The postanesthesia care unit (PACU) is a pivotal and busy component of the modern surgical care system. The PACU has multiple missions, not only caring for patients with a myriad of primary disease states with variable acuity but also addressing multiple comorbidities. Specifically, these PACU missions may include caring for: patients recovering from anesthesia who originate from an adjacent operating room suite; patients anesthetized in remote locations for interventional radiology, cardiology, and gastroenterology procedures; and those needing extended postoperative care for whom intermediate care beds are not available.1–3 Therefore, it is not surprising that the PACU is frequently the bottleneck of the surgical care system.4 Moreover, it is unrivalled by any other inpatient unit when examined from the viewpoint of patient throughput and diversity of pathologies. Therefore, the dearth of research performed on the clinical and operational aspects of this ubiquitous and essential unit is surprising. This contrasts with the many detailed studies that have enhanced our understanding of the activities in the operating room and intensive care unit. The lack of ready understanding of the PACU has rendered it the “black box” of the surgical care system.
The introduction into the PACU of computerized patient data management systems capable of automatically capturing physiological variables (a natural evolution of anesthesia information management systems) promises to provide a wealth of new information.4,5 Epstein and colleagues6 nicely demonstrated the usefulness of computerized PACU systems by using data from such a system to analyze the temporal distribution of hypoxemic episodes. Moreover, this study portends similar studies analyzing large data sets, which should help elucidate the mysteries of the PACU. However, it is important to recognize that the function of retrospective mining of large databases is to provide direction and hypothesis generation for more focused prospective studies that can lead to improvements in patient care,7 rather than drawing direct conclusions of the usefulness of a proposed (hypothetical) change. Among the limitations of database mining is its ability to detect only associations and not causality.8
Epstein and colleagues reported that hypoxemic episodes, which are often used as a proxy for respiratory compromise, are a high-frequency event in the PACU and commonly occur in the absence of advanced respiratory care providers. Furthermore, despite the efforts of available nursing staff, timely resolution of desaturation events outside of the operating room is challenging and protracted, potentially placing patients at increased risk. However, one must put these findings in perspective because the reliability of pulse oximetry as an indicator of respiratory compromise has often been questioned, with varying rates of false-negative and false-positive results reported.9–12 Most notably, it has been difficult to establish a generally accepted “low saturation” cutoff, or the temporal duration over which a desaturation event becomes “dangerous,”10 especially because the various concentrations of supplemental oxygen administered in the PACU often make it hard to interpret oxygenation data.12 Therefore, studies are needed that track long-term patient outcomes and examine how these outcomes correlate with the length and severity of desaturation events so that insightful conclusions can be drawn regarding the potential impacts of particular desaturation events.
Even if we accept that low oxygen saturation for extended periods of time is detrimental to patient health (speaking in general terms and without specific cutoff values in mind), it is better to identify impending respiratory compromise before desaturation sets in, rather than trying to resolve it after it has occurred. Basic physiology teaches us that hypoxemic episodes are a late response to hypoventilation:13 a decrease in ventilation is followed by an increase in arterial co2 (PaCO2) and finally a decrease in SpO2, which is delayed further in the presence of supplemental oxygen. Over the years, there have been numerous attempts at monitoring end-tidal CO2 as a proxy for PaCO2, with limited success.14–17 An earlier indicator of respiratory compromise than pulse oximetry, end-tidal CO2, has proven difficult to measure in spontaneously breathing nonintubated patients, and as a result, has not come into general use in the PACU.18,19
A potential physiologic solution for assessing respiratory status is to directly monitor ventilation. Real-time ventilation monitoring has been a fundamental part of anesthesia care since the early 20th century, but only for intubated patients. Recently, continuous noninvasive respiratory volume monitoring that provides measurements of minute ventilation, tidal volume, and respiratory rate in nonintubated patients has become available.20–22 These measurements should provide a more timely identification of respiratory compromise and also provide staff with a real-time indicator of the effects of opioid dosing, airway maneuvers, continuous positive airway pressure/bilevel positive airway pressure, or other therapeutic interventions. Early identification of respiratory compromise using real-time respiratory volume monitoring has the potential to provide a longer window for skilled anesthesia providers to arrive, evaluate, and treat PACU patients, thus improving patient safety. Moreover, real-time respiratory volume monitoring data may help clinicians develop individualized opioid treatment regimens, identify patients at risk in the PACU, and take necessary precautions to prevent desaturation events, rather than reacting to their occurrence. Identifying at-risk patients and individualizing treatment plans might reduce the incidence of respiratory compromise in the PACU and allow for better patient management using currently available resources rather than drawing additional resources to resolve respiratory compromise after it has occurred.
