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    Mary Frances Mullins DNP CRNA graduated in June 2016 from Grand Canyon University with her Doctor of Nursing Practice (DNP) degree. In 2001, she graduated from the Uniformed Services University in Bethesda with an MSN in nurse anesthesia. She also holds CPAN and CAPA certification and currently works at Memorial Medical Center in Modesto, CA

    Preoperative Screening for Obstructive Sleep Apnea: Enhancing Perioperative Safety

    Abstract
    Nearly 25 million people in the United States suffer from obstructive sleep apnea (OSA). This serious under-recognized, under-diagnosed medical disorder is associated with significant comorbidities as well as increased perioperative risks. Therefore, preoperative screening for OSA using a validated OSA screening tool such as the STOP-Bang OSA screening questionnaire is imperative. Using a quantitative methodology with a comparative design, this author observed for statistically significant differences in the proportion of postoperative hypoxemia between two sample groups. Group A (n=100) was comprised of adult (ages 18-75) general anesthesia elective surgery patients who were screened preoperatively for OSA on the STOP-Bang OSA screening instrument. Group B (n=100) was comprised of adult (ages 18-75) general anesthesia elective surgery patients who were not screened preoperatively for OSA on the STOP-Bang OSA screening instrument. A Chi-square analysis was conducted comparing the proportion of positive postoperative hypoxemia occurrences in the Post Anesthesia Care Unit (PACU). The proportion of patients who experienced hypoxemia in the PACU pre implementation of the STOP-Bang screening program was not equal to the proportion of patients who experienced hypoxemia in the PACU post implementation of the program, χ2 (1, N = 94) = 2.085, p = .149. This was statistically nonsignificant, but clinically relevant. Clinician awareness of the potential existence of OSA can guide the perioperative care plan to safely meet the special needs of surgical patients with OSA.


    Table of Contents
    List of Tables. ix
    List of Figures. x
    Chapter 1: Introduction to the Project 1
    Background of the Project 2
    Problem Statement 4
    Purpose of the Project 5
    Clinical Question. 6
    Advancing Scientific Knowledge. 6
    Significance of the Project 7
    Rationale for Methodology. 9
    Nature of the Project Design. 9
    Definition of Terms. 10
    Assumptions, Limitations, and Delimitations. 13
    Summary and Organization of the Remainder of the Project 15
    Chapter 2: Literature Review.. 18
    Background. 20
    Conceptual Framework for Implementing Preoperative STOP-Bang OSA Screening: The Iowa Model 22
    Literature Review.. 25
    Obstructive Sleep Apnea: Pathogenesis and Comorbidities. 25
    Obstructive Sleep Apnea: Cardinal Features. 27
    Treatment of Obstructive Sleep Apnea. 27
    Obstructive Sleep Apnea: Preoperative Diagnosis. 30
    Obstructive Sleep Apnea Associated Perioperative Complications. 36
    Perioperative Management of Patients with Obstructive Sleep Apnea. 45
    Healthcare Professional Attitudes on Perioperative Care of Patients with OSA.. 46
    Summary. 47
    Chapter 3: Methodology. 51
    Project Methodology. 52
    Project Design. 53
    Population and Sample Selection. 55
    Instrumentation. 55
    Validity. 57
    Reliability. 58
    Data Collection Procedures. 59
    Data Analysis Procedures. 60
    Ethical Considerations. 61
    Limitations. 62
    Summary. 63
    Chapter 4: Data Analysis and Results. 66
    Descriptive Data. 67
    Data Analysis Procedures. 70
    Results. 70
    Summary. 77
    Chapter 5: Summary, Conclusions, and Recommendations. 79
    Summary of the Project 81
    Summary of Findings and Conclusions. 82
    Practical, Future, and Theoretical Implications. 85
    Recommendations for Future Projects. 86
    Recommendations for Future Practice. 87
    Conclusion. 88
    References. 90
    Appendix A.. 107
    Appendix B.. 108
    Appendix C.. 109
    Appendix D.. 111
    Appendix E. 112



    List of Tables

    Table 1. Descriptive Statistics of Demographic Variables.................................................. 70
    Table 2. Pearson Chi-Square Goodness of Fit Between Implementation of the STOP-Bang Screening Program and Proportion of Patients who Experience Hypoxemia in the PACU................ 73

    List of Figures

    Figure 1. STOP-Bang Questionnaire Total Score Occurrence Frequency ........................ 75
    Figure 2. STOP-Bang Obstructive Sleep Apnea Level of Risk Percent ............................ 76
    Figure 3. Hypoxemia Frequency Occurrence .................................................. .................. 77



    Chapter 1: Introduction to the Project

    Obstructive sleep apnea (OSA) is a prevalent sleep-associated breathing disorder characterized by intermittent, repetitive, partial or complete obstruction of the upper airway which last more than ten seconds (The Joint Commission, 2015). The Joint Commission notes that many surgical patients suffer from undiagnosed OSA, a condition associated with increased risk of complication during the perioperative period. Patients presenting to surgical services with OSA are at increased for perioperative morbidity, postoperative complications, difficult airway management, longer hospital length of stay, and a higher incidence of admission to the Intensive Care Unit (ICU) (Chung, Yuan, and Chung, 2008).

    Preoperative screening for OSA is an important measure to help increase clinician recognition of patients potentially at risk for this serious disorder (Diffee, Beach, and Cuellar, 2012). This authorís Direct Practice Improvement (DPI) project encompassed the implementation of a preoperative OSA screening program in a community hospital with a 427-bed capacity. Screening for OSA was accomplished with the STOP-Bang OSA screening questionnaire (Appendix A). This quality improvement project was selected because of its potential to promote patient safety and well-being in the perioperative period.

    This chapter will provide an introduction to the DPI project. Several aspects of the project will be outlined herein. These include the background of the project; problem statement; project purpose; clinical question; advancement of scientific knowledge; project significance; rationale for methodology; nature of project design; term definitions; assumptions, limitations, and delimitations; and organization and summary of the rest of the project.

    Background of the Project

    Obstructive sleep apnea (OSA) is a widespread disorder (Franklin and Lindberg, 2015). According to the American Academy of Dental Sleep Medicine (2016), nearly 25 million people in the United States suffer from OSA. However, it is estimated that up to 80% of people who have OSA have not been definitively diagnosed (American Sleep Apnea Association, 2015).

    Patients with OSA are at increased risk for problematic perioperative airway management, including difficult mask ventilation and difficult endotracheal intubation (Auckley and Bolden, 2012; Porhomayon, El-Solh, Chhangani, and Nader, 2011). Individuals with OSA frequently have upper airway anatomical anomalies that predispose them to difficult airway management (Mador, et al., 2013). It has been well-documented that patients with OSA are exceptionally sensitive to anesthetic agents, sedatives, and opioids which predisposes to upper airway collapse (Fouladpour, Jesudoss, Bolden, Shaman, and Auckley, 2016; Gross et al., 2014).

    Modifications to the perioperative care plan for patients with known, or suspected, OSA can enhance the safety of this vulnerable population (Vasu, Grewal, and Doghramji, 2012). One desirable measure is for the anesthesia provider to use volatile anesthetic gases that are rapidly eliminated, such as sevoflurane and desflurane (Minokadeh, Bishop, and Benumof, 2011), as well as exceedingly short-acting opioids such as remifentanil (Auckley and Bolden, 2012). A multimodal approach for general anesthesia maintenance and intraoperative analgesia may significantly reduce the OSA patientís postoperative narcotic requirement (Auckley and Bolden). Nonsteroidal anti-inflammatory medications, alpha-2 agonists, ketamine, acetaminophen, and regional anesthetic techniques may be useful for this purpose (Auckley and Bolden).

    Full reversal of the OSA patientsí neuromuscular blockade should be verified at the end of the surgical procedure (Chung, 2010). It should be definitively ascertained that the patient with OSA meets all extubation criteria prior to removal of the endotracheal tube (Chung). Chung emphasizes the importance of ensuring that the OSA patient is fully conscious and cooperative prior to extubation.
    For patients with OSA, postoperative narcotic and sedative medications should be carefully titrated and their use should be minimized (Vasu et al., 2012). When feasible, non-narcotic analgesics such as ketorolac should be administered to patients with OSA during the early recovery period (Minokadeh et al., 2011). It is imperative that patients who are at increased risk for OSA based on STOP-Bang screening results are monitored closely in the Post Anesthesia Care Unit (PACU) for hypoxemia and other complications (Vasu et al.).

    In the PACU, patient positioning to allow for maximal alveolar expansion and increased functional residual capacity (FRC) should be considered; therefore, the non-supine position should be encouraged whenever possible (Vasu et al., 2012). The use of Continuous Positive Airway Pressure (CPAP) during the recovery period may be useful to prevent upper airway obstruction (Gross et al., 2014). During the postoperative period, CPAP has been repeatedly shown to treat OSA effectively, thus preventing airway compromise (Liao et al., 2013).

    Problem Statement

    The focus of this authorís DPI quality improvement project was on the importance of implementing a preoperative OSA screening protocol at a 427-bed community medical center. When clinicians are aware of the potential for OSA, the perioperative care plan can be modified accordingly. Therefore, the intention of implementing the OSA screening protocol was to promote perioperative safety. For this project, the population affected was comprised of adult patients (ages 18-75) who had elective surgery under general anesthesia.

