And next patient, please!
As I exited the doctor's consultation room, her words began to slip away from my memory. It's a common occurrence, a fleeting recollection of the essential details we discussed. Perhaps the information will resurface in the hours to come, or perhaps it will dissipate into the abyss of forgetfulness.
Reassured by conversations with loved ones, I realized that this struggle with "medical speak amnesia" is not mine alone. In fact, this phenomenon has been the subject of academic research for nearly half a century, with studies like Bradshaw, P., & Ley, P., & Kincey. J., & Bradshaw, J. (1975) shedding light on the challenge of recalling medical advice.
They found factors that hindered recall, e.g. complexity and amount of information impact recall accuracy and high anxiety (which we all experience during a visit to the doctor) is associated with poorer recall. They also found factors that could help improve recall, e.g. active engagement during consultation and clear language, written information, and repetition.
Understanding and remembering are vital for better outcomes— a key to increased patient satisfaction, improved quality of life, and reduced follow-up appointments. So, how can we ensure that the doctor's message lingers in the minds of patients, regardless of their background or literacy level?
Time constraints plague doctors as appointments are crammed back-to-back. They barely have a moment to share the core medical message, let alone verify its reception. With just a couple of minutes before the next patient's arrival, their attention is divided by necessary administrative tasks.
Ideally, every consultation would have an extra presence—a companion who is intelligent, a record-breaking note-taker, and empathetic. Unfortunately, such individuals are exceedingly rare, expensive, and inevitably exhausted.
Therefore, the next best solution lies in an assistant—Intelligent, yet Artificial.
The integration of Artificial Intelligence (AI) into healthcare has the potential to revolutionise patient care and medical practices. One area where AI is making significant strides is speech-to-text transcription during patient consultations. Advanced AI algorithms enable medical professionals to seamlessly convert spoken words into concise text documents, highlighting critical findings and instructions.
In cases where text processing poses challenges for patients, the Artificial Intelligent Assistant can replace text with instructive images during the consultation. This technology streamlines the process, allowing doctors to provide focused care and empowering patients with clear summaries of their medical encounters.
But the question remains: Can AI facilitate efficient documentation and enhance patient engagement in healthcare settings?
AI-powered speech-to-text transcription technology, fueled by sophisticated Natural Language Processing (NLP) algorithms, represents a cutting-edge solution. This technology has been tried and tested in various fields, including service call centers.
The NLP algorithms have undergone extensive training on vast medical databases, enabling them to accurately recognise and interpret specialized terminology, medical jargon, and contextual nuances.
When seamlessly integrated into the consultation process, this technology converts a medical doctor's spoken words into a real-time written text document.
In traditional consultations, doctors find themselves juggling multiple tasks: actively listening to patients, making clinical decisions, and documenting relevant information.
Imagine with the introduction of AI speech-to-text transcription, this could significantly simplify this process. Doctors would now wholeheartedly engage with their patients, address their concerns, and make accurate diagnoses without the burden of extensive note-taking.
AI-powered transcription captures the essential details of the conversation, generating comprehensive summaries that doctors can review and validate after the consultation.
This streamlined approach enhances patient care by minimising oversight, ensuring critical information is captured, and more importantly tailored to the audience receiving it.
Although the AI-generated capture provides a concise summary of the consultation's important findings and instructions, it is still a direct translation of the doctor's words, which may not always be clear to the patient.
To ensure clear understanding and execution of the message, it needs to be tailored to each patient, taking into account their individual preferences and needs. This requires the healthcare professional to have knowledge of the patient's characteristics, motivations, and drivers. Identifying different patient archetypes or personas can help in this process, which is typically part of a patient-centric design process.
By understanding patient behaviour and creating personas, healthcare professionals can personalise their messages and decide how to summarize them in text, images, or a combination.
Simultaneously, the consultation results can be further contextualised and distilled to provide the relevant information and instructions to other healthcare professionals in the system. Whether the medication required for the pharmacist to dispense, or followup procedures for the nursing team to carry out. This information can be delivered at the right time and place, enabling each member in the ecosystem to focus on their role with accuracy and efficiency.
Clear and concise documentation created through AI-powered transcription fosters better patient understanding and engagement. Patients equipped with summarised documents are more likely to comprehend their conditions, treatment options, and potential risks.
As a result, they become better equipped to make informed decisions about their healthcare and adhere to prescribed treatment plans.
Moreover, these summaries serve as invaluable educational tools when connected to a wider knowledge database. Enabling patients to gain deeper insights into their health conditions and the significance of following medical advice.
This increased knowledge nurtures a sense of partnership between patients and healthcare providers, leading to improved patient compliance and stronger doctor-patient relationships.
While AI-powered summarisation technology offers significant benefits, it also presents challenges. Accurate recognition of spoken words and contextual understanding can still pose obstacles, particularly in cases involving strong accents, background noise, or complex medical terminology. Continuous AI training is necessary to address these challenges.
Despite the advanced capabilities of AI, the human touch remains indispensable in healthcare. AI-generated summaries are designed to undergo review by medical doctors before being shared with patients.
This crucial step ensures the accuracy and relevance of the presented information. Doctors can make necessary edits, provide contextual information, or elaborate on specific points, guaranteeing that the summary accurately reflects the nuances of the consultation.
In any implementation of healthcare technology, data privacy and security must remain paramount. Patient confidentiality must be maintained at all times, and AI-powered systems should adhere to stringent regulations and industry best practices.
Employing encryption, secure storage, and anonymisation techniques is essential to safeguard patient information and ensure compliance with data protection laws.
The integration of AI-powered speech-to-text-and-image transcription into healthcare consultations marks a significant milestone in patient care. This technology will streamline the documentation process, allowing doctors to focus on their patients while capturing critical information accurately.
AI-generated summaries empower patients with accessible and concise information, fostering better engagement and adherence to treatment plans.
But AI alone is not enough. As stated earlier, it is an assistive technology. We still need (and will continue to need) the human perspective and control to make it really beneficial and engaging for both patients as well as healthcare staff.
For that to happen, we have to start with identifying the needs of patients and staff. Taking a user centric approach to uncover what drives their behaviour, what is of real value to them and why.
From my experience, I have found it is never the technology itself or the product features, but how it is designed to align with those more human needs. For example, how might it support them to feel more in control, to easily connect with people they trust and improve their overall quality of life.
These are some of the factors that will help direct this ‘brave new technology’ down a more meaningful path. By doing so, we can look forward to improved patient outcomes and better staff experiences, for now, and in the future to come.
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