How to Improve Operating Room Utilization: The Metrics That Actually Matter

🎯 Key Takeaways

• The OR drives 60–70% of hospital revenue: Research finds the OR accounts for 60–70% of total hospital revenue and up to 40% of costs, making utilization improvement one of the highest-impact financial opportunities for hospital leadership [1].
• Less than 50% of OR time is spent doing surgery: A 2025 JMIR study found less than 50% of operating time is actually spent performing surgery, with errors in procedure length estimation occurring in ~75% of cases [3].
• Optimal OR utilization is 85–90%, not 100%: A peer-reviewed simulation found OR utilization above 85–90% leads to patient delays and staff overtime. In practice, many programs target 75–80% prime-time utilization while preserving enough capacity for add-ons, emergencies, and schedule variation [4].
• First-case on-time starts below 90% cost $1.56M+ annually per 10-room OR: Moving a 10-room OR from 50% to the 90% industry-standard first-case on-time start rate generates an estimated $1.56 million in annualized OR capacity recovery at $100/minute [5].
• Turnover times above 20 minutes lose 90+ minutes per OR per day: A benchmark turnover of 20 minutes vs. the common 30–35-minute reality means 15 minutes lost per case; in a 6-case OR day that exceeds 90 minutes of recoverable capacity [6].
• ML-driven scheduling recovers measurable OR hours: Opmed's predictive model reduced cardiac case length prediction error at Mayo Clinic from 60 to 34 minutes MAE, and Geisinger reports saving hundreds of OR hours annually with 40%+ improvement in prediction accuracy [Opmed].

Why OR Utilization Is the CFO's Highest-Leverage Operational Metric

No asset in a hospital's portfolio generates and consumes resources at the rate the operating room does. A well-cited review in surgical operations literature identifies the OR as a major driver of hospital financial performance, accounting for up to 40% of total hospital costs and 60–70% of total hospital revenue [1]. Research published in JAMA Surgery and the Annals of Surgery quantifies elective inpatient and outpatient surgical procedures at $195–$212 billion in annual hospital reimbursement and $48–$65 billion in net income across the U.S. healthcare system [2]. Elective surgical cases specifically contribute approximately 78% of total inpatient and outpatient surgical gross revenue [7].

Against that revenue backdrop, the utilization gap is striking. A 2025 study published in JMIR Medical Informatics found that less than 50% of operating time is actually spent performing surgery, with procedure length estimation errors occurring in approximately 75% of cases [3]. A separate peer-reviewed analysis found 32–50% of daily OR schedules are under booked while 37–42% are overbooked, which means the same surgical schedule can leave some rooms idle while pushing others into overtime [3]. AHRQ's Healthcare Cost and Utilization Project found that inpatient stays involving OR procedures accounted for 47.3% of all inpatient aggregate costs in 2018, across 14.4 million procedures totaling $210.3 billion — reinforcing the scale of the opportunity [8].

The practical implication for a Surgical Services Director or CFO: a 5–10% improvement in adjusted OR utilization across a 10-room surgical suite, at $36–$47 per OR-minute, translates to hundreds of recoverable OR hours and millions of dollars in incremental annual margin. The question is not whether improving OR utilization is worth the investment. The question is which metrics to optimize, and in what order.

The Metrics Most Organizations Are Tracking (And Why They're Not Enough)

Most surgical services programs track 2 operational metrics with intensity: first-case on-time starts and turnover time. Both are legitimate. Neither is sufficient on its own, and optimizing only these 2 metrics has been shown to produce surprisingly modest improvement in overall OR utilization.

A comprehensive multi-hospital OR utilization study found that despite sustained improvement in first-case start times and turnover duration, overall utilization did not improve significantly because the root cause of underutilization was not limited to those time windows. The root cause was block time structure, case duration inaccuracy, and underutilization of prime time hours outside the first case and turnover windows [9]. This finding is consistent with peer-reviewed research on OR scheduling: interventions targeting turnover or first-case delays alone produce only small reductions in OR labor costs, with the degree of reduction insufficient to materially change the financial profile of the surgical program [10].

The implication is not to stop tracking first-case starts and turnover. It is to track them in context, alongside the 5 metrics that explain the broader utilization picture — and to understand that improving a lagging indicator (overall utilization rate) requires acting on the leading indicators that actually drive it.

