Introduction
In recent years, the eruption of technologies has transformed the healthcare sector. Large and small hospitals, as well as physician offices, have begun to adapt their processes to new technologies to bring a change in their regulatory environment and improve patients’ overall quality of care.
From communication to just the tingling of senses, the cutting-edge technologies have left us in wonder. Talking of communication, amongst the many more surprises that IT has given to life, Speech Recognition (SR) is one of them. SR is the ability of a program to recognize words in spoken language and transform them into a machine-readable format.
According to BCC Research, the global market for Speech Recognition (SR) will grow from $104.4 billion in 2016 to $184.9 billion in 2021. As a result, more and more custom software development companies have started acknowledging such tech among their existing software solutions like Bespoke development, application migration, software support and maintenance, and so forth.
Healthcare is an area in which SR has established a strong foothold. Several years ago, the HIMSS described voice recognition as an “aggressively” rising market with a 20% annual growth rate. According to a KLAS report, despite 50% of physicians’ reluctance to use the technology, 9 out of 10 hospitals intend to expand SR use.
To gain a better understanding of how this technology works, it’s helpful to discuss its key subtypes:
Front-end (user-dependent): the words are automatically turned to text, eliminating the need for a transcriptionist.
Back-end (independent of the user): the words are captured digitally and then processed by a computer, followed by a proofread by an editor.
Considering The Advantages And Disadvantages
Any technology that generates a massive boom as a result of its numerous advantages frequently creates new obstacles. This article will discuss some of the technology’s advantages as well as potential solutions to the obstacles associated with deploying SR in healthcare.
How Voice Recognition Helps Clinicians Increase Their Productivity?
Ben Brown, Vice President of business development and investment services at KLAS Enterprises, is confident that using speech recognition technology results in a significant increase in productivity:
“We saw radiologists who adopted speech recognition see a significant increase in productivity and competitiveness.”
Let’s take a closer look at the benefits of speech recognition that enable such a productivity improvement in healthcare enterprises.
Reduced paperwork
The attractiveness of SR is that it enables physicians to lessen their administrative burden. Clinicians can avoid writing or typing multiple medical records, including testing and therapy notes, when they have a recording system on hand.
They just dictate into portable devices (phones or voice recorders) and then get the necessary data in a digital format.
Additionally, suppose speech recognition technologies are connected with existing EHR software. In that case, doctors will be able to dictate directly to the PC-based EHR system, eliminating the need for manual data processing and management.
Savings in time
Without a doubt, dictating takes less time than writing or typing. By utilizing SR technology, clinicians gain time back for their primary responsibilities — attending to patients. Additionally, dictation software enables shorter average report times, which contributes to more fast decision making.
Ben Brown admits that one of the SR’s advantages is time savings, and he prefers front-end systems in this aspect because they do not necessitate an editor. “When doctors perform on-the-spot voice recognition, they may finish patient reports considerably faster than if they wait for a transcriptionist to prepare a document that must then be reviewed, amended, and finalized,” he explains.
As counterintuitive as it may appear, back-end SR also has a time-saving advantage over front-end SR. Physicians no longer have to audit their records repeatedly and manually rectify problems as a result of such systems. They can rely on transcriptionists to complete the document and then evaluate it once the revisions are complete.
Enhanced workflows
Many physicians are certain that speech recognition can improve their processes since SR systems automatically queue dictations from multiple users to specified assistants and route dictation files selectively.
Additionally, front-end systems are trained to recognize users, their accents, and past corrections, resulting in the system “learning” typical speech patterns.
Dr. Nick van Terheyden, Chief Medical Officer at NTT DATA, Inc., is a strong advocate for such user-dependent solutions. He is confident that with a 90% accuracy rate, they will significantly improve the whole workflow. “The software is quite smart and is capable of differentiating between accents and specialties, which becomes part of the provider’s profile. Physicians can write extremely precise documents with this data and a minimal amount of training.”
Responding To Challenges
Although SR technology is not without flaws and appears to introduce a slew of complications, many of them are straightforward to resolve.
Noise in the environment
Unfortunately, hospitals generate a great deal of noise from patients, family members, and medical assistants. This has a detrimental effect on the recording process and increases the likelihood of SR tools making errors. In this instance, the use of noise-canceling microphones may be a viable alternative.
Various degrees of quality
Gary David, Ph.D., an associate professor of sociology at Bentley University in Waltham, conducted a study on the influence of front-end SR on physicians’ jobs. He acknowledges that physicians have the responsibility for ensuring the quality of records in the absence of a medical transcriptionist.
“These programs continue to make errors, and in my research, I discovered that physicians occasionally overlook minor errors such as swapping ‘he’ for ‘she.’ Occasionally, the flaws can be extremely difficult to detect.”
As a result, David believes that entrusting physicians with quality control is a bad idea. Rather than that, it is prudent to rely on back-end SR via transcribing service providers.
Accents that are strong
Here, medical specialists’ perspectives diverge. Nick van Terheyden believes that front-end technologies are sufficiently competent to discern accents. However, Brown’s research indicates that the recognition of accents and words with many meanings remains the speech recognition industry’s holy grail.
It may be beneficial for physicians to speak more clearly or to employ back-end technologies that claim to use thousands of samples, increasing the likelihood of working with a certain accent.
Outages of electricity
There is a risk of losing critical data when working with any form of equipment or software. As a result, it is critical to build a robust backup strategy, enable autosave, and utilize UPS systems.
Other Issues
There are a few additional considerations to make before implementing SR technology in healthcare organizations.
Errors in transcription
This is a problem that affects both front-end and back-end systems. On the one hand, physicians may be overworked and overlook minor errors (according to Gary David’s research). On the other side, transcription service providers may overlook crucial details as well.
In any case, people have a proclivity towards error. When data is entered manually, the same errors may occur.
In the case of back-end SR, poor grammar becomes a serious issue when the system fails to recognize a specific user and their common errors, necessitating an editor to double-check.
Cost
The cost of setting up a voice recognition system is fairly high. Additionally, the cost increases with back-end SR, as hospitals must hire additional people, such as transcriptionists or editors. However, certain healthcare facilities that have implemented computerized medical transcription software have reported significant price savings.
Adoption difficulties
Other factors, such as the physicians’ age or speech difficulties, may influence successful voice recognition adoption. For instance, experts recognize that younger physicians are more ready and able to utilize technology than more established practitioners.
Security
Security is another aspect that requires close consideration. It is critical that the SR solution selected is HIPAA compliant.
Each method of speech recognition has distinct advantages and disadvantages. David and van Terheyden concur that this technology has the potential to both simplify and complicate practitioners’ life. That is why they believe it is critical to “allow physicians to optimize workflow using whichever system they prefer.”
Final Thoughts
In this article, we discussed the benefits and drawbacks of SR deployment in hospitals and determine whether this technology represents a substantial advancement or adds to existing problems.
We uncovered a slew of benefits of speech recognition based on statistics and expert medical conclusions, including increased productivity and improved work procedures. However, upon further analysis, we discovered a number of difficulties.
Several of these obstacles are minor and readily overcome (noise or power outages). However, certain issues (accent recognition or poor grammar) require special attention from experts in custom medical software development. The way developers overcome present obstacles will determine whether the future of SR technology is bright or bleak.
