What is AI and how is it used?
AI stands for Artificial Intelligence, or the implementation of a machine to imitate intelligent human behavior. Over the past few years, AI has contributed to treatment design, drug creation, digital consultation, CT scans and other testing.
Though this technology is making a splash in all kinds of industries, it’s a big topic of discussion for the healthcare field–specifically in regards to voice recognition software. Before diving into voice recognition and its relation to healthcare, let’s look at the benefits and risks of using AI.
Benefits of AI in Healthcare
- AI has been used for the advancement of treatments.
- The precision and efficiency of AI makes human errors less likely.
- AI allows physicians to search public databases with info from thousands of doctors and patients. With more information comes more personalized diagnoses.
AI Risks in Healthcare
- Because AI is fairly new, it’s more probable for it to be less accurate and reliable.
- A program is only as good as the data it learns, meaning big and newer health cases are at risk for inaccuracy.
- AI hasn’t been perfected, so doctors will still need to provide their expertise. This throws the supposed efficiency of AI into question.
Though this new medical technology shows some huge potential for healthcare, tools like voice recognition are posing some big threats.
What is Voice Recognition?
Voice or speaker recognition is the ability of a machine or program to receive and interpret dictation or to understand and carry out spoken commands. Voice recognition is a form of AI and much like the rest of artificial intelligence softwares, voice recognition is making a splash in the healthcare field.
While there’s no denying that artificial intelligence has done great things for the industry, we’re looking critically at the very real threats that voice recognition poses for physicians and their practices.
Issues with Voice Recognition in Healthcare
1. Voice Recognition Is Not Immune to Replicating Human Error
Human-generated case histories are the root of healthcare data history. For AI to implement new records, it needs adaptable and dynamic algorithms. This means more time and precision on the physician’s part to integrate any new information.
A specific example of this is voice recognition software. Though on the rise in the healthcare industry, it poses quite a big threat. While it can help physicians gather patient information quickly, it can’t quite pick up on the intent of the physician. Errors as small as missing a punctuation point can have detrimental effects on the documentation of patient visits and health records.
2. Training Complications with AI
Yes, artificial intelligence is in fact intelligent. However, the wealth of knowledge that these machines have must come from somewhere. The majority of AI is data logistics or machine learning algorithms. Advances in data sets are what fuels all of its changes and advancements.
Not only that, but these data sets must be accurate and concise in order to be effective at all. Even with all of the right data, the quality of that data can still be compromised. In summation, the time and intricacy that goes into training the technology is an entire project of its own.
3. Relying Too Heavily On Voice Recognition
Quite literally, VRS picks up on spoken words and documents them directly into the system. That’s it. A machine can enter the words of the physician, but much like Siri on our phones, the results are not always accurate.
A physician’s notes need to be completely accurate, concise documentation in order to achieve proper patient care. With an error rate of over 5%, voice recognition software just isn’t cutting it. This error rate requires a human to go back in and check for inaccuracies, taking up even more valuable time from our physicians.
AI wasn’t created, at least not yet, to cure cancer or to completely supersede the need for doctors. It was created, however, to carry out minor, discrete problems and processes that create value. However, relying too heavily or too completely on artificial intelligence in voice recognition software can be quite problematic.
4. The Great Ethics Debate
Artificial intelligence in healthcare is often meant to relieve physicians of some of their never-ending workload. However, the ethical debate that comes into question is, to what extent will AI replace physicians all-together? As we know, AI has a long way to go. In its current state, the option for machines to replace doctors entirely is not plausible.
When it comes to voice recognition, the discrepancy grows even more. Say for example that the voice recognition software picks up the wrong words from the physician. The physician said the correct thing, but the software documented something else. Who is ultimately responsible for that error–the machine or the physician working with it?
5. Voice Recognition Interference of Patient-Provider Relationship
The healthy balance between technology and doctors is essential for optimal patient care.
Here’s what we mean by that: Much like any other industry, humans want to feel cared for and understood. A machine simply can’t understand the specific needs of a patient like a physician can. In other words, even the best, most intelligent technology in the world can’t replicate the sympathy and care of a human being.
Electronic health records (EHRs) are a perfect example of patient-provider interference.
EHRs tend to cause an interference with the patient-provider relationship, as they suck time away from already-limited appointments. They also prevent clinicians from picking up on non-verbal cues by keeping their eyes locked on their computers instead of on the person in front of them.
Alternatives to AI for your practice
At the end of the day, the most important aspect of a physician’s job is to provide the utmost care to their patients. As we now know, a huge factor that goes into proper patient care is the health of the patient-provider relationship. Likewise, if a patient doesn’t feel that their physician is caring for and properly assessing their needs, the patient-provider relationship is likely to suffer.
What’s worse is that systems like voice recognition, meant to save the physician time, are actually making the job of a physician more difficult. Voice recognition misses out on huge aspects of human speech, such as the intent of the physician. Instead of saving physicians time, it’s likely the physician will have to go back into the data collected by the system and edit as needed.
An alternative to using voice recognition in your practice is hiring a medical transcription service company for these time-consuming services. Medical transcriptionists are humans who are trained to understand and transcribe the intricate details of a physician’s diagnosis. And what’s more, they can decode all of the aspects of a physician’s speech that a computer simply cannot–making your transcription more accurate and reliable.
Artificial intelligence is certainly on the rise in the healthcare world. However, the risks of completely immersing the medical world in AI pose potential threats to the industry and more specifically, to the care of patients.
To learn more about medical transcription services and all of the ways they can help improve your practice, reach out to one of our professionals today.