Track these six key metrics using an ASC analytics solution to help you monitor your anesthesia provider's performance.
Tracking anesthesia key performance indicators (KPIs) is critical to ensuring your anesthesia providers deliver the high-quality services that support optimal outcomes and high levels of patient satisfaction. Measuring anesthesia quality KPIs can tell you if anesthesia provider performance is up to your organization's standard of excellence and help pinpoint the best opportunities for quantifiable improvement.
There are many KPIs you can track, which may feel overwhelming. Selecting the most important anesthesia quality metrics will help ensure these KPIs receive the attention they deserve, while reducing the time and energy spent on less significant metrics. An analytics solution can help identify the anesthesia quality KPIs worthy of increased scrutiny and support efforts to internally benchmark your data.
These six anesthesia KPIs represent the core metrics most organizations track to evaluate quality, efficiency, and patient safety. For each KPI, your analytics solution can reveal contributing factors, provider-specific patterns, and opportunities for targeted improvement.
Definition: Tracks whether patient temperature remains within your organization’s defined normal range
Why it matters: Temperature deviations can indicate increased clinical risk.
How analytics helps: Reveals patterns by provider, case type, patient characteristics, or documentation errors
This temperature-management KPI tracks whether a patient's temperature shifts outside of what your organization determines will be its "normal range," which can indicate an increased likelihood of patient harm. While it’s preferable to keep the normothermia metric at zero percent (i.e., no patient's temperature was ever abnormal), it’s not unusual for some patients to experience abnormal temperatures.
An analytics solution can help you dive into this anesthesia quality metric to determine:
When such instances occur
Which of your anesthesia providers was caring for the patient with the abnormal temperature
Case details that may have contributed to the abnormal temperature (e.g., procedure type, patient age, patient ASA score)
Whether the abnormal temperature was actually a documentation error that can be adjusted in the patient’s chart
Using this information, you can start changing your policies and processes to improve your normothermia KPI.
Definition: Measures whether anesthesia providers capture patient temperature within your defined time window (e.g., within 15 minutes of PACU start)
Why it matters: Late documentation can delay intervention when a patient’s temperature deviates.
How analytics helps: Identifies providers or case types with lower timeliness compliance
What you’re looking for with this anesthesia quality metric is whether anesthesia providers are capturing patient temperatures according to your timeliness standards. If data capture occurs outside a timely window, this potentially puts patients at increased risk if they experience abnormal temperatures when tracking isn’t occurring.
A timely temperature capture typically occurs within the 15 minutes immediately after PACU start time. If the patient doesn’t go to PACU, a timely temperature capture occurs 30 minutes immediately after anesthesia end time. Delaying temperature capture reduces the timeliness percentage. Using an analytics solution can help you identify which of your anesthesia providers don’t consistently capture patient temperature "on time" and, therefore, require assistance to improve their performance and patient safety in the process.
Definition: Measures the percentage of cases in which a patient experiences PONV
Why it matters: PONV strongly influences patient satisfaction, even when clinical outcomes are excellent.
How analytics helps: Tracks trends by provider, anesthetic technique, patient risk factors, and case complexity
Any instance of PONV raises the likelihood that a patient will reflect poorly on their experience with your organization, even if their procedure delivered a positive clinical outcome. Tracking this anesthesia quality KPI — and digging into it using an analytics solution — can help you implement changes that can have an immediate impact on patient satisfaction scores.
A high-level way of tracking this KPI is by examining PONV percentage over time for all patients. Implementing effective changes will help bring and keep this percentage down.
Going a level deeper, consider the ability to track PONV occurrence by anesthesia provider and anesthesia type. If one or more providers have a PONV percentage above the mean for your organization, you can compare their practices to those with better scores to determine why their approach may be contributing to the higher rate of incident. If you have one or more providers with a PONV percentage well below the mean, assess their approach to determine how they can achieve more preferable results.
You may also find that your organization needs to reassess its approach to PONV management based on specific patient factors (e.g., age, ASA score, comorbidities) or case characteristics (e.g., procedure type, duration, invasiveness). With more insight into the factors influencing this anesthesia quality metric, you can better target improvement efforts.
