Engineering Wellness and Efficiency in the Generative AI Era
Engineering Wellness and Efficiency in the Generative AI Era
Healthcare leaders face mounting pressure to reduce costs, enhance experiences, and stay ahead of regulatory changes. Artificial intelligence (AI) and Generative AI (GenAI) offer game-changing opportunities for the industry. For healthcare providers, it stands to revolutionize proactive health management, hyper-personalized services, and streamlined operations. Meanwhile, for health insurers, it has the potential to reshape health insurance benefit design, risk management, and member wellness.
This Guide for Healthcare Leaders Analyzes
- Transformative opportunities for AI
- Potential impacts
- Key implementation challenges
- The case for rapid adoption
Transformative Opportunities With Generative AI
Rapid technology advances are driving consumer expectations and options for care. The U.S. healthcare industry stands on the cusp of a transformative era powered by advanced analytics and holistic business transformation.
GenAI transcends traditional artificial intelligence by creating original content – text, images, audio, code, and data – from input or examples. According to Forrester, “Firms that actively harness generative AI (genAI) to enhance experiences, offerings, and productivity will realize outsized growth and will outpace their competition.”
In this sea of change, health systems and insurers continue to explore new ways to improve outcomes and organizational resiliency.
GenAI – with its ability to analyze large datasets, identify patterns and trends, and surface new content based on insights that were previously unknown – is transforming areas like search, product descriptions and recommendations, virtual agents, agent assistance, coding, content creation, narrative reporting, and process automation.
The important question on many leaders’ minds is how to operationalize GenAI safely and equitably, and how to do so in ways that will generate return on investment and truly advance health outcomes.
Transformative Shift
From Cost Management to Health Enablement
To genuinely appreciate AI’s transformative potential, one must contrast it with the industry’s status quo approaches.
Healthcare providers have long been reactive, addressing symptoms and conditions after they occur. In contrast, AI enables a proactive approach that focuses on early intervention, continuous monitoring, and personalized care pathways based on individual patient data, genetics, and lifestyle factors. This shift marks a profound reimagining of the provider's role: from delivering treatment to cultivating health.
For health insurers, the transformation is similar, sparking a move from traditional cost management to proactive health enablement. AI can be harnessed to offer hyper-personalized benefit plans, predictive risk analytics, and real-time insights that not only manage costs but also enhance member experience and engagement.
| Status Quo Approaches | New AI Approaches |
|---|---|
Reactive Reactionary utilization, treatment, and claims management |
Proactive Early intervention and optimized outcomes enabled by predictive analytics, continuous monitoring, and real-time risk adjustments |
Cookie Cutter Standardized care protocols and benefit plans |
Tailored Treatment and plan designs based on individual health data |
Data Silos Disjointed data systems across departments |
Integrated, Actionable Data Connected data ecosystems with robust governance and real-time insights |
Manual Processes Time-consuming, error-laden manual steps |
Intelligent Automations AI-augmented workflows with automated approvals and rapid diagnostics |
Limit Personalization Generic consumer communications |
Hyper-Personalization Individual-specific engagement and care plans |
The implications are clear. AI is not just a technology upgrade – it's the foundation for a fundamentally new model of healthcare delivery and insurance management.
Tackling AI Implementation Challenges
Implementing AI is not without its hurdles. Both healthcare providers and insurers must navigate challenges around data privacy, regulatory compliance, integration with legacy systems, cultural adoption, and demonstrating ROI.
| Pain Point | Potential Value Gained From AI |
|---|---|
| Data Privacy and Security: Handling sensitive health data requires strict adherence to regulations like HIPAA. | Building patient and member trust through privacy-by-design models reduces data breaches by up to 60%. |
| Regulatory Complexity: Compliance with evolving regulations is critical. | AI-powered compliance tools can reduce regulatory-related errors by up to 30%. |
| Integration with Legacy Systems: Outdated systems are prevalent and resistant to change. | Custom solutions that modernize the tech stack can improve operational efficiency by 35%. |
| Reliable Data: Poor or noisy data is a top barrier to enterprise AI adoption. | Unified, democratized data ultimately improves the finances, management, and operations of a health system. |
| Health Inequity: While AI has the potential to improve health outcomes, it also poses risks that could exacerbate existing health disparities if not implemented responsibly. | AI and data analytics can help close health disparity gaps by analyzing large, diverse datasets. |
| Staff Training and Cultural Adoption: Successful AI utilization requires skilled staff. | Tailored training programs can increase AI tool utilization by 40%. |
| Doubt on Return on Investment (ROI): High upfront implementation costs pose barriers. | AI can lead to a 10-15% reduction in overall costs within 3-5 years. |
Transformation Demands More Than Just Technology
Healthcare providers and insurers cannot simply implement AI solutions. Instead, organizations need to engineer revolutions in care delivery and member engagement. This means adopting a comprehensive approach that harmonizes technology, processes, and people for lasting impact.
