Is unstructured data more useful in medical transcription?

Unstructured data in medical transcription is the information collected and logged that does not follow a particular flow or pattern. With the technology becoming more advanced by days, the digital data in healthcare is gearing up the industry to a great extent and are finding new, better and effective ways of patient care. It is necessary for the US that patients are filling up forms and these forms build up records and are used as their medical history for any future diagnosis. However, the new thing is how these data are stored in the digital spaces.

With data becoming more prominent in healthcare, doctors are now more focused on the best way to collect these data from patients. While structured data comes up with obvious values, unstructured data offers more accuracy. From the very beginning, doctors decide whether to ask the same set of questions to the patients that visit them or whether they should collect their intimate details to create rich patient profiles. In medical transcription, structured data is no longer the only place from which meaning information can be collected and derived. It has become more feasible for the healthcare industry to analyze unstructured data sources.

In the case of unstructured notes, doctors only collect specific details that they seem to be relevant to the patient cases. Hence these do not streamline perfectly with the other patient's data. So, what are the benefits of unstructured notes? Unstructured notes are believed to enhance patient care and if experts can find meaningful ways in which these notes can be organized, it could lead to a big breakthrough.

Unstructured data plays an important role in fraud detection. Care cost in healthcare is high, and we need to know if people are at risk before they actually get sick. Not only that, but healthcare providers also need to stay up to date with new researches which helps in providing better patient care. Yes, structured data can provide the necessary streamline information needed by doctors. However, to solve any business problem it will be like finding a needle in the haystack. Many times structured data only solves problems partially, but, during situations like these healthcare providers mostly rely on the unstructured notes.

At times it is seen that two patients with the same diagnosis can have two different paths to recovery based on their social disparities. Information about these cannot be readily available in the structured data forms but in the unstructured ones. Unstructured data sets like physician notes can be of rescue in scenarios like these.

We set a few other examples of these unstructured data that comes up to rescue in medical transcription:

Ø  Medical journals read by machines to extract relevant information to make these available to the providers

Ø  Different notes can be analyzed to detect any negative or positive patient sentiments and for finding out opportunities to reduce call volume and call handling time.

Ø  Doctors’ notes can be easily mined for medical documentation accuracy, disease onset prediction, etc.