The purpose and operational realities of the PACU are institution specific. Some may take the path of additional monitoring, and others may identify the need for additional clinical staff. Regardless, future studies utilizing information from large computerized databases are needed. Ideally, they should be multi-institutional, with population sizes from each institution large enough to allow for interinstitutional comparisons. The paper by Epstein et al.6 includes an initial effort at interinstitutional studies by including data from a second institution that confirm the major findings of the paper. Moreover, to facilitate data analysis, it is preferable to avoid using free-text and instead use “structured responses.” For example, in the study by Epstein et al.,6 the investigators analyzed free-text, an arduous task that does not always provide the needed information. Because hypoxemic episodes are not uncommon, and in some cases, resolving them may require narcotic reversal or reintubation, it would have been advantageous to have imbedded screens containing objective questions into the computerized system to gather data on these occurrences. Such data are also important for quality improvement purposes. The study by Epstein et al.6 not only provides valuable clinical and administrative information about the PACU, it also demonstrates the advantages and limitations of mining large databases. Such studies will be useful to validate both new technologies and alternative staffing models in the future. As PACU information systems become more prevalent, they should provide further insights into the clinical and other aspects of PACU care.
Name: Charles Weissman, MD.
Contribution: This author helped write the manuscript.
Attestation: Charles Weissman approved the final manuscript.
Conflicts of Interest: This author has no conflicts of interest to declare.
Name: Jenny Freeman, MD.
Contribution: This author helped write the manuscript.
Attestation: Jenny Freeman approved the final manuscript.
Conflicts of Interest: Jenny Freeman worked for Respiratory Motion, Inc. and has equity interest in Respiratory Motion, Inc.
This manuscript was handled by: Sorin J. Brull, MD, FCARCSI (Hon).
1. Odom-Forren J. ICU overflow in the PACU. J Perianesth Nurs. 2014;29:81–2
2. Reed H. The development of an extended care facility in the recovery unit: the post-anaesthesia care unit. J Perioper Pract. 2011;21:210–4
3. Lalani SB, Ali F, Kanji Z. Prolonged-stay patients in the PACU: a review of the literature. J Perianesth Nurs. 2013;28:151–5
4. Jenkins J. Eliminating common PACU delays. J Healthc Inf Manag. 2007;21:53–8
5. Jensen PB, Jensen LJ, Brunak S. Mining electronic health records: towards better research applications and clinical care. Nat Rev Genet. 2012;13:395–405
6. Epstein RH, Dexter F, Lopez MG, Ehrenfeld JM. Anesthesiologist staffing considerations consequent to the temporal distribution of hypoxemic episodes in the postanesthesia care unit. Anesth Analg. 2014;119:1322–33
7. Sessler DI. Big Data – and its contributions to peri-operative medicine. Anaesthesia. 2014;69:100–5
8. Genta RM, Sonnenberg A. Big data in gastroenterology research. Nat Rev Gastroenterol Hepatol. 2014;11:386–90
9. Downs JB. Prevention of hypoxemia: the simple, logical, but incorrect solution. J Clin Anesth. 1994;6:180–1
10. Downs JB. Has oxygen administration delayed appropriate respiratory care? Fallacies regarding oxygen therapy. Respir Care. 2003;48:611–20
11. Jurban A. Pulse oximetry. Crit Care. 1999;3:R11–7
12. Fu ES, Downs JB, Schweiger JW, Miguel RV, Smith RA. Supplemental oxygen impairs detection of hypoventilation by pulse oximetry. Chest. 2004;126:1552–8
13. Lynn LA, Curry JP. Patterns of unexpected in-hospital deaths: a root cause analysis. Patient Saf Surg. 2011;5:3
14. Liu SY, Lee TS, Bongard F. Accuracy of capnography in nonintubated surgical patients. Chest. 1992;102:1512–5
15. Cheifetz IM, MacIntyre NR. Respiratory controversies in the critical care setting. Respir Care. 2007;52:636–44
16. Good ML Capnography: Uses, Interpretation, and Pitfalls. 1990 Philadelphia, PA Amer Soc Anesthesiologists, JB Lippincott Co:1–23
17. Kaneko Y. Clinical perspectives on capnography during sedation and general anesthesia in dentistry. Anesth Prog. 1995;42:126–30
18. Fakuda K, Ichimohe T, Kaneko Y. Is measurement of end-tidal CO2
through nasal cannula reliable? Anesth Prog. 1997;44:23–26
19. Ramsay MA, Usman M, Lagow E, Mendoza M, Untalan E, De Vol E. The accuracy, precision and reliability of measuring ventilatory rate and detecting ventilatory pause by rainbow acoustic monitoring and capnometry. Anesth Analg. 2013;117:69–75
20. Voscopoulos C, Brayanov J, Ladd D, Lalli M, Panasyuk A, Freeman J. Evaluation of a novel non-invasive respiration monitor providing continuous measurement of minute ventilation in ambulatory subjects in a variety of clinical scenarios. Anesth Analg. 2013;117:91–100
21. Voscopoulos C, Ladd D, Brayanov J, George E. Non-invasive respiratory volume monitoring to develop a risk algorithm for the safe use of opioids. Crit Care Med. 2013;41:A16
22. Voscopoulos C, MacNabb CM, Freeman J, Galvagno SM, Ladd D, George E. Continuous non-invasive respiratory volume monitoring for the identification of patients at risk for opioid induced respiratory depression and obstructive breathing patterns. J Trauma Acute Surg. 2014;77:S208–15