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Perioperative Temperature Measurement Considerations Relevant to Reporting Requirements for National Quality Programs Using Data From Anesthesia Information Management Systems

Epstein, Richard H. MD*; Dexter, Franklin MD, PhD; Hofer, Ira S. MD; Rodriguez, Luis I. MD*; Schwenk, Eric S. MD§; Maga, Joni M. MD*; Hindman, Bradley J. MD

doi: 10.1213/ANE.0000000000002098
Patient Safety: Original Clinical Research Report
Free
SDC

BACKGROUND: Perioperative hypothermia may increase the incidences of wound infection, blood loss, transfusion, and cardiac morbidity. US national quality programs for perioperative normothermia specify the presence of at least 1 “body temperature” ≥35.5°C during the interval from 30 minutes before to 15 minutes after the anesthesia end time. Using data from 4 academic hospitals, we evaluated timing and measurement considerations relevant to the current requirements to guide hospitals wishing to report perioperative temperature measures using electronic data sources.

METHODS: Anesthesia information management system databases from 4 hospitals were queried to obtain intraoperative temperatures and intervals to the anesthesia end time from discontinuation of temperature monitoring, end of surgery, and extubation. Inclusion criteria included age >16 years, use of a tracheal tube or supraglottic airway, and case duration ≥60 minutes. The end-of-case temperature was determined as the maximum intraoperative temperature recorded within 30 minutes before the anesthesia end time (ie, the temperature that would be used for reporting purposes). The fractions of cases with intervals >30 minutes between the last intraoperative temperature and the anesthesia end time were determined.

RESULTS: Among the hospitals, averages (binned by quarters) of 34.5% to 59.5% of cases had intraoperative temperature monitoring discontinued >30 minutes before the anesthesia end time. Even if temperature measurement had been continued until extubation, averages of 5.9% to 20.8% of cases would have exceeded the allowed 30-minute window. Averages of 8.9% to 21.3% of cases had end-of-case intraoperative temperatures <35.5°C (ie, a quality measure failure).

CONCLUSIONS: Because of timing considerations, a substantial fraction of cases would have been ineligible to use the end-of-case intraoperative temperature for national quality program reporting. Thus, retrieval of postanesthesia care unit temperatures would have been necessary. A substantive percentage of cases had end-of-case intraoperative temperatures below the 35.5°C threshold, also requiring postoperative measurement to determine whether the quality measure was satisfied. Institutions considering reporting national quality measures for perioperative normothermia should consider the technical and logistical issues identified to achieve a high level of compliance based on the specified regulatory language.

Published ahead of print June 8, 2017.

From the *Department of Anesthesiology, Perioperative Medicine & Pain Management, Miller School of Medicine, University of Miami, Miami, Florida

Department of Anesthesia, University of Iowa, Iowa City, Iowa

Department of Anesthesiology and Perioperative Medicine, University of California, Los Angeles, California

§Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, Pennsylvania.

Published ahead of print June 8, 2017.

Accepted for publication March 28, 2017.

Funding: Departmental.

The authors declare no conflicts of interest.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s website.

Data from this study were presented, in part, at the 2017 Annual Meeting of the Society for Technology in Anesthesia.

Reprints will not be available from the authors.

Address correspondence to Richard H. Epstein, MD, Department of Anesthesiology, Perioperative Medicine & Pain Management, University of Miami, Miller School of Medicine, 1400 NW 12th Ave, Suite 3075, Miami, FL. Address e-mail to repstein@med.miami.edu.

Intraoperative hypothermia may increase the incidences of wound infection,1 transfusion and/or blood loss,1–4 cardiac morbidity,5 and prolongs hospitalization.1 Maintenance of perioperative normothermia is a quality objective of the United States of America’s Centers for Medicare and Medicaid Services (CMS) Physician Quality Reporting System (PQRS).6,7 In January 2016, the PQRS #193 measure (Perioperative Temperature Management) was replaced with a new measure, PQRS #424. The former quality measure (PQRS #193) was primarily a process measure, satisfied by documenting the use of an active warming device. The primary reason for its elimination was that the measure had “topped out,” as CMS retires measures in its incentive programs once widespread adoption with high performance has been achieved.8 In contrast, the new quality measure PQRS #424 is an outcomes measure for all patients undergoing general or neuraxial anesthesia lasting ≥60 minutes, requiring at least 1 “body temperature” ≥35.5°C measured within the interval from 30 minutes before to 15 minutes after the anesthesia end time, inclusive.9 From a CMS perspective, the “anesthesia end time” is when anesthesia billing for a case terminates. PQRS #424 is the only anesthesia-related quality measure that is both currently endorsed by the National Quality Forum (NQF 2681) and where the American Society of Anesthesiologists (ASA) is the measure steward.10

