Digitization, however, has brought extraordinary changes in healthcare — including the integration of data into clinical practice. With more and more information now available, clinical, demographic and administrative data can be used to effectively tailor treatments for individuals and develop targeted interventions for patient populations.
Today, big data continues to be further enhanced by the development of technologies that deep sequence and map the human genome, as well as systems that aggregate, consume and analyze the volumes of information produced. Taking these enormous amounts of data and mapping it to known treatment protocols and evidence-based care planning, enables doctors to treat patients in a highly-individualized manner. Matching drug therapy to the condition for the right patient has massive implications for improved outcomes, cost, and time savings, with the benefit of improving the care experience for the patient.
Continued innovations in machine learning, advanced algorithms and AI will power more nuanced precision medicine for deeper insights at the point of care. Platforms that can deliver this knowledge to practitioners in an accurate, timely fashion across the enterprise, will become the path forward for population health.
Accurate Patient Identification – a Vital Foundation
These platforms, nevertheless, are equally dependent on accurate demographic matching of patient data, so that a “Single Best Record” or “Golden Record” eliminates duplicates. It is vital that this matching allows the accommodation of multiple identifiers across systems, including those outside the healthcare domain, like social care, to ensure the delivery of a full and complete medical record. Workflow will also need to have the agility to facilitate modifications to one’s information such as changes in address or marital status, as well as the flexibility to configure data schemas that reflect the latest requirements.
Accurate patient matching and identity management technologies like Enterprise Master Patient Indexes (EMPIs) provide faster, more accurate identification that can be extended to multiple scenarios within the healthcare environment. Managing individuals across diverse systems, agencies and geographic locations is why an EMPI is crucial in addressing interoperability in a scalable and manageable architecture.
Since robust information exchange can only flourish when individuals are accurately and consistently matched with their data, an EMPI can facilitate care quality and patient safety by accurately de-duplicating and reconciling records. EMPI integration yields immediate value in data access and integrity to support the requirements of coordinated, accountable, individualized care.
Biometric technologies like facial recognition provide faster, more accurate identification, which can be extended to multiple scenarios within the healthcare environment to enable more-informed advances in precision medicine. Biometrics can extend the reach of patient identification, giving organizations more flexibility, accuracy, and confidence when locating, aggregating, and sharing records. This advanced technology can be deployed in various types of environments, from self-service kiosks to the Emergency Room, enabling rapid identification of patients and access to their clinical information across the enterprise.
Accurate and timely patient identification across systems, locales and specialties will be the foundational component for precision medicine. As healthcare continues to evolve to a data-driven enterprise, precision medicine is poised to shape the next century in medicine with far more personalized, precise care delivery models.
Royston Adamson-Green is Director, Channel Sales EMEA & APAC, at NextGate, a leader in healthcare identity management, managing 250 million lives for health systems and HIEs in the U.S. and around the globe.
The views, opinions and positions expressed within these guest posts are those of the author alone and do not represent those of Becker’s Hospital Review/Becker’s Healthcare. The accuracy, completeness and validity of any statements made within this article are not guaranteed. We accept no liability for any errors, omissions or representations. The copyright of this content belongs to the author and any liability with regards to infringement of intellectual property rights remains with them.
