Entity

Care Plan

The documented treatment plan for a patient including goals, interventions, responsible providers, and target outcomes for acute or chronic conditions.

Last updated: February 2026Data current as of: February 2026

Why This Object Matters for AI

AI care coordination and chronic disease management require explicit care plans to track adherence and recommend interventions; without them, AI cannot align to treatment goals.

Clinical Operations & Patient Care Capacity Profile

Typical CMC levels for clinical operations & patient care in Healthcare organizations.

Formality
L3
Capture
L3
Structure
L3
Accessibility
L2
Maintenance
L3
Integration
L2

CMC Dimension Scenarios

What each CMC level looks like specifically for Care Plan. Baseline level is highlighted.

L0

Care plans do not exist in any documented form. The attending physician has a mental model of the treatment approach, but nothing is written down. When a covering physician takes over, they start from scratch — 'what are we doing for this patient?' is answered by reviewing orders and guessing at the intent behind them.

None — AI cannot coordinate care or track treatment adherence because no care plan exists in any system to reference.

Document care plans in any form — even a brief written note in the chart stating treatment goals, planned interventions, and responsible providers for each active problem.

L1

Care plans exist as free-text notes in the chart — the physician writes 'Plan: continue antibiotics, PT consult, discharge when tolerating PO.' The format and detail vary by provider. Some care plans are a single sentence, others are a paragraph. There is no standard structure, and finding the current care plan means reading through recent progress notes looking for the plan section.

AI could extract care plan fragments from progress note plan sections using NLP, but inconsistent formats and varying levels of detail make reliable care plan reconstruction difficult. Goal tracking is impossible because goals are not explicitly documented.

Implement structured care plan documentation in the EHR — define templates with required fields for goals, interventions, responsible providers, and target dates that are maintained separately from progress notes.

L2

Care plans are documented in structured EHR templates with defined sections for problems, goals, interventions, responsible providers, and target timelines. Every admitted patient has a care plan created at admission and updated at defined intervals. The care plan is a distinct document in the chart, not buried in progress notes. But the content within each section is still free-text narrative.

AI can locate and read care plans reliably from structured templates. Basic task tracking (has PT been consulted? has the dietician seen the patient?) is possible. Cannot track quantitative goal progress because goals are described in narrative rather than measurable terms.

Add structured, measurable elements to care plans — define goals with quantitative targets (ambulate 200 feet by day 3), link interventions to specific order sets, and code problems using standard clinical terminologies.

L3Current Baseline

Care plans contain structured, measurable elements. Goals have quantitative targets and deadlines. Interventions link to specific orders and consults in the EHR. Problems are coded with ICD-10. A care coordinator can query 'show me all patients whose mobility goal is behind target' and get an actionable list because care plan elements are structured and queryable.

AI can track care plan adherence quantitatively — monitoring whether interventions are completed on schedule, whether goals are being met, and which patients are falling behind their care plan timeline. Automated discharge readiness scoring is possible.

Implement formal care plan schemas with entity relationships — link each goal to the clinical evidence supporting it, connect interventions to outcome measures, and encode care team assignments with escalation pathways.

L4

Care plans are schema-driven with formal entity relationships. Each goal links to supporting clinical evidence and outcome measures. Interventions connect to clinical guidelines and best practice protocols. Care team assignments include defined roles, escalation pathways, and handoff triggers. An AI agent can evaluate whether a care plan follows evidence-based guidelines and identify deviations.

AI can evaluate care plan quality against clinical guidelines, recommend evidence-based interventions, and autonomously generate care plan components for well-defined clinical pathways. Care coordination task assignment can be automated based on care plan logic.

Implement real-time dynamic care plans that auto-update based on clinical events — when a lab result changes, the care plan adjusts goals and interventions automatically, evolving with the patient's clinical trajectory.

L5

Care plans are living documents that evolve in real-time with the patient's clinical trajectory. When a lab result indicates improvement, goals auto-advance. When a complication occurs, new interventions are proposed and care team assignments shift. The care plan is not a static document reviewed periodically — it is a continuously adapting clinical roadmap that reflects the patient's current state and projected trajectory.

Can autonomously maintain and evolve care plans in real-time, adjusting goals, proposing interventions, and coordinating care team activities based on continuous clinical context analysis.

Ceiling of the CMC framework for this dimension.

Capabilities That Depend on Care Plan

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Remote Monitoring Data Stream

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