Role of Artificial Intelligence in improving EHR/EMR and Medical Coding and billing

N. Manikanta

Medical Records Officer, Kauvery Hospital, Electronic city, Bangalore

*Correspondence: +91 77605 64296, manisweetu631@gmail.com

Background

Patient medical records have long been viewed as inflexible, difficult to use, archaic, and costly to configure. However, these records are critical to improving the patient experience throughout their care journey. They provide healthcare professionals with the information needed to help make good clinical decisions and evaluate care management plans across the entire continuum of care. Other benefits include ensuring accuracy and timeliness of payment for services performed and helping to mitigate malpractice risks.

Artificial Intelligence (AI) has been a key driver in digital healthcare transformation with digital applications being used to help patients become better decision-makers for their own health while driving efficiencies and reducing costs across the healthcare industry.

But what about AI’s role in medical health records?

Key opportunities of AI in medical records

Improve productivity

AI tools have recently been developed that can help healthcare providers (HCPs) extract clinically-relevant insights from free text housed in medical records or insurance claims.

One such tool, Healthcare Natural Language API, released by Google Cloud, generates a structured data representation of the medical knowledge stored in the data for downstream analysis and automation. This extracted information can include medical concepts, such as medications, procedures, medical conditions etc. and functional features- such as side effects and medication dosage.

Despite the headway being made in this field, the challenge for AI-based tools is extracting data in a standardized format that takes into consideration the entire patient journey. In order to maximize AI in medical records, healthcare organizations are starting to work closely with data scientists to understand what data is relevant and how to generate value from it, which ultimately leads to value for the patient.

Accelerate digital health

While many physicians express frustration recording patient medical information electronically – indicating that the time it takes to complete entering data is time lost with their patient – they also think that it is the way of the future.

Some hospitals have implemented scribes to sit in on appointments to document the visit while the physician focuses on the patient. AI is coming into play as several companies are working on developing digital scribes – machine-learning algorithms that can take a conversation between a doctor and patient, deconstruct the text and use it to fill in the relevant information in the patient’s electronic medical record (EMR). This can also help mitigate the risk of physician burnout and standardize data input, which is a challenge with EMRs.

Improve personalized care

The use of AI in medical records can help identify patterns and perform outcome predictions. Subsequently, this information can be used to tailor specific treatments to an individual, even down to the level of what physician may be best suited to cater to their needs and outcomes that matter most to them.

As a practical example, especially during the early phases of the pandemic, patients with pre-existing but non-COVID-19-related conditions could be paired with available caregivers based on their data and the outcomes observed across providers. This could potentially help them avoid long waiting times or keep up with their routine health checks in the case that their regular doctor is not available due to office closures. This not only offers improved patient outcomes but also improves access to care on an individual basis.

The use of AI can also enable doctors to be alerted to preventative screenings, vaccinations or check-ups which takes; personalized healthcare to a new level.

Decision support

AI-based clinical decision support (CDS) tools are being used to improve care delivery. These tools can analyze large volumes of data to provide diagnostic assistance, and treatment guidance and evaluate disease prognosis and progression.

Despite the many advantages to CDS tools, due to the vast number of them, their design needs to be carefully implemented to ensure that they do what they are intended to do – Create less work for HCPs and not more.

One thing is certain

People from all sectors of the healthcare industry need to be part of the CDS design and implementation process for this to be successful.

AI and the future of medical records

Innovation will continue to advance AI’s role in medical records. It is already being used to analyze large amounts of data to improve productivity, accelerate digital health, improve personalized care and support the clinical decision-making process.

As the healthcare industry embraces technology, the evolution of the data scientist role and the focus on data within healthcare organizations will grow.

Patient experience and outcomes will progressively improve, and this will be partially attributable to the data collected within this valuable resource.

Artificial intelligence is a hot topic right now. Many people are wondering how it will change the way we live our lives. In the medical field, there are many ways that AI can be used to improve patient care. One area where AI can be particularly useful is in medical billing and coding. In this blog post, we will discuss how AI can be used in medical billing and coding, and why it is such an important tool for hospitals and clinics.

Stay tuned!

Artificial Intelligence in medical billing and coding: How it can help???

AI is also a valuable tool for managing insurance claims and ensuring that they are processed quickly and without any errors. One of the most important ways that AI can be used in medical billing and coding is by automating the process. Automation can help to speed up the billing process and ensure that all bills are processed accurately.

In addition, AI can be used to identify errors in bills and correct them. This can help to reduce the amount of money that hospitals and clinics lose due to incorrect bills.

Another way that AI can be used in medical billing and coding is by helping to manage patient data. By collecting and analyzing patient data, AI can help healthcare providers identify trends and patterns. This information can then be used to improve patient care and treatment plans. Additionally, AI can be used to create detailed reports on patient health data. These reports can be used by healthcare providers to improve patient care and make more informed decisions about treatments.

AI can also be used in medical billing and coding to help with insurance claims. By analyzing insurance data, AI can help identify potential problems with insurance claims. This information can then be used to correct the claims before they are sent to the insurance company. This can help to ensure that the claim is processed quickly and without any issues. Overall, AI can be a valuable tool for medical billing and coding. Its ability to process large amounts of data quickly makes it an ideal tool for identifying errors and correcting them. Additionally, its ability to analyze data can help improve patient care and treatment plans.

What does this mean for Medical Billers and Coders?

The use of AI in medical billing and coding is still in its early stages, but it is clear that it has the potential to improve these processes. As more and more hospitals and clinics begin to use AI, Medical Billers and Coders will need to be familiar with its capabilities and how to best use it to improve their work. Medical billing and coding are complex tasks that require a lot of attention to detail. Errors can occur at any stage of the process, from entering patient information into the system to submitting claims for reimbursement.

AI can help identify these errors and correct them, which can save time and money for both the hospital or clinic and the insurance company. In addition, AI can be used to analyse data collected by insurance companies and identify patterns that may indicate fraud or abuse. AI represents a major change in the way medical billing and coding is done. Hospitals and clinics need to be familiar with its capabilities and how to best use it to improve their work.

Conclusion

The sooner they adopt these new technologies, the more likely they are to stay competitive in an increasingly complex healthcare landscape. Become a vital part of the healthcare cycle; if taken together, medical coding and billing form a link between patients, healthcare providers, and insurance companies. As a medical biller or coder, you’ll need to be accurate, detail-oriented, and well organized as you’ll be a vital part of any healthcare provider’s staff.

Manikanta

N. Manikanta

Medical Records Officer

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