The Common Denominator for Quality and Efficiency: 3 Keys to Patient Identity Resolution
Managing patient identities across the care continuum has never been more complex or more important. Care delivery teams use vastly more technology today than ever before, and patients have the ability to initiate care team interactions through methods such as patient portals, kiosks and smartphone apps that were largely unavailable only a few years ago.
A shift in reimbursement risks due to growing adoption of value-based contracts magnifies the need to manage patient care across all types of settings. A health system's ability to manage and link data to unique patient identities is critical. This process can either create a foundation of continuity to enable population health analytics, care coordination and revenue cycle effectiveness, or it can produce the undesired outcomes of operational delays and poor patient experiences.
Linking patient datasets can help clarify an integrated picture of seemingly unconnected care delivery interactions and serve as a crucial starting point to analyzing data that can ultimately improve clinical practice and change patient behavior. Achieving the quality, cost and health goals of the industry demands a deeper look at the common denominator, which is the patient identity.
Patient identity processes today
Patient identity resolution involves a system of interdependent patient identity processes. Addressing one patient identity resolution process without considering others may fail to take strategic interrelationships into account and cause the overall system to fall short of the intended improvements. Unaddressed patient identity needs may cause the health system to accept unnecessarily high operational costs and largely avoidable risks.
For example, biometric patient identification systems are weakened without prior authentication of the patient prior to gathering the biometric. Patient identity verification systems are diluted if they fail to help distinguish between existing and new patients. Additionally, the lack of consideration about how these patient identity processes foster matching of patient information across the health system may consume time, operational effort and capital without achieving the targeted return on investment.
The quality of patient information within underlying registries, the accuracy of patient-presented information and knowing that patients are who they claim to be facilitates and informs actions within the ecosystem. Did you know retrieving correct medical records, acquiring cohorts of patient data for analysis and allowing patients to view their protected health information online each demand different identity resolution capabilities? If implemented in concert, the system of patient identity processes acts as a layered defense against maliciousness and fosters efficient health system operations and effective patient interactions.
Key 1: Data quality
The quality of patient data impacts care delivery and administrative initiatives across the patient continuum. Improving care delivery quality often starts with gathering data to identify practice variation and which clinical practices result in the best outcomes. If patient level data can't be linked because of insufficient patient identifiers, researchers are left with smaller sample sizes that are less capable of supplying the desired insight. Similarly, administrative operations such as billing can be less costly and easier for patients to understand if they are aggregated and explained together as an episode of care instead of discrete and unconnected interactions. This ability to aggregate clinical and revenue cycle information requires resolution of patient identities across care settings and technologies.
Patient-identity proofing and access management processes improve patient identity resolution by distinguishing identities for in-person and remote patient encounters. They ensure that patients are who they claim to be before issuing tokens, collecting biometrics or enrolling for patient portals. Related services confirm the accuracy of patient-presented identity attributes and help detect and prevent fraud.
Simultaneously gathering biometrics, issuing smartcards and enrolling in password reset services enables the patient to traverse the health system, leaving high-quality, linkable identity footprints at each health system interaction. Attaining high-quality patient identity resolution at the beginning of each encounter sets up the clinical staff for safer patient care and the administrative staff for more efficient revenue cycle operations.
Key 2: Data minimization
Data minimization is the concept of gathering the minimum necessary identity attributes to distinguish one patient from another. Balancing between gathering enough patient identity information and gathering too much can be tricky. Requiring patients to provide more identity data than is absolutely necessary puts them on guard as they are likely cautious after witnessing publicized medical identity breaches across the country. Healthcare providers that collect sensitive patient information like Social Security numbers may maintain a higher risk profile than necessary; if a breach occurs, they and their patient communities have more to lose.
When a patient access team member misidentifies a patient and retrieves the wrong medical record information, patient care and patient satisfaction can suffer. If a standard set of patient data is gathered but fails to distinguish a unique patient identity, an ideal exception process should prompt team members for the minimum additional data required to do so. Reducing dependence on sensitive or unnecessary patient data gathering and simplifying the classification of patient identities for patient access teams improves the patient experience and lowers provider risk.
Key 3: Data accessibility
Data accessibility refers to the ability to recall existing data or request supplemental data about the existing patient population. Health systems with mountains of clinical and administrative patient data may find themselves with a lack of computing power to match massive datasets and query them in a meaningful way. Querying massive datasets to answer questions ushers in an identity resolution crisis that creates the need for corresponding pre-processing expertise and supercomputing speed and scalability.
Stakeholders throughout the health system will need to access slices of distilled information to shape programs and practices at strategic and operational levels. The ability to pre-process a large variety of structured and unstructured datasets at the patient identity level facilitates analysis and delivery of meaningful insight.
Data accessibility also plays a growing role in addressing community needs. Understanding one's patient population outside of health system interactions may guide different prevention and outreach activities than if only internal datasets are considered. For instance, if patients don't own vehicles, plans for post-discharge follow-up appointments and picking up new prescriptions may need to be tailored accordingly. If patients are undergoing stressful life events such as divorce or bankruptcy, clinicians may be able to direct the patient to other sources of help so that patients can focus more on treatment adherence. In short, access to the right internal and external data can help provide the insight to shape better care delivery decisions for your patients and communities.
Implications of inadequate patient identity resolution
Ineffective patient identity resolution can waste millions of dollars for health systems. The inability to discern unique patient identities can lead to duplicate records, which cause rework for your patient care team and inefficiencies for business offices. Additionally, high-risk patients who cannot be contacted can lead to avoidable and potentially unreimbursed emergency visits and inpatient admissions. Overall, the impact of increased medical identity fraud can lead to denied claims, patient safety risks and administrative struggles to sort medical record fact from fiction.
If practice teams fail to resolve a presenting patient to an existing patient record, the practitioner may only have the verbalized medical history available to consider. In another scenario, practitioners that cannot share patient information because their patient identifiers don't sync may default to re-gathering specimens, repeating tests or duplicating images. Quality incentives and value-based contracts will grow the importance of patient identity resolution to facilitate information sharing and prevent overutilization.
Because of the impact patient identities have on healthcare operations and patient experiences, the industry is compelled to identify and resolve patient identity inadequacies. In view of this, data quality, data minimization and data accessibility are key to improving administrative and care delivery operations, reducing avoidable risk and enabling the insight necessary to understand clinical variation and reach new heights of quality.
Todd Bennett is responsible for LexisNexis® patient access and patient identity management solutions used to improve data quality and facilitate high-trust interactions between patients, providers and provider communities. Mr. Bennett participates in numerous industry associations including HIMSS, HFMA and DirectTrust. Previously, he developed transparency and care coordination products and worked directly with hospital leaders and staff to improve operational efficiency. He graduated from the United States Military Academy at West Point with a bachelor's degree in engineering management and from Georgia Southern University with a master's degree in business administration.
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