As part of its response to the proposed rule by CMS regarding the physician fee schedule,11 the ASA recommended acceptance of measure NQF 2681 as a means to satisfy requirements under the Merit-Based Incentive Payment System (MIPS); this has been approved by CMS as an outcomes measure.12 MIPS was established as part of the Medicare Access and Children's Health Insurance Program (CHIP) Reauthorization Act of 2015.13 The first year for Medicare Access and CHIP Reauthorization Act of 2015 data collection is 2017 and will replace PQRS in 2019.

In this informatics study, we used anesthesia information management systems (AIMS) data from 4 large, academic hospitals to provide guidance to organizations desiring to report on PQRS #424 or NQF 2681. The primary issue relates to the requirement that the intraoperative temperature is reportable as a quality measure only if it is recorded within 30 minutes before the anesthesia end time. In a study of 50 patients undergoing laparoscopic surgery, the average time from temperature probe removal in the operating room (OR) to postanesthesia care unit (PACU) arrival was 30 ± 12 (SD) minutes.14 Because the median time for the transfer of care at 2 large academic hospitals was 5 minutes,15 most cases from the laparoscopy study14 likely would have been ineligible for the intraoperative temperature to be used for reporting, based on timing considerations. Consequently, for the quality reporting process, PACU temperatures would need to be retrieved and matched to the corresponding anesthesia records. We also report on the percentages of patients at the 4 hospitals where the reportable intraoperative temperature (ie, measured within 30 minutes of the anesthesia end time) was <35.5°C.

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METHODS

The protocol was reviewed by the Institutional Review Board at the University of Miami Hospital (UMH), Thomas Jefferson University Hospital (TJUH), Jackson Memorial Hospital (JMH), and the University of California Los Angeles (UCLA), each of which concluded that this study did not meet the US regulatory definition of human subjects research. De-identified retrospective data were extracted from the AIMS databases at the 4 institutions. The different date ranges for each hospital correspond to the available data in their respective data warehouses at the time of analysis (Table 1). None of the 4 hospitals were reporting on PQRS #424 or NQF 2681 during the study interval, no feedback related to intervals from temperature monitoring discontinuation to the anesthesia end time was provided, and no instructions were transmitted to anesthesia providers related to maintaining intraoperative measurement of temperature as long as possible. The Standards for Quality Improvement Reporting Excellence (SQUIRE) checklist was followed in the preparation of this manuscript.16

Table 1.

Table 1.

Similar to the Sun et al17 study, we included noncardiac bypass cases where: (1) the patient was >16 years of age; (2) general anesthesia was administered; (3) a tracheal or supraglottic airway was inserted; (4) the case lasted at least 60 minutes; and (5) temperature monitoring was performed. However, unlike Sun et al, cases were not excluded if an esophageal intraoperative measurement site was not documented because the temperature probe location was frequently not specified. We included all sources of intraoperative temperatures to match what would be the routine use of intraoperative temperature data for quality reporting, because the quality measures do not specify the measurement technology or the site of measurement. Neuraxial cases were excluded, as in Sun et al, because these would not have had core temperatures measured.17

For each case, all sequentially recorded temperatures (nominally at 1-minute intervals) were retrieved. We defined the “end-of-case temperature” as the maximum intraoperative temperature within 30 minutes before the anesthesia end time; this would be the intraoperative temperature used for quality reporting purposes. Intervals were calculated between the anesthesia end time and the following intraoperative milestone events: (1) the time of the last intraoperative temperature (“last temperature time”); (2) the time when surgery end occurred (“surgery end”); and (3) the time of extubation or removal of a supraglottic airway (“extubation”). We analyzed the interval from both end of surgery and extubation to the anesthesia end time because these represent 2 potential strategies for groups wishing to report temperature using only intraoperative measurements. That is, providers would be instructed to maintain core temperature recording until one of these events occurred, rather than to discontinue monitoring sooner.

