As of press-time, the Senate had yet to vote on the bill.
Patient matching is critical for all healthcare organizations and particularly those involved in mergers and acquisitions. It's also important as hospitals and health systems join Accountable Care Organizations that depend on care coordination and accurate patient matching. Without a patient matching strategy, disparate electronic health records (EHR) leave organizations extremely vulnerable to medical errors and unnecessary costs.
Consider the preventable costs associated with a patient who undergoes two MRIs because of a spelling error, preventing staff from locating his record that includes results from the original test. Or a patient who undergoes additional unnecessary tests after her breast biopsy results are mismatched with that of someone with the same name. Or a patient who develops complications necessitating hospitalization after a provider prescribes her the wrong medication because allergy information is partially spread across multiple duplicate records. These types of errors occur every day and in every setting. Every scan, lab test, doctor’s appointment and hospital stay becomes an additional point where mistakes can be introduced into the medical record.
Even organizations participating in a health information exchange (HIE) continue to struggle with identity management challenges. Although some HIEs help organizations clean up their data, challenges related to data quality and completeness as well as a lack of data standardization make patient matching in HIEs extremely difficult. The responsibility ultimately lies with the hospital or health system to develop a patient matching strategy that enables value-based care and that ultimately improves patient safety.
Consider these three tips to create a patient matching strategy that lays the foundation for value-based care:
1. Standardize data collection system-wide. For example, will the organization use 'street' or 'St.' in the address field? A recent study¹ found that standardizing addresses using the U.S. Postal Services standard could improve match rates by up to three percent. This doesn't sound like a lot, but when extrapolated nationwide, it equates to tens of thousands of records or more per day. When standardizing addresses and last names, match rates improve by up to eight percent. Other questions to consider: Will the organization hyphenate two-word last names? Will it use middle initial or full middle name? Will it use 'Jr.' or 'II'? Standard formatting is just as important as the type of information the organization collects. For example, will it collect birth order (for multiples)? Email addresses? Biometric information? Maiden name? Previous address?
2. Provide ongoing education to registration personnel. Data standardization begins with highly-trained registration staff. Many organizations have found success with a centralized registration model; however, what's most important is that staff understand the gravity of the information they collect. Training should include the following topics: Criteria to use when searching for a patient, acceptable methods to verify a patient's identity, specific scripted (and standardized) questions to ask during the registration process, how to handle emergency scenarios and more.
3. Focus on data cleansing, linking. Because human error is not entirely avoidable, organizations should also utilize data management services. Using dynamic, statistically-based linking technologies and vast referential databases, an external data partner can validate patient contact information, augment records using public and proprietary information and create a unique non-SSN dependent identifier that acts as the linking agent for all data points associated with a specific individual. A data partner can also scrub massive patient databases to identify duplicate records that staff can remove or merge, helping to reduce digital storage costs and streamline operational efficiencies.
Patient matching must be a critical part of the conversation about value-based care. An organization’s efforts to improve outcomes and reduce costs may be quickly eclipsed by an inability to match patients to records with confidence.
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