Cost Modeling: How New Power Policies Could Affect Total Cost of Ownership for Hosted EHRs

Why healthcare IT leaders must stress-test TCO now

Short version: 2026 policy proposals and state actions to levy data centers for grid upgrades are material cost-risk for hosted EHRs. If passed through by cloud and colocation providers, these levies can increase hosting fees, add unpredictable energy surcharges, and change long-term budgeting assumptions for migration and managed services.

For CTOs, IT directors and finance leads responsible for Allscripts and other hosted EHRs, that means you must: (1) quantify exposure with scenario-driven cost models, (2) insert contractual protections and operational mitigations, and (3) re-evaluate ROI and migration plans under new energy-cost regimes. This article gives practical, numeric TCO scenarios and an action plan you can use during vendor negotiations and budgeting cycles.

Policy context — what changed in 2025–2026

Late 2025 and into early 2026 brought accelerating legislative activity around data-center energy costs. Federal and state lawmakers, motivated by rapid AI-driven demand growth and grid strain, proposed or enacted measures that shift some portion of grid-upgrade and capacity costs onto large energy consumers — including data centers. In January 2026, a federal directive requiring data centers to shoulder a larger share of power-plant and transmission upgrade costs made the risk concrete for cloud and colocation operators.

What this means in practice:

• New per-kWh levies or capacity charges (e.g., $/kWh or $/kW-year) can be layered on top of existing utility rates.
• State-level proposals may target high-growth regions (PJM, NYISO, CAISO, ERCOT) with capacity contributions or connection fees.
• Providers will decide how to recover costs — absorb, amortize, or pass through to customers as energy surcharges or line-item charges.

How levies map into hosted EHR TCO

TCO for hosted EHRs is built from obvious and hidden components. Energy levies hit several of these directly:

• Direct hosting fees — base compute, storage, and network costs that include the provider’s energy line items.
• Pass-through charges — variable energy surcharges, capacity or grid-upgrade levies billed separately.
• Indirect costs — changes in DR strategy, extra redundancy, migration timing, and capital reserved for on-prem alternatives.
• Compliance and service upgrades — investments in backup power, renewables, or PPA contracts to stabilize pricing and meet HIPAA/SOC2 requirements.

Modeling framework — components and assumptions

Before presenting scenarios, use this standard set of inputs to make your own models or adapt the worked example below:

• IT load (kW): the average IT power draw for your EHR footprint (servers, storage, network).
• PUE (Power Usage Effectiveness): industry mid-range is 1.2–1.6; modern hyperscale often 1.1–1.3.
• Utility rate ($/kWh): baseline regional rate including energy and delivery.
• Levies: expressed as $/kWh surcharge and/or $/kW-year capacity charge.
• Allocation factor: how many customer tenants share the infrastructure (for multi-tenant hosts).
• Contract terms: fixed vs pass-through; notice periods; surcharge caps.

Key formulae (simple)

1. Total annual IT energy (kWh) = IT load (kW) × 24 × 365
2. Total facility energy (kWh) = Total annual IT energy × PUE
3. Baseline energy cost = Total facility energy × utility rate
4. Levy cost = Total facility energy × levy ($/kWh) + capacity charge ($/kW-year) × IT load
5. Per-customer annual impact = Levy cost ÷ number of customers (or allocation share)

Three TCO scenarios: baseline, moderate levy, high levy

We model a representative hosted EHR footprint to demonstrate possible impacts. This is a realistic but simplified example you can copy into a spreadsheet.

Shared assumptions

• IT load: 100 kW (continuous) — equivalent to a midsize production cluster supporting ~10–20 ambulatory clinics or a small hospital instance.
• PUE: 1.25 (efficient modern facility)
• Utility rate: $0.10/kWh baseline
• Allocation: 10 hosted EHR customers share the footprint equally

Calculations (shared)

• Total annual IT energy = 100 kW × 24 × 365 = 876,000 kWh
• Total facility energy = 876,000 × 1.25 = 1,095,000 kWh
• Baseline annual energy cost = 1,095,000 × $0.10 = $109,500

Scenario A — Baseline (no levy)

• Levy cost = $0
• Per-customer annual energy cost = $109,500 ÷ 10 = $10,950 (or $912/month)
• Note: energy is typically a fraction of total hosting fees; in many contracts providers bundle this within compute/storage pricing.