PACU temperatures were available electronically at UCLA, but not at the other 3 hospitals. These PACU temperatures were measured from a variety of sites, including oral, temporal artery, bladder, axillary, and tympanic membrane. Because the national quality measures neither distinguish among temperature sources, nor provide different thresholds for core or surface measurements, PACU temperature data from the various sites were pooled. No clinical information was retrieved related to either the patients or other aspects of their surgery.

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Statistical Methods

At each hospital, using all cases, the intervals >0 minutes from the 3 milestone events (“last temperature time,” “end surgery,” “extubation”) to the anesthesia end event were sorted. The fractions of cases where the interval was >30 minutes were determined. The 95% Clopper–Pearson binomial confidence intervals (CIs) for these fractions were calculated. These values represent the percentages of cases for which the intraoperative temperature would have been ineligible for reporting (see Table 2). The fractions of cases excluded from reporting using the last temperature time were conservative (ie, an underestimate), because the time of the last temperature would always be the same as or later than the time of the maximum temperature. Calculations were performed using Excel formulas (Microsoft, Redmond, WA).

Table 2.

Table 2.

At each hospital, for each quarter, the mean of the end-of-case temperature and the fraction of cases where this temperature was <35.5°C were calculated. The paired Student t test was used to compare these differences to 0 using Systat 13 (Systat Software, Inc, San Jose, CA), with P < .05 necessary to claim statistical significance. These values represent the percentage of cases that would have failed the performance measure threshold of 35.5°C (see Table 3).

Table 3.

Table 3.

In the Appendix, using data from UCLA, temperatures from both the OR and the PACU were considered for all cases meeting the PQRS #424 reporting requirements (ie, all patients, regardless of age, having general or neuraxial anesthesia with a case duration ≥60 minutes). The objective of this observational analysis was to determine the extent to which cases from this institution would have satisfied the national reporting measure. This process was not feasible for the other study hospitals because of the absence of electronic temperature data in the PACU.

No power analysis was conducted because all qualifying cases, comprising between 12 and 30 quarters of data at each hospital, were analyzed. Thus, we expected tiny standard errors. The date ranges for each institution corresponded to the availability of electronically recorded temperature measurements in their respective AIMS databases.

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RESULTS

The numbers of cases and data intervals available for analysis (Table 1) were as follows: TJUH (84,283, 28 quarters); UMH (29,020, 12 quarters); JMH (65,543, 29 quarters); and UCLA (56,680, 13 quarters). Numbers of cases excluded and corresponding explanations are presented in Table 1.

Calculations of the percentages of cases that would be excluded from reporting under PQRS #424 due to an interval >30 minutes from various intraoperative milestones are presented in Table 2. Based on when intraoperative temperature monitoring was discontinued by the anesthesia provider, averages (binned by quarters) of 34.5% to 59.5% of all cases would have been ineligible to use an intraoperative temperature because the interval from the last temperature until anesthesia end was >30 minutes (Table 2).a Even if temperature had been measured until extubation, averages of 5.9% to 20.8% of all cases (binned by quarters) would have been ineligible for temperature measure reporting by the ≤30-minute criterion (Table 2). Figure 1 shows the interval data from UMH from each of the 3 milestones. Corresponding graphs from the other hospitals studied are provided in Supplemental Digital Content, Document, http://links.lww.com/AA/B746.

Figure 1.

Figure 1.

There was heterogeneity among the 4 study hospitals in the end-of-case temperature (ie, maximum temperature ≤30 minutes before the anesthesia end time), ranging from 36.1°C to 36.5°C (Table 3), but each was close to the final core (esophageal) temperature reported by Sun et al (36.3°C).18 The percentages of patients with end-of-case temperatures <35.5°C at UMH, TJUH, JMH, and UCLA were 23.5%, 15.5%, 8.8%, and 16.8%, respectively (Table 3). In practice, for such patients, obtaining a PACU temperature ≥35.5°C up to 15 minutes after the anesthesia end time would be required to meet the temperature quality measure. At UCLA, among cases with both an end-of-case temperature and PACU temperature eligible for quality reporting, only 1.2% (N = 13 quarters; 95% CI, 1.0%–1.4%) of the PACU temperatures were <35.5°C, whereas 16.4% (N = 13; 95% CI, 15.3%–17.5%) of the OR values were below this threshold (P < .0001 by paired Student t test).