The Five Metrics That Actually Move OR Utilization

1. Prime-Time Utilization Rate

Prime-time utilization measures the percentage of available minutes during core surgical hours (typically 7 AM–3 PM or 7 AM–4 PM) that are filled with case minutes. It is one of the most actionable utilization metrics because it reflects the time window when the OR is fully staffed, fully resourced, and operating at lowest cost per minute. Cases performed outside prime time carry significantly higher labor costs due to overtime, on-call staff, and resource inefficiency [11].

The industry benchmark for prime-time utilization is 75–80% — high enough to maximize throughput while preserving the slack capacity needed to absorb emergency add-on cases without cascading delays [4]. A peer-reviewed simulation study established that OR utilization above 85–90% leads to patient delays and staff overtime, confirming that 100% fill is not the operational goal [4]. Programs with prime-time utilization consistently below 60–65% have material capacity available for additional case volume that the current scheduling architecture is not capturing.

2. Adjusted Block Utilization

Block utilization is the percentage of allocated block time actually used by the surgeon or service to whom it was assigned. Raw block utilization (total block minutes used divided by total block minutes assigned) consistently overstates true efficiency because it includes turnover time in the denominator. Adjusted block utilization — total case minutes plus intra-block turnover divided by total allocated block time minus released time — is the operationally meaningful figure; benchmark targets typically range from 65% to 80% adjusted block utilization [4][6].

A block utilization rate below 65–70% for a given surgeon or service is generally the threshold at which reallocation conversations become appropriate [6]. The difficulty, documented in peer-reviewed research, is that block utilization cannot be estimated accurately for low-volume surgeons from less than a year of data — and even with a full year, 95% confidence intervals for individual surgeon utilization can span 40+ percentage points [12]. The practical implication: make block reallocation decisions at the service level using 12 months of data, not at the individual surgeon level using 3-month snapshots.

3. Case Duration Prediction Accuracy (Mean Absolute Error)

Case duration prediction accuracy is the single metric most predictive of downstream schedule performance. Errors in scheduled case duration compound through the day: an underbooked room sits idle, an overbooked room runs into overtime, and both outcomes cost more than the cost of better prediction would have required. Research published in JMIR Medical Informatics in 2025 found that ML-based prediction approaches significantly outperform mean-based estimates, and that combining patient-level duration prediction with schedule optimization (the "predict-then-optimize" approach) recovers measurable OR hours that purely mean-based scheduling leaves on the table [3].

The relevant KPI is Mean Absolute Error (MAE) — the average deviation in minutes between scheduled and actual case duration across all cases. An MAE above 30–40 minutes is a diagnostic indicator that the scheduling system is using insufficiently granular duration estimates. Opmed's predictive model reduced cardiac case length prediction MAE at Mayo Clinic from 60 minutes to 34 minutes per case — a 43% improvement in intraday schedule stability that directly translates to fewer overruns and better room-by-room throughput [Opmed Mayo Case Study].

4. First-Case On-Time Start Rate (FCOTS) in Financial Context

First-case on-time start rate — the percentage of first scheduled cases that begin within 5 minutes of the planned start time — has a well-quantified financial impact when calculated correctly. The industry standard is 90% [5][6]. A 10-room OR facility moving from a 50% FCOTS rate to the 90% benchmark, starting cases an average of 15 minutes late, generates an estimated $1.56 million in annualized capacity recovery at $100 per minute [5].

The critical qualification: FCOTS is a leading indicator for the first 2 hours of the OR day. Its impact on full-day utilization is significant but partial, and programs that optimize exclusively for FCOTS without addressing case duration accuracy and block utilization will see narrower improvement than the financial model suggests. FCOTS should be tracked alongside, not instead of, prime-time utilization and block utilization.

5. Turnover Time and Contribution Margin Per OR Hour

Turnover time — the interval from when a patient exits the OR to when the next patient enters — benchmarks at approximately 20 minutes in high-performing programs [6]. Most facilities run 30–35 minutes, meaning 15 minutes of recoverable capacity per case. In a 6-case OR day, that excess represents 90+ minutes of time that could otherwise accommodate an additional case or eliminate end-of-day overtime [6].

