Beyond Limits AI solutions go beyond conventional AI to unlock human potential and transform business. We bring a highly sophisticated approach to solving healthcare problems, combining conventional numerical AI techniques with advanced symbolic reasoning to provide human-like insights. We reduce risk, provide explainable solutions, and bring insights powered by human expertise and advanced AI.
For healthcare professionals, the problem isn’t too little information. It’s not too much information, either. The problem is getting the right information to make a better decision at the right time. The answer to providing more consistent care is to drive better insights from clinical data, scale expert knowledge, and distribute the expertise to the point of care. To assist physicians with today’s difficult clinical decisions, we build clinical knowledge and experience into scalable expert decision-support systems. For patients with chronic or multiple conditions, the AI system can monitor the treatment regimen to reduce adverse medical errors that might occur due to complex polypharmacy or co-morbidities.
AI systems powered by Beyond Limits human-like reasoning provide clinical care options in a clear, evidence-based audit trail that can be queried for answers. Clinicians can’t settle for “black box” solutions from conventional machine learning and deep learning approaches. There is too much at stake for their patients. Unlike “black box” approaches, Beyond Limits cognitive AI delivers clear explanations of its cognitive reasoning in transparent, evidence-based audit trails, including risks and uncertainties. We empower clinicians with the information needed to make the best care decisions for their patients.
The trend to more intensive patient monitoring is not going to stop. Unfortunately, most monitoring systems tend to be narrowly focused and rigid, and frequently produce alarm alerts without reference to overall patient health and treatment plans. False positives can lead to alarm fatigue, and in some cases, overlooked patient deterioration can lead to death.
The Cognitive AI Solution
Beyond Limits builds cognitive AI systems that interpret vast amounts of data from disparate sources to produce actionable information for patient care teams. Real-time monitoring, historical patient data, lab results, chart notes, evidence-based clinical guidelines, drug interactions, etc., are all combined by the system to better understand and personalize treatment suggestions.
In addition to diagnostic applications, Beyond Limits systems can prognosticate to proactively alert medical staff about patients who are deteriorating. The system explains its reasoning in clear, evidence-based audit trails and displays confidence values that express the probability of an alerted condition.
Only 5% of the US health system population accounts for more than 50% of costs, largely in hospitalization. Current systems for managing population health depend on manual processes – a sure prescription for inefficiency and excessive cost. A Beyond Limits AI system can assess longitudinal population health data or prospective risk factors so effective treatment options can be identified and promoted by PHM decision-makers. A cognitive system can also identify which patients are most likely to respond to care interventions. Symbolic AI from Beyond Limits can help PHM teams move from a ‘one size fits all’ for a given population to a more precise “one size fits one” approach. By optimizing care for individual patients and understanding risks, patterns, and trends for populations, outcomes can be improved while effectively managing costs.
Routine healthcare administration is hampered by outdated, manual, inefficient processes that lead to poor financial outcomes for providers. Beyond Limits cognitive AI can help organizations connect the dots while shifting from fee-for-service reimbursement to value based care.
Healthcare AI technology can reduce the friction, errors and cost in registration, scheduling, charge capture, health information management, and billing and collections. The goal is to reduce the number of denied insurance claims, speed explanation of benefits (EOB) reconciliation, improve the quality of information, streamline denial management, and automate processes.
To Avoid Repeat Denials, Break Through Silos
Redoing work erodes efficiency in any system, and in healthcare, claims denial is a big contributor to inefficiency. An AI system can manage denials by profiling claims by groups and associations according to their denial risk with traceability showing underlying variables that trigger denials. One obstacle to integration of RCM is that data from front-end and back-end systems reside in silos, with little to no ability for cross-analysis. Silos prevent comprehensive, systematic and data-driven methods to identify the specific reasons behind a pattern of claims denials. Our AI systems can employ human-like reasoning to eliminate this disconnect and can assess the denial risk of potential claims to intervene before a claim is submitted. Our systems can prevent problems, not solve them after the fact.