Behavioral Health Medicare Patient Profile and Impact Analysis Case Study

Client question

A behavioral health client wanted to understand the Medicare patients receiving its services and use claims data to support care strategy, billing review, partnership discussions, and value-based care positioning.

The client also wanted to identify upstream providers who appeared to send patients into therapy and evaluate whether patient utilization changed after engagement with the behavioral health organization.

Data foundation

FastHSR started with client-provided provider identifiers and used recent Medicare claims to identify the attributed patient population. The analytic file linked patient demographics, diagnoses, service use, Medicare payments, therapy claims, provider activity, and upstream evaluation and management encounters.

• Patient identification: identify Medicare beneficiaries with claims connected to the client-provided providers.
• Claims sources: use Medicare claims across care settings to describe utilization and cost patterns.
• Provider layer: connect claims to rendering providers, therapy clinicians, and upstream evaluation and management providers.
• Measurement windows: construct baseline and follow-up windows around patient engagement.

Patient profile analysis

FastHSR built a patient profile to help the client understand who its Medicare patients were and how they used the broader healthcare system outside therapy encounters.

• Demographics including age, sex, race and ethnicity, and dual eligibility.
• Geographic distribution by patient county and market.
• Diagnosis and comorbidity summaries.
• Hospitalizations, emergency department visits, readmissions, and cost of care.
• Patient segmentation for clinical strategy and market planning.

Practice pattern analysis

FastHSR analyzed how behavioral health care was delivered across clinicians and patients. The goal was to identify patterns that could inform care model design, staffing, billing review, and operational consistency.

• Therapy cadence: number of sessions and spacing between sessions.
• Provider activity: differences across clinicians and patient groups.
• Billing patterns: CPT and HCPCS code use across therapy encounters.
• Patient mix: practice patterns stratified by demographic and clinical characteristics.

Referral pathway detection

The analysis also looked upstream. FastHSR identified potential referral relationships by examining evaluation and management visits that occurred before therapy sessions and by measuring shared patients between providers and therapy clinicians.

• Identify providers with repeated shared patients with therapy clinicians.
• Flag temporal sequences where an evaluation and management visit preceded a therapy session.
• Summarize potential referral sources by provider, specialty, organization, and geography.
• Distinguish high-volume shared-patient relationships from incidental overlap.

Pre/post effectiveness evaluation

FastHSR designed a pre/post framework to compare healthcare utilization and costs before and after patient engagement. The analysis was intended to support early value-based care conversations and payer partnership discussions, while clearly separating descriptive results from causal claims.

• Define each patient's first observed engagement date.
• Construct pre-engagement and post-engagement measurement windows.
• Compare total cost of care before and after engagement.
• Compare hospitalizations, emergency department visits, and readmissions.
• Stratify results by patient segment, therapy cadence, and provider pattern where sample size allowed.

Findings

The analysis gave the client a clearer view of its Medicare patient population, including patient mix, geographic reach, clinical complexity, and broader healthcare utilization. Practice-pattern outputs showed where therapy cadence, billing mix, and provider activity varied across patients and clinicians.

The referral-pathway work created a practical list of upstream provider relationships for partnership development. The pre/post framework gave the client a starting point for value-based care evidence, with appropriate caution that stronger causal evaluation would require additional design and validation.

Deliverables

• Medicare behavioral health patient profile.
• Demographic, geographic, diagnosis, utilization, and cost summaries.
• Therapy cadence and practice-pattern analysis.
• CPT and HCPCS billing pattern summaries.
• Potential referral pathway file based on shared patients and temporal sequencing.
• Pre/post cost and utilization analysis around patient engagement.
• Interpretive notes for value-based care positioning and payer discussions.

Use cases

• Behavioral health value-based care strategy.
• Medicare patient population profiling.
• Therapy care model and cadence review.
• Billing pattern and coding mix analysis.
• Referral source identification and partnership development.
• Payer-facing evidence development.

Frequently asked questions

How can Medicare claims help a behavioral health organization?

Medicare claims can show patient demographics, clinical complexity, healthcare utilization, therapy service patterns, provider relationships, and costs outside the organization's own internal data.

How can referral sources be identified without a direct referral field?

Claims can identify providers who share patients with therapy clinicians and evaluate whether upstream evaluation and management visits occurred shortly before therapy engagement. This creates a practical referral signal.

Can this support value-based care discussions?

Yes. Patient profiles and pre/post utilization summaries can support early value-based care positioning, while more rigorous causal evaluation can be added as the evidence strategy matures.

For behavioral health claims analytics, Medicare patient profiling, referral pathway analysis, or pre/post impact evaluation, please email us.

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