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The Future of AI for Healthcare Providers

By 11.01.23
Reading time: 4 minutes

The security of health records is a source of some concern for Americans, according to a Pew Research Center survey exploring public views on AI in health and medicine. The survey found that 37% think using AI in health and medicine would make the security of patients’ records worse, compared with 22% who think it would improve security.

Concerns over patient records are just the tip of the AI iceberg for healthcare organizations. Many providers struggle to figure out how to protect while simultaneously leveraging their patients’ data – especially with the evolution of AI. 

AI has added an additional layer of complexity that can both help and hurt organizations if it is not used in the right way. Here, we look at how healthcare providers are reexamining their data strategy and ecosystems and considering solutions such as Salesforce Data Cloud that serve as customer data platforms that safeguard actionable insights powered by AI.

The challenges of AI in healthcare

The world of healthcare technology is rapidly advancing with several tools to store, index, and search the explosion of patient-centric data. Health data comes from a variety of sources, including clinical systems of record, medical devices, long-term care management solutions, payer claims, pharmacies, health information exchanges, and clinical trial management systems. Such systems produce or consume data and support applications that enable clinicians to deliver personalized care or care managers to identify gaps in care with patient populations.  

Healthcare is an industry heavily guided by rules and regulations around compliance and security. These regulations extend to the use of data in electronic medical records (EHR) with HIPAA rules about how electronic protected health information (ePHI) is processed, stored, transmitted, and disclosed. The use of EHR can quickly become problematic when it comes to a healthcare organization’s service center, where agents may need access to EHR to provide an optimal patient interaction. 

But what happens to EHR when AI is added to the mix? 

Generative AI is supposed to improve productivity, automate processes, and solve problems. And it does all those things and more but faces a roadblock when it comes to EHR compliance. That’s because generative AI insights are powered by data, which becomes challenging when that same data must be protected. According to a recent paper on regulatory considerations on artificial intelligence for health by Dr. Jeremy Farrar, Chief Scientist at the World Health Organization, validating data, being clear about the intended use of AI, and committing to data quality, privacy, and protection are key considerations for using AI in healthcare and therapeutic development.

A healthcare framework for adopting AI

When determining where to start with AI, healthcare providers should consider these critical questions for identifying the most advantageous use cases:

  • What is the problem you are trying to solve?
  • How does AI improve the patient experience, engagement, or health outcome?
  • What is the business value? 
  • How do you plan to measure success?

Silverline’s analysis from conversations with our healthcare and life sciences clients has resulted in use cases falling into three main themes:

  1. Personalization: Patient contact centers with triage nurses and schedulers can utilize health scores to provide a personalized response to the patient’s inquiry rapidly. Scores are calculated by aggregating and harmonizing clinical, device, and claims data from various sources.
  2. Population: Care managers and navigators recommend interventions to barriers or close gaps in care. Patient cohorts or registries are formed by segmenting the patient population on attributes related to demographics or social determinants.
  3. Personalization at scale: Automated patient outreach may be necessary when care measures fall outside specific thresholds and interventions. Care measures are available through near real-time data integrations with medical devices or EHRs.

Implementing AI use cases in healthcare

Providers use Salesforce Data Cloud to ingest first-party data from a variety of sources — such as a health information exchange, EHR application, or claims management system — or use tools that have integrations with third-party data providers to embed in Salesforce Health Cloud. Einstein GPT infuses Salesforce’s proprietary AI models with generative AI technology and real-time data from Salesforce Data Cloud to ingest, harmonize, and unify the provider’s patient data. 

The Einstein Trust Layer allows providers to benefit from generative AI without compromising their patient data. This solution helps healthcare providers work towards de-identifying the patient data, especially when it comes to clinical or diagnostics information, and controls the level of security that a call center agent or website needs to conduct an informed patient interaction.

One of the primary use cases for generative AI for healthcare providers is fetching data to inform the call starts at a patient access center by giving agents a unified patient profile. Background data about medications, allergies, or procedures can be gathered from the caller’s EHR and sent to Einstein GPT for summarization. The summarization gives the agent a 360-degree view of the patient to reduce call times and create a better patient experience. 

Healthcare providers can also leverage an AI chatbot to “generate” conversational experiences from specific data sets on their web pages. Combining the intelligence of what the AI chatbot knows about the patient and what is happening in real-time on the website can generate a personalized response that ultimately leads to better patient care and health outcomes.

For example, if a patient is on the provider’s directory looking to make an appointment, the chatbot can focus on the patient’s past and future appointment data. Or it can use specific keywords in the patient’s visit history to match the issue with a specialist, such as an orthopedist for back pain. 

Silverline has the frameworks to identify healthcare provider AI use cases and use those frameworks to recommend secure and compliant solutions that will bring the best time to value, ROI, and patient satisfaction scores to your organization. Find out how Silverline’s healthcare experience and expertise can help you on your Salesforce AI journey.

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