Cancer screening programs are important parts of preventing illness in the United States. Finding cancer early, especially colorectal cancer (CRC), helps patients get treatment sooner and have better health results. New computer programs using artificial intelligence (AI) help make communication in these programs more personal. This aims to get more patients involved and follow screening plans. This article looks at how AI-driven personalized communication affects patient engagement and behavior, focusing on colorectal cancer screening in the U.S. It shows how AI care agents that speak many languages and use conversation help reach more people and increase participation.
Traditional efforts to invite people for cancer screening usually use mailed letters or phone calls by staff, but these ways sometimes fail to reach people who do not speak English well or who do not use online health systems. AI systems have been tested to give outreach in the right language by automated calls and digital tools. This helps give education, reminders, and helps order test kits like the fecal immunochemical test (FIT) for colorectal cancer.
One big study by WellSpan Health looked at 1,878 patients who could get CRC screening. This included 517 Spanish speakers and 1,361 English speakers. The AI agents made calls in the patient’s preferred language, explained CRC, and helped with FIT kit requests. The study found that Spanish speakers used the AI system more than English speakers.
This challenges the idea that people who don’t speak English well are less likely to use technology in healthcare. For example, 18.2% of Spanish-speaking patients chose FIT testing, while only 7.1% of English speakers did. The AI connected with 69.6% of Spanish speakers but only 53.0% of English speakers. Phone calls with Spanish speakers lasted longer on average (6.05 minutes) than calls with English speakers (4.03 minutes). The results showed that the choice to speak Spanish was linked to more FIT test sign-ups even when other factors were considered.
This shows that AI talking in the patient’s language helps more people take part in preventive care, especially groups that usually get less attention in normal healthcare outreach. It also shows how technology that respects culture and language can help reduce differences in healthcare access.
AI-driven communication affects how patients behave by encouraging healthy actions like scheduling and completing tests. Digital behavior change tools (DBCIs) that use AI and machine learning send messages and reminders that fit the person’s situation.
A review in the Mayo Clinic Proceedings: Digital Health looked at 32 studies about AI in DBCIs for health behavior change. It found that types of AI like machine learning, reinforcement learning, natural language understanding (NLU), and conversational AI help keep patients involved and following preventive steps. Most studies focused on heart and metabolic health and lifestyle, but cancer screening was also an important area.
Conversational AI helps by understanding how patients respond and changing the talk in real time. This can make patients more motivated, lower dropouts, and help with challenges like language or health knowledge.
For medical groups in the U.S. with many Spanish speakers, using AI that speaks many languages can help increase screening rates. By giving clear and personal information based on patient choices, AI can help patients follow health steps needed for early cancer detection.
One problem for medical offices is managing many calls and following up with patients. AI systems can help by making front-office work easier and lowering the workload for staff.
Companies such as Simbo AI offer AI tools that automate patient calls and replies for healthcare providers. These systems offer:
These robots help front-office staff by handling repeated tasks. This lets staff spend time on harder patient needs. Also, AI keeps personal communication with different patient groups, which helps close the gap in preventive care outreach.
New research also shows that mixing AI with new technologies like 5G networks and the Internet of Medical Things (IoMT) helps with patient monitoring and better connections. These are mostly used in remote care now but may help cancer screening by keeping track of patients and helping them stick to care plans.
Healthcare groups in Pennsylvania and Maryland like WellSpan Health showed that AI can lower inequalities in colorectal cancer screening. The study found that Spanish-speaking patients are open to AI communication and more likely to sign up for screening than English speakers with AI outreach.
This progress moves toward fairer healthcare access. Non-English speakers and people without online accounts usually get less attention from digital outreach. AI that “speaks” patients’ languages and understands culture through tailored messages opens up easier ways to take part in care.
For medical offices in diverse parts of the United States, using AI that can talk in many languages is necessary. AI can also reach many other language groups to help meet local patient needs better.
Even though AI helps with patient engagement and work efficiency, there are challenges that health leaders and IT workers must consider:
These issues show that even though AI tools provide benefits, healthcare organizations must have rules to use AI responsibly.
The studies show promising short-term results from AI outreach but stress the need for longer studies. It is still unclear if initial increases in test sign-ups turn into steady patient follow-through and better health over time.
Also, expanding AI to work with electronic health records (EHRs), care coordination, and patient education beyond screening might support long-term disease prevention better.
Research on the long-term impact on health and cost will help health leaders decide how to best use AI in prevention work.
Medical office leaders and IT managers are important in adopting and improving AI in screening programs. Key points for healthcare leaders in the U.S. include:
By focusing on these, medical offices can improve screening rates and overall preventive health care.
The primary objective was to evaluate the effectiveness of a multilingual AI care agent in engaging Spanish-speaking patients for colorectal cancer screening compared to English-speaking patients.
The study included 1878 patients eligible for colorectal cancer screening; 517 were Spanish-speaking and 1361 were English-speaking patients without active web-based health profiles.
The AI agent made personalized telephone calls in the patient’s preferred language, provided education about colorectal cancer screening, and facilitated fecal immunochemical test (FIT) kit requests.
The primary outcome was the fecal immunochemical test (FIT) opt-in rate to gauge patient engagement with colorectal cancer screening.
Spanish-speaking patients had significantly higher engagement: FIT opt-in rates were 18.2% versus 7.1%, connect rates were 69.6% versus 53.0%, and call durations averaged 6.05 minutes versus 4.03 minutes for English speakers.
Yes, Spanish language preference was an independent predictor of FIT test opt-in with an adjusted odds ratio of 2.012, meaning Spanish speakers were twice as likely to opt-in after controlling for demographic factors and call duration.
Spanish-speaking patients were younger (mean age 57 vs 61 years) and more likely to be female (49.1% vs 38.4%) compared to English-speaking patients.
The findings suggest that language-concordant AI outreach can reduce longstanding disparities in preventive care access by significantly increasing engagement among non-English-speaking populations.
Limitations included being conducted in a single healthcare system, a short study duration, and the absence of follow-up data on whether patients completed screenings after opting in.
Future research should focus on assessing long-term adherence to screenings and determine whether increased engagement with AI outreach translates into improved clinical outcomes for patients.
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