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Care Management

Care management coordinates support for patients with ongoing needs across care teams, outreach, follow-up, and resources.

industryPublished 2026/06/11Last verified 2026/07/17

Healthcare compliance context

This definition is for healthcare technology research only and is not medical, care management, legal, or compliance advice.

Care management is the workflow of coordinating support for patients who need ongoing follow-up, navigation, outreach, or services. AI may help prioritize lists, summarize patient context, route tasks, or generate outreach drafts.

Buyers should keep care-team ownership explicit and review source data, bias, patient consent, escalation, and documentation workflow.

Application scenario: In care setting review, this term helps teams connect a vendor claim to the clinical, administrative, compliance, or patient-facing workflow where it applies. Procurement impact: Buyers should evaluate evidence, implementation effort, integration needs, security, privacy, pricing assumptions, support, and compliance responsibilities before shortlisting or contracting for a tool that depends on this capability.

Sources and review notes

These links support definition-level research and do not establish the regulatory status, safety, or suitability of any product.

AHRQ describes care coordination as the deliberate organization of patient-care activities and information exchange among participants, including the patient, while noting that no single consensus definition covers every use. CMS's chronic care management guidance describes patient-centered care plans, goals, monitoring, medical and psychosocial needs, caregivers, outside resources, specialty coordination, and periodic review for eligible Medicare services. CMS's advanced primary care management guidance adds continuity, urgent access, transitions, preventive-service follow-up, and ongoing communication across clinical and community providers. These CMS requirements are program- and billing-specific and do not define all care management, validate an AI system, determine clinical eligibility or priority, or prove engagement, utilization, outcome, equity, or cost improvement. Organizations must define accountable clinicians and care-team roles, population and payer rules, patient goals and consent, source-data completeness and timeliness, identity and care-plan provenance, medication and transition reconciliation, communication accessibility, risk-model validation and fairness, urgent and clinical escalation, closed-loop task ownership, staff override, outcome measurement, and auditable documentation.

FAQs

What should care management AI avoid?
It should avoid opaque prioritization, biased outreach, unsupported clinical advice, and unclear ownership of patient follow-up.

Related research

Use related glossary terms and healthcare AI tool profiles to connect terminology checks with vendor due diligence.