Contribution margin per OR hour completes the financial picture. Not all cases are equally profitable; contribution margin per OR-hour varies among surgeons performing the same procedure type, and contribution margin is negative for approximately 26% of cases in programs where OR utilization is extensive and every hour is scheduled [13]. Optimizing for case volume without tracking contribution margin can improve utilization rate while degrading financial performance. The operationally mature metric is contribution margin per available OR-hour, which integrates case selection, surgeon efficiency, and utilization into a single financial signal.

OR Utilization Metric Framework: What to Track and Why

What Improvement Actually Looks Like in OR Hours and Dollars

The metrics above are diagnostic tools. Their value lies in translating the diagnosis into a quantified improvement opportunity. The math framework for a 10-room OR surgical program running at $36–$47 per minute:

Prime-time utilization improvement of 10 percentage points — from 65% to 75% across 10 rooms, 250 OR days per year — recovers approximately 2,500 OR hours of previously stranded capacity. At $36–$47 per minute, that represents $5.4–$7.1 million in potential annual margin improvement for procedures the rooms were already staffed to accommodate [1][8].

First-case on-time starts from 50% to 90% on 10 rooms generates the $1.56 million annualized impact cited in Plante Moran's industry benchmark analysis [5]. The key constraint is that this improvement must be sustained at scale — improvement in individual surgeons' start times without program-level operational changes tends to regress to the mean within 90–120 days.

Turnover time reduction from 35 to 20 minutes across 6 cases per OR per day recovers 90 minutes per room per day, or 375 OR hours per year per room across a 250-day year. Across a 10-room program, that is 3,750 hours of potential additional case capacity annually — the equivalent of 3–4 additional fully utilized OR rooms without expanding physical space.

Geisinger Health's experience with Opmed validates the aggregate impact: after implementing Opmed's AI-driven scheduling infrastructure, Geisinger reports saving hundreds of OR hours annually and achieving a 40% or greater improvement in case duration prediction accuracy, with Jeffrey Adams (Chief Administrative Officer, Surgical Services) publicly attributing the outcome to the operational infrastructure rather than surgical volume changes [Opmed].

"The operating room is the financial nexus of the modern hospital, accounting for up to 40% of a hospital's costs and 60–70% of revenue."

— Best Practice & Research: Clinical Anaesthesiology, ScienceDirect [1]

How AI Scheduling Changes What's Measurable and Improvable

The 5 metrics above are not new. Hospital administrators have known for decades that block utilization and case duration accuracy drive OR performance — the Association of periOperative Registered Nurses (AORN) and the American College of Surgeons (ACS) both confirm that these metrics are the core operational levers for sustainable OR improvement [18]. What has changed is the operational infrastructure available to act on these metrics in real time — and the data architecture that makes accurate measurement possible at all.

Traditional EHR-based scheduling produces a static daily OR board built on historical averages. It cannot update case duration estimates as the surgical day evolves, cannot reallocate block time dynamically when a surgeon cancels, and cannot surface real-time alerts when a room is trending toward overtime or when prime-time slots are approaching stranded capacity. The consequence, documented in the clinical literature, is that 87% of OR cases deviate from their planned start time by more than 10 minutes — a figure that has not materially improved despite decades of attention to first-case starts and turnover [14].

AI-powered scheduling platforms analyze each case's actual predictors — surgeon, procedure type, patient ASA classification, team composition, time of day — to generate patient-specific duration estimates rather than averages. They monitor intraday schedule performance and surface risk flags before overruns become cancellations. They apply block utilization logic across trailing 12-month data to recommend reallocation that the quarterly block committee review misses.

The 2025 JMIR Medical Informatics study on ML-based elective orthopedic scheduling found that combining patient-level duration prediction with schedule optimization — the predict-then-optimize approach — improved schedule performance over mean-based scheduling across two years of simulation [3]. Across Opmed's customer base, the operational translation is measurable: Geisinger's 40%+ improvement in prediction accuracy and hundreds of recovered OR hours annually [Opmed]; Mayo Clinic's cardiac case MAE improvement from 60 to 34 minutes [Opmed Mayo Case Study].

