The massive transformation of the healthcare industry can be summed up as adopting the latest digital technologies such as Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Predictive Analytics, Data Science to revamp patient care.
The massive transformation of the healthcare industry can be summed up as adopting the latest digital technologies such as Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Predictive Analytics, Data Science to revamp patient care. Combining the power of AI in Electronic Medical Records (EMR) is mainly for the enhancement of data discovery, extracting information, and offering personalized treatment recommendations to patients.
The technological advancements in medical imaging and the expansion of medical diagnostics, as well as screenings, produce huge volumes of patient health data. The biggest challenge with electronic medical records for integrated healthcare delivery systems is that they are usually not flexible, have complex usability and configuration are costly. All the data related to care procedures, patient’s health, administrative process, etc. also cannot be captured efficiently or effectively by the EMR systems.
The options are scarce to bridge the gap between systems and procedures so that alignment can be enhanced. A well-structured design that can seamlessly integrate and streamlined EMR systems can assist in this regard in order to fit them properly into the workflows. Generally, developing such systems is time taking and difficult. In such circumstances, an open-source EMR system provides some intermission that is freely available.
Despite the software being free for providing customized EMR systems demand a significant amount of programming as well as infrastructure. These open-source systems are maintained without any hassle as the systems are mainly designed for small medical practices. The other category i.e. AI-enabled EMR systems that are more important as leveraging Artificial Intelligence can make the EHR systems more flexible. As AI comes with great capabilities, it helps in making these electronic medical record systems friendly to doctors.
Electronic Medical Records (EMR) systems powered by Artificial Intelligence (AI) provide solutions with an array of distinguished functionalities. ML and NLP technology help in recording the medical experiences of the patients, handling large volumes of EMR data for identifying important documents and evaluating patient satisfaction, etc. The Machine Learning models amalgamated with advanced NLP empowers healthcare providers to transcribe the speech from the voice recognition system into text.
Eventually, the algorithms can be trained well on large volumes of patient data that comprise treatment details, the equipment used for treatment, the concerned doctor. respective doctor, etc, and then segmented individually based on patient, illness, treatment, etc. It will enhance the document and information search from large databases. Machine Learning and predictive analytics models also empower healthcare providers with advanced analytics on patient satisfaction that allows predicting the risk of the patients.
The different powerful AI applications used to enhance EMR systems are broadly classified and comprehensively discussed below:
It is very important that the patient’s data is accessible without any hassle to the providers for relevant and faster diagnosis of the problems and makes accurate decisions for effective treatment. Furthermore, clarity should be provided to the doctors to interpret the data accurately. Streamlining the huge volume of EMR that comprises patients’ health conditions is a big challenge.
Many hospitals stated that public health agencies are not able to receive effective patient data as one of the biggest hindrances for the doctors was the global COVID-19 pandemic period. When the power of AI is combined with EMR systems, it empowers the doctors to quickly access, withdrawals, export patient data electronically, and export patient data with high accuracy.
Predictive analytics has a big contribution towards healthcare and improving the effectiveness of EMR systems. These models from Big Data have the potential to alert doctors and clinicians on lethal diseases. Artificial Intelligence (AI) can also gear up medical image interpretation algorithms that could be integrated into the EMR systems. It helps in providing better decision support and strategies for treatment.
More and more healthcare organizations are breaking the ice and deploying the capabilities of Artificial Intelligence (AI) to develop NLP-powered tools that can easily integrate with the electronic medical records in capturing data from the clinical notes, thereby, empowering health service providers to focus more on their patients and the treatment process.
Fusing AI capabilities into your EMR system will help in making more informed decisions on treatment procedures and strategies that are usually generic. The AI-based EMR systems are proficient in providing more machine learning solutions that enable them to offer personalized care and also learn new and real-time data that are emerging.
Healthcare is lacking one of the most common standards for capturing, managing, and transmitting patient data. It becomes difficult to analyze patient information from different EHR systems. Without syntactic and semantic interoperability, the risk of information getting lost will be always there while sharing digitally with multiple health providers. It creates further delays, authenticity, and finally impacts the quality of care and patient outcomes. Gradually organizations have opened up to implement the latest AI and ML technology to fix the interoperability issues in clinical documentation.
The global COVID-19 pandemic has prioritized patient-centric care, which is only possible via smarter and efficiently functioning EMR systems. The prolonged impact of the deadly pandemic has also raised the need of the hour to adopt advanced technologies. Its high time for telehealth compatibility in electronic medical records systems. The use of Artificial Intelligence in EMR systems can make the integration seamless for both patients and healthcare providers.
While some healthcare providers, who were reluctant, are coming out of their shells and are adopting new technologies to integrate AI capabilities to enhance specific application areas. While many other providers are developing in-house AI solutions for their EMR systems.
At the time of emergency, the EMR systems act as the best saviors of life by providing the complete medical history (treatment & doctors) of the patients. As they are safely stored electronically and enable healthcare providers to access patient data from any location anytime. These systems can improve and enhance communication, not just only among the doctors, but also between physicians and patients. When the communication is better, it will lead to improved care. Ignoring the most common challenges such as physician burnout, higher costs involved, and lack of interoperability between disparate systems, EMR systems have a great potential to provide value to the healthcare sector.
Net Health mission is to harness data for human health. We offer EHR software and predictive, actionable analytics for medical specialties, including rehab therapy, wound care, home health and hospice, and employee health and occupational medicine. Net Health solutions are trusted in over 23,000 facilities across the continuum of care. Our EHR software enables caregivers and their organizations to engage effectively with patients, streamline documentation, staff efficiently, secure maximum appropriate reimbursement and maintain regulatory compliance. Our unique approach to analytics seamlessly presents insights in clinical and operational workflows to improve care and business performance.
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