    The problem statement for this project was: It is unknown whether adult (ages 18-75) general anesthesia elective surgery patients who undergo preoperative screening for OSA on the STOP-Bang questionnaire (at a 427-bed community medical center) during the one-month period following implementation of an OSA screening protocol will experience postoperative hypoxemia less frequently than adult (ages 18-75) general anesthesia elective surgery patients who do not undergo preoperative screening for OSA on the STOP-Bang questionnaire during the one-month period prior to implementation of the OSA screening protocol. To answer this question, a prospective chart audit of 100 patient records in the Electronic Health Record (EHR) of patients who were screened for OSA, and a retrospective chart audit of 100 patient records in the EHR of patients who were not screened for OSA, was conducted by this author to determine if postoperative hypoxemia would occur significantly more frequently in one group over the other. The most common complication encountered by patients who have OSA is hypoxemia (Pereira, Xara, Mendonca, Santos, and Abelha, 2013).

    Purpose of the Project

    The purpose of this project was to introduce a preoperative OSA screening protocol to the community hospital where this author is employed. As previously described, the program was initially executed on a trial basis. It was the intention of this author to collect evidence to support permanent adoption of the OSA screening program to optimize the perioperative safety of patients with occult OSA.
    Subramanyam and Chung (2010) note the importance of preoperatively identifying patients at high risk for OSA based on STOP-Bang OSA screening questionnaire results. Clinician recognition of patients who potentially have OSA may help to optimize the OSA patientsí preoperative status and to define the goals for perioperative management (Subramanyam and Chung). This project yielded results similar to the results found by Subramanyam and Chung, consequently contributing to the field of perioperative medicine and nursing.

    This project employed a quantitative methodology. The quantitative methodology aligned with the projectís combined prospective/retrospective comparative design. The sample population was comprised of 200 adult (ages 18-75) general anesthesia elective surgery patients, 100 of whom underwent preoperative screening for OSA with the STOP-Bang questionnaire, and 100 of whom did not undergo preoperative screening for OSA with the STOP-Bang questionnaire. The geographical location for the project was a community hospital with 427 beds, located in the Central Valley of California, where 10,000 surgeries are performed annually.

    For this project, the independent variable was STOP-Bang OSA screening. The dependent variable was postoperative hypoxemia in the PACU. During the one-month period following implementation of the OSA screening protocol, 100 EHRs from each group were analyzed by this author. The incidence of postoperative hypoxemia that occurred in each group was compared. As postulated by this author, the incidence of postoperative hypoxemia in the PACU was higher in the group who did not undergo preoperative OSA screening.

    Clinical Question

    The following was the clinical PICOT question for this project: During the one-month period following initiation of a STOP-Bang OSA screening protocol, will adult (ages 18-75) general anesthesia elective surgery patients who undergo preoperative OSA screening on the STOP-Bang questionnaire, compared to adult (ages 18-75) general anesthesia elective surgery patients who do not undergo preoperative OSA screening on the STOP-Bang questionnaire during the one-month period prior to initiation of a STOP-Bang OSA screening protocol, experience postoperative hypoxemia (defined by Liu et al. (2010) as a hemoglobin oxygen saturation ≤ 95% on pulse oximetry monitoring) less frequently in the PACU? The independent variable was STOP-Bang OSA screening. The dependent variable was postoperative hypoxemia in the PACU.

    Advancing Scientific Knowledge

    There is a plethora of literature that substantiates the importance of preoperative recognition of OSA by clinicians (STOP-Bang.ca, 2016). Kornegay and Brame (2015) note that the long-term adverse effects of OSA on health outcomes have been well-documented. However, most of the research on the perioperative risks related to OSA has been conducted during the last twenty years (Memtsoudis, Besculides, and Mazumdar, 2013). It is well-known that the process of translating research into evidence-based clinical practice can take as long as twenty years (Agency for Healthcare Research and Quality, 2001). It was anticipated that this authorís DPI project would narrow the chasm between research and clinical practice.

    The Joint Commissionís Division of Healthcare Improvement cites the following safety concerns regarding OSA: lack of training for healthcare professionals to screen for and recognize OSA, and failure to assess patients for OSA (The Joint Commission, 2015). Therefore a central aim of this DPI project was to heighten clinician awareness of the significance of OSA in the perioperative period with the purpose of promoting patient safety. The Iowa Model for Evidence-Based Practice to Promote Quality Care was the conceptual framework for this DPI project. Permission to use the Iowa Model was obtained from the owner of that intellectual property (Appendix B). The Iowa Model provides the structure to guide nurses in the implementation of evidence-based clinical practice changes (White and Spruce, 2015).

    Since the beginning of the DNP program, this author investigated comprehensive research on OSA to validate the importance of implementation of this DPI project. Critically-appraised literature on the topic was disseminated to stakeholders during the last 18 months. Stakeholders, including administrators, managers, and anesthesia providers expressed enthusiasm regarding the project and its worth.

    Significance of the Project

    This DPI project had significant merit because it underscored the importance of preoperative screening for OSA. Knowledge of the surgical patientís high index of suspicion for OSA is important to surgeons, anesthesia providers, and perioperative nurses. Heightened clinician awareness of the potential for OSA based on the STOP-Bang score allows for apposite perioperative care plan modifications designed to enhance patient safety.

    Hypoxemia is the most common perioperative complication in patients who have OSA (Pereira et al., 2013). Hypoxemia and other perioperative complications may be attenuated, or avoided, when the perioperative care plan is tailored to the meet the special needs of the patient with OSA. Some of these potential perioperative care plan modifications for patients with known or suspected OSA have been identified in this chapter. This will be expounded upon in subsequent chapters.

    Auckley, Cox, Bolden, and Thornton (2015) recently conducted a survey to assess the attitudes of physicians in various specialties regarding OSA; a total of 783 surveys were completed and returned. The preponderance of surveyed participants said that they consider OSA to be an independent risk factor for morbidity and mortality in the perioperative period (Auckley et al.). Auckley et al. also found that the majority of respondents had personally experienced an adverse outcome related to OSA. The results of this study provided additional support for this authorís DPI project.

    Another noteworthy reason for conducting this DPI project was that patients who were identified at high risk for OSA, based on the STOP-Bang questionnaire score, were consequently referred for a polysomnography study to determine if a definitive diagnosis of OSA existed. If a definitive diagnosis of OSA was determined by the sleep study, subsequent treatment with CPAP may attenuate or prevent the long-term negative effects of OSA on health outcomes (Yang, Huang, Lan, Wu, and Huang, 2015). Therefore, this referral process had, and continues to have the potential to considerably improve health outcomes of patients with OSA and is a potential indirect outcome of this proposed DPI project.

    Rationale for Methodology

    A quantitative methodology with a comparative design was selected for this DPI project. This author sought to obtain numerical data for the proportion of patients who experienced postoperative hypoxemia in the PACU in the group of patients who were screened preoperatively for OSA compared to the group of patients who were not screened preoperatively for OSA. Numerical data is most appropriately analyzed through quantitative methods.

    A quantitative methodological approach was selected for this DPI project over a mixed or qualitative methodology. A quantitative methodology is concerned with objectivity (Nieswiadomy, 2012). A qualitative methodology is concerned with the subjective meaning of experiences to individuals (Nieswiadomy); therefore, a qualitative approach was not selected for this project. The rationale for not selecting a mixed methodology approach was due to the limited time allotted for project completion.

    A quantitative methodology is inherently objective. Ingham-Broomfield (2014) notes that quantitative research falls underneath the umbrella of the concept of positivism. The theory of positivism originated from the perspective that knowledge is a derivative of the positive information of discernable experience, and the best way of attaining it is through methods of inquiry that are scientific (Changing Minds, 2016).

    Nature of the Project Design

    The design for this project was one that was a combined prospective/retrospective comparative, in alignment with the projectís quantitative methodological approach. This design was selected over other designs because it is the best design to answer the clinical question. As strongly recommended by Zaccagnini and White (2014), the authors of the designated textbook for the Grand Canyon University Doctor of Nursing Practice (DNP) program, this DNP student consulted with a statistician prior to deciding on the best design for this particular DPI project.

    A comparative design study observes the variations among intact groups on a particular variable of interest (Nieswiadomy, 2012). The dependent variable for this project was postoperative hypoxemia in the PACU. In a comparative design, it is not possible to manipulate the independent variable (Nieswiadomy). The independent variable for this project was STOP-Bang OSA screening.

    During the one-month period following the implementation of the STOP-Bang OSA screening project, this author conducted a combined prospective/retrospective EHR audit. The prospective audit was of 100 EHRs of postoperative patients who were screened for OSA preoperatively on the STOP-Bang questionnaire and the retrospective audit was of 100 EHRs of postoperative patients who were not screened for OSA preoperatively on the STOP-Bang questionnaire. The charts were selected by a consecutive sampling technique. In a consecutive sampling technique all subjects who meet inclusion criteria are selected until the required sample size is achieved (Lundsford and Lundsford, 1995). A comparison of the incidence of postoperative hypoxemia in the PACU was made between the two groups.

    Definition of Terms

    The following section of this paper will define the medical terms, variables, and jargon that have been discussed throughout this chapter. The terms will be defined according to the context in which they apply to the proposed DPI project. For clarity, lay terminology is used.

    Alveolar. Alveolar pertains to alveolus. These are the small compartments in the lungs which contain air. The lungís breathing tubes terminate at the level of the alveolus. Here oxygen is added to the bloodstream and carbon dioxide is removed (air exchange) (Merriam-Webster, 2016).

