Clinical Variation in Healthcare

Clinical variation costs healthcare $265B annually, while burnout adds billions more. Healthcare organizations face significant challenges when clinical variation goes unmanaged.

But what is clinical variation, and what strategies can you implement to reduce it?

Our latest report, based on data from 65 hospitals, breaks down key metrics you need to understand in order to reduce clinical variation at your health system—and provides tangible next steps for your informatics, analytics, or EHR teams.

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The hidden costs of unwarranted clinical variation

Financial

Unwarranted variation drives substantial healthcare waste. Unnecessary lab tests, redundant imaging studies, and non-evidence-based treatment protocols cost healthcare systems hundreds of thousands to millions of dollars annually. Poorly managed order sets containing outdated or unnecessary items directly contribute to this waste, as clinicians may default to ordering tests and treatments that don't align with current evidence-based guidelines.

Operational

Clinical informatics teams spend countless hours managing thousands of order sets, clinical pathways, and decision support tools—often without clear visibility into which content drives variation. Traditional order set review processes are notoriously slow, taking months to complete while new clinical evidence is continuously emerging. Regulatory compliance becomes reactive rather than proactive, with organizations scrambling to prepare for Joint Commission and CMS audits.

Quality and safety

Inconsistent clinical pathways increase the risk of adverse events and medical errors. Multiple order sets for the same diagnosis with conflicting recommendations create confusion at the point of care. Quality improvement initiatives struggle to gain traction when baseline clinical practices vary widely across departments and facilities.

What is clinical variation?

Clinical variation refers to the differences in healthcare delivery, treatment decisions, and clinical outcomes across providers, facilities, and patient populations—even when patients present with similar conditions. This phenomenon affects healthcare quality, patient safety, and operational efficiency across the industry.

Unwarranted variation

This problematic variation often stems from inconsistent clinician training and experience, ineffective clinical decision support, outdated protocols, or fragmented EHR content management. For example, consider two emergency physicians: Dr. B, who completed his residency in the 1960s—long before the advent of MRI and today’s evidence-based stroke pathways—and Dr. M, who finished residency just last year and regularly led journal clubs on the latest randomized control trials. Both are talented and dedicated physicians, yet their approaches to managing a patient with stroke symptoms might differ significantly.

Without reliable, current clinical decision support and well-maintained order sets, those differences can translate into unwarranted variation in care. And that variation matters—because for stroke, the evidence is clear about which interventions are essential and which high-risk or costly treatments should be avoided. Aligning both Dr. B and Dr. M around the same evidence-based practices requires not only good intentions but also modern, governed, and consistently reviewed clinical content.

Ineffective order set management and review processes are among the leading contributors to unwarranted clinical variation, as healthcare organizations struggle to maintain consistency across hundreds or thousands of clinical ordering workflows.

Root causes of clinical variation

EHR content proliferation

Modern electronic health record systems including Epic Systems and Oracle Health enable libraries of sprawling clinical content. Multiple order sets for the same condition, unmonitored alerts, outdated clinical pathways, and redundant decision support tools create confusion and inconsistency. Without systematic management, duplicate and obsolete content accumulates unchecked, making it nearly impossible for clinicians to choose the right ordering pathway.

Resource constraints

Lean clinical informatics teams face impossible demands: managing thousands of clinical workflows, reviewing hundreds of order sets, and responding to continuous regulatory requirements—all while supporting quality improvement initiatives. The decision support review backlog continues to grow while teams struggle to keep pace with clinical advancements and regulatory changes.

Inadequate review process

Manual order set review is time-consuming and unsustainable. Traditional review cycles can take 6+ months per order set, creating massive backlogs while clinical evidence continues to evolve. Reviewers lack data on how order sets are actually being used, which items are frequently deleted or modified, and whether the content aligns with current outcomes.

Siloed CDS

Clinical teams, IT departments, and operational stakeholders typically work in isolation when managing EHR content. Order set ownership is often unclear, with no centralized system to track content authorship, approval status, or review schedules.

Limited analytics

EHR-native analytics tools provide insufficient visibility into clinical content usage, performance, and impact. Teams cannot easily answer critical questions like: Which order sets are generating the most variation? Where are clinicians modifying default orders? Which alert hasn't been reviewed in years?

Strategies for reducing clinical variation

Evidence-based clinical standardization

Successful variation reduction starts with establishing evidence-based workflows aligned with current best-practice guidelines. Healthcare organizations must regularly review and update order sets, protocols, and other clinical decision support tools to reflect the latest medical evidence and regulatory requirements.