In the Appendix, we provide details of an algorithm to generate a PQRS or NQF perioperative temperature report and results from its application using OR and PACU data from UCLA. The Appendix highlights the issues related to missing temperatures and artifacts, presence of intraoperative temperatures from multiple sites, and use of PACU temperatures. The Appendix provides guidance to departments who will need to present a detailed data specification to the reporting group within their hospital’s information systems department.

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DISCUSSION

Our results demonstrate that for 34.5% to 59.5% of cases among the 4 hospitals studied, the end-of-case (ie, intraoperative) temperature could not be used for PQRS #424 or NQF 2681 reporting because the interval between cessation of temperature monitoring in the OR to the anesthesia end time exceeded 30 minutes. Even if temperatures had been recorded until the time of extubation, between 5.9% and 20.8% of cases would have been excluded solely based on timing considerations. Because the mean percentage of cases for which process data were reported under PQRS #193 in 2013 was 93.11%,19 this implies that it would still be necessary to retrieve and match PACU temperatures for many (>30%) anesthesia records. This conclusion is supported by the data from UCLA in the Appendix; by including the PACU temperatures, the percentage of cases meeting the temperature quality measure increased from 46.4% to 84.1%. For hospitals where OR and/or PACU temperatures are still recorded on paper, the temperature quality reporting process will require manual data entry (see limitations).

To compare our temperature results to Sun et al17 and to focus on core temperature measurements, we studied a subset of the cases for which reporting would be eligible under PQRS #424 and NQF 2681 (ie, temperature recorded <30 minutes from anesthesia end time). Many cases (10%–22%) failed to meet the quality threshold of 35.5°C based on the end-of-case temperature.

The example from UCLA in the Appendix highlights the challenges of developing a scalable, automated process for even as “simple” a measurement as the final intraoperative temperature. Information system analysts responsible for generating such reports will need a data specification that indicates, in detail, how to deal with the various data problems noted. These challenges are likely generalizable to all physiologic parameters that are potential sources for automated quality reporting.

The ASA application to the NQF requesting incorporation of PQRS #424 as a quality measurement stated “… it has become possible for an attentive anesthesia provider to maintain normothermia in any patient under general anesthesia, regardless of surgical conditions, and this is now the expected standard of care [emphases added].”20 The data from the 4 academic institutions presented in this manuscript suggest that this is not fully so, even using a threshold of 35.5°C, a relatively hypothermic value. Steelman et al21 found that when active warming was used in the OR, 5.8% patients were hypothermic (defined in this study as temperature <36°C) upon admission to the PACU, as measured using temporal artery thermography. The corresponding incidence of such hypothermia (<36°C) measured in the PACU at UCLA was similar, at 4.6% (N = 13 quarters; 95% CI, 4.3%–4.9%).

There are several limitations to our study. First, all 4 study hospitals were large, academic institutions, with many cases performed by trainees. Thus, some of the time intervals between case milestones and the anesthesia end time might be longer than in nonacademic practice settings, reducing the number of manually retrieved PACU temperatures that would be needed. However, it is not likely that these intervals are considerably longer. At one of the study hospitals (TJUH), it was previously reported that the time from extubation to exiting the OR was ≤15 minutes in 84.6% ± 0.4% (standard error) of cases,22 and that the anesthesia end time occurred within 15 minutes of PACU arrival in 96.9% (99% binomial CI 95.9% to 96.2%).23

Second, there is much greater penetrance of AIMS in academic settings24 than in nonacademic settings.18 Post hoc manual retrieval of temperatures from paper OR and PACU records, or perhaps contemporaneous electronic recording of the arrival PACU temperature in a cloud-based application would be required where temperatures are not captured electronically in the hospital’s electronic health record system. However, manual data entry would likely be subject to the same types of errors and omissions as have been noted for manual data entry in the AIMS.25–27 Regardless, electronic reporting of compliance with PQRS #424 or NQF 2681 would be preferable to manual entry and subsequent compilation of the data.

