Closing the last mile of value-based care with AI

The last mile of AI-enabled VBC: Turning insights into action

Value-based care insights create value only when practices can act on them. For independent practices participating in VBC arrangements, that means getting relevant clinical, payer, and performance information to clinicians and quality teams while there is still an opportunity to improve care and results.

This is a persistent last-mile challenge in VBC: translating population-level information into action within everyday workflows. Reports, payer portals, and standalone analytics tools may identify important opportunities, but practices are often left to connect those insights to the clinicians and teams responsible for addressing them.

AI can help close that distance. The opportunity is not simply to generate more insights, but to combine AI with clinical and payer data and make useful intelligence available where teams address care gaps, evaluate diagnoses, and monitor VBC performance.

Put VBC insights where clinicians can act on them

Identifying a potential diagnosis gap is only part of the job. A clinician still needs enough information to determine whether the diagnosis is supported by the patient’s record and, if so, document it appropriately. If finding that evidence requires searching through the chart or consulting a separate tool, a useful insight can create additional work before it leads to action.

athenahealth’s Clinically Inferred Diagnosis Gaps is designed to bring that information together in the clinician’s existing diagnosis-gap workflow. The capability uses generative AI to analyze information already in the patient’s chart and:

• Surface a potential diagnosis gap related to the Centers for Medicare & Medicaid Services Hierarchical Condition Category (CMS-HCC) risk-adjustment model.¹
• Show the clinical evidence behind the suggestion, drawing from relevant information such as lab and imaging results, vital signs, demographics, and previous notes.
• Give the clinician the context to evaluate the suggestion without treating the AI inference as a clinical decision.
• Leave the decision with the clinician, who determines whether the diagnosis is accurate and appropriate and what action, if any, to take.

AI is helping surface an opportunity and the evidence behind it, not making the diagnosis. By putting both into an existing clinical workflow, practices can make VBC insights more actionable at the point of care.

Bring payer insights into the clinical workflow

The article has a strong “insight-to-action” thesis, but it sometimes presents athenahealth’s AI-native VBC capabilities as a comprehensive population health management solution. The capabilities described are more precisely VBC workflow enablement: surfacing gaps, integrating payer intelligence, supporting quality analysis, and embedding action in clinical workflows.

The distinction matters because sophisticated risk-bearing organizations generally expect “population health management” to include functions such as attribution, longitudinal risk stratification, utilization and cost analytics, claims-based surveillance, care management, network performance, financial forecasting, and intervention tracking. This article does not establish that full scope.  

Patients receive care across different settings, giving payers information that may reveal potential diagnosis gaps beyond what a clinician encounters during an individual visit. Bringing those payer-supplied gaps into the clinical workflow can give clinicians additional information to consider while the patient is in front of them.

athenahealth’s moment of care diagnosis-gap workflow connects payer-supplied information with an upcoming patient appointment. A payer can send a potential diagnosis gap to athenahealth, where the clinician can review it during the encounter. If the clinician determines that a diagnosis is appropriate, they can document it through the existing workflow, and information about how the gap was addressed can be communicated back to the payer.

Payer information can also complement insights generated from the patient chart. When both a payer and athenahealth’s AI identify the same potential diagnosis gap, the diagnosis-gap workflow can display information from both sources, giving the clinician more context for evaluating the gap.

For practices participating in VBC, bringing outside information into an existing clinical workflow can reduce the need to reconcile insights across separate systems and make payer-supplied opportunities easier to act on at the point of care.

Find VBC opportunities across your patient population

The same need to turn information into action extends beyond an individual patient visit. Quality and population health leaders need to answer practical questions across entire patient populations: Which patients still have an open care gap? How are clinicians performing on specific quality measures? Where should the team focus its attention next? Getting those answers can require configuring reports, combining results, or exporting data for further analysis.

Sage™, athenaOne's AI assistant, is designed to make that investigation more direct. Users can ask supported questions about VBC performance in everyday language and receive written insights, tables, and charts. They can then ask follow-up questions to explore the results further.

For example, a quality leader might ask:

• “How are we doing on enrolled MIPS measures?”
• “Who are the top or lowest performing clinicians?”
• “Which patients are not satisfied for colorectal screening?”

Rather than requiring users to translate each question into a predefined report, Sage gives them another way to investigate VBC performance and zero in on the patients, clinicians, or measures that need a closer look. For independent practices, that can make population-level information more accessible to the people responsible for turning it into action.

Turn population data into a clearer view of VBC performance

Identifying patients and opportunities is an important part of managing performance under VBC. Practice leaders also need to understand what is happening across their patient populations: where performance is strong, where trends are emerging, and where additional attention may be needed.

Data Explorer brings reporting together in one place and applies AI to help users identify patient populations, explore trends across panels, and uncover opportunities to improve outcomes. As a result, quality and operational leaders gain another way to move between the broader performance picture and the populations that may warrant a closer look.

This level of visibility can support a more continuous approach to managing VBC performance. Insights can point teams toward opportunities for action, while reporting and performance data can help them understand where the practice stands and where to focus next.

For practices balancing multiple quality and VBC priorities, making performance information easier to explore can help teams focus their time and resources on the areas that need attention most.

Reduce the work between VBC insight and action    

AI insights, payer data, population analytics, and performance reporting can each help practices manage VBC. Their greater value comes from reducing the work required to move between them.

When information is spread across separate reports, payer portals, analytics tools, and clinical systems, practice teams may have to find and reconcile data before they can decide what needs attention. Bringing more of that intelligence into the environment where clinicians and quality teams already work creates a more direct path:

Find an opportunity → add relevant context → get the information to someone who can act → understand performance

For independent practices, reducing the manual work between those steps can be particularly valuable. Instead of requiring teams to connect information across multiple tools and workflows, technology can help close the distance between knowing what needs attention and being able to act on it.

That is the larger opportunity for AI-enabled VBC: not simply generating more information, but making useful clinical, payer, and performance insights easier to put to work.

Explore athenahealth’s value-based care capabilities and see how athenaOne® can help your practice put VBC insights into action.