For Surgical Services Directors and CFOs who want to quantify their OR's specific capacity recovery opportunity, Opmed's time savings calculator takes facility-specific inputs and returns an estimate of recoverable OR hours in about 90 seconds. Calculate your potential OR time savings with Opmed →

Move from Utilization Measurement to Utilization Recovery

OR utilization improvement is not a process improvement project — it is the financial performance strategy for a hospital's highest-revenue, highest-cost asset. The 5 metrics that actually drive improvement — prime-time utilization, adjusted block utilization, case duration prediction accuracy, first-case on-time start rate, and contribution margin per OR hour — are all addressable with the right operational infrastructure. The difference between a surgical program that measures these metrics and one that actually improves them is the scheduling architecture that closes the loop between data and daily decisions.

The programs recovering hundreds of OR hours annually — Geisinger Health saved hundreds of OR hours per year and achieved a 40%+ improvement in case duration prediction accuracy [Opmed] — are not doing so by working harder or adding rooms. They are operating from a schedule built on patient-specific duration predictions, real-time risk visibility, and block allocation logic that responds to trailing utilization data rather than quarterly committee review. That is the operational shift that moves a CFO's utilization dashboard from a reporting exercise to a margin recovery tool.

Calculate your potential OR time savings with Opmed →

Related Resources

Continue exploring OR performance with these resources from the Opmed team:

• Why Does Your OR Schedule Fall Apart Before the Day Even Starts? — Piece #5 in the OR Scheduling Cluster: the root-cause companion to this utilization post
• What Is OR Block Scheduling? A Complete Guide for Surgical Services Leaders — Piece #1 in the OR Scheduling Cluster: block time fundamentals
• Operating Room Utilization Benchmarks: How Does Your OR Stack Up? — Piece #22: benchmarking your program against peer institutions
• Transforming Cardiac Surgery Scheduling at Mayo Clinic with Opmed.ai — Case study: MAE from 60 to 34 minutes per cardiac case
• OR Time Savings Calculator — Estimate your facility's recoverable OR hours in 90 seconds

Editorial Note

This article is for informational purposes for healthcare operations leaders and does not constitute clinical, legal, or financial advice. All compliance, reimbursement, and operational decisions should be made in consultation with qualified counsel, your facility's compliance team, and CMS guidance specific to your facility type and circumstances.

Opmed.ai is a healthcare operations platform; our outcomes data reflects aggregate performance across customer facilities and individual results will vary based on facility size, staffing, patient mix, and implementation scope.

Last reviewed: April 2026 by the Opmed Editorial Team.

References

[1] Rothstein DH, Raval MV. Operating Room Efficiency. Best Practice & Research: Clinical Anaesthesiology, ScienceDirect, 2018. https://www.sciencedirect.com/science/article/abs/pii/S1055858618300040 — accessed April 2026. [OR = 40% of hospital costs, 60–70% of revenue]

[2] Bose SK et al. The likely economic impact of fewer elective surgical procedures on US hospitals during the COVID-19 pandemic. PMC7388821. https://pmc.ncbi.nlm.nih.gov/articles/PMC7388821/ — accessed April 2026. [$195.4–$212.2B in hospital reimbursement; $48–$64.8B net income annually]

[3] Lex JR et al. Using Machine Learning to Predict-Then-Optimize Elective Orthopedic Surgery Scheduling to Improve Operating Room Utilization. JMIR Medical Informatics, September 2025. PMC12422739. https://medinform.jmir.org/2025/1/e70857 — accessed April 2026. [<50% of OR time spent doing surgery; ~75% estimation error; 32–50% underbooked; 37–42% overbooked]

[4] Strum DP et al. Determining optimum operating room utilization. Anesthesia & Analgesia, 2003. PubMed 12651670. https://pubmed.ncbi.nlm.nih.gov/12651670/ — accessed April 2026. [85–90% optimal; above = delays and overtime]

[5] Plante Moran. First-Case On-Time Starts: A Proven Strategy to Improve Your OR Efficiency, January 2023. https://www.plantemoran.com/explore-our-thinking/insight/2023/01/first-case-ontime-a-proven-strategy-to-improve-your-or-efficiency — accessed April 2026. [FCOTS 90% standard; 50%→90% on 10-room OR = $1.56M annualized at $100/min]