Definition: Percentage of surgical cases that require transfer directly to ICU after the intraoperative phase
Why it matters: Higher ICU rates can signal issues with case selection, anesthesia approach, or clinical complexity.
How analytics helps: Surfaces patterns by procedure type, provider, and surgeon
You'll inevitably experience instances in which the intraoperative phase is followed by a patient going directly to the intensive care unit (ICU) instead of moving on to the post-op/recovery phase. It's valuable to know the overall percentage of your cases that require such a transfer.
With an analytics solution, you can examine the percentage of ICU cases further. Are there similarities across these cases? Are they associated with a specific procedure(s), anesthesia provider(s), or surgeon(s)? As you identify themes, it will be easier to implement and measure the effectiveness of solutions.
Definition: Measures workflow efficiency across anesthesia–surgeon pairings (e.g., wheel-in to induction time, induction to incision time)
Why it matters: Certain pairings consistently perform faster or slower, which influences OR throughput.
How analytics helps: Identifies optimal pairings for scheduling and highlights productivity gaps
By comparing productivity across different surgeon-anesthesia provider pairings for the same procedure, you can optimize scheduling — teaming up personnel that excel together and avoiding those with lower performance.
Using an analytics solution, you can compare how two pairings perform from the time a patient is wheeled in until induction time is documented, for example. Other possible areas of comparison: induction to incision time, anesthesia duration, surgery duration, and PACU duration.
Definition: Tracks which medications and combinations are administered intraoperatively and postoperatively
Why it matters: Different drug combinations influence PACU duration, PONV rates, and overall recovery quality.
How analytics helps: Enables hypothesis testing to determine which combinations deliver best outcomes
When you routinely collect data concerning medication administration, you gain the ability to perform a wide range of hypothesis testing around the combinations of drugs administered and how they may affect the surgical outcome and quality of the patient experience.
Take the recovery phase of care. Let's say most patients receive propofol, but some anesthesia providers choose to administer lidocaine alongside propofol. By tracking this information, together with anesthesia quality metrics such as PACU duration and PONV, you gain the ability to determine whether one medication combination is more effective than others at achieving desired results.
Although many anesthesia KPIs are available for tracking, analytics can help narrow the list to the metrics that offer the most meaningful improvement opportunities. Prioritizing the right KPIs helps maintain focus and ensures steady progress toward higher-quality care.
While most organizations share a common set of core anesthesia KPIs, an analytics solution greatly expands the number and types of metrics available for tracking and benchmarking. This may initially feel overwhelming, but analytics can highlight which KPIs warrant increased attention and better support the ongoing measurement of performance improvement efforts.
When used effectively, analytics provide deep visibility into anesthesia quality data and reveal where change is most needed. These insights can guide process improvements, influence provider behavior, and help elevate overall OR performance. The result is higher-quality care that delivers stronger outcomes and an improved experience for patients, providers, and staff.
What are anesthesia key performance indicators (KPIs)?
Anesthesia KPIs are specific metrics that assess the efficacy of anesthesia service delivery in supporting positive patient outcomes and experiences.
Why is it important to track the right anesthesia KPIs?It can be overwhelming for practices to choose from the seemingly endless number of anesthesia KPIs. Selecting the right KPIs can help an organization pinpoint their specific areas in need of improvement. Rather than tracking and benchmarking all metrics, filtering out less significant KPIs enables teams to focus more on the metrics that matter most to their organization and patients.
Which anesthesia KPIs are best to track?While KPIs differ depending on the organization and its needs, most organizations should track normothermia rates, temperature timeliness, rates of postoperative nausea and vomiting, percentage of ICU cases, anesthesia provider and surgeon productivity, and medication administration.
How can an analytics solution help my organization monitor anesthesia KPIs?An analytics solution can streamline data collection and help summarize KPI data for easier and more effective use. With an analytics solution, teams can identify performance by specific KPI, anesthesia provider, medication type, time of administration, patient reaction, and more.