A third limitation is that the sites of intraoperative temperature monitoring were generally not documented. However, this makes our data more reflective of the real-world application of PQRS #424 and NQF 2681 because these measures do not allow for the exclusion of cases based on the site of measurement. From the perspective of CMS regulation, it is irrelevant how accurately or from what site temperatures are measured. Rather, all that matters are the values and that they were measured within the allowable time frame. For hospitals desiring to report on national perioperative temperature measures, this may result in focused attention on more accurate capture of temperature and/or not prematurely discontinuing measurement in the OR. This may also include the application of noninvasive technologies that better reflect core values, such as those based on thermal flux using cutaneous probes.28 Additional benefits of the use of this technology would be applicability in patients not undergoing general anesthesia, the ability to record temperatures until the time the patient left the OR, and a capability to resume continuous measurement on arrival to the PACU.

A fourth limitation is that we excluded neuraxial cases from study. We did this because we wanted to focus, as much as possible, on core temperature measurement. For most neuraxial cases, temperatures are measured from skin sites. Including these cases would have created a negative bias for the end-of-case intraoperative temperatures, as skin temperature is considerably lower than core temperature. (For patients with an intraoperative temperature below the threshold, checking the arrival PACU temperature would be desirable to determine if the measure passed.) The use of noninvasive core temperature devices (see previous paragraph) would eliminate such bias. There would seldom be delays between the end of surgery and leaving the OR among patients receiving a neuraxial anesthesia, in contrast to patients undergoing general anesthesia with prolonged emergence.29–31 Thus, we would not expect timing issues related to the use intraoperatively of noninvasive core temperature devices during neuraxial anesthesia. Furthermore, because hospitals will need to use PACU temperatures for many patients receiving general anesthesia, the issue is moot as to the percentage of cases in which neuraxial anesthesia is administered.

A fifth limitation is that we excluded children in our primary analyses, as did Sun et al.18 Thus, our quantitative findings may not be applicable to pediatric populations. However, the national quality measures do not exclude patients based on age. We address this in the Appendix, where such exclusions were not made.

A sixth limitation of our study’s relevance is that it relates only to the specifications of PQRS #424 and NQF 2681 as they are written and would be used in practice, not to the science of temperature monitoring and intraoperative thermoregulation. First, when temperature was measured continuously, the presence (versus absence) of active warming decreased morbidity (ie, the demonstrations of improved outcomes were not based on the end-of-case temperatures, but rather on the group assignment to the use or disuse of active warming).1–5 The previous temperature management standard, PQRS #193, was the corresponding process measure that matched well to these randomized trials. Second, when temperature is measured continuously, the risk of mortality when there is an episode of malignant hyperthermia is reduced.32 There is appropriate cost utility of continuous temperature measurement throughout the anesthetic based solely on this rare disease.33 Consequently, our results should not be extrapolated to suggest weakness in quality measures based on the appropriate use of active patient warming and/or the continuous measurement of temperature. The problems we address relate to the written specifications of PQRS #424 and NQF 2681 as a measure of quality. Third, the specifications rely on a fixed threshold temperature, ≥35.5°C. Even though virtually all of the 58,814 noncardiac surgery patients in Sun et al were warmed with forced air after induction, core (esophageal) temperatures were <35.5°C in 30%, 20%,15%, and 10% of patients at 1, 2, 3, and 4 hours, respectively.18 It would not be logical to conclude that the quality of anesthesia care improved with increasing case duration; rather, it took time to rewarm patients after the redistribution of heat from the core to the periphery with induction of anesthesia. In the same study, Sun et al showed that the incidence of end of surgery hypothermia (<35.5°C) varied among procedures (eg, 0.9% [1/109] in operations on the ear versus 17.8% [8/45] in operations on the respiratory system).18 It would not be logical to conclude that the quality of anesthesia care was better among patients undergoing ear surgery. Fourth, and finally, the PQRS #424 and NQF 2681 specifications include all patients, but the studies in which benefits of active warming were demonstrated were in surgical populations at high risk for an adverse event.1,2,5 The 2015 Cochrane systematic review of randomized trials in broad populations found no evidence of benefit with active intraoperative warming with regard to perioperative mortality (2 trials; risk ratio = 1.01; 95% CI, 0.26–4.00).34 On the basis of data from 18 trials, the systematic review also concluded that forced air warming decreased mean intraoperative blood loss by only 51 mL (95% CI, 13–88 mL) with no significant decrease in the number of patients being transfused (8 trials; risk ratio = 0.79; 95% CI, 0.50–1.23).28

Figure 2.