    Apnea. Apnea is the cessation of breathing (Merriam-Webster Dictionary, 2016).

    Apnea-Hypopnea Index (AHI). The apnea-hypopnea index (AHI) is the number of times per hour a person stops breathing completely or has a diminished inflow of air (shallow breathing) for ≥ ten seconds per episode as measured by a polysomnography study (Medical Dictionary by Farlex, 2016).

    Continuous Positive Airway Pressure (CPAP). Continuous Positive Airway Pressure (CPAP) is air pressure provided by a machine and delivered by a face mask to maintain upper airway patency. The degree of air pressure delivered upon inhalation is the same as the degree of air pressure that is delivered upon expiration (Mayo Clinic, 2016).

    Functional Residual Capacity (FRC). The functional residual capacity refers to the volume of air remaining in the lungs after a normal exhalation (Chandra, Kuppu, and Malathi, 2013).

    Hypopnea. Hypopnea is an abnormal decrease in rate and depth of breathing (Medical Dictionary by Farlex, 2016).

    Hypoxemia. Hypoxemia, for the purposes of this project, is defined as any drop in the oxygen saturation of hemoglobin to ≤ 95% as measured by pulse oximetry (Liu et al., 2010). The dependent variable for this project is postoperative hypoxemia in the PACU.

    Obstructive Sleep Apnea. Obstructive sleep apnea (OSA) is a sleep disorder characterized by recurring intermittent cessation of breathing lasting ≥ ten seconds during sleep (Seet, Han, and Chung, 2013). It is defined by an apnea-hypopnea index (AHI) ≥ five (Chung, Liao, Yegneswaran, Shapiro, and Kang, 2014). Patients with this disease experience an exaggerated depression of throat muscle tone during sleep leading to partial or complete loss of upper airway patency (Isono, 2009). The severity of OSA is measured by the AHI: An AHI of 5-14 indicates mild sleep apnea; an AHI of 15-29 indicates moderate sleep apnea; and an AHI of ≥ 30 indicates severe OSA (American Academy of Sleep Medicine, 2016).

    Polysomnography. Polysomnography is a sleep study that is conducted overnight in the home or during an overnight stay in a sleep laboratory. It is a test conducted to diagnose sleep disorders, including OSA. During a polysomnography sleep study, the patientsí blood oxygen level, brain waves, heart rate, breathing rate, and eye and leg movements are measured and recorded (Mayo Clinic, 2016).

    Pulse Oximetry. Pulse oximetry is a test that is used to measure the level of oxygen (oxygen saturation) in the bloodstream. A clip (probe) is placed on a part of the body such as a finger, toe, or ear lobe. The probe uses light to measure the blood oxygen level (Johns Hopkins Medicine Health, 2016).

    STOP-Bang Questionnaire. The STOP-Bang questionnaire (Appendix A) is a tool that is used to screen for undiagnosed OSA (Chung, Yang, and Liao, 2013). It was developed in 2008 by Dr. Frances Chung and her team in Toronto, Canada (STOP-Bang.ca, 2016). The questionnaire is comprised of eight questions which can be answered yes or no. The Acronym STOP-Bang stands for Snoring (loudly), Tiredness (during waking hours), Observed (observed apnea during sleep), Pressure (hypertension), Body mass index (≥ 35 kg/m2), Age (≥ 50-years-old), Neck circumference (≥ 16 inches for women and ≥ 17 inches for men, measured at the Adamís apple), and Gender (male) (Seet, Chua, and Liaw, 2015). A STOP-Bang score between zero to two means that the patient has a low index of suspicion for having occult OSA; a STOP-Bang score between three to four means that the patient has an intermediate index of suspicion for having occult OSA; and a score between five to eight means that the patient has a high index of suspicion for having occult OSA (STOP-Bang.ca, 2016). Permission to use the STOP-Bang questionnaire was granted by the intellectual property owners (Appendix C).
    The Independent variable for this project is STOP-Bang OSA screening.

    Assumptions, Limitations, and Delimitations

    The following section of this paper addresses assumptions, limitations, and delimitations that were inherent in this project. Assumptions are beliefs accepted as true, although not necessarily proven (Nieswiadomy (2012). Limitations are methodological or theoretical flaws in a study that may decrease the generalizability of the findings (Burns and Grove, 2003). Delimitations are boundaries set by the researcher to narrow the scope of a study (Mansor, 2008).

    An assumption that was inherent in this project was that it was assumed that the STOP-Bang screening conducted by the PAT nurses was done accurately. The STOP-Bang OSA screening questionnaire is concise and easy to administer (Acar, Uysal, Kaya, Ceyhan, and Dikmen, 2014). All 14 PAT nurses were instructed on how to conduct STOP-Bang OSA screening by this author. A correct return demonstration ensured competency.

    Another assumption was that anesthesia providers and surgical services healthcare personnel would initiate appropriate interventions when STOP-Bang scores indicated a high index of suspicion for OSA. Recommended perioperative care plan modifications for patients with known or suspected OSA are specified in the Practice Guidelines for the Perioperative Management of Patients with Obstructive Sleep Apnea: An Updated Report by the American Society of Anesthesiologists Task Force on Perioperative Management of Patients with Obstructive Sleep Apnea (Gross et al., 2014). It is reasonably assumed that prudent anesthesia providers would adhere to the recommendations for care of the OSA surgical patient outlined by the American Society of Anesthesiologists (ASA).

    A limitation that was present in this project was that the sample size of 200 subjects was relatively small. This could have resulted in the inability to achieve statistical significance. However, it was not feasible to use a large sample size due to the time allotted to complete this DPI project. With a quantitative methodology, the larger the sample size, the higher the probability that the sample will accurately represent the population of interest (Macnee and McCabe, 2008).

    Another limitation was the retrospective component of the design. In a retrospective chart audit, there is always a chance that data may have been missed or miscoded (Liu et al., 2010). This is a typical limitation encountered whenever data is retrospectively abstracted (Liu et al.).

    A delimitation of this project was related to extraneous variables. Extraneous variables are variables that either cannot be controlled by the researcher, or that the researcher chooses not to control, which can affect the study results (Nieswiadomy, 2012). A noteworthy extraneous variable in this case was the broad age range of subjects (ages 18-75). This could have been a factor in the occurrence of postoperative hypoxemia unrelated to OSA. The broad age range for subject inclusion in this project was a decision made by this author to ensure that a sufficient sample could be obtained in the relatively short time period allotted for data collection and analysis.

    Another delimitation was that the project was conducted at a single institution. It is well-known that the obesity prevalence is higher than the national average in Californiaís Central Valley (National Public Radio, 2014) where the project was conducted. Obesity is known to be a primary risk factor for OSA (Minokadeh et al., 2011). Therefore, the incidence of undiagnosed OSA may have been much higher in the sample population for this project than might have been found if the project had been conducted in other regions. However, it was not possible for a single DNP student to conduct a DNP project at institutions in multiple geographic locations.

    Summary and Organization of the Remainder of the Project

    The condition of OSA is prevalent (Franklin and Lindberg, 2015). In the United States approximately 25 million people suffer from the disorder (American Academy of Dental Sleep Medicine, 2016). Although an exorbitant number of people are afflicted with OSA, it is estimated that up to 80% of people who have OSA have not been definitively diagnosed by polysomnography (American Sleep Apnea Association, 2015).

    Preoperative screening for obstructive sleep apnea (OSA) is an indispensable measure to increase clinician awareness of patients potentially at risk for this serious disorder (Diffee et al., 2012). A plethora of literature corroborates the importance of preoperative recognition of OSA by clinicians (STOP-Bang.ca, 2016). The validated STOP-Bang OSA screening questionnaire is a convenient tool for OSA screening (Chung et al., 2012).

    The previously described DPI project entailed implementing an OSA preoperative screening program using the STOP-Bang instrument at a 427-bed community hospital. The objective of this DPI project was to preoperatively identify surgical patients who had a high index of suspicion for OSA, as well as to heighten clinician awareness of the significance of OSA in the perioperative period. The ultimate goal was to promote patient safety in the perioperative period.

    The Iowa Model was the conceptual framework for this quality improvement project. The Iowa Model provides a robust structure to guide nurses in the implementation of evidence-based clinical practice changes (White and Spruce, 2015). For this DPI project, the clinical practice change was the implementation of the preoperative OSA screening program outlined in this chapter.

    The DPI project outlined in this chapter was worth conducting. As a quality improvement project, it had the potential to enhance perioperative patient safety. Substantial evidence supports the value of preoperative screening for OSA. By conducting this DPI project, this author intended to bridge the gap between the existing evidence and best clinical practice.

    The next chapter, chapter two, describes the projectís conceptual framework in detail. A thorough review of the literature is presented. In chapter three, the methodology for the project is outlined and detailed. Chapter three documents how the project was conducted. In chapter three, enough detail of the project methodology is provided so that replication of the project by others is possible. In chapter four, the data is summarized. A description of how the data was analyzed is presented and the results are revealed. The final chapter of this DPI project is chapter five. In chapter five, a comprehensive summary of the overall project is provided. The findings and conclusions, project implications, and future practice recommendations are presented in chapter five.

    The timeline for completing the investigation and writing the DPI project was as follows. The STOP-Bang OSA screening commenced as anticipated in April, 2016. At that time, the prospective and retrospective EHR chart audits described in this chapter were conducted. The EHR chart audits were completed over a three week period. Data analysis and writing up of the DPI project took two weeks to complete. The project was completed as projected by early May, 2016.

