Technology has radically changed the state of modern healthcare. Artificial intelligence is especially useful for healthcare facilities.
Traditional paper methods to collect patient information have been around for decades. Through these methods, clinical diagnostic information, social and behavioral aspects, and family histories are stored as physical files that are unscalable. They do not just raise storage concerns. The manifestation of physical files can lead to complex access management which can create a cluttered and inconsistent structure. Also, the lack of document auditing and tracking capability of information flow can become a problem. As a result of these operational concerns, there is a significant risk to patient welfare, and a lack of accurate analysis and indexing which negatively impacts clinical efficiency.
However, the proliferation of digital transformation has given rise to Electronic Health Record (EHR) – patient’s digital record containing information about the ailment, treatment, schedules, visits to the provider for healthcare services, scan reports, and other information that helps providers make appropriate patient care delivery decisions and deliver the best quality of care. Healthcare providers also have to make sure that they abide by HIPAA when following these data collection protocols.
EHR gives access to patient’s medical and treatment histories and is considered a key tool in care delivery.
How Healthcare Is Speeding Up Digital Transformation In EHR
There is an increased pressure for providers to deliver a strong patient experience and better clinical outcomes. Therefore, “digital transformation” is becoming a global craze in the healthcare sector. EHR is now becoming the ‘beating drum’ of it.
However, the usability of EHR has become a significant concern amongst healthcare staff, particularly post-COVID-19 due to a high volume of unstructured data from clinicians’ notes, scan reports, etc., and also the burnout owing to “administrative burdens” in the management of EHR. This has paved the way for the adoption of advanced digital technologies such as data analytics and artificial intelligence (AI) that help improve operations. ensure greater accuracy in extracting the patient data from EHRs and help deliver better patient care.
Medical Code Extraction with KANINI
With the adaptation of digital technologies being centric on business transformation strategy, the need for a solution that charters automation, insight, and flexibility is becoming more critical than ever. Early results have shown that artificial intelligence can enable identifying, extracting, and matching data from EHRs through medical code extraction. Medical code extraction uses machine learning and natural language processing (NLP) technologies that contextualize unstructured, large volumes of data accurately and quickly to extract data from EHRs and match the data with relevant medical codes.
Utilizing these technologies to accurately analyze and ‘connect the dots’ with the data stored in EHR records helps to shorten procedural timeframes, reduce errors in data, perform real-time audits, reduce administrative activity and automate accurate outcomes to support staff in managing patient diagnoses and billing.
Operationally, medical code extraction technologies ensure an ability to analyze and understand text input and language and ensure an accurate transition of mapping medical codes to medical documents, promoting documentation compliance.
Why Should You Work with Kanini?
KANINI is known for redefining excellence, and our digital and data transformation strategy delivers agile, scalable, and flexible on-demand services designed to achieve excelling patient experience and business outcomes almost immediately. We work closely with our partners to deliver reliable and adaptable productizations, utilizing data analytics and AI, offering significant value and cognitive insight through data engineering and intelligent document processing cycles, efficient migration strategies to a cloud-based service, and optimizing existing implementations to meet market demands.
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