Scenario B — Moderate levy (policy enacted with modest surcharge)

Assume an energy surcharge of $0.01/kWh and a small capacity charge of $10/kW-year.

• Levy ($/kWh) cost = 1,095,000 × $0.01 = $10,950
• Capacity cost = $10/kW-year × 100 kW = $1,000
• Total levy cost = $11,950
• Per-customer annual impact = $11,950 ÷ 10 = $1,195 (or $100/month)
• Percentage increase vs baseline energy cost = $11,950 ÷ $109,500 ≈ 10.9%

Scenario C — High levy (aggressive policy and capacity pricing)

Assume $0.05/kWh surcharge and $50/kW-year capacity charge.

• Levy ($/kWh) cost = 1,095,000 × $0.05 = $54,750
• Capacity cost = $50/kW-year × 100 kW = $5,000
• Total levy cost = $59,750
• Per-customer annual impact = $59,750 ÷ 10 = $5,975 (or $498/month)
• Percentage increase vs baseline energy cost = $59,750 ÷ $109,500 ≈ 54.6%

Interpreting the scenarios for hosted EHR budgeting and ROI

The numeric examples show energy levies can be non-trivial relative to the energy portion of hosting fees. While energy is often 5–15% of a provider’s total cost-of-service, in high-levy regimes that percentage can increase and force providers to decide between absorbing margin or passing costs to customers.

For healthcare buyers evaluating migrations, the critical impacts are:

• Short-term budget shock: Monthly hosting invoices could show a new line-item “energy surcharge” that wasn’t in prior forecasts.
• Long-term TCO drift: Multi-year ROI on migration may be reduced if levies persist and escalate.
• Contract exposure: Contracts with annual auto-pass-through clauses can compound unpredictability.

Practical mitigations — negotiation, architecture and ops

Healthcare organizations can reduce risk and control long-term TCO via contractual, architectural and operational measures. Below are concrete levers to use during procurement and in production.

Contractual levers

• Cap pass-throughs: Negotiate a cap on energy surcharges (e.g., max $/kWh or % of base hosting fee per year).
• Fixed-term energy pricing: Seek multi-year fixed energy rates or shared-hedging agreements where the provider bears volatility.
• Notice and audit rights: Require 90–180 days’ notice of new levies and the right to audit energy bills and allocations.
• Service credits: Align penalty/credit structures to SLA degradation caused by provider cost-cutting tradeoffs.

Architectural & operational levers

• Right-size and thin-provision: Use autoscaling, containerization and instance types optimized for CPU-to-power efficiency to reduce average kW.
• Geographic diversification: Place non-latency-sensitive workloads in lower-cost grids/regions to reduce energy exposure (ensure data residency and HIPAA compliance first).
• Time-of-use scheduling: Shift batch jobs and non-critical workloads to lower-cost hours when grid demand — and levies tied to peak periods — is lower.
• Demand-response and DR strategy: Participate in demand-response programs (via provider) to earn credits; re-assess DR tiers (cold vs warm) balancing risk and cost.
• On-site or contracted renewables: Require or prioritize providers with PPAs or on-site renewables that hedge energy prices and potentially reduce levy exposure; consider backup and resilience options reviewed in backup power guides.

Financial hedges and planning

• Scenario-based budget planning: Build three-year budgets with Best/Expected/Worst-case levy assumptions. Use the scenario outputs above to stress-test ROI.
• CapEx vs OpEx trade-off: In some cases, a hybrid approach (partial on-prem for peak loads) may reduce overall levy exposure. Recalculate NPV with levy scenarios.
• Dedicated negotiation points: Make levy treatment a procurement scoring criterion (weight it explicitly when comparing bids).

Vendor selection criteria — what to ask potential hosts

When evaluating vendors for Allscripts EHR hosting:

• Ask for detailed energy-cost allocation methodology and historical energy-led pass-throughs.
• Request scenarios in vendor proposals that show the cost delta for +$0.01, +$0.02, +$0.05 per kWh and per-kW capacity charges.
• Confirm involvement in PPAs, renewable procurement and demand-response programs.
• Require transparency on PUE and efficiency metrics for the facility hosting your EHR.

