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Athena Health is an electronic health records (EHR) system created to help medical institutions and physicians with coordination and delivery of care, particularly order transmission and revenue cycle management. Athena Health includes a variety of modules: Athena Clarity, Athena Coordinator, Athena Communicator, Athena Collector, and Athena Clinicals ( AthenaHealth Reviews ). Each of the modules has specific functions and a unique set of features, including data analytics and requirement management, among others. One of the main benefits of the system is its ability to develop an efficient platform for communication between doctors and patients. Another advantage of Athena Health is the fact that it offers practice management solutions with low up-front costs ( AthenaHealth Reviews par. 1). With the assistance of Athena Health, the process of documenting medical data is simplified through an effective organizational framework for patient records. In addition, the system saves time for doctors by automatically sending and processing claims ( AthenaHealth Reviews ). Athena Health also features a user-friendly marketplace, which makes an abundance of third-party applications available to physicians.
To have a more objective view of the system, it is important to discuss its disadvantages as well. As for the weaknesses of Athena Health, the billing system is overly robust, which is a source of concern for the customers ( AthenaHealth Reviews ). Apart from that, billing services from Athena Health can amount to considerable costs ( AthenaHealth Reviews ). Another factor that affects customers satisfaction with the system is the support department, which is rated significantly lower than expected ( AthenaHealth Reviews ). Moreover, Athena Health does not offer a free trial option, which makes it harder for hospitals to assess the effectiveness of the service. Although Athena Health has various benefits, it is crucial for hospitals, medical communities, and healthcare professionals to be aware of the systems disadvantages.
As for the software solutions, Athena Health should be run using the Server-Cloud system. This ensures that patient records and other medical data can be easily refreshed. In addition, cloud-based EHR systems provide an opportunity for faster communication between patients and health providers, which makes the delivery of care more efficient ( AthenaHealth Reviews ). On-premises solutions also lack the level of security and sophistication cloud-based systems possess. Athena Health could be most beneficial in a primary care setting due to its ability to automatically send and process claims, as well as ensure efficient communication. The system can improve primary care quality by using patient records to identify specific groups in need of preventative services. People with such chronic illnesses as arthritis or diabetes may forget to book an appointment and visit the office. Therefore, Athena Health might be a perfect solution to address population health, which can lead to long-term improvement in the quality of care.
The future of medicine is dependent on scalable innovations, including electronic health records. EHR systems have the potential to use artificial intelligence (AI) to collect and evaluate medical data faster and easier (Jeter Hansen). A digital scribe can transform complex interactions with patients into concise progress reports. An AI assistant can offer doctors optimal care options by synthesizing data from the electronic registry. One of the most important developments possible because of EHR innovation is a persons ability to use their smartphones to communicate directly with health providers through an abundance of applications, tailored specifically for them (Jeter Hansen). Moreover, EHR data is critical in improving the quality of care in the future since it allows scientists to construct predictive statistical models (Rajkumar et al. 1). Such frameworks will have the ability to accurately predict medical events for a variety of scenarios.
Works Cited
AthenaHealth Reviews. EHR Guide, Web.
Jeter Hansen, Amy. A Roadmap for the Future of Electronic Health Records. Stanford Medicine, 2018, Web.
Rajkomar, Alvin, et al. Scalable and Accurate Deep Learning with Electronic Health Records. npj Digital Medicine, vol. 1, no. 18, 2018, pp. 1-10. Springer Nature Limited, Web.
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