    Chapter 2: Literature Review

    Obstructive sleep apnea (OSA) is a prevalent disorder (Franklin and Lindberg, 2015). Undiagnosed and untreated OSA is associated with serious health consequences (Cohen and Townsend, 2013). The incidence of OSA among surgical patients is greater than in the general population (Kadam, Markman, Neumann, and Kingisepp, 2015). This is concerning because surgical patients with OSA have an increased risk for perioperative complications (Kaw, Gali, and Collop, 2011). Consequently, it is imperative that patients with OSA are recognized in the preoperative period. This review will deliberate the importance of preoperative OSA screening to promote optimal perioperative management, subsequently leading to safe, quality patient outcomes.

    This authorís Direct Practice Improvement (DPI) project was to implement a preoperative OSA screening program, for a period of one month, at a 427-bed community hospital using the validated STOP-Bang OSA screening questionnaire. Preoperative recognition of OSA by clinicians begins with OSA screening (Diffee et al., 2012). Upon initiation of the OSA screening protocol, the Preadmission Testing (PAT) nurses screened all adult (ages 18-75-years old) elective surgery patients for OSA during the preoperative interview. The purpose of this DPI quality improvement project was to enhance patient safety in the perioperative period.

    Prior to going live with the OSA screening program, all 14 PAT nurses were instructed by this author on how to conduct OSA screening using the STOP-Bang instrument. The education was provided through one-on-one instruction with each PAT nurse. After the training, competency was assessed by way of a return demonstration.

    Following implementation of the OSA screening protocol, this Doctor of Nursing Practice (DNP) student conducted a combined prospective/retrospective chart audit comparing the incidence of postoperative hypoxemia (defined by Liu et al. (2010) as any decrease in hemoglobin oxygen saturation to ≤ 95%) in the PACU in patients who were screened for OSA on the STOP-Bang questionnaire, compared to those who were not screened for OSA on the STOP-Bang instrument. Hypoxemia is the most common complication experienced by patients with OSA perioperatively (Pereira et al., 2013). This author postulated that the incidence of hypoxemia would be higher in the cohort who were not screened for OSA on the STOP-Bang questionnaire, compared to the cohort who were screened for OSA on the STOP-Bang questionnaire. It was anticipated by this author that the results of the project would support the transition to permanent implementation of the preoperative OSA screening protocol at the 427-bed community hospital where the project was conducted.

    The conceptual framework for this DPI project was the Iowa Model of Evidence-Based Practice to Promote Quality Care (Iowa Model). The application of the Iowa model to the DPI project is described herein. This precedes the literature review.

    Systematic reviews, meta analyses, randomized control trials, observational studies, and case reports on OSA were acquired from databases including Pubmed, Cochrane Library, CINAHL, Up-to-Date, Clinicalkey, Medline, and Access Medicine. Medical Subject Headings (MeSH) and keywords used to access literature germane to this DPI project included obstructive sleep apnea, STOP-Bang, obstructive sleep apnea screening, and conceptual framework. The research was critically appraised and synthesized by this author. In this review, study purposes, hypotheses, methodology, design, data collection methods, and data analysis approaches are elucidated.

    This chapter comprises a thorough review of the literature on OSA. The emphasis is placed on major subthemes. These include pathogenesis, comorbidities, cardinal features, treatment, preoperative diagnosis, perioperative complications, perioperative management, and appraisal of attitudes among healthcare professionals regarding perioperative care of patients with OSA.

    Background

    The most common respiratory sleep disorder is OSA (Ayas et al., 2014). An estimated 25 million Americans are afflicted with OSA (American Academy of Dental Sleep Medicine, 2016). Approximately 80% of OSA cases are undiagnosed (American Sleep Apnea Association, 2015). According to Peppard et al. (2013), it is estimated that up to one out of every four men, and one out of every ten women in the United States has OSA. The prevalence of OSA increases with advancing age (American Lung Association, 2015). Obesity is a major OSA risk factor, as well as the leading cause of OSA in the United States (Minokadeh et al., 2011).

    The long-term untoward consequences of OSA on health outcomes have been well-documented (Kornegay and Brame, 2015). However, the effects of OSA on perioperative risks have only recently been evaluated, largely within the past two decades, through institutional and population-based research (Memtsoudis et al., 2013). These increased perioperative risks associated with OSA are significant since it is estimated that up to 25% of elective surgery candidates are afflicted with OSA, and up to 80% of patients in high-risk populations (bariatric surgery candidates for instance) suffer from OSA (Memtsoudis et al.; Weingarten et al., 2011).

    Patients who suffer from OSA are at increased risk for perioperative complications for a number of reasons, including the presence of OSA related comorbidities, particularly cardiovascular disease (De Torres-Alba et al., 2013). Other causes include upper airway anomalies commonly associated with OSA (Mador et al., 2013), as well as an increased sensitivity to anesthetic agents, narcotics, and sedatives (Gross et al., 2014). Patients with OSA often experience an exaggerated response to the effects of anesthetic gases and medications (Fouladpour et al., 2016). This subsequently leads to an amplified loss of pharyngeal muscle tone with subsequent upper airway obstruction resulting in hypopnea and apnea (Fouladpour et al.). Difficult airway management, including difficult endotracheal intubation has also been linked to OSA (Porhomayon et al., 2011).

    Patients with OSA are at an increased risk for a multitude of perioperative complications (Ankinchetty and Chung, 2011). The vast majority of people with OSA have not been definitively diagnosed by a polysomnography sleep study (McNicholas, Luo, and Zhong, 2015). Therefore, the value of preoperative screening for OSA cannot be over-emphasized.

    To enhance patient safety, The Joint Commission, the American Society of Anesthesiologists (ASA), and the American Society of Perianesthesia Nurses (ASPAN) recommend preoperative screening for OSA (ASPAN OSA Practice Recommendation Work Team, 2012; Gross et al., 2014; The Joint Commission, 2015). Although no general consensus has been reached on which of several available OSA screening instruments should be used, the STOP-Bang questionnaire has gained popularity in recent years (Farney, Walker, Farney, Snow, and Walker, 2011). The STOP-Bang questionnaire has been validated by a number of studies (Chung et al., 2012). It is exceedingly easy to administer, and takes less than a minute to complete (Spence, Han, McGuire, and Couture, 2015). Luo, Xu, and Jiong (2014) found the STOP-Bang screening instrument to be superior to other validated OSA screening tools, including the Berlin Questionnaire and the Epworth Sleepiness Scale. According to the ASPAN OSA Practice Recommendation Work Team, there has been limited application of OSA screening tools in the perianesthesia patient, other than the STOP-Bang questionnaire, established in the OSA literature. Therefore, for this DPI project, the STOP-Bang tool was deemed by this author as the most suitable OSA questionnaire for use in the perianesthesia setting.

    Conceptual Framework for Implementing Preoperative STOP-Bang OSA Screening: The Iowa Model
    The Iowa Model for Evidence-Based Practice to Promote Quality Care was selected to provide the framework of this authorís DPI project. The Iowa model is the intellectual property of the University of Iowa Hospitals and Clinics. Written permission to use the Iowa Model Implementation Guide was sought by this author and granted (Appendix B).

    Melnyk, Fineout-Overholt, Gallagher-Ford, and Kaplan (2012) note that nursesí recognition of the implementation of healthcare changes based on evidence-based practice (EBP) promotes quality patient outcomes, while simultaneously controlling healthcare costs. Evidence-based practice is a problem-solving method to clinical decision-making that incorporates solid evidence from well-designed research studies with cliniciansí expertise, and patientsí values and preferences (Melnyk et al). The Iowa model provides the necessary structure to help nurses implement best practices based on the evidence.

    The Iowa Model has been extensively validated as a highly-effective model to facilitate change in nursing (White and Spruce, 2015). It is imperative that nursing practice change be founded on the best available evidence. The Iowa Model provides a systematic framework for nursing practice change by integrating clinical inquiry, judgement, and critical thinking (Kowal, 2010). The Iowa model guides clinical decision-making and evidence-based practice application from the practitionersí and organizational perspectives (White and Spruce).

    White and Spruce (2015) note that many healthcare organizations and clinicians do not consistently deliver care based on the evidence; many are unaware of the best available evidence to guide practice change. Evidence-based practice (EBP) protocols can prevent complications and lead to improved patient outcomes. Using the Iowa Model as the foundation to implement EBP changes has historically been shown to help decrease the chasm between research and practice (White and Spruce).
    This authorís DPI project fits within other quality improvement projects based on the Iowa Model. Lakdawala (2011) employed the Iowa Model as the algorithm for the necessary step-by-step team approach to facilitate successful implementation and sustainability of an OSA preoperative screening protocol, using the STOP-Bang instrument, at a large acute care facility. Lakdawalaís research revealed that prior to implementation of the OSA screening protocol, 3% (n=124) of surgical patients were identified as having OSA. After a one-month pilot of the OSA screening protocol, 17% (n=143) of surgical patients were identified as high-risk for OSA (Lakdawala). Screening surgical patients for OSA preoperatively, using the STOP-Bang questionnaire, was determined to be an essential component of the preoperative patient assessment by Lakdawala and her team.