Anonymized case study — reassuring outcomes from proactive mitigation

Background: A regional health system moved its Allscripts production cluster to a multi-tenant colocation in 2024. By early 2026 a state levy was proposed in their market. The colocation announced a planned energy surcharge tied to the levy.

Actions taken: The health system invoked contract language requiring 120 days’ notice and audit rights. It worked with its provider to:

• Shift non-clinical analytics to a secondary region with lower levy exposure.
• Negotiate a three-year capped energy surcharge (max $0.02/kWh equivalent) in exchange for a modest increase in committed usage.
• Collaborate on a demand-response pilot to reduce peak kW and share credits.

Result: The effective per-customer energy surcharge was limited to ~6% of previous energy spend, avoiding worse-case outcomes and preserving the migration ROI. The provider retained margin through committed-use revenue and the customer preserved predictable budgeting.

Modeling checklist — build your own TCO worksheet

Copy these columns into a spreadsheet and run the three levy scenarios above across your actual load and allocation figures:

1. IT load (kW)
2. PUE
3. Baseline utility ($/kWh)
4. Levy ($/kWh)
5. Capacity charge ($/kW-year)
6. Total facility energy (kWh)
7. Baseline energy cost
8. Levy cost
9. Per-customer allocated levy
10. Effect on multi-year NPV and payback

Future predictions — what to expect in 2026 and beyond

Expect a patchwork of regional policies in 2026 as states implement varied approaches. Near-term realities:

• Providers in high-growth AI hubs (PJM, parts of the Northeast and California) will feel the biggest pressure to pass costs through.
• We will see more line-item energy surcharges on invoices instead of bundled increases — because transparency reduces buyer pushback.
• Providers with strong renewable portfolios and long-term PPAs will have a competitive advantage and will market that to healthcare buyers worried about TCO stability.
• AI and high-performance workloads will be priced separately; healthcare workloads could benefit from distinct, efficiency-optimized offers.

Action now reduces uncertainty later. Scenario-planning and contractual clarity are the simplest ways to protect EHR budgets in a world where energy policy is shifting fast.

Quick-action checklist for IT and finance teams

• Run the three levy scenarios against your actual kW and allocation within 30 days.
• Require vendors to provide energy-allocation detail as part of RFP responses.
• Negotiate caps on pass-throughs and demand minimum notice periods.
• Prioritize providers with PPA coverage or regional energy hedges.
• Evaluate shifting non-critical workloads to alternate regions or schedules.

Conclusion and next steps

The introduction of data-center levies in 2026 has the potential to meaningfully change hosted EHR TCO. For healthcare organizations, the window to act is now: build scenario-driven models, lock in contractual protections, and use architectural levers to reduce kW to the greatest practical extent.

Need a starting point? We offer a customizable TCO worksheet and a vendor-question checklist built for Allscripts migrations that maps levy scenarios to multi-year ROI. Use the checklist during RFPs and renewals to ensure energy-policy risk is quantified and mitigated.

Call to action: Contact Allscripts.cloud for a complimentary TCO scenario review that models moderate- and high-levy regimes against your current or planned EHR footprint. We’ll deliver a one-page executive summary you can take to finance and the board.

Related Reading

• Energy Orchestration at the Edge: Practical Smart Home Strategies for 2026
• Developer Productivity and Cost Signals in 2026: Polyglot Repos, Caching and Multisite Governance
• Building Resilient Architectures: Design Patterns to Survive Multi-Provider Failures
• Observability in 2026: Subscription Health, ETL, and Real-Time SLOs for Cloud Teams
• How to Source Affordable, Licensable Music After Streaming Price Increases
• Vehicle Maintenance Tracking: Applying Aviation-Style Recordkeeping to Ground Fleets
• When Customization Feels Like Placebo: A Guide to Choosing Personalized Gifts That Actually Matter
• Gym-to-Glow: Quick Post-Workout Cleansers for People Who Lift, Cycle or Run
• The Evolution of High-Protein Meal Replacements in 2026: Formulation, AI Nutrition, and Clinical Outcomes