Empowering physicians in the age of health care AI

Rajiv Mahale, Cedar Gate Technologies: ©Cedar Gate Technologies

Advanced technologies like artificial intelligence (AI) and machine learning (ML) are gaining traction in health care. They have the potential to improve patient care and simplify time-consuming administrative work. They are increasingly critical for health care providers and organizations participating in risk-based contracts and value-based care (VBC) models.

Many people think about technology's potential to help with administrative tasks like automating repetitive jobs that take up valuable time or helping with medical coding and billing. But AI and ML also have tremendous potential to improve care. These technologies can uncover patterns, predict disease risk, recommend interventions at the point of care, and supplement the judgment of physicians and care teams to enable more informed decisions within the flow of patient care. This, in turn, will lead to better outcomes for everyone.

Reducing administrative workload

Physicians spend many years in education and training to prepare them for medical care. However, once they enter the medical field, they often spend a significant part of their workday on administrative tasks. In addition to documenting patient encounters in an electronic health record, providers also:

• Manage claims and deal with insurance
• Manage preauthorizations and appeal denials
• Communicate with other physicians and referral partners
• Send reports to administrative staff and executives
• Manage daily office and HR functions

These tasks often take physicians away from patient care activities. Many providers say they contribute to the problem of burnout and staffing shortages that affect almost 50% of U.S. doctors. However, many technologies available today have the potential to alleviate some of this burden.

AI tools and technologies can help streamline these tasks. Software can automate processes like referrals and authorizations, ensuring accuracy and minimizing delays from data entry errors. Automated tools can pull information from EHRs, claims history, and analytics data, compile it into reports, and share it with stakeholders.

AI tools can also help identify data anomalies in reports that may be difficult to spot using standard rules-based approaches. Employing these tools can improve data quality and the integrity of insights gleaned from analytics software. Organizations can also use the tools to automate report delivery so the information gets to the right stakeholders at the right time. It leaves providers free to invest more in patient care.

Physicians (and staff) don't have to worry about compliance issues or missed reporting deadlines. With these time-consuming tasks done, they have more time for patient care, better work-life balance, and less stress from overwhelming workloads.

Support for informed clinical decision-making and personalized medicine
AI that connects a diverse set of data points – such as EHR data, claims data, social determinants of health, and others – can improve clinical decision support tools. It provides a more comprehensive view of past behaviors, clinical history, and patient needs to enhance insights for providers.

The information from AI tools boosts care teams' productivity and supplements physicians' judgment. It can identify specific opportunities to improve cost and quality, removing the "noise" from things like false positives in many datasets. After revealing insights they may not have uncovered otherwise, AI can give providers actionable next steps to consider that are backed by data. All this information is immediately available in the exam room while the patient sits with the doctor.

AI-driven foundational models can be trained using the language of claims and clinical data. They can also factor in time to better understand when to deliver outreach for optimal outcomes. The ability to identify the areas of opportunity and the appropriate time for intervention is at the heart of efficiently executing patient-centric care plans. Models analyze multiple data points to create individualized treatment plans, including:

1. Medical history
2. Genetics
3. Social determinants of health
4. Lifestyle or behavioral factors

Physicians participating in value-based care models certainly benefit from this approach. VBC programs incentivize quality over volume and benefit from individualized treatment plans.

Disease prediction for earlier intervention
AI-driven software also offers predictive analytics to help physicians, advanced practice clinicians, and care team members make more informed decisions. One promising way these models, powered by AI and ML, can improve U.S. health care is by helping physicians identify who might be at risk of developing chronic conditions. Conditions like diabetes, coronary artery disease, and COPD are some of the most prevalent and costly conditions to treat.

Software can integrate data from AI predictive models with care management software to make the insights actionable. Care teams use the information to design effective intervention strategies for higher-risk individuals. Physicians can also use insights to prioritize their time and resources. Knowing which patients need more focused attention improves patient outcomes and proactively addresses patient needs.

Efficient coding, billing & compliance support
Accurate medical coding and billing are crucial for physicians to get paid on time and avoid compliance issues. Accuracy and efficiency are even more critical in a VBC world where alternative payment models (APMs) like prospective bundles and capitation will become the norm.

Administering APMs is complex and time-consuming, but AI-driven analytics can help with coding and billing. Algorithms can identify opportunities to provide accurate coding to reflect the risk of members and ensure accurate payments. Reducing the chance of human error improves revenue cycle management efficiency.

Finally, AI helps physicians navigate a complicated regulatory environment. Algorithms review patient documentation for compliance issues, flagging potential fraud or missing data so organizations can proactively respond. It reduces the risk of legal problems and simplifies the administrative work necessary to ensure regulatory compliance.

The future of physician-AI collaboration
AI and ML are not just dreams for the future – they are making an impact today. Their potential to continue revolutionizing healthcare is exciting. As they advance, they bring better tools to identify near-real-time interventions and customized treatments based on a patient's socioeconomic, environmental, and lifestyle factors.

But new technologies and advances also come with risks. AI models can produce poor results and inaccurate information. In health care, where the stakes are very high, it's critical that physicians and care teams apply the technologies carefully and only in appropriate situations and use cases.

When used correctly, AI can boost productivity, help refocus providers on patient care, and empower better outcomes. Physicians and care teams embracing these new technologies will be better prepared to provide high-quality care in an increasingly complex, data-driven healthcare future.

Rajiv Mahale, is chief product & business development officer at Cedar Gate Technologies.