Patient Matching Strategies In An M&A Environment
By Dan Cidon, Chief Technology Officer, NextGate
Despite intense efforts and significant investments to implement EHRs, duplicate records continue to plague providers. Patient data matching functionalities within EHRs often lack the complexities to reconcile records from disparate and external systems. The resulting number of duplicate and incomplete records leads to patient safety errors, skewed reporting and analytics, administrative burdens, and lost revenue.
This becomes even more problematic following a merger or acquisition — as providers look to remain competitive, reduce costs, increase market share, and transition to value based care models. In this “bigger is better” environment, harmonizing records from other hospitals, medical groups, outpatient clinics, and affiliated subsidiaries when establishing a larger integrated delivery network, is an essential component in effectively managing patients across the care continuum.
Whether converting to a single enterprise EHR or connecting existing legacy applications via a best-of-breed approach, consolidating patient and provider data following a hospital transaction is a significant undertaking with profound implications for quality and outcomes. The absence of just a single medication in an individual’s record can greatly impact a decision made by a clinician. A longitudinal view of patient information across the care continuum is not only essential for informed clinical-decision making and patient safety, but also supports a seamless patient experience during every encounter within the network.
A sound patient ID management strategy when undergoing a hospital merger or acquisition facilitates interoperability across organizational, geographic, and technological boundaries and ensures patients are accurately and consistently matched with their data. However, this cannot be solved by any one EHR vendor alone. While the industry awaits the fruition of a national patient identifier, leveraging an enterprise master patient index (EMPI) is essential in helping evolving IDNs map, reconcile, and de-duplicate records whenever a consolidation or acquisition occurs to ensure data is orchestrated seamlessly across the network. EMPIs correlate and cross reference patient IDs across various systems and settings by linking individual records and preventing the creation of new ones.
Beyond removing duplicates and automating record cleanup, an EMPI enables access to patient data in a single location. An enterprise unique identifier (EUID) generated by an EMPI serves as a link to an individual’s record in any system, streamlining clinical and administrative workflows for patient data access points like medication history, lab results, and visit summaries.
Enterprise EHR Or Best Of Breed?
Following a merger, CIOs and their organizations must decide whether to start over with the newly acquired facility and perform a “rip and replace,” or preserve its existing IT applications and map the data to a designated third party platform.
Moving to a single enterprise EHR is an approach some healthcare institutions are taking to streamline documentation and standardize workflow protocols. This can provide benefits in information sharing within the network — provided every patient record is correctly and uniquely identified. An integrated platform across the enterprise can also be favorable for IDNs that anticipate future growth or expansion.
While a one-size-fits all EHR approach might be suitable for some organizations, it’s important to note that consolidating patient data into a single EHR is both capital and labor intensive. It’s a massive financial undertaking that can take years to implement, as changes to internal processes and workflows are instituted — all while simultaneously keeping the lights on.
Another such data integration strategy is a best of breed approach, in which health systems “glue together” multiple applications across the IDN. Standards such as HL7’s FHIR have made it easier for organizations to break down data silos and integrate information from various systems.
Operating in a single-system EMR environment can be especially challenging for physicians and small practices that work with applications very different from those of large IDNs and hospitals. While patient data remains decentralized, best-of-breed allows the IDN to select the best system for each functionality rather than having a single system perform all functions.
Many CIOs argue, however, best-of-breed platforms make for a difficult IT ecosystem in terms of interoperability and technical support, since a multi-vendor system does not provide the same simplified environment as a single vendor approach.
It’s still unclear if a single enterprise versus best-of-breed approach has an advantage in healthcare. Many health IT executives we spoke to at HIMSS are realizing the functionality they forfeited for an enterprise EHR platform is coming at a cost in terms of clinical and administrative workflow, while those that have opted for best of breed are yearning for fully unified health information exchange.
A Single Identifier For Patients
In either case, an EMPI can complement the approach of choice without sacrificing clinical workflow, data exchange or care coordination. IDNs utilizing an EMPI can reconcile and de-duplicate patient records at any newly acquired provider where it can then be imported and checked against the primary or existing EMR system. The EMPI can uncover individuals who have received care at both organizations — even when the records don’t match exactly.
For example, in cases where a female patient received care at one facility as a child without a recorded Social Security Number, and in another after marrying, the EMPI can spot the same first name and birth date, and flag it. This ensures each medical record matches one-to-one for every patient when an acquired system goes live. EMPI algorithms account for data errors and variances, nicknames and aliases, phonetic spellings, multiple births, and “Jane Doe’s.” EMPIs can perform cross-facility patient record matching and clean up, and identify duplicate records within the same system or across disparate systems that house historical patient data for more thorough health information management research
The EMPI also allows an individual’s data to be reconciled in real time following a go-live, so the individual is identified the moment he or she enters the system, thus avoiding the creation of new duplicates.
As a centralized index of patient demographics, an EMPI enables enterprise-wide patient searches and seamless data exchange, regardless of the organization’s data migration approach.