Comprehensive EHR content governance

Strong governance structures bring together clinical, IT, and operational stakeholders to oversee EHR content throughout its lifecycle. Effective governance includes engaging the right stakeholders, systematic content creation, review, optimization, and retirement processes—ensuring clinical tools remain current and aligned with organizational quality goals.

Data-driven decision making

Organizations need visibility into clinical content usage patterns, ordering behaviors, and decision support effectiveness. Advanced analytics capabilities enable teams to identify variation sources, measure intervention impacts, and prioritize optimization efforts based on potential quality and cost improvements.

Democratized access to insights

Breaking down data accessibility barriers allows multidisciplinary teams to collaborate on variation reduction initiatives. When clinical staff, quality improvement specialists, and informatics professionals can explore EHR data together, organizations accelerate problem identification and solution implementation.

Measuring clinical variation reduction success

Healthcare organizations should track multiple metrics when addressing clinical variation:

Timeline metrics: Reduction in clinical decision-making and content review timelines
Financial metrics: Cost savings from eliminated unnecessary testing, imaging, or treatments
Quality metrics: Decreased adverse events, improved guideline adherence, and enhanced patient outcomes
Efficiency metrics: Accelerated order set review processes and streamlined workflow implementations
Compliance metrics: Improved regulatory audit readiness and documentation completeness

The path forward: EHR optimization solutions to reduce clinical variation and increase clinical standardization

Modern healthcare organizations require specialized platforms that transform clinical decision support from a burden into a competitive advantage. The most effective solutions offer:

Centralized clinical knowledge management

Platforms that centralize CDS knowledge across the enterprise enable organizations to establish single sources of truth for clinical content. This centralization breaks down operational silos and ensures consistent governance.

Automated workflow optimization

Automation capabilities reduce tedious manual tasks, freeing clinical informatics teams to focus on strategic initiatives. Automated compliance documentation systems transform reactive scrambles into proactive regulatory readiness.

Advanced analytics and visibility

Solutions providing superior visibility compared to EHR-native tools enable organizations to uncover and fix root causes of digital workflow inefficiencies. Drill-down capabilities support data exploration across users with varying technical literacy levels.

Rapid implementation and adoption

Healthcare organizations need solutions that integrate seamlessly with existing EHR systems through secure, read-only data extraction requiring minimal IT effort. Quick implementation timelines—measured in months, not years—ensure rapid time-to-value.

Real-world clinical variation reduction results

Leading healthcare organizations have demonstrated dramatic improvements in clinical standardization and variation reduction:

Accelerated governance: Organizations have achieved 85% reductions in clinical decision timelines, moving from six-month processes to two-week cycles
Enhanced efficiency: Teams report 10x increase in order set review capacity and 5x faster content review processes
Significant cost savings: Health systems identify $700,000+ in annual savings opportunities through targeted variation reduction initiatives
Improved outcomes: Proactive monitoring enables 40% reductions in non-critical resource utilization during supply chain crises

Clinical decision support standardization

Healthcare organizations ready to address clinical variation should consider comprehensive EHR optimization platforms that:

Provide unlimited access across clinical, informatics, and operational teams
Deliver curated insights highlighting high-impact improvement opportunities
Accelerate order set review processes with data-driven analytics and streamlined workflows
Support proactive risk detection and measurable quality improvement tracking
Enable clinical standardization that reduces waste and minimizes patient safety risk

Frequently asked questions about reducing clinical variation

What causes clinical variation in order sets?

Order set variation stems from EHR content proliferation, slow review cycles, lack of available usage analytics, and siloed governance. Without centralized management and data-driven insights, duplicate and outdated order sets accumulate, creating inconsistent clinical pathways.

How long does traditional order set review take?

Traditional manual review processes can take up to 6 months per order set, creating unsustainable backlogs. Modern optimization platforms can reduce this timeline to 2 weeks while increasing review capacity by 10x.

How much can healthcare organizations save by reducing order set variation?

Organizations report savings ranging from hundreds of thousands to millions of dollars annually. One regional health system saved $700,000 by optimizing pneumonia order sets to reduce unnecessary testing by 57%.

How does Phrase Health support reducing clinical variation?

Phrase Health specializes in helping healthcare organizations optimize electronic health records and clinical decision support systems to reduce unwarranted clinical variation. With proven results across 70+ hospitals since 2019, the platform centralizes CDS knowledge, automates tedious tasks, and breaks down operational silos—empowering healthcare teams to focus on exceptional patient care while maintaining operational excellence.