{"id":8440,"date":"2022-10-07T13:38:29","date_gmt":"2022-10-07T08:08:29","guid":{"rendered":"https:\/\/itechindia.co\/us\/?p=8440"},"modified":"2025-09-24T06:39:18","modified_gmt":"2025-09-24T06:39:18","slug":"https-itechindia-co-us-blog-document-digitization-healthcare","status":"publish","type":"post","link":"https:\/\/itechindia.co\/us\/blog\/document-digitization-healthcare\/","title":{"rendered":"AI-based Document Digitization in HealthCare"},"content":{"rendered":"

\"AI-based<\/p>\n

What\u2019s wrong with keeping paper records, after all, we have done it for decades? The answer is that times have not only changed but regulations have too. The <\/span>Cures Act Final Rule <\/span><\/a>makes it mandatory for all healthcare providers in America to make medical documents available in sharable electronic form. Further, the volume of documents in any medical practice and other commercial healthcare environments is too high to employ a manual method of converting physical documents into a digital form.<\/span><\/p>\n

As more and more practices and clinics continue to implement EHR systems, they are faced with the hard reality that scanning legacy patient chart information, as well as newly generated medical records, is a bigger challenge than they expected. For bulk conversion of medical documents, there is only one accurate and efficient route, AI-powered<\/span> document digitization<\/b>. In healthcare and across industries, we have seen the reallocation of staff and space that previously handled paper-based systems. AI in healthcare<\/a> brings along with it a significant saving in cost and efficiencies<\/span><\/p>\n

Computer vision: converting patient records to HIPAA compliant EHR<\/b><\/h2>\n

Computer vision has numerous use cases in the healthcare industry, one of the applications is to digitize physical documents and store them in digital storage systems such as Electronic Health Records. Computer vision or machine vision is the ability of computers to see and comprehend.\u00a0<\/span><\/p>\n

The technology uses a document scanner to \u2018read physical documents and convert them into binary data. Optical character recognition software looks at the scanned document and marks the light area as background and the dark area as text. How it differentiates what the text is depends on the type of OCR software used.<\/span><\/p>\n

There are two types of OCR technology depending on its level of sophistication i.e. if AI is incorporated or not.<\/span><\/p>\n

1. Simple optical character recognition software<\/b><\/h3>\n

The earlier OCR technology that is still deployed by many companies, uses different font and image patterns that are stored as templates. When a document is scanned, the <\/span>pattern-matching software<\/b> will compare each character in the text to the internal database of templates. It optically recognizes a word present in its internal dictionary with that in the new document. While OCR technology is fast it is not always accurate. This is because the unlimited font types or handwriting styles can make the process complicated.<\/span><\/p>\n

Simple OCR software could be a feasible solution when there is only one rule-based format. For instance, it really falters when it comes to handwritten information. The reality though is that a healthcare organization works with a variety of documents. So, OCR since it cannot understand context, might not solve many fundamental issues that exist in a business.<\/span><\/p>\n

2. Intelligent character recognition software<\/b><\/h3>\n

Intelligent document processing (IDP) <\/span><\/a>reads text in the same way that humans do. It uses advanced methods that integrate machine learning technology and neural networks to train the algorithms to <\/span>analyze text over many levels<\/b>. It looks at the images for attributes like curves, lines, intersections and loops and then combines them to validate the text and get the final result.<\/span><\/p>\n

Let\u2019s be clear though, <\/span>IDP still uses OCR<\/b> but it combines it with intelligent technologies so that it can process large variety of documents. Bank checks are a <\/span>good illustration <\/b>of the intelligence in intelligent character recognition software. Depending on the bank, each check looks different. Intelligent software is programmed to pull relevant information based on context. For instance, IDP recognizes that $500 is the same as 500 dollars – that is understanding context.<\/span><\/p>\n

In the health industry some use cases for intelligent document processing are<\/span><\/p>\n