Figure 2.

In summary, we found that successful reporting for the perioperative temperature quality measures PQRS #424 or NQF 2681 will likely depend on the ability to capture PACU temperatures. For the many hospitals where PACU care is documented on paper, substantive manual effort will be required. A substantial rate of failure to meet the threshold temperature of 35.5°C should be anticipated if using intraoperative values alone, obtained with measurement technologies currently in widespread use and current patterns of discontinuation of temperature monitoring (ie, before the end of surgery or at extubation). Hospitals considering reporting on perioperative temperature maintenance measures to satisfy anesthesia quality standards should consider the findings in this article when establishing their temperature quality program. For high compliance reporting with minimal additional effort on the part of clinicians, automated methods of data capture and use of highly accurate temperature measurement technologies (ie, reflective of core temperature) that can be applied noninvasively (ie, applicable for all patients) and used continuously during the entire perioperative period likely will be useful.

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Appendix. Algorithm to Process Intraoperative Temperatures for Quality Reporting at UCLA

Algorithm Details (see Figure 2)

  1. Select cases qualifying for temperature reporting
    1. Exclude cases with interval from Enter OR to Leave OR <60 minutes
    2. Exclude cases neither GA nor neuraxial anesthesia
      1. ) UCLA: PACU handoff note contains the anesthesia type of general or neuraxial
      2. ) Hospitals where the anesthesia type is not reliably noted could exclude cases not GA or neuraxial as:
        1. Not intubated and no tracheal tube and no supraglottic airway device noted
        2. No volatile agent >0.5 minimum alveolar concentration (MAC)
        3. No note in the anesthesia record indicating either spinal or epidural
  2. Extract temperature data with patient location (OR or PACU), timestamp and site of measurement within 30 minutes before and 15 minutes after the anesthesia end time
    1. Remove temperatures >40°C as likely artifacts
    2. If temperatures recorded from multiple sites, order them by preference for use (eg, esophageal before skin temperature)
    3. Use the temperature from the 1° source if present, then 2° source if absent, etc, else null if no temperature for the minute
    4. If no temperatures are present for a case, set the temperature = null
  3. Determine the maximum intraoperative temperature for each case
    1. End-of-case temperature
  4. Determine if the end-of-case OR temperature is ≥35.5°C
    1. If yes, measure passes
  5. Determine the maximum PACU temperature
  6. Is the maximum PACU temperature ≥35.5°C
    1. If yes, measure passes
    2. If no, measure fails

Compliance rate = # cases passing/ (# cases passing + # cases failing)

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Summary

Among all cases requiring PQRS temperature:

  • 46.4% would pass using the end-of-case OR temperature alone
  • 84.1% would pass using the maximum temperature from 30 minutes before to 15 minutes after the anesthesia end time
  • 15.9% of cases would fail the temperature measure
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DISCLOSURES

Name: Richard H. Epstein, MD.

Contribution: This author helped design the study, conduct the study, analyze the data, and write the manuscript.

Name: Franklin Dexter, MD, PhD.

Contribution: This author helped design the study, conduct the study, analyze the data, and write the manuscript.

Name: Ira S. Hofer, MD.

Contribution: This author helped design the study, conduct the study, analyze the data, and write the manuscript.

Name: Luis I. Rodriguez, MD.

Contribution: This author helped conduct the study and write the manuscript.

Name: Eric S. Schwenk, MD.

Contribution: This author helped conduct the study and write the manuscript.

Name: Joni M. Maga, MD.

Contribution: This author helped conduct the study and write the manuscript.

Name: Bradley J. Hindman, MD.

Contribution: This author helped write the manuscript.

This manuscript was handled by: Richard C. Prielipp, MD.

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FOOTNOTE

aThere were no statistically significant downward trends in the percentage of cases excluded due to this timing consideration over the last 8 quarters of data at the 3 hospitals where data were available for 2016 (Table 1). This might have occurred in anticipation of the change to outcomes reporting under PQRS #424 in 2016, although there were no related communications to providers at any of the hospitals asking them to change their behavior related to the 30-minute timing window before the anesthesia end time (see Methods).

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REFERENCES

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