Artificial intelligence is not new to healthcare. AI applications were first used in the 1970s to help with biomedical problems.
These days, AI spans numerous healthcare applications, from appointment scheduling and post-discharge follow-up to symptom assessment, dissemination of patient education, answering of common patient questions, retrieval of basic billing information and more.
A recent Becker’s Healthcare survey among healthcare leaders points to AI’s popularity in the industry:
- Five out of 10 survey participants on average indicated their patients are using AI-based tools for patient engagement.
- Nearly two-thirds said their organizations have experienced greater patient satisfaction. Half have seen higher levels of staff satisfaction, and nearly half have seen increased revenue.
- More than half of survey respondents said they plan to begin applying AI to patient engagement communications.
Yes, the adoption of AI certainly has the potential to transform the healthcare industry. However, the importance of ethical and responsible AI in healthcare cannot be overstated as it is essential for ensuring patient safety, equity and trust.
What is Responsible AI?
There are many definitions for responsible AI. The International Organization for Standardization (ISO) describes it as the practice of developing and using AI systems in a way that benefits society while minimizing the risk of negative consequences. Key principles of AI ethics consist of:
- Fairness: Datasets used for training the AI system must be given careful consideration to avoid discrimination.
- Transparency: AI systems should be designed in a way that allows users to understand how the algorithms work.
- Non-maleficence: AI systems should avoid harming individuals, society or the environment.
- Accountability: Developers, organizations and policymakers must ensure AI is developed and used responsibly.
- Privacy: AI must protect people’s personal data, which involves developing mechanisms for individuals to control how their data is collected and used.
- Robustness: AI systems should be secure – that is, resilient to errors, adversarial attacks and unexpected inputs.
- Inclusiveness: Engaging with diverse perspectives helps identify potential ethical concerns of AI and ensures a collective effort to address them.
Key to responsibly utilizing AI in healthcare is ensuring that it augments operations instead of replacing them. AI solutions should be designed with input from healthcare providers and professionals with experience in technology for the industry.
Healthcare providers should be transparent about the type of generative AI they are using, including the source(s) of their information. They must prioritize informed consent protection and mitigate concerns about possibly leaking protected health information (PHI).
Benefits of Responsible AI in Enhancing Patient Support
Today’s healthcare consumers expect convenience, and conversational AI provides that through 24/7 availability. Plus, it does so without adding to the workload of healthcare provider staff, most of whom already are dealing with burnout from labor shortages.
Three of the primary ways in which responsible AI is enhancing patient support are:
1. Boosted Patient Engagement
Research has linked higher levels of patient engagement to the greater use of preventive care, less smoking and obesity, more positive rankings of relationships with providers, less delay in seeking care, greater awareness of treatment guidelines, improved clinical indicators, a reduced number of hospital and emergency visits and lower hospital readmission rates. And, effective patient engagement can improve patient outcomes, quality of life and safety as well as decrease healthcare costs.
Even with these perks, many healthcare providers aren’t winning in the patient engagement game. In a survey of more than 300 clinical leaders and healthcare executives, more than 70 percent of the respondents reported having less than half of their patients highly engaged, and 42 percent said less than 25 percent of their patients were highly engaged.
Patient engagement isn’t just a positive result of utilizing AI. It also can potentially lead to improvement in the acceptability of AI technology and support its transition into clinical practice. How? By fostering seamless communication between providers and their patients and empowering patients to take an active role in their healthcare journey. When patients are actively engaged, they are more likely to attend doctor appointments and recommended screenings, leading to better health outcomes.
Conversational AI, which should be part of an overall patient engagement strategy, provides a human-like interaction for patients while giving them information specific to their healthcare. This personalized communication engages patients by being able to provide meaningful guidance and information and ensures that a broader patient demographic receives the care they need.
2. Optimized Operational Efficiency
Healthcare providers and their staff continue to be encumbered by a plethora of administrative tasks, many of which are repetitive and time-consuming. Though technology can be employed to streamline such tasks, solutions should seamlessly integrate into existing healthcare workflows to automate tedious administrative responsibilities instead of creating more of a burden.
Voice-enabled conversational AI helps to reduce the administrative burden of physicians’ staff by handling many common patient inbound and outbound calls, automating error-prone operational tasks and improving resource allocation. Physicians and their staff can reduce administrative backlogs and focus more on actions that require human expertise.
Additional advantages of using conversational AI in healthcare include:
- Better resource allocation
- Shorter wait times for patients
- Enabling of self-service appointment scheduling for patients
- Freeing of staff to handle more complex patient-centric issues
- Elimination of operational bottlenecks
- A reduction in operational costs
- Minimized staff downtime
- Improved staff satisfaction and retention
- Enhanced “brand” awareness
3. Improved Health Outcomes
One of the most substantial ways responsible AI contributes to improved outcomes is through expanded access to care. When patients have more convenient access to care through self-service, they are more likely to have a better overall experience with their healthcare provider, promoting increased engagement and better health outcomes.
Along with promoting increased access to care, conversational AI solutions enable patient-centric care communication, a component of quality outcomes. They empower patients with immediate access to accessible, reliable and accurate information at any time of day to ensure timely responses to queries or concerns, ultimately contributing to improved health outcomes.
The level of personalized care offered by responsible AI tools allows patients to receive relevant and practical advice that fits their unique health needs. The result of such targeted patient education is improved adherence to treatment plans for more effective outcomes.
Next Steps
In the next part of this blog, we’ll outline the key challenges and risks with responsible AI. And, we’ll discuss practical use cases for patient support. In the meantime, listen to a sample recording of Providertech.ai, or contact us for more information.