    Brown (2014) outlines the Iowa Model of Evidence-Based Practice. The seven sections of the model include: Problem-focused and knowledge-focused triggers; Priority of the topic; Formation of a team; Obtaining sufficient research to guide practice; Piloting the change in practice; Adoption of the practice; and Analysis, evaluation, and dissemination. This framework will support the introduction, development, and evaluation of a preoperative STOP-Bang OSA screening protocol.
    The problem-focused trigger for this authorís DPI project was that surgical patients at the selected 427-bed community hospital were not screened preoperatively for OSA. There had been reports of perioperative respiratory complications plausibly related to undiagnosed sleep apnea. This issue provided a sense of urgency for implementation of a preoperative OSA screening protocol.

    Knowledge-focused triggers also applied to this authorís DPI project. These pertained to the plethora of current research that strongly supports the recommendation for preoperative screening for OSA. Practice guidelines for the perioperative management of patients with obstructive sleep apnea: An updated report by the American Society of Anesthesiologists task force on perioperative management of patients with obstructive sleep apnea highly recommends preoperative OSA screening (Gross et al., 2014). These triggers made the DPI project a high priority for the organization.

    This author extensively examined critically-appraised research to support the projectís implementation. This literature was systematically disseminated to team members. Team members were encouraged to continue to be involved in the process of obtaining relevant and sufficient evidence to vindicate the project.

    Literature Review

    A thorough review of the literature on OSA will now be presented. As outlined in the introduction to this chapter, emphasis is on major subthemes. Obstructive sleep apnea pathogenesis, comorbidities, cardinal features, treatment, preoperative diagnosis, perioperative complications, perioperative management, and appraisal of attitudes among healthcare professionals regarding perioperative care of patients with OSA are subsequently described.

    Obstructive Sleep Apnea: Pathogenesis and Comorbidities

    Yaggi and Strohl (2010) describe the human upper airway as a complex anatomical structure characterized by an extended posterior pharyngeal space, a 90 degree bend in airflow, and an absence of rigidity. Upper airway patency depends on a balance between forces that promote collapse, and those that maintain patency (Yaggi and Strohl). According to the American Thoracic Society (2015), people with OSA often have a narrower upper airway than those individuals who do not have OSA. This narrowing may be caused by variations in structural factors including tongue size, jaw angle, upper airway length, neck physiognomies, and deposition of adipose tissue in obese individuals (American Thoracic Society). Compared to a typical upper airway structure, a narrower upper airway is predisposed to collapse when pharyngeal skeletal muscles relax during sleep (Pham and Schwartz, 2015). Subsequent interruption of air flow due to airway collapse results in hypopnea and apnea (Pham and Schwartz).

    Individuals with OSA experience frequent, repetitive episodes of partial and complete upper airway obstruction during sleep (Pengo and Steier, 2015). Subsequent transient arousal events lead to the restoration of airway patency (Azagra-Calero, Espinar-Escalona, Barrera-Mora, Llamas-Carreras, and Solano-Reina, 2012). Fragmented sleep leads to excessive daytime somnolence, the hallmark sign of OSA (Dadig and Edwards, 2015).

    Repeated nocturnal apnea and hypopnea episodes induce hypoxia and hypercapnia, with subsequent stimulation of the sympathetic nervous system, the renin-angiotensin-aldosterone system, and other humoral systems (Abboud and Kumar, 2014; Genta-Pereira, Pedrosa, Lorenzi-Filho, and Drager, 2010). The ensuing stress response with consequential catecholamine and hormonal surges can induce vascular inflammation and damage (Kohler and Stradling, 2010). Pak, Grander, and Pak (2014) discuss more than twenty years of evidence showing the strong association between OSA and cardiovascular disease. The mechanism has not conclusively been established; however, inflammatory processes have been heavily implicated as a key link between the two (Pak et al.). Patients with OSA, especially if it is moderate or severe and untreated, are at increased risk for a wide-range of cardiovascular diseases, including hypertension, coronary artery disease, arrhythmias, myocardial infarction, congestive heart failure, and stroke (UpToDate, 2015). Metabolic syndrome is also common among patients with OSA (Sharma et al., 2011).

    Obstructive Sleep Apnea: Cardinal Features

    Snoring is a key feature of OSA (Acar et al., 2016). Another principal finding is observed apnea, frequently reported by the OSA patientís bed partner (Spence et al., 2015). Other primary features include frequent, repetitive arousal from sleep, daytime sleepiness, morning headaches, impaired concentration, and hypertension (Azagra-Calero et al., 2012).

    Treatment of Obstructive Sleep Apnea

    Obstructive sleep apnea is a chronic, treatable disorder (Donovan, Boeder, Malhotra, and Patel, 2015). The potential benefits of successful OSA treatment include enhanced quality of life, control of hypertension, reduced cardiovascular morbidity and mortality, and reduced healthcare costs (Yang et al., 2015). The cornerstones of OSA therapy are weight loss and Continuous Positive Airway Pressure (CPAP) (UpToDate, 2015).

    Obesity and OSA have a tendency to coexist (Diffee et al., 2012). Both obesity and OSA are associated with other morbidities; however, their causal relationship to these disorders remains unclear (Pak et al., 2014). Chirinos et al. (2014) evaluated the incremental effect of CPAP, in combination with a weight loss intervention, over the effect of each intervention alone on hypertension, inflammation, insulin resistance, and dyslipidemia in obese patients with OSA.

    One hundred and eighty one patients with moderate to severe OSA, obesity, and serum C-reactive protein (CRP) levels more than 1.0 mg per liter were randomly assigned to receive CPAP therapy, a weight loss intervention, or CPAP in combination with a weight loss intervention for a 24 week period (Chirinos et al.). Follow up data was available for 146 of the study participants (Chirinos et al.). Those participants who were assigned to the weight loss intervention group and those assigned to the combined weight loss and CPAP therapy group had reductions in insulin resistance, serum triglycerides, and CRP levels (Chirinos et al.). Patients in the CPAP only group did not show any of those changes (Chirinos et al). Chirinos et al. found that blood pressure levels were reduced in all three groups.
    Guralnick, Pant, Minhaj, Sweitzer, and Mokhlesi (2012) report that OSA is prevalent among the surgical population, and that preoperative screening for OSA is recommended. Guralnick et al. also note that it is unclear if patients diagnosed preoperatively with OSA adhere to prescribed CPAP treatment. Guralnick et al. conducted a study with the aim of objectively quantifying adherence to CPAP, exploring barriers to CPAP adherence, and establishing an optimal CPAP setting among a group of preoperative patients with OSA as part of the preoperative assessment.

    This study by Guralnick et al. had a retrospective observational design. Data was collected on all adult preoperative patients seen by an anesthesiologist in the Anesthesia Perioperative Medicine Clinic (APMC) who screened positive for OSA on the STOP-Bang instrument, and subsequently underwent laboratory polysomnography testing prior to surgery (Guralnick et al.). Patients with moderate to severe OSA were offered CPAP (Guralnick et al.). CPAP adherence was objectively recorded (Guralnick et al.).

    Guralnick et al. reported that during the two-year study period, 211 of the 431 referred patients completed a polysomnography sleep study. Sixty-five percent of those patients required CPAP therapy (Guralnick et al.). Severe OSA was significantly more prevalent in patients with a STOP-Bang score of equal to, or more than five, as opposed to those who scored between three and four on the questionnaire (Guralnick et al.).

    Guralnick et al. concluded that CPAP adherence was extremely low in this study. Male gender, African American race, and symptoms of depression were independently related to the reduced use of CPAP (Guralnick et al.). Further research is warranted to overcome barriers to CPAP adherence and acceptance in the perioperative setting (Guralnick et al.).

    There is an increased incidence of OSA among patients with endocrine disorders, such as acromegaly (Korostovtseva et al., 2013). Following transphenoidal surgical treatment of acromegaly, there is controversy regarding the use of CPAP therapy (Rahimi, Mariappan, Tharmaradinam, Manninen, and Venkatraghavan, 2014). Rahimi et al. conducted a study with the aim of comparing the perioperative complications and perioperative management in patients undergoing transphenoidal surgery, with or without OSA.

    A retrospective chart review of 469 patients who underwent transphenoidal surgery was conducted by Rahimi et al. One hundred and five of the 469 patients screened positive for OSA by STOP-Bang assessment (Rahimi et al.). Preoperative polysomnography testing was positive for OSA in 38 patients (Rahimi et al.).

    According to Rahimi et al., ten patients (26%) with OSA experienced hypoxemia postoperatively. Seven of those patients were treated with high-flow oxygen via face mask, while three were treated with CPAP (Rahimi et al.). Two patients in the OSA negative group experienced postoperative hypoxemia and were treated with high-flow oxygen via face mask (Rahimi et al.).

    Rahimi et al. concluded that hypoxemia in OSA patients following transphenoidal surgery can be treated in some, but not all cases with high-flow oxygen. A small number of patients were safely treated with CPAP (Rahimi et al). Rahimi et al. recommend further prospective studies to determine the safe use of CPAP in patients following transphenoidal surgery.

    These studies indicate that CPAP therapy is the benchmark of OSA treatment (Chirinos et al., 2014; Rahimi et al., 2014). The findings from the study by Chirinos et al. confirm the positive effects of CPAP therapy on attenuating hypertension. The findings from the study by Rahimi, et al. demonstrate the efficacy of CPAP therapy on the treatment of postoperative hypoxemia.

