Artificial intelligence is among the most important and thoroughly examined innovations within the healthcare industry. Physicians, health administration professionals, and numerous other positions within the medical community will be affected positively and negatively by the integration of A.I. into their organizations. However, this shift will not make these occupations in the healthcare field obsolete, but rather shape new approaches that were not possible before.
As a proactive company of experts in health support services, we at ECLAT Health Solutions work to anticipate the proliferation of A.I. within the healthcare industry in the most advantageous way, so that we can become more effective and efficient in our areas of expertise, such as precise medical coding quality assurance, revenue cycle consulting, and many more. We desire to do our part in utilizing A.I. to its fullest capacity in order to help you and your healthcare organization run more proficiently.
How Will Artificial Intelligence Advance Healthcare?
In their article on A.I. in healthcare, Babson College Professor in Information Technology and Management, Thomas Davenport, and Deloitte Consulting Managing Director, Ravi Kalakota, state that “Artificial intelligence is not one technology, but rather a collection of them.” This means that A.I. is not simply a process involving a single system to be integrated, but several, each affecting one or many aspects of your organization. Here are some examples of these technologies and how they are or can be implemented in the healthcare industry:
Automated Information Processing
According to HealthLeaders, approximately $140 billion in lost physician time is caused by the creation of EHR clinical documentation. One of the essential A.I. technologies that may help with this is presented in Davenport and Kalakota’s paper, known as “Robotic process automation” or RPA. They report that an RPA system “performs structured digital tasks for administrative purposes”, to the extent that they have been used in well-known tedious tasks within the healthcare field, such as updating patient records or billing. If implemented effectively through a medical coding company that provides quality assurance, then it can improve a healthcare provider’s efficiency, allowing clinicians more time to care for patients rather than from the constant need to complete clinical documentation, as well as help complete claims processing, revenue cycle, and medical records management. These improvements in practices can thus ensure the integrity and accuracy of an organization’s EHR and EMR systems.
Machine Learning & “Precision Medicine”
Machine learning is another crucial component to the collection of systems that make up A.I., as well as one of its most common forms. Alexander Fogel and Joseph Kvedar, in their article on A.I. in healthcare, aptly describe machine learning as “computer algorithms learn[ing] from data without human direction”.
Both they, as well as Davenport and Kolkata, indicate that machine learning is utilized in many industries in different ways. Moreover, the latter pair state that machine learning is applied in healthcare to perform what is known as precision medicine. This involves the prediction of a treatment that will best fit a certain patient based on their attributes and the context of their treatment.
A more complex form of machine learning has also developed, known as a “neural network”, which can determine whether a patient will obtain a disease based on the inputs, outputs, and numerous variables, or “features” that accurately relate inputs to specific outputs. An even more complex form is a “deep learning” neural network, which includes several thousand levels of features that can more accurately predict patient outcomes. They are often used in oncology-related image analysis, such as radionics, wherein deep learning machines are used to scan and recognize the presence of cancer in radiological images. This is just one way that an A.I’s machine learning capability is being used to greatly improve patient care and physician’s effectiveness.
Natural Language Processing & Clinical Documentation
Another technological development described by Davenport and Kalkota is natural language processing, which includes functions such as speech recognition, text analysis, translation, and other language-related operations. The potential that NLP systems have for the healthcare industry is exponential, particularly when it comes to the recording, filing, and storage of patient information. It will inevitably make the creation and access of files and records within a healthcare organization’s EHR and EMR systems faster, easier, and more efficient, saving clinical and administrative staff an incredible amount of time and energy from performing the essential task of maintaining accurate clinical documentation.
ECLAT Health Solutions: Reliable Medical Coding Quality Assurance
Artificial intelligence is likely the next great technological shift since shifting from physical to electronic records. Undoubtedly, it has already made great strides in revolutionizing the healthcare industry in numerous ways. However, at their helm must be clinical and technical professionals that work to ensure these systems function to their highest potential. At ECLAT Health Solutions, we supported numerous healthcare organizations through various transitions in their systems. We seek to integrate our services, such as excellent medical coding quality assurance, revenue cycle management consulting, clinical documentation improvement, and many more, with the oncoming advancements in artificial intelligence. Through this, we want to become an effective and efficient source of support for healthcare providers and organizations. Fill out our form to schedule a free consultation to learn more about our services.