A well-formed strategy aligns key business needs with people, technology, and processes.
Developing a strategy is an important step for healthcare organizations exploring emerging technologies. However, it’s important to not think of advanced analytics, AI, and GenAI as the strategy itself, but as an enabler.
The approach should be rooted in developing tailored, ethical AI solutions that address critical pain points in the healthcare industry while prioritizing consumer care and services, experiences, regulatory mandates, and privacy.
Advanced analytics and intelligent automation can drive sustainable cost savings and proactively address long-standing health industry challenges, including operational inefficiencies, personalization, quality of care and service, adverse utilization, prior authorization, concurrent review, and claims processing.
See How We've Helped Others
success story
Enabling Better Insights Into Key Patient Data Using GenAI
We implemented a generative AI model to search through structured and unstructured data in the EMR and migrate that patient data to a data warehouse.
success story
Accelerating CSR Support of Benefits Questions Using GenAI
We leveraged AWS's AI foundation models and APIs to create a natural language generative AI benefits assistant that mines a library of ingested documents and returns tailored, reliable answers based on the member's plan and coverage.
success story
Building Clarity and Accelerating Value With GenAI Innovation
Leveraging our AI AMP framework, we led an envisioning workshop to help our client reimagine the servicing experience and identify priorities for rapid protypes and GenAI tooling.
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Seize the Strategic Edge
The future of healthcare is being rewritten now. The question isn't whether AI will transform the healthcare landscape, but who will lead that transformation. Will you be left on the sidelines, or will you join Perficient in building a world where health is proactively managed through the power of AI?
Let’s forge the future. Together.
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Perficient combines strategy, industry best practices, and technology expertise to help healthcare leaders navigate intense technological and regulatory requirements while controlling costs and improving the consumer experience.
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Meet an Expert
Priyal Patel, MHA
Priyal is an expert in business transformation and advancing health outcomes through AI and technology. With a combined 20 years of clinical, management, and consulting experience in healthcare, she excels in implementing solutions that enhance consumer experience, reduce costs, and improve operational efficiency. Priyal serves as a strategic advisor to clients and has a proven ability to solve complex problems and bridge gaps between vision and execution.
Joel Thimsen
Joel is an IT leader with a passion for solving complex problems through innovations in technology. During his nearly 20 years in IT, he has architected and led successful transformations for Fortune 500 companies, focusing on highly regulated industries. As a principal of healthcare and life sciences at Perficient, he advises clients on digital transformation, enterprise IT strategy, AI enabled solutions, and modern cloud and data platforms.
Felix Bradbury, RN, ScD, FACHE
Felix is a senior GenAI solutions architect with more than 30 years in healthcare management, data science, and AI. Dr. Bradbury develops innovative and enduring GenAI-driven solutions that enhance operational efficiency, effectiveness, and patient outcomes. As an adjunct professor of Generative AI at UT Health Science Center, Felix prepares doctoral students to lead AI initiatives in healthcare. His background as a medical economist, nurse, and data scientist enables him to integrate clinical insights with advanced analytics to create a sustainable strategic advantage for clients.
Brian Flanagan
Brian is a principal of AI at Perficient, where he serves as a trusted client advisor and is responsible for developing digital strategies that drive business results. With more than 25 years of experience, Brian has a deep understanding of the digital landscape and a proven track record of delivering innovative and engaging customer experiences. He stays ahead of the curve and consistently looks for opportunities to enhance the customer experience through next-generation technologies.
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