    Obstructive Sleep Apnea: Preoperative Diagnosis

    The gold standard for the diagnosis of OSA is laboratory polysomnography (Gasparini et al., 2015). Patients who do not have access to laboratory polysomnography may be diagnosed with OSA by portable home polysomnography (Rosen et al., 2012). However, as previously noted, the vast majority of patients with OSA are undiagnosed (American Sleep Apnea Association, 2015). The STOP-Bang OSA screening instrument has been validated by numerous studies as an effective tool to diagnose patients with a high index of suspicion for OSA (Chung et al., 2012). In screening for OSA, it has been demonstrated that the STOP-Bang tool exhibits high methodological validity and reasonable accuracy (Abrishami, Khajehdehi, and Chung, 2010). The STOP-Bang questionnaire is simple to use due to its yes/no format (Acar et al., 2014). Based on the evidence, this author recommends the use of STOP-Bang screening for all elective surgical patients to identify patients at increased risk for perioperative complications, and to allow for implementation of an appropriate plan of care.

    In a research study by Kulkarni, Horst, Eberhardt, Kumar, and Sarker (2014), the authorsí purpose was to determine, preoperatively, the risk of OSA among surgical patients in a tertiary care hospital setting. Kulkarni et al. presented a single hypothesis. The researchers postulated that preoperative assessment with the STOP-Bang OSA screening questionnaire would help identify patients with undiagnosed OSA and possibly lead to apposite management of the condition (Kulkarni et al.).

    Kulkarni et al. prospectively screened 371 patients who presented to an outpatient general surgery center for OSA risk, utilizing the STOP-Bang OSA screening instrument. Surgical patients were categorized as high-risk for OSA with a score of more than, or equal to three on the STOP-Bang screening tool (Kulkarni et al.). The study cohort included adult male and female patients (Kulkarni et al.). Patients with neck masses that possibly could affect OSA symptoms were excluded from the study (Kulkarni et al.). When available, polysomnography results were reviewed (Kulkarni et al.).

    Kulkarni et al. concluded that a substantial percentage of patients who present to a general surgery clinic are at increased risk for OSA. Kulkarni et al. validated the strength of the STOP-Bang instrument by comparing its performance to the forty-six patients who had been previously evaluated by polysomnography testing. Kulkarni et al. recommended additional research concerning the significances of the preoperative diagnosis and treatment of OSA on perioperative care and complications.

    In a study by Vana, Silva, and Goldberg (2013), the authorsí purpose was to compare the diagnostic capabilities of the Epworth Sleepiness Scale (ESS) to the prognostic ability of the STOP-Bang questionnaire in identifying patients with OSA. Vana et al. queried whether the administration of the STOP-Bang questionnaire to a cohort of sleep clinic patients would positively identify a greater number of patients at risk for OSA prior to polysomnography testing than the current practice of using the ESS alone. Vana et al. also sought to determine whether the joint scoring of the ESS and the STOP-Bang tool would appropriately identify more OSA patients.

    A convenience sample was employed for the cross-sectional study design (Vana et al.). Sleep clinic patients not previously diagnosed with OSA were invited to participate in the study (Vana et al.). Patients were approached in consecutive order until a total of 60 participants were recruited (Vana et al.).

    This study by Vana et al. had numerous limitations. Limitations noted by the researchers were that the sample size of 60 was very small; Caucasians made up the majority of the sample population; and patients with OSA symptoms might have been more willing to participate in the study than those who did not have OSA symptoms (Vana et al.). Additionally, the incidence of OSA in this convenience sample was greater than would be expected in the general population because all of the study participants had been referred to the sleep clinic on account of their already high index of suspicion for OSA (Vana et al.).

    Vana et al. determined that compared to the ESS, the STOP-Bang instrument identified more patients with OSA. The sensitivity of either instrument did not increase when jointly scored (Vana et al.). To validate their study results, Vana et al. recommended large multi-center studies be conducted on multi-racial populations.

    Chung et al. (2013) recognized the STOP-Bang questionnaire as a validated screening instrument for OSA in the surgical patient population. Chung et al. were uncertain of the capability of the tool in recognizing OSA in obese patients. Chung et al. conducted a study in which the objective was to appraise the predictive performance of the STOP-Bang instrument for identifying obese patients with OSA.

    After obtaining consent, preoperative patients were screened for OSA by the STOP-Bang questionnaire (Chung et al.). Portable or laboratory polysomnography was performed on 667 of the study participants (Chung et al.). Analysis of the predictive parameters of specificity, sensitivity, and negative and positive predictive values was conducted (Chung et al.).

    In this study, Chung et al. found that a STOP-Bang score of three had a 90% sensitivity and an 85% positive predictive value in 310 obese patients. A score of four showed an 87.5% sensitivity and a negative predictive value of 90.5% for detecting severe OSA (Chung et al.). A score of six had an 85.2% specificity to diagnose severe OSA (Chung et al.). In 140 obese patients, a score of four on the STOP-Bang questionnaire had an 85% sensitivity for identification of severe OSA (Chung et al.).
    Limitations of this study were recognized by Chung et al. Because both portable and laboratory polysomnography were performed, the study could be criticized (Chung et al.). In addition, since surgical patients comprised the study population, the researchers acknowledged that the results may not apply to other patient populations (Chung et al.). Further validation is warranted in diverse patient populations (Chung et al.).

    Chung et al. (2013) concluded that in the obese population of this study, the STOP-Bang score was validated. A score of four has an 88% sensitivity (Chung et al.). A STOP-Bang score of six is more specific for confirming severe OSA (Chung et al.).

    Luo et al. (2014) note that the most superlative OSA screening instrument is presently unknown. Luo et al. found few prospective studies comparing the various questionnaires in a population. The purpose of the study by Luo et al. was to evaluate four OSA screening questionnaires: the STOP-Bang questionnaire, the Epworth Sleepiness Scale (ESS), the Berlin questionnaire, and the STOP questionnaire in screening patients at increased risk of OSA (Luo et al.). This was conducted in a sleep disorder clinic to illustrate the superiority of the STOP-Bang questionnaire (Luo et al).

    Two-hundred and twelve patients suspected to have OSA, who planned to undergo a laboratory polysomnography sleep study in a sleep clinic, were prospectively sequentially enrolled from May 2011 to January 2012 (Luo et al.). Patients previously diagnosed with OSA were excluded from the study (Luo et al.). Also excluded were patients with incomplete questionnaires (Luo et al.).
    The results of this study by Luo et al. found that the STOP-Bang questionnaire is superior to the ESS, Berlin questionnaire, and STOP questionnaire in terms of OSA predictive value. These results support the researcherís hypothesis (Luo et al.). Luo et al. recommend that the STOP-Bang tool be used further in screening for OSA in the general population.

    In a study by Silva, Vana, Goodwin, Sherill, and Quan (2011), the objective was to evaluate the prognostic abilities of four sleep disorder breathing (SDB) screening instruments: the Four-Variable screening tool, STOP, STOP-Bang, and ESS. Providers often must decide which patients to refer for polysomnography testing (Silva et al.). The instruments were selected because of their potential utility in clinical practice (Silva et al.).

    Included in this large study by Silva et al. were 4,770 participants who underwent polysomnography testing. Two weeks prior to the in-home, overnight, portable polysomnography evaluation, the four sleep questionnaires were mailed to the study participants to be completed prior to commencement of the sleep study (Silva et al.). Each of the questionnaires was compared on the parameters of specificity, sensitivity, and the probability ratio for a positive or negative result (Silva et al.).
    Silva et al. concluded that the STOP-Bang questionnaire identified more patients with moderate and severe SDB. The STOP-Bang instrument performed better than the STOP questionnaire (Silva et al.). To avoid missing cases of SDB that could potentially lead to adverse outcomes, clinicians may prefer to use the STOP-Bang instrument due to its high sensitivity (Silva et al.).

    Silva et al. recommend that multiple SDB questionnaires be concomitantly evaluated at various hospital and clinical settings. This would allow for comparison of important variances within the same populaces (Silva et al.). Ideally, questionnaires with high sensitivities should be selected for SDB screening (Silva et al.).

    These studies evaluated the validity and clinical utility of the STOP-Bang OSA screening questionnaire. The findings of the study by Kulkarni et al. (2014) determined that a substantial number of patients in the surgical population are at high risk for OSA. Kulkarni et al. further validated the STOP-Bang questionnaire. Chung et al. (2013) validated the STOP-Bang tool in the obese populace. Vana et al. (2013) indicated that the STOP-Bang questionnaire is superior to the ESS. The study by Luo et al. (2014) found that in terms of OSA predictive value, STOP-Bang surpassed the ESS, Berlin questionnaire, and STOP questionnaire. Silva et al. (2011) found the STOP-Bang questionnaire superior to the Four-Variable, STOP, and ESS.

    Obstructive Sleep Apnea Associated Perioperative Complications

    It has been well-documented that patients with OSA are likely to suffer from comorbidities that have potential to increase their risk of perioperative complications (Kim, Koo, Lee, and Lee, 2016). Additionally, patients with OSA are particularly sensitive to anesthetic agents and medications that could possibly result in airway compromise during the perioperative period (Gross et al., 2014). There is a plethora of evidence in the literature which highlights the subsistence of increased risk for perioperative adverse outcomes among surgical patients with OSA.

