Next generation of EHR Data Models | Healthcare IT Services

Next generation of EHR Data Models: The solution for legacy problems

A Glimpse of the EHR history

The history of electronic health records (EHRs) dates back to the 1960s when the first computerized medical records were created. However, widespread adoption of EHRs did not occur until the 21st century, driven by technological advances and increased pressure to improve the efficiency and quality of healthcare. But now, in 2023 we are seeing rapid advancements in the technology structure of EHRs.

This change was bound to happen. In an age when we are planning to make roads on the moon, it is very evident that technology will evolve across all fields.

In this blog, we will discuss the problems in legacy EHR systems and how a next-gen EHR data model can solve them

Problems in the existing/legacy EHR systems

  • Knowledge deficit among users: The legacy systems are older and have not been updated with the latest technology or features. As a result, users may not be familiar with how to use them or may not be aware of all of the system’s capabilities. As legacy systems are not widely used anymore, there is a lack of training or resources available for users. Additionally, as new EHR systems are developed and implemented, users may not have the opportunity to work with legacy systems and therefore, may not have the opportunity to develop expertise in working with them.
  • Disjointed patient care: Legacy EHRs can lead to disjointed patient care due to several factors. One major issue is the lack of interoperability, which makes it difficult for healthcare providers to access a patient’s complete medical history, leading to delays in treatment, misdiagnoses, and other issues. Additionally, legacy EHRs often lack in advanced features such as clinical decision support, patient engagement, and care coordination that new EHRs have, making it challenging for healthcare providers to provide high-quality care. Furthermore, legacy EHRs may not be able to integrate with newer technologies such as telemedicine, mHealth, and other digital tools which can enhance the patient care experience.
  • Fragmented data modeling: Fragmented data models in legacy EHRs can be a significant challenge because they make it difficult to access and integrate patient information from different sources. In a fragmented data model, patient data is often stored in silos or isolated systems, which can make it difficult to access and share information across different departments or care settings. This can lead to a lack of continuity of care and can make it difficult for healthcare providers to make informed decisions about patient care. Additionally, fragmented data models can make it difficult to implement advanced analytics and population health management strategies, as the data is not easily accessible or integrated. This can impede the ability to identify trends and patterns in patient health, which can be used to improve care and reduce costs.

 Why a Next Gen EHR data model is a solution.

  • Adaptable patient-driven individual models: The provider network, payers, and other related information blocks are all represented as Person records in modern, extendable information bases. Try to display the various individual types in a single inheritable and linked table rather than having a separate table for each type of person (for example, a different table for a patient versus a doctor).
  • Multi-facility organization model: An entity known as an organization should be used to organize facilities, tenants, hospitals, insurance companies, departments, clinics, administration, and associated data. Organization record types are likely to apply to any entity that isn’t a person. A single table with the necessary characteristics should therefore enough.
  • Patient Identification: In a legal system with multiple entities, no single identification method controls all systems. An object can have multiple mappings, including a primary key for internal consistency and external identifiers for ID lookups and deduplication when integrating different systems. A person’s records should be able to support multiple identification values. 
  • Different databases for PHI and transactional data: Separating clinical and transactional attributes in PHI will improve data quality, enhance security, and ensure compliance. By keeping clinical and transactional data separate, providers can ensure that the clinical data is accurate and up-to-date. In contrast, transactional data is used only for billing and administrative purposes. Additionally, it makes it easier to secure the data and comply with all relevant regulations such as HIPAA and HITECH. It also allows for more targeted analytics and reporting, making it easier for providers to identify trends, patterns, and areas for improvement in patient care, and allows for sharing the necessary data with different parties while keeping the sensitive data private.
  • Expandable database: The entire healthcare industry is going digital faster than anyone had expected. This and the growing population of humans mean that there will be more data to store. It is important to ensure that your database is expandable. This will allow for long-term data archiving and better data control.
  • Multi-user and multi-device support: To have a well-connected provider network it is imperative that your database is multi-user friendly and can support multiple applications. Very soon most personal fitness applications will be connected to EHRs since they collect valuable real-time health data. ta. Therefore, your EHR should not only be multi-application friendly, it should also be able to track and record the changes made by different applications.

What we can do for you  

Next-gen data models for EHRs (Electronic Health Records) are essential for improving the quality of patient care and streamlining healthcare operations. These new models can help providers manage and analyze large amounts of data in real time, making it easier to identify trends and patterns in patient care.

However, implementing these new models can be a complex and time-consuming process, which is why it is important to work with a solution partner that has the necessary experience and expertise. Nalashaa, with over 10 years of experience in providing Healthcare IT services, is well-positioned to help providers achieve their goals and fully leverage the benefits of next-gen data models for EHRs. Our team of experts can help you navigate the implementation process and ensure that your EHRs are fully optimized to meet your specific needs.

Connect with us at info@nalashaa.com

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Mitrajit Das

Mitrajit Das

A writer with a keen interest in the Healthcare domain and B2B content marketing. He enjoys writing and creating pieces around the latest Healthcare IT trends using the simplest of words.
Mitrajit Das
Mitrajit Das

A writer with a keen interest in the Healthcare domain and B2B content marketing. He enjoys writing and creating pieces around the latest Healthcare IT trends using the simplest of words.

All stories by: Mitrajit Das