Alleviating data entry hassles of healthcare professionals

Reducing Data Entry Issues Faced by Healthcare Professionals A recent post in wired.com drew attention to the issue of big data. In the busy world today, no one has the time or patience for tedious data entry. Everyone is looking for means to avoid manual data entry and do things in an easier and better way. Just as Microsoft’s new Xbox One recognizes users’ faces and logs them in automatically, modern technologies in healthcare are helping physicians in clinical documentation, without the hassle of data entry. If implemented thoughtfully, the technology has the potential to streamline clinical workflow, increase coding accuracy and efficiency and meet complex ICD-10 documentation requirements.

Use of Big Data Algorithms The auto sign-in feature of Xbox One is greatly welcomed by people, as it saves considerable time. Doctors are a very busy group, always hard pressed for time.

They can very well use big data algorithms to ensure better patient care. The problem though, is that big data algorithms require a lot of data to be entered in the first place. How is a busy physician to find time for data entry and also attend to a large number of patients?

Challenges of Big Data Algorithms

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The main issue with big data algorithm is its data hunger. A lot of patient data has to be entered before you can have the expected results. For example, an algorithm for diagnosing heart attacks may use up to 40 data elements.

Entering all that data is really difficult for physicians managing an overcrowded emergency department.

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Big data algorithms are similar to online decision support tools that are freely available. They also have the same issue of data entry. For example, to predict the likelihood a patient will die requires the user to enter 17 pieces of data, including formulas that must be calculated separately.

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Tools demanding large volume data entry are used less often used by doctors and are less efficient.

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Feeding data from the Electronic Health Record (EHR) to decision support tools is also not a reliable option. Sometimes it is not clear that which data is to be entered and sometimes the needed inputs may not be recorded exactly in the right format or with the right details.

Computer-assisted Option

Physician Documentation

(CAPD)

− An Alternative

A new technology called ‘Computer-assisted physician documentation (CAPD)’ has been developed by 3M Health Information Systems and Nuance Communications to alleviate the issues associated with big data algorithms. It uses real-time natural language understanding (NLU) to convert the clinician’s sentences into computerreadable codes. Other benefits offered by CAPB are: 

They automatically populate decision support algorithms

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Provides real time decision support by automatically identifying a missing input and immediately prompting the clinician to add it

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To produce more specific ICD-10-compliant clinical documentation in real time

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Ability to bootstrap by identifying important missing data and either grab it from another source, infer it from existing data, or prompt the clinician to add it during the normal course of documentation

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Saves a lot of time by auto-generating some of the doctor’s notes, billing notes, regulatory reporting codes, and by building a provisional set of orders based on the doctor’s notes.

Anyway, these real time prompts cannot replace human intervention completely. It is not going to catch every error and it may not be perfect. However, doctors cannot waste their precious time on data entry of clinical documents. In this situation, a

medical transcription company can help, going beyond its traditional function of merely transcribing notes to become a valuable data entry provider managing the complex data entry requirements of healthcare professionals.

A professional BPO company offering medical transcription services can not only maximize the efficiency and standardize transcription business processes, but can also reduce a lot of the costs associated with in-house transcription departments.