Coding Within Healthcare
What is Diagnostic Coding?
Diagnostic Coding Types
The Power of Data
Support of early diagnosis
The main feature of civilization is the production, consumption, and accumulation of information in all branches of human activity. All human life, in one way or another, relates to the receipt, accumulation and processing of information.
Any living organism, including humans, is a carrier of genetic information that is inherited. Genetic information is stored in all cells of the body in DNA molecules. The human DNA molecule includes about three billion base pairs, and it encodes all the information about the human body: its appearance, health or predisposition to disease, and physical ability.
People intake information about the world through their senses. To correctly navigate the world, people store information that they then use to make decisions and communicate with other people.
For any operation on information (even such a simple one as saving), it must be somehow represented (recorded, fixed). In the context of healthcare, this process has a special name – diagnostic coding.
Coding within healthcare
Diagnostic coding is successfully used in the healthcare sector. They help to significantly reduce the time for patient identification, eliminate possible errors in identification, and automate the process of personalized accounting of medicines.
What is diagnostic coding?
We are familiar with the transformation of medical records into a format used in healthcare, such as diagnostic coding. It also helps convert often time-consuming medical reports into concise, data-friendly codes. Medical coders are the people responsible for converting doctors' reports into usable medical codes.
Diagnostic coding types
There are three code sets that you will use daily as a medical coder and what they do.
1. International classification of diseases (ICD)
These are diagnostic codes that provide a standardized way of describing the causes of injury, illness, and death.
This code was established in the 1940s and comes from the World Health Organization (WHO). In the 60 years since it was first published, it has changed several times.
2. Terminology of the current procedure (CPT)
Most medical surgeries are performed in a doctor's office using codes. They published the American Medical Association (AMA) code. These codes are annually compiled by the American Medical Association (AMA).
CPT codes are five-digit numerical numbers divided into three groups. The first type is the most common and is divided into six categories.
3. Generic Health Procedures Coding System (HPCCS)
The term "dive" refers to a group of codes based on CPT codes. HCPCS codes developed by CMS (the same organization that developed the CPT) and maintained by the AMA primarily correspond to services, procedures, and equipment not covered by the CPT codes.
Also included are durable medical equipment, prosthetics, ambulances, and certain drugs and medications.
The power of data
Data and computers play a crucial role in the medical field. Computers are needed for efficient data storage, quick access & exchange of information, and for conducting medical tests and simulating complex surgical procedures.
In medical practice, computer software is used:
- to translate documents in and outside hospitals into electronic form
- to process medical research data (doctor's examination data, X-ray, ultrasound, etc.)
- to provide access to medical history via the Internet for the patient and the doctor
- to inform about the results of research via SMS or email
- to remotely communicate with patients
- for the systematization of research data
These technological developments increase the level of medical quality of services provided. A single centralized system will avoid problems with obtaining information, and it will be possible for any doctor, even from another city, to obtain a patient's medical history, regardless of where they are registered.
Support of early diagnosis
It is impossible not to mention the various Clinical Decision Support Systems (CDSS), which have their own AI. Across several studies, the online version of CDSS Isabel (Isabel), when analyzing data from 50 patients, made the correct diagnosis in 96% of cases.
This result surpassed human efforts since people correctly diagnosed pathologies in an average of 95% of outpatients. Medical data in the form of images, which are used in the diagnosis of various diseases, lend themselves especially well to AI analysis.
In one of the works, experts taught artificial intelligence to recognize diabetic retinopathy. As a result, in a mixed analysis of normal and pathological images, AI showed several errors comparable to that of a human.
An algorithm developed at the University of Malaya (Malaysia) found pathologies with 100% accuracy when studying 340 brain MRI images. Interesting data was obtained from the analysis of patients' handwriting by artificial intelligence. Studying the handwritten text, the computer vision algorithm with an accuracy of 79% divided 55 patients into “healthy” and “having signs of Parkinson’s disease”.
The above examples of AI are designed to help doctors, not to work on their own. However, the results obtained are of great importance, since diagnostics using artificial intelligence systems will be better, faster, and cheaper soon. Over time, AI will be able to replace humans in many “visual” medical fields – radiology, ophthalmology, and, of course, dermatoscopy.
Diagnostic coding has a wide range of applications. It is necessary that people (not only professional programmers but also ordinary users) understand diagnostic coding information and the possible ways to encode different types of information. Through this process, the next frontier of medical practice and diagnostic coding can be penetrated.
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