EHR-level data analysis of target medical practices — provider concentration risk, payer mix trajectory, and revenue integrity from actual encounter data. Delivered in 5 to 10 business days.
Harine Management provides private equity firms and healthcare investors with EHR-level data analysis of target medical practices — extracting encounter-level volume, revenue trends, provider concentration risk, payer mix trajectory, and AR aging directly from the practice's EHR rather than from management-provided summaries. The output is structured for data rooms and investment committee presentations and delivered in 5 to 10 business days.
PE firms evaluating medical practices depend primarily on management-provided financials — income statements, AR aging summaries, and stated collection rates that represent what leadership chose to share, not necessarily what the EHR data actually shows. Provider concentration risk — what percentage of revenue walks out the door if one physician retires or leaves — is almost never disclosed in a management presentation in a form that is accurate and auditable.
Payer mix trajectory — whether the commercial-to-Medicaid ratio has been shifting over the past 24 months, and in which direction — is visible in raw EHR billing data but invisible in a P&L summary. Stated collection rates are often calculated differently than acquirers would calculate them from the same underlying data. And the denial rate your target reports is typically the denial rate their billing company reports about themselves.
The gap between what a practice reports and what its EHR encounter data actually shows is where deal risk lives. Standard financial due diligence does not reach it.
This is the information gap that EHR-level analysis closes. Every row below represents a real risk category that standard healthcare financial due diligence does not surface from first principles.
| What traditional due diligence sees | What EHR-level analytics surfaces |
|---|---|
| Management-prepared revenue summary | CPT-level revenue by provider, payer, and visit type — from raw encounter records |
| Stated collection rate | Actual collection rate calculated from billing records, with denial rate by payer and CPT code |
| Provider headcount and credentials | Individual wRVU production by provider — 24-month trend, not a point-in-time snapshot |
| Payer mix at time of LOI | Payer mix trajectory over 24 months — direction, rate of shift, and margin implication |
| AR aging summary (self-reported) | AR aging by provider, payer, and 30/60/90/120+ day bucket — derived directly from the EHR |
| Total annual visit count | Volume by location, provider, visit type, and day of week — with trend and seasonality |
| Revenue per provider (blended) | Net revenue per visit by CPT code — adjusted for contractual allowances and write-offs |
| Provider attrition (as disclosed) | Provider concentration risk — revenue-at-risk if the top 1, 2, or 3 physicians leave |
| Billing company performance summary | Independent EHR-derived denial rate versus the billing company's own reported performance |
Most medical practice acquisitions close without functioning analytics infrastructure. The practice has been running on tribal knowledge and a relationship with its billing company. Post-close, the PE firm needs operational visibility the practice has never had to provide before.
Harine Management offers a dedicated post-acquisition service that builds the EHR data pipeline, establishes baseline KPIs, standardizes reporting to portfolio cadence, and stands up early-warning dashboards — targeting operational within 30 days of close. The measurement layer is in place before the first board meeting, giving the value creation plan a baseline to measure against from day one of ownership.
For firms with multiple healthcare portfolio companies, all holdings can be standardized to the same metric definitions and reporting format — enabling the operations team to review all practices in a single consolidated dashboard.
Most engagements begin with a 20-minute conversation about the target and the timeline. We will tell you exactly what can be extracted and what the analysis will show before any engagement is confirmed.
Start the Conversation