The introduction of the electronic health record (EHR) ushered in a new era as health care went digital over the past decade. The plan was to digitize patient medical histories in order to enhance professional collaboration, improve patient care, reduce system-wide costs, and other benefits.
Today, the original aims and promises of the EHR system are in question. Debates are stirring regarding the safety and security of electronic health records while limitations of the system itself are surfacing.
The Promise of Electronic Health Records
The government invested billions of dollars in incentives to help health professionals install and learn to use EHR systems. These patient-centered records made real-time clinical information shareable among all providers involved in a patient’s care.
Standardizing record-keeping was also projected to improve workflow, reduce errors, and avoid duplicate treatments. By joining all parties—doctors, therapists, specialists, laboratories, hospitals, pharmacies, schools, workplace clinics, and emergency rooms—the broader view of each patient, with evidence-based support, was expected to improve care and outcomes reporting.
Market research published by global health-care research and advisory firm HIMSS Analytics indicates general dissatisfaction with existing EHR platforms, based upon the following metrics: appearance, functionality with other clinical systems, integration with medical devices, ease of installation, ease of use, quality of support, downtime, and overall contentment.
According to the Office of the National Coordinator for Health IT, health-care facilities can spend up to $70,000 per EHR system and much more over the long term in maintenance and upgrading costs. Furthermore, big data means bigger workload, larger workforce, and heightened cyber-security concerns.
Yet one of the greatest challenges as yet unmet by EHR systems is the conversion of large “unstructured” data sets into practical, useful insights. While great expectations accompanied big-data investments, the very structure of traditional EHR databases— organized into predetermined categories of rows, columns and tables—precludes the integration of doctors’ notes, medical transcripts, and other unstructured data. Likewise, conventional relational databases pose a problem for the interoperability of population health analytics, one of the original promises of EHRs.
New Databases Deliver
Fortunately, hope is on the horizon thanks to technology and the introduction of new databases capable of integrating and interpreting unstructured information. These flexible models are richer in their analytical capacities and are able to extract insight from stored data to offer preventive measures, performance predictions, and efficiency maximization. They provide a practical solution to existing EHR issues while augmenting the value of the system itself.