AI will also play a key role in the two other technologies that respondents rated most highly as saving time in the next five years. It is a clinical documentation tool and software for analyzing images and test results. His one example of the former is AI-driven ambient voice technology (AVT). AVT uses speech-to-text software to automatically transcribe patient visits and then uses natural language processing to convert these transcriptions into summary notes and letters. Asif Bachlani (Consultant Psychiatrist at Priory Group and Associate Non-Executive Director at Kent and Medway NHS and Social Care Partnership Trust) says voice recognition technology will “significantly take the burden off frontline clinical staff managers. He said there is a possibility that it could be reduced. Ben Jeeves (Deputy Chief Clinical Information Officer, Clinical Safety Officer, Advanced Practice Physiotherapist, Midlands Partnership Universities NHS Foundation Trust, North Integrated Musculoskeletal Service) similarly highlighted the “heavy burden” on administrators, saying: We envisioned a future where AVT could lead to a “complete cure.” By removing the administrative processes associated with all clinical interactions that we currently require, the quality of consultations and patient interactions has been significantly improved.
When it comes to software that analyzes images and test results, some of the more ambitious aspirations for time-saving potential may take time to materialize. Stephen Harden, consultant radiologist at Southampton University Hospital and vice president of clinical radiology at the Royal College of Radiologists, says that current technology can effectively identify and measure the likelihood of lung nodules in his AI-enabled lung cancer research. I talked about my experience with screening. “It’s not a huge speedup, but it does speed it up to some degree,” he said, but also emphasized that the technology offers “real benefits” in maintaining the quality of image interpretation. However, in the longer term, there is significant interest in the potential for AI to act as a “pre-reader” of images, allowing more innovative ways to save time and support workforce capabilities. may be provided. Harden explains: “Once fully developed and implemented, reliable and accurate AI is expected to provide invaluable assistance to radiologists and diagnostic imaging departments.”
Rapid evidence review uncovers a potentially promising evidence base from a sample of 500 studies on the potential for time-savings through automated screening and interpretation of test results, X-rays, patient records, voicemails, etc. . Of his 34 studies in this area included in the sample, 85% reported a positive impact on staff time. However, as noted in the review, new technologies tend to have less evidence available about their impact, with more studies published in which the new technology found positive results than studies in which it did not work well. It may very well be possible. In contrast, more established technologies, such as EHRs, have generated a broader evidence base, which is more likely to include studies with mixed or negative results.
Imagining which technologies could free up time beyond the immediate future requires a significant degree of speculation. The exploratory nature of the interview format helped address the nuances of this question. We asked experts to comment on potential opportunities for the next 10 years, even his 20 years, and beyond, and many interviewees said they do not envision these long-term periods. I pointed out the fundamental difficulty of this.
Several interviewees discussed the potential of AI and other innovations to improve data analysis to support patient care and broader population health. Experts spoke of a more “proactive” model of care. This allows AI to generate intelligence about a patient’s health or identify patients who are at risk or vulnerable to developing certain conditions, with the aim of targeting early intervention and helping patients self-manage. Individuals and groups can be identified. Interviewees explained that this could improve patient health and address health disparities, as well as potentially reduce demand and increase system capacity.
We already have data in front of us. That’s how we use it. And I think if you start learning how to use the data that’s already available, if you can automate some of the information gathering and analysis, you can really make a difference and actually save a lot of time… Obstacles Whether it’s a risk or a risk, identifying things early will save you time in the long run.
Faith Ndebele, Consultant Psychiatrist at Solent NHS Trust and Chair of the Digital Psychiatry Special Interest Group, Royal College of Psychiatrists
If you can use a voice assistant within your EHR to ask, “This patient’s blood pressure is a little low, could you have done something else in the last 24 hours to stop this?” It will be very powerful.after that [for the technology] I will come after checking all the blood test results and medicines etc. [up] With relevant information. That would be the most helpful thing I can think of. It will save you a lot of time.
Joseph Alderman, Registrar of Anesthesia and Intensive Care at Birmingham University Hospitals, University of Birmingham NHS Foundation Trust and Postdoctoral Fellow
However, interviewees also acknowledged that there are barriers to realizing these goals, including fluctuations in data quality and the need to develop better data analysis capacity among NHS staff.
