The DFW Hospital Council posts guest blogs by Associate Members. The following was provided by NextGate.
By David Bennett, NextGate
Despite intense efforts and significant investments to implement EHRs, duplicate and disjointed medical records continue to plague providers. The financial impact is substantial— duplicate records cost the U.S. healthcare system more than $6 billion annually and individual hospitals $1.5M per year.1 The problem not only negatively impacts a provider’s bottom line, but incites medical errors, skewed reporting and analytics, redundant medical testing, administrative waste and poor patient satisfaction.
The issue of patient misidentification and duplicate records grows increasingly complex as more data is generated and more applications are introduced into the healthcare environment. As population health and accountable care take hold, organizations now find themselves under increased pressure to effectively identify, track and manage individuals across care settings.
As a result, organizations need unprecedented clarity and reliability into one’s medical record to avoid redundant or unnecessary tests and procedures, erroneous reporting and analytics, billing inaccuracies, administrative burdens, denied claims and lost revenue. A single, comprehensive view of patient information is essential for informed clinical-decision making, effective episodic care and cost management, and a seamless provider and patient experience during every encounter.
CHALLENGES TO PATIENT MATCHING AND IDENTIFICATION
Duplicate records often occur as a result of multiple name variations, data entry errors, and lack of data standardization processes. A typo or absence of a single digit in one’s birth date, address, or phone number can result in the creation of a duplicate. Patients move, marry, divorce and visit multiple providers in their community—where new records are created and the potential for duplicates grows.
Data fragmentation spread throughout the continuum contributes to the proliferation of duplicate and incomplete patient records. The disjointed nature of IT systems means that individuals receiving care and services from more than a single provider in the network often have medical records in several locations. Large-scale M&A and consolidations exacerbate the issue, as acquired EHR systems and legacy applications often reside in silos.
Reliance on EHR matching functionalities to manage patient populations only add to the problem since EHRs are exceedingly limited in their ability to compare and match records from external sources, especially those outside of the network. Match rates can be as low as 50 percent when providers attempt to match records using the same EHR vendor.2
In an industry daunted by applications and IT systems that fail to communicate or share data effectively, another contributing challenge to patient identification is inconsistent use of standards. The result is inconsistent, unreliable demographic information, triggering further harm in data quality and synchronization.
Duplicate and incomplete records can severely impact a hospital’s bottom line. This is critically important as organizations become more dependent on initiatives such as ACOs, population health, HIEs and precision medicine, all of which rely on accurate and easily accessible patient data.
To improve operational efficiencies and performance, CFOs and revenue cycle leaders should consider investing in automated, enterprise-grade patient identification technology that facilitates fluid health information exchange while improving the integrity of their data.
Enterprise master patient indexes (EMPIs), for example, allow organizations to identify and link patient data spread throughout multiple disparate sources, systems and sites of care. Tired of proprietary EHR systems that only provide a limited view of a patient’s health history, progressive healthcare organizations are leveraging EMPIs as a strategic and competitive advantage for strengthening their organizations’ fiscal health.
For many institutions, automated patient ID matching software like EMPIs are rapidly transforming from a line of defense against duplicate records to the default approach for interoperability and enterprise-wide connectivity across various systems and locations. An enterprise unique identifier (EUID) generated by the EMPI serves as a link to an individual’s record in any given application, streamlining clinical and administrative workflows for patient data access points like medication history, lab results, and visit summaries. EMPIs can also provide extensive data stewardship capabilities to maintain the integrity of the patient record and minimize manual remediation by health information management (HIM) professionals. Primary growth in EMPI investments are taking place in the cloud which allow evolving organizations to scale with greater agility and integrate outside sources of information more easily, including social care and mental and behavioral health.
As healthcare becomes consumer-driven, it is equally critical to consider use of other identification mechanisms to ensure that patient demographic information is accurate and up-to-date. Use of personal smartphones, for example, to streamline registration and allow patients to play an active role in managing and updating their data can help to improve patient matching efforts at key stages where data errors often occur; during enrollment and at registration.
Third-party data, including public record and credit bureau information, is also being used in conjunction with an EMPI for real-time decisioning and instant validation of one’s identity, thereby avoiding the risks associated with duplicate record creation and identity fraud.
As value-based models occupy a larger share of healthcare reimbursement, an organization’s ability to gather accurate, longitudinal patient data and effectively put that data to work to influence costs of care will become imperative. With duplicate records reaching $1,950 per patient3, leveraging patient identification technology as the foundation for robust interoperability and highly-coordinated care, will position one’s organization for success in an era of increased accountability.
David Bennett is Regional Vice President for NextGate, a global leader in healthcare enterprise identification.
1. Black Book Research. April 2018. https://www.newswire.com/news/improving-provider-interoperability-congruently-increasing-patient-20426295
2. Pew Charitable Trusts. October 2018. https://www.pewtrusts.org/en/research-and-analysis/reports/2018/10/02/enhanced-patient-matching-critical-to-achieving-full-promise-of-digital-health-records
3. Black Book Research. April 2018. https://www.newswire.com/news/improving-provider-interoperability-congruently-increasing-patient-20426295