    Kaw, Pasupuleti, Walker, Ramaswamy, and Foldvary-Schafer (2012) postulate that a significant number of patients with undiagnosed OSA may routinely present for surgery. Kaw et al. conducted a study with two specific objectives. First, Kaw et al. sought to determine the frequency and type of postoperative complications experienced by patients with undiagnosed OSA undergoing elective surgery. Second, Kaw et al. sought to analyze the influence of OSA severity on the rate of perioperative complications.
    The study population was selected from 39,771 patients who submitted to preoperative assessment from January 2002 through December 2006 (Kaw et al.). Adult patients undergoing surgery within three years of OSA diagnosis, by polysomnography testing, were considered (Kaw et al.). Patients who had regional or local anesthesia were excluded (Kaw et al.). Patients with an apnea-hypopnea index (AHI) of equal to, or greater than five were considered to have OSA (Kaw et al.). The AHI is an index based on the total number of apneic and hypopneic episodes of breathing per hour which is used to assess the severity of OSA (Chung et al., 2014). The control group was comprised of patients with an AHI of less than five (Kaw et al.).

    A total of 1,759 surgical patients underwent a polysomnography sleep study (Kaw et al.). Of those, 471 met study criteria (Kaw et al.). The study cohort was comprised of 282 patients with OSA, while the control group consisted of 189 OSA negative patients (Kaw et al.).

    Kaw et al. reported 40 (14.2%) complications in the OSA group, compared with five (2.5%) complications in the control group. Significant complications occurred in the OSA group, including hypoxemia, respiratory arrest, atrial fibrillation, myocardial infarction, and congestive heart failure (Kaw et al.). This study concluded that OSA is an independent risk factor for hypoxemia, Intensive Care Unit transfers (ICU), and extended hospital stays (Kaw et al.).

    Lockhart et al. (2013) noted that an investigation at Barnes-Jewish Hospital in Saint Louis, Missouri, found that approximately 22 % of adult patients presenting for surgery screened positive for high risk of OSA. Lockhart et al. recognized that many OSA patients have comorbidities that increase the risk of perioperative complications. It was the objective of Lockhart et al. to determine if a definitive diagnoses of OSA, based on polysomnography results, or a positive screening result for OSA was correlated with an increased risk for 30-day to one-year mortality.

    The Barnes-Jewish Apnea Prevalence in Every Admission Study (B-J APNEAS) was a prospective cohort study (Lockhart et al.). Unselected surgical patients over the age of 18 were enrolled prospectively between February 2006 and April 2010 (Lockhart et al.). All of those patients were preoperatively screened for OSA using a combination of screening tools that included the STOP-Bang questionnaire (Lockhart et al.).

    The sample was comprised of 14,962 patients, of whom 1,939 (12.9%) had a reported history of OSA (Lockhart et al.). There was no significant difference in 30-day mortality found in the general surgical population and those patients who screened positive for OSA (Lockhart et al.). Significant differences in one-year mortality were noted between high and low OSA risk groups as identified by the STOP-Bang screens (Lockhart et al.). After risk factors were adjusted, the STOP-Bang instrument did not independently predict one-year postoperative mortality (Lockhart et al.).

    Lockhart et al. concluded that neither a diagnosis of OSA by polysomnography, nor a positive OSA screening result, was associated with 30-day or one-year mortality. Differences in one-year postoperative mortality were noted with the STOP-Bang screening tool (Lockhart et al.). This study underlined uncertainties and priorities for research in the medical community (Lockhart et al.).
    It is presumed that OSA is a risk factor for perioperative morbidity and mortality (Spence et al., 2015). Liao, Yegneswaran, Vairavanathan, Zilberman, and Chung (2009) determined that there is insufficient evidence to correlate perioperative respiratory complications with OSA. The purpose of the study by Liao et al. was to test the hypothesis that OSA is a risk factor for the development of perioperative complications.

    This was a retrospective matched cohort study (Liao et al.). The participants who were accepted for this study were adult patients preoperatively diagnosed with OSA and scheduled for elective surgery (Liao et al.). The comparator group was comprised of surgical patients without OSA based on a one-to-one match (Liao et al.). Matching criteria included age difference less than five years, gender, and type of surgery (Liao et al.).

    The 240 pairs of study subjects included 184 (77%) men and 56 (23%) women (Liao et al.). OSA patients had a higher mean body mass index and higher incidence of comorbidities, including obesity and hypertension (Liao et al.). Oxygen desaturation was the most commonly observed difference between the OSA and the non-OSA cohorts (Liao et al.).

    Liao et al. concluded that OSA patients have an increased risk for perioperative complications. The most common complication was hypoxemia (Liao et al.). Compared to non-OSA patients, OSA patients more often required prolonged oxygen therapy and additional monitoring (Liao et al.).

    The objective of the study by Gupta, Parvizi, Hanssen, and Gay (2001) was to evaluate the prevalence and nature of perioperative complications suffered by patients who underwent knee replacement or hip replacement surgery and had a prior diagnosis of OSA, compared with a matched cohort without OSA also having knee replacement or hip replacement surgery. In the study by Gupta et al. there were 101 OSA patients and 101 match controls. Complications occurred in 39 patients (39%) in the OSA group compared to 18 patients (18%) in the control group (Gupta et al.). Serious complications occurred in 24 patients (24%) in the OSA cohort compared with nine patients (9%) in the control group (Gupta et al.). Significantly longer hospital length of stays were experienced by patients in the OSA cohort (Gupta et al.). These results support the conclusion by Gupta et al. that adverse perioperative complications occur at an increased rate in OSA patients who undergo knee replacement or hip replacement surgery, compared to a matched control group.

    Proczko et al. (2014) note that in patients undergoing surgery under a general anesthetic, OSA is associated with perioperative complications. These complications range from hypoxemia to sudden death (Proczko et al.). Proczko et al. hypothesized that morbidly obese patients diagnosed with OSA by a polysomnography sleep study, and using prescribed CPAP, have less frequent and less severe perioperative complications and a reduced length of hospital stay when compared to patients who have a medical history that meets three or more STOP-Bang criteria who are not using CPAP treatment.
    Pulmonary complications and postoperative hospital stay were analyzed in three groups of morbidly obese patients who underwent bariatric surgery from January 2009 to November 2013 (Proczko et al.). Group A consisted of 99 patients preoperatively diagnosed with OSA by a polysomnography sleep study (Proczko et al.). This group of patients used CPAP before and after surgery (Proczko et al.). Group B was comprised of 182 patients who were not diagnosed with OSA by polysomnography, but met at least three criteria on the STOP-Bang questionnaire (Proczko et al.). This group did not use CPAP (Proczko et al.). The reference group, group C, consisted of 412 patients who scored only one to two items on the STOP-Bang tool (Proczko et al.).

    Perioperatively, group B patients experienced significantly higher rates of pulmonary complications, poorer oxygen saturation, worse respiratory rates, and an increased length of hospital stay (Proczko et al.). There were also two cases of sudden death in this group (Proczko et al.). Based on these results, Proczko et al. concluded that patients who meet at least three STOP-Bang criteria have an increased incidence of perioperative complications and longer hospital stays than OSA patients who are using CPAP.

    Vasu et al. (2010) conducted a study to determine whether high preoperative STOP-Bang scores correlated with an increased degree of perioperative OSA complications. In this retrospective cohort study, Vasu et al. hypothesized that OSA is an independent risk factor for perioperative cardiac and pulmonary complications. The usefulness of the STOP-Bang screening tool in the surgical setting was evaluated (Vasu et al.).

    Preoperative STOP-Bang screening was piloted among 180 elective surgical patients (Vasu et al.). Excluded from the study were patients with kidney failure and/or decreased serum albumin (Vasu et al.). Study criteria were met by 135 participants (Vasu et al.). Women represented 55.6% of the cohort, while men represented 44.4% (Vasu et al.). Participant mean age was 57.9 (Vasu et al.). Patients who were classified as obese made up 25.2% of the cohort (Vasu et al.). STOP-Bang results indicated that 41.5% of the participants had a high index of suspicion for OSA (Vasu et al.).
    Vasu et al. found that patients in this study determined to be at high-risk for OSA experienced an increased rate of adverse perioperative events, when compared to patients deemed low-risk for OSA. These results support the studyís hypothesis (Vasu et al.). Vasu et al. recommend that other investigators assess the STOP-Bang questionnaire to provide external validation of the study results.
    It has been suggested that a close relationship subsists between difficult endotracheal intubation and OSA (Porhomayon et al., 2011). This can present a challenge for anesthesia providers because difficult intubation may contribute to morbidity and mortality in the perioperative period (Porhomayon et al.). Auckley and Bolden (2012) found that patients with OSA are at risk for difficult endotracheal intubation, as well as difficult mask ventilation.

    In a study by Acar et al. (2014), the authors hypothesized that the STOP-Bang instrument can effectively predict difficult intubation. Acar et al. conducted a prospective cohort study. Two-hundred surgical patients over the age of 18, scheduled for elective surgery under general anesthesia, were included in the study (Acar et al.). The purpose of the study was to determine the ability of the STOP-Bang instrument to predict difficult intubation (Acar et al.),

    Two prominent findings were revealed by this study (Acar et al.). Firstly, difficult intubation occurred more frequently in 83 out of 200 patients in the high risk for OSA group based on STOP-Bang scores versus patients in the low risk for OSA group (13.3% versus 2.6%) (Acar et al.). Secondly, a STOP-Bang score of three or greater was seen more often in patients with difficult intubation (Acar et al.). Acar et al. concluded that a STOP-Bang score of three or more was a predictor of difficult intubation.
    In the study by Acar et al. 78.6% of patients who experienced difficult intubation were determined to be at high risk for OSA. Whereas, in the study by Chung, Yegneswaran, Herrera, Shenderey, and Shapiro (2008), 66% of patients with difficult intubation had OSA confirmed by polysomnography testing. Therefore, the actual percentage in the study by Acar et al. would be expected to be lower since their suspected OSA patient cases were not confirmed by polysomnography.