[6] Plante Moran. Key Metrics to Improve Your Operating Room Utilization. https://www.plantemoran.com/explore-our-thinking/insight/2019/02/key-metrics-to-improve-your-operating-room-utilization — accessed April 2026. [20-min turnover benchmark; 30–35-min real-world average; 65–70% block threshold]

[7] Uppal S et al. Balancing revenue generation with capacity generation. PMC7711259. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7711259/ — accessed April 2026. [Elective surgical cases = 78% of surgical gross revenue]

[8] McDermott KW, Liang L. Overview of Operating Room Procedures During Inpatient Stays in U.S. Hospitals, 2018. HCUP Statistical Brief #281. AHRQ, August 2021. https://hcup-us.ahrq.gov/reports/statbriefs/sb281-Operating-Room-Procedures-During-Hospitalization-2018.jsp — accessed April 2026.

[9] Health IT Outcomes / UCHealth study. The Data Proves It: First Case Starts and Turnover Time Are Not Your Best Metrics. 2017. https://www.healthitoutcomes.com/doc/the-data-proves-first-case-starts-turnover-your-best-metrics-0001 — accessed April 2026.

[10] Wang J. Operating Room Adjusted Utilization Study. Health Systems Engineering, Wayne State University. https://hse.eng.wayne.edu/Research/Wang-OR%20Utilization.pdf — accessed April 2026. [Turnover and FCOTS interventions alone produce only small labor cost reductions]

[11] The Operating Room Global (TORG) Foundation. Key Performance Indicators (KPIs) of the Operating Room. https://operatingroomissues.org/key-performance-indicators-kpis-of-the-operating-room/ — accessed April 2026.

[12] Dexter F et al. Operating room utilization alone is not an accurate metric for the allocation of OR block time to individual surgeons with low caseloads. Anesthesiology, 2003. PubMed 12717148. https://pubmed.ncbi.nlm.nih.gov/12717148/ — accessed April 2026.

[13] Dexter F, Abouleish AE. Hospital profitability per hour of operating room time can vary among surgeons. Anesthesia & Analgesia, 2001. PubMed 11524339. https://pubmed.ncbi.nlm.nih.gov/11524339/ — accessed April 2026. [Contribution margin negative for 26% of cases]

[14] Zander M et al. (case deviation data from PMC5406398). Timeliness of Operating Room Case Planning and Time Utilization. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5406398/ — accessed April 2026. [87% of OR cases deviate >10 min from planned start time]

[15] Childers CP, Maggard-Gibbons M. Understanding costs of care in the operating room. JAMA Surgery, 2018. PMC5875376. https://pmc.ncbi.nlm.nih.gov/articles/PMC5875376/ — accessed April 2026. [$36–$47/minute facility-level cost]

[16] McIntyre L et al. Cancellation of elective surgery: rates, reasons and effect on patient satisfaction. PMC8064262. https://pmc.ncbi.nlm.nih.gov/articles/PMC8064262/ — accessed April 2026. [83.5% of cancellations are administrative/structural]

[Opmed Mayo Case Study] Transforming Cardiac Surgery Scheduling at Mayo Clinic With Opmed.ai. https://www.opmed.ai/blog-posts/transforming-cardiac-surgery-scheduling-at-mayo-clinic-with-opmed-ai — accessed April 2026. [Case length MAE reduced from 60 to 34 minutes; published Opmed case study]

[Opmed] Opmed.ai customer outcomes data, 2026 — includes Geisinger Health (hundreds of OR hours saved annually; 40%+ prediction accuracy improvement; Jeffrey Adams, CAO Surgical Services) and aggregate calculator outcomes. https://www.opmed.ai/ and https://online.opmed.ai/calculate

[17] American Hospital Association (AHA). Hospital Statistics: Perioperative Services as Primary Revenue Driver. https://www.aha.org — accessed April 2026. [AHA identifies perioperative services as the single largest revenue-generating department in most U.S. hospitals]

[18] Association of periOperative Registered Nurses (AORN) / American College of Surgeons (ACS). OR Management and Benchmarking Guidance. https://www.aorn.org — accessed April 2026. [AORN and ACS confirm adjusted block utilization, case duration accuracy, and FCOTS as core operational levers for OR improvement]