Healthcare News & Insights

How artificial intelligence technology could improve communication at hospitals

Artificial intelligence (AI) is making its mark in many fields, and heath care is no exception. As AI technology becomes more readily available to hospitals in the near future, it’ll impact many aspects of care delivery, from provider decision making to patient communication. 

Research headed by The Dartmouth Institute for Health Policy and Clinical Practice shows how artificial intelligence can have practical applications for boosting clinicians’ communication skills.

AI can help providers, patients

Communication often isn’t emphasized in medical training, so many providers and clinical staff struggle when they’re trying to discuss key elements of the treatment process with patients and their families. However, advanced AI can assess how well clinicians communicate, and give them detailed advice for improving their skills and techniques.

Using recordings from past patient visits, AI can point out the strengths and weaknesses in each interaction, and offer suggestions for improvement.

In particular, researchers highlighted three key ways artificial intelligence can analyze conversations to help providers communicate more effectively:

  1. Analysis of words and phrases. AI has the capability to analyze word choice and phrasing in conversations between providers and patients. With this technology, providers could receive feedback on how well patients understood them, and their effectiveness at taking an appropriate history for a patient. AI will specifically look for issues such as excessive use of jargon. It’ll also offer diagnostic suggestions. As technology advances, AI could work in real time, helping providers better diagnose illnesses and offer better treatment options.
  2. Turn-taking analysis. Using turn-taking analysis, providers can figure out whether they’re leaving enough space in the conversation for patients and their families to talk and bring up any concerns they may have. If patients don’t feel like they’re given room to talk, they may feel uncomfortable discussing their care. They may also feel less inclined to follow their treatment plan post-discharge. AI can make clinicians more mindful of giving patients time to talk, and it can also encourage providers to ask better follow-up questions so they can get more accurate info out of patients when it’s their turn to speak.
  3. Analysis of tone and style in interactions. Advanced AI analysis can pick up on differences in patients’ tone and vocal pitch that typically happen in times of distress. This can provide unique insight into a patient’s health condition. For example, a depressed person is more likely to have specific changes in vocal pitch. Pointing this out to a clinician can prompt additional questions to evaluate a patient’s mental health. In addition, certain vocal changes may be an early indicator of heart failure, which could allow providers to head off a significant health crisis. AI tone analysis can also pick up on any changes in clinicians’ voices that may suggest they’re dealing with issues that would distract them from patient care, including burnout and fatigue.

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