    The number of ambulatory surgery centers are increasing (Liu et al., 2010). It is not clear if it is safe to discharge patients with OSA to home immediately following ambulatory surgery procedures. Liu et al. conducted a study to determine if a correlation subsists between a preoperative OSA diagnosis and adverse perioperative outcomes.

    Liu et al. conducted a retrospective audit of 206 charts of patients with a diagnosis of OSA. Charts were reviewed for adverse perioperative events, including hypoxemia (Liu et al.). Outcome data were extracted from the records and analyzed (Liu et al.).

    The majority of the patients (95%) had regional anesthesia, as opposed to general anesthesia (Liu et al.). In the recovery room, 34% of patients experienced hypoxemia (Liu et al.). None of the patients in this study suffered major complications (Liu et al.). Liu et al. note that further research is warranted to determine the association between OSA and perioperative complications among patients who receive general anesthesia.

    In a study by Corso et al. (2014), the authors aimed to evaluate the clinical usefulness of screening for OSA to determine the prevalence of patients at high risk for OSA in the surgical population, the incidence of perioperative adverse outcomes, and the incidence of difficult airway management. This was a prospective observational study of adult elective surgery patients (Corso et al.). Patients were screened with the STOP-Bang instrument preoperatively (Corso et al.). Data collected included demographics, type of surgery, rates of difficult intubation and difficult mask ventilation, postoperative course, and complications within 48 hours (Corso et al.).

    Corso et al. consecutively recruited a total of 3,452 patients. Of those, 2,997 (87%) were deemed at low risk for OSA, and 455 (13%) were identified as high risk for OSA (Corso et al.). There were 113 (3%) postoperative complications, 315 (9%) incidences of difficult mask ventilation, and 375 (11%) cases of difficult intubation observed (Corso et al.).

    This study demonstrated the high prevalence of OSA patients among the surgical population (Corso et al.). The increased perioperative complication rates justify implementation of perioperative OSA management strategies (Corso et al.). The STOP-Bang questionnaire is a useful instrument for triage (Corso et al.).

    These studies support the concept that patients with OSA experience perioperative complications at greater frequency and severity than patients who do not have OSA. Kaw et al. (2012) determined that OSA surgical patients are at greater risk for hypoxemia, ICU transfers, and longer hospital length of stay. Proczko et al. (2014) also found that patients with OSA experienced a higher rate of complications and longer hospital stays than patients without OSA. Corso (2014), Liao (2009), Liu (2010), and Vasu (2010) found a higher incidence of perioperative complications among OSA patients, with hypoxemia being the most common adverse event. Gupta et al. (2001) found a greater prevalence of adverse postoperative outcomes among OSA patients who underwent knee replacement or hip replacement surgery, compared with patients who underwent knee replacement or hip replacement surgery who did not have OSA. Acar et al. (2014) showed that patients who screened STOP-Bang positive for OSA are at greater risk for difficult intubation than STOP-Bang negative patients. Lockhart (2010) did not find any difference in 30-day or one-year mortality between patients with OSA and those without OSA.

    Perioperative Management of Patients with Obstructive Sleep Apnea

    Optimizing the perioperative care of OSA patients is imperative from a patient safety standpoint. Gross et al. (2014) note that when feasible, preoperative weight loss should be encouraged. CPAP initiation should be considered preoperatively, particularly in patients who have severe OSA (Gross et al.).
    Current literature is insufficient to appraise the effects of numerous anesthetic techniques as they specifically apply to OSA patients (Gross et al.). The literature is also insufficient to evaluate the impact of airway management for OSA patients (e.g., awake intubation) (Gross et al.). Likewise, there is deficient evidence to evaluate patient monitoring techniques as they are specifically applicable to OSA patients (Gross et al.).

    The consultants on the American Society of Anesthesiologists (ASA) Task Force on Perioperative Management of Patients with Obstructive Sleep Apnea (2014) recommend the use of local and regional anesthesia when appropriate. Task force members stalwartly agree that the potential for postoperative respiratory compromise is an important consideration when choosing intraoperative medications and anesthetic agents (Gross et al., 2014). Because of the susceptibility to upper airway collapse, OSA patients are particularly vulnerable to the respiratory depressant effects of opioids, sedatives, and anesthetic inhalation agents (Gross et al.). The consultants and members of the ASA also agree that OSA patients previously prescribed CPAP should use the device whenever sedation is being administered (Gross et al.).

    Healthcare Professional Attitudes on Perioperative Care of Patients with OSA

    The prevalence of OSA among the surgical population is not precisely known, but varies with rates consistent with the general populace, to up to 70% in certain populations (Chung et al., 2008). Patients presenting for bariatric and orthopedic surgery may be particularly prone to OSA (Gupta et al., 2001; Weingarten et al., 2011). Significant perioperative complications are associated with OSA (Kaw et al., 2011). Auckley et al. (2015) conducted a national survey study to determine the attitudes of physicians involved in the perioperative management of patients with OSA.

    A modification of the perioperative survey used by Turner, VanDenKerkhof, Lam, and Mackillop (2006) to survey anesthesiologists in Canada was mailed to 3000 physicians practicing in the United States. These physicians practiced in a variety of specialties, including anesthesiology, primary care, sleep medicine, and general surgery (Auckley et al., 2015). The survey queried the physicians regarding their attitudes and practice patterns related to OSA patients in the perioperative venue (Auckley et al.).
    Of 2,730 eligible participants, 783 surveys were returned (Auckley et al.). Overall, the vast majority (94%) of polled physicians indicated that they believe OSA is an independent risk factor for perioperative morbidity and mortality (Auckley et al.). No difference by specialty was noted (Auckley et al.). Fifty-two percent of participants reported having encountered a patient in the perioperative setting who suffered an adverse outcome related to OSA (Auckley et al.). Seventy-one percent reported that they regularly conduct OSA screening preoperatively (Auckley et al.). Only 27% of those surveyed reported that their hospital had a written policy and procedure in place for the perioperative management of OSA patients (Auckley et al.).

    Auckley et al. concluded that most physicians felt that OSA is a significant risk factor for complications in the perioperative period and most had experience with an adverse outcome related to OSA. Most institutions lack OSA management guidelines (Auckley et al.). Further work is necessary to assist physicians in identifying and intervening with OSA patients, perioperatively, to prevent adverse outcomes (Auckley et al.).

    The preceding literature review presented substantial support for the justification to implement this authorís DPI project, which entailed initiating a preoperative OSA screening protocol using the STOP-Bang OSA screening questionnaire at the selected 427-bed community hospital. Specifically, the study by Vana et al. (2013) determined that the STOP-Bang tool identified more patients with OSA than the validated and renowned ESS. The etiology of perioperative OSA complications were elucidated. In particular, the study by Rahimi et al. (2014) underscored the increased incidence of postoperative hypoxemia, the dependent variable for this DPI project, in patients with OSA when compared to patients without OSA.

    Summary

    This chapter introduced this authorís project planning strategy, project implementation plan, and evaluation of the preoperative OSA screening protocol using the STOP-Bang instrument. After attending a 30-minute OSA education session, the PAT nurses began screening all adult elective surgery patients for OSA, during the preoperative interview, using the STOP-Bang OSA screening questionnaire. The purpose of the DPI quality-improvement project was to improve patient safety in the perioperative period.

    The conceptual framework for implementing preoperative STOP-Bang OSA screening was the Iowa Model for Evidence-Based Practice to Promote Quality Care (Iowa Model, 2001). The Iowa Model provides a systematic framework for nursing practice change by integrating clinical inquiry, judgement, and critical thinking (Kowal, 2010). A thorough explanation of the Iowa model was described. Furthermore, the method by which the conceptual model served as the foundation to guide implementation of the practice change was detailed.

    The literature review provided a critical analysis and synthesis of current well-designed studies relevant to OSA. Central subthemes that were elucidated included OSA pathogenesis, cardinal features, treatment, preoperative diagnosis, perioperative complications, and evaluation of healthcare providersí attitudes regarding perioperative care of patients with OSA. The prevalence of OSA among the surgical population was highlighted. Significant comorbidities associated with OSA were described in detail. The importance of, and rationale for pertinent perioperative care plan modifications were identified.
    Patients with OSA are at increased risk for perioperative complications for a number of reasons (Gross et al., 2014). One reason is that there is a high incidence of comorbidities among patients with OSA, particularly cardiovascular disease and metabolic syndrome (Genta-Pereira et al., 2010; Sharma et al., 2011). Compared to healthy patients, patients whose health is impaired due to disease are at greater risk for complications when they undergo anesthesia and surgery (Kim et al., 2016).

    Other significant reasons that patients with OSA are at greater perioperative risk than patients without OSA have been identified and explored. These include existence of upper airway anomalies frequently characteristic of patients with OSA, as well as increased sensitivity to anesthetic gases, opioids, and sedatives (Gross et al., 2014). Porhomayon et al. (2011) and Auckley and Bolden (2012) described the close association between the presence of OSA and the increased incidence of difficult mask ventilation and endotracheal intubation. Any of these aforementioned challenges may result in perioperative hypