Health management platform DexCare innovatively applies artificial intelligence (AI) to solve healthcare access challenges. Its AI-powered platform helps healthcare systems overcome rising costs, limited capacity, and fragmented digital infrastructure.
Faced with worsening healthcare outcomes and rising costs for Americans, Derek Strath, co-founder of DexCare, sees opportunity in crisis and leads efforts to apply AI and machine learning (ML) to healthcare’s toughest operational challenges — from overcrowded emergency rooms to disconnected digital systems.
Streat, familiar with using AI to solve healthcare problems, guides DexCare in its AI and machine learning strategy to solve the industry’s most pressing challenges: skyrocketing costs, resource constraints, and the inability to do more with less. Its platform helps break down data silos to optimise care and deliver compelling purchasing experiences.
This combination improves patient access to care and optimises healthcare resources. DexCare enables health systems to serve 40% more patients with their existing clinical resources.
Strath acknowledges that some cutting-edge companies use AI to improve clinical and medical research. However, advanced AI tools like conversational generative AI are less common in the healthcare access space. DexCare addresses this gap in care.
“Access is poor, and we strongly believe that there have not been enough solutions to balance the needs and goals of patients, providers, and the healthcare system,” he told TechNewsWorld.
Improving Patient Access With Predictive AI
Achieving that balance depends on the underlying information drawn from healthcare providers’ neural networks, ML models, classification systems, and advancements in generative AI. These elements build on one another.
To improve customer experience (CX), the DexCare platform helps healthcare professionals optimise the algorithm so everyone wins. Street explained that the goal is to ensure that patients receive what best suits their intent and motivations while respecting the capabilities and needs of healthcare professionals.
He describes the platform’s technology as a data-driven foundational pyramid optimised and managed by AI. These components provide highly accurate outcome predictions for recommended treatment options.
“It could be a doctor in a clinic or a nurse in a virtual care system,” he suggested. “I’m
not talking about clinical outcomes. I’m talking about what you’re looking for.”
Ultimately, that managed balance will not burn out all your providers. It will make this a sustainable business line for the health system.
From Providence Prototype to Scalable Solution
Strath defined DexCare as an access optimisation company. He explained that the platform emerged from a ground-up design at Providence Health System.
After four years of development and validation, he launched the technology for broader use in the healthcare sector.
It is widely tested and highly effective in its function. This has also allowed us to provide scalable solutions for other organisations. Our expansion makes access to healthcare easier for consumers and patients and more sustainable for the healthcare providers and health systems we serve, he said.
Digital Marquee for Consumers, Service Management for Providers
DexCare’s AI works on several levels. It serves the healthcare system or healthcare facility as a contact centre. This part attracts and selects audiences, consumers, and patients. Its digital assets can include websites, landing pages, or screening kiosks.
Another platform part intelligently directs patients to the safest and most optimal treatment option. This process uses accumulated data and automatically allocates healthcare system resources.
“It manages schedules, staff, and available space and automatically allocates them when and where they can be most productive,” Street explained.
The platform stands out for its load-balancing capabilities. It uses AI to optimise all of these components. The decision engine uses AI to ensure that the resources selected and the services needed are aligned so that medical treatment can be delivered most efficiently and efficiently to meet the patient’s and the organisation’s needs.
How DexCare Integrates With CRM Platforms
DexCare is not customer relationship management software, Strath said. Instead, the platform is a plug-in that integrates AI tools and data services with other platforms like Salesforce and Oracle.
“We’re making it as flexible as possible. It’s so scalable that we can now reach about 20% of the U.S. population through our health system partners,” he explained.
Patients don’t realise they’re interacting with the DexCare Experience console, which is owned by Kaiser, Providence, and SSM Health, some of the health systems that use the DexCare platform. The platform is flexible and familiar with the needs of different healthcare organisations.
For example, appointment management technologies book appointments and offer synchronous virtual solutions.
“Regardless of the modality or setting, we can connect to the healthcare system you use or use your core resources,” Street said.
He noted that the intelligent data collection integrated into the DexCare platform provides access to patients’ electronic health records (EHRs), which include demographics, medical history, diagnoses, medications, allergies, immunisation records, lab results, and treatment plans.
“The application programming interface [API] gives us real-time availability, allows us to predict a certain provider’s capacity, and maintains EMR as a source of truth,” said Streat.
AI’s Long-Term Role in Health Care Access
Healthcare management using conversational generative AI provides insight into where organisations are struggling, need to adjust their operations, or need to redeploy staff to manage patient flow. All of this is done on the backend of the platform.
According to Stritt, the initial value proposition is simple. It helps attract 20 to 30 per cent more patients to the healthcare system. Organisations generate nine times the value of the initial visit in subsequent revenue from additional services, Stritt said.
Another aspect of the value proposition, he said, is lower marginal cost per visit. This is due to the alignment of resources with patients, allowing load balancing across the organisation’s network.
“It depends on the specific use case, but we’ve found up to 40% additional capacity in the health care system without adding additional resources,” he said.
How? That’s where AI’s underlying data comes in. It helps doctors decide which patients to assign to which providers.
“Not everyone needs to see an expensive doctor in the office,” Strath argued. “Sometimes a nurse for a virtual consultation or educational information will do the trick.”
Despite all the financial metrics, patients want to get care and move forward, which is the whole point, he suggested.
Why Generative AI Lags in Health Care
Strath lamented the rapid advancement of generative AI sophistication, which includes conversational interfaces, analytics capabilities, and predictive domains. These technologies are used in other industries and businesses but have not yet been widely adopted by healthcare systems.
He noted that part of the delay is because healthcare access needs are varied and do not lend themselves to conversational AI solutions rapidly deployed in legacy systems. Ultimately, transforming healthcare requires implementing solutions at scale.
“In the health care system, the infrastructure of the health care system, and the infrastructure that’s needed to run the record-keeping systems, it’s just a different world,” he said.
Strath believes that AI will allow us to stop searching through a long list of doctors online and book an appointment with a robot operator with a pleasant accent.
“We will focus on the intelligence inside and continue to apply it to these simpler ways of interacting with the health care system. I’m incredibly excited about that,” he concluded.