An Introduction to Best Next Action (BNA), the Engine Powering Proactive Primary Care
Primary care is a domain of immense breadth and inherent uncertainty, where the scope is not a single organ system but the entire human condition. A single patient’s health record contains a staggering volume of data, from demographics and family history to every clinical note and lab result. The fundamental challenge is that primary care teams cannot continuously assess and act on the needs of large patient populations without additional capacity. For clinicians managing a wide spectrum of health needs, from acute and chronic illnesses to preventive care, evaluating this data for one patient is a challenge; for an entire panel, it’s humanly impossible. Time burden and complexity are the primary obstacles to effective, scalable care, and critical connections can be obscured by the sheer scale of the information.
While standard AI can synthesize this data into a clear view, the true evolution required for the messy, unpredictable reality of whole-person care is agentic AI. This is the designated role of Best Next Action (BNA), the core intelligence engine within the Tom AI-powered platform.
Moving beyond simple analysis, BNA was engineered to translate healthcare data into decisioned, prioritized, and actionable care interventions. It uses a multi-layered logic grounded in clinical expertise to not only make evaluating all available patient data a reality but to recommend the best next course of action. By applying this agentic approach, BNA addresses the core challenges of primary care and the business drivers of modern health systems, paving the way for proactive and truly personalized care.
The Logic of Decisive Intelligence
Best Next Action functions as a system of continuous, multi-layered reasoning. It systematically translates raw data into proactive intervention through a sophisticated, automated process that brings scale and consistency to clinical best practices.
1. Comprehensive Data Curation:
The process begins with the creation of a living, multi-dimensional patient portrait. The system routinely curates a vast array of data types beyond the capacity of a human to review in a single session. This includes data from the EHR (diagnoses, medications, lab values, etc.), claims data revealing encounters with outside specialists, administrative data (scheduling, insurance, etc.), and contextual data relevant to care coordination and follow-up.This holistic ingestion ensures that subsequent analysis is based on the most complete and up-to-date patient story available.
2. Automated Opportunity Identification:
With this rich, curated dataset, the system methodically identifies risks, care gaps, and opportunities for intervention. This is not a static checklist, but a dynamic process of pattern recognition that identifies overdue preventive screenings and labs, flags patients with chronic conditions who have missed key follow-ups, and detects subtle but significant changes in clinical data such as a gradual increase in blood pressure readings or lab values trending out of a desired range. It pinpoints administrative issues, like a follow-up visit that was never scheduled, that often represent critical breaks in the chain of care.
3. Service Prioritization:
Like a clinician, Best Next Action (BNA) assesses multiple patient needs, identifies the ones that matter most from a clinical perspective, and prioritizes them into a coherent plan based on clinical urgency, potential impact on outcomes, evidence-based guidelines, and patient context. A single patient might have several concurrent needs such as an overdue screening, poorly controlled blood pressure, and a routine appointment to confirm. Beyond simply flagging these issues, BNA initiates action such as pre-visit preparation, a check-in for a patient with diabetes, or assistance in scheduling a needed test. Creating a prioritized list and taking action improves patient outcomes and reduces the care team’s burden, all while aligning with what matters most to both the patient and the provider.
A Proactive Operating Model
BNA’s proactive operating model is driven by two complementary functions.
First, it performs systematic panel review. Even when no new information has arrived, it periodically asks the critical questions for every patient: What has changed? What is overdue? What opportunity exists to improve this patient’s health? This provides a level of proactive oversight that scales quickly and without overburdening the clinical team.
Second, it is event driven. When new clinical information becomes available, such as a lab result or a specialist’s note, that data acts as a trigger for an immediate review. The engine evaluates the new information in the context of the patient’s existing record to determine if care priorities need to be adjusted. This response to new data allows the care model to adapt quickly to the changing nature of a patient’s health journey.
Driving Financial and Operational Health
In today’s challenging healthcare environment, clinical innovation must quickly prove its financial and operational viability. Best Next Action is engineered to be a primary driver of health system sustainability, creating tangible value across both value-based and fee-for-service reimbursement models.
In value-based care where success is predicated on improving outcomes while controlling costs through a focus on early detection, prevention, and wellness, BNA is a powerful tool for systematically and proactively finding care opportunities and closing gaps in care. Gaps such as missed screenings, poor medication adherence, and lack of chronic disease follow-up are major drivers of poor outcomes and/or high downstream costs. Historically, closing them has required significant investment in manual outreach programs. As BNA improves the care for the individual patient, it also directly impacts quality scores and reduces the likelihood of costly acute events, bolstering performance in risk-based contracts. By proactively identifying necessary screenings for conditions like breast, cervical, or colorectal cancer, BNA not only closes critical care gaps but can also increase downstream service utilization for the institution.
In the fee-for-service domain, optimizing resource utilization is paramount. BNA contributes directly by reducing administrative waste, increasing staff capacity, and improving patient access. By unburdening clinicians from routine tasks, it frees capacity, allowing providers to potentially expand their patient panel without increasing their personal workload.
For instance, intelligent reminders significantly reduce patient no-show rates, preventing lost revenue and optimizing clinician schedules. BNA also automates chronic condition monitoring between appointments. For example, Tom can track patients with diabetes, collect data such as self-reported blood glucose readings, and alert the care team to significant deviations. By collecting self-reported readings and other relevant information remotely, routine follow-ups may not require an in-person visit, freeing up valuable appointment slots for patients who truly need to see their PCP.
A New Care Delivery Workflow
The cornerstone of the BNA vision is to enhance primary care team capacity by working alongside clinicians as a support system, not a substitute. The system is designed to reduce the burden of routine data and administrative tasks, freeing physicians, nurses, and care managers to focus their limited time on complex medical decision-making and the empathetic human interactions where they are most needed. BNA functions as a transparent partner, sharing its reasoning as it works to close care gaps and support patients between visits.
By systematically identifying needs, prioritizing actions, and automating interventions, Best Next Action helps health systems translate their data into a functional operational asset. This supports a fundamental shift in the care delivery model from being reactive to proactive. The result is a more scalable and consistent approach to care management that enables organizations to address their operational needs while improving the quality of patient care.
What this Means for the Patient
For the individual patient, this proactive approach translates into a more continuous and personal healthcare experience.
It means having an extra layer of security, knowing that a system is working in the background to ensure critical data isn’t inadvertently overlooked, or a necessary screening isn’t forgotten. It changes the dynamic of their care from a series of disconnected appointments to a continuous, supportive relationship with their provider.
