Electronic health records (EHRs) have gone a long way from being just an electronic version of a patient’s chart on paper. Today, EHR systems include personal electronic health information, that is information pertaining to the health of an individual or health care provided to an individual. They provide instant access to personal and population-level information to authorized. In this capacity, EHRs support decision making in healthcare, efficient healthcare delivery, ensure quality and safety. What may future bring to the universe of EHRs? What new functionalities are expected, what new roles will future EHRs solutions take?
From health records to health plans
Future EHRs will facilitate the adoption of value-based care, the approach that rewards healthcare providers for health outcomes rather than the volume of services. The purpose of EHRs is to provide comprehensive health management and care continuity when implemented with interoperability standards. They augment the capabilities of healthcare professionals by providing them with a consolidated view of all data, insights with decision support tools and automated diagnostics with intelligent algorithms. Through these capacities, electronic health records will transition from being a personal medical record to a personal health management plan, focusing on delivering information to the healthcare provider and the patient.
To population level health plans
Advanced EHRs are expected to include population health tools to allow healthcare systems to meet their wider community needs, and their goals and interests. This includes surveillance tools to monitor community health or detect outbreaks based on problem clusters. The master plans generated by such EHR solutions may target not only individual patients, but entire populations.
Hence, future EHRs may shift focus from transaction (documenting a visit to a doctor, retrieving a lab result, sending a prescription to a pharmacy) to intelligence (ability to analyze patient data, suggest new treatments, identify unusual clinical findings). Introduction of predictive analytics to EHR solutions allows to harness accumulated data to support clinical support decision systems and point doctors to potential developments, analyze suggested treatment solutions. Future EHRs will also allow customized user experience. It may be achieved by employing modular, cloud-based approaches that will enable enterprise integration and scaling.
More interoperable and open communication tool
Interoperability has come a long way; currently it is a requirement and an implemented functionality with all major EHR solutions to “talk to each other”. However, they do not communicate directly. Middleware (integration engines) are used to facilitate the exchange of data, for example, through the latest FHIR standards.
In the future, EHRs are expected to rely more on open interoperability standards. Also, data stored in EHRs may be open to receive health data from medical devices, both stationary and wearable. The interoperability of EHRs will allow patients to receive and healthcare providers to provide access to health records no matter where patients and doctors go.
This will allow doctors to communicate with one another, as well as with testing labs, pharmacies, medical imaging and emergency facilities.
Thus, continuity of care will be facilitated by a wider implementation of interoperability standards.
Help automating decision making in healthcare
The amount of data that healthcare providers collect from patients is already immense, and it will only increase in the future. EHR systems is the most effective means of managing health data. Here data analytics and live dashboards are already used for more effective decision making.
Many healthcare providers have already started automating their business processes based on the data stored in the EHR systems.
This trend will be reinforced once the business, IT and healthcare processes are synced to perform together.
More accessible to smaller players
Currently, EHRs are implemented and used by hospitals and large private and public multi-facility networks, who rely often on government incentives to be implemented. The same is not true for smaller medical practices. Lower prices of deployment and standard solutions, including cloud based, “EHR-as-a-service” solutions that target smaller, independent healthcare providers are already available, their further adoption across healthcare systems is expected.
Targeting patient engagement
Patient portals are provided to engage individuals in improving their health literacy, participation as well as maintenance of healthier lifestyles. Including data from wearable medical and lifestyle devices are becoming paramount as these details give physicians insight into their patients’ health. Notifications for appointments reduce cancellations while increasing patient engagement.
Future EHRs may be enriched with the organizing functionalities and may employ engagement/reward tokens for following doctor’s orders and maintaining healthy lifestyles. Though this area is in early development, several notable projects are in development or early deployment, more relevant activities are expected in the future.
Less efforts in data entry
Current EHRs expect doctors and nurses to type in their notes. Some are more usable than others. Voice recognition technology is used by some to optimize data entry. Emerging virtual assistants are used to help find information faster. The practice of data entry of today copies traditional (text-based + OCR) approaches. It is often a challenge to doctors and nurses; they have to type data in or write it in hope that their writing is understood correctly by optical character recognition software.
Future EHRs are expected to employ voice recognition in combination with AI, in the format of present virtual assistants.
Future EHRs may employ blockchain, AI, NLP, app extensions
Integration of blockchain in EHR solutions is in early phases, though several solutions are already available. Application of blockchain will ensure confidentiality, security, scalability; employment of smart contracts will allow actions without human involvement. Doctors will be able to query an AI system using natural language to obtain specific information about a patient. A machine learning system will review available data and compare it to expected results, advising doctors of any potential health risks quickly. Natural language processing combined with AI will increase efficiency and mitigate errors. AI based algorithms may help form a patient’s combined health plan. It will combine appropriate algorithms for treating multiple diseases and conditions of a patient, automatically resolving conflicts and redundancies. App extensions will provide the interoperability that current EHR solutions may lack for external interactions. Some apps are already available through proprietary application marketplaces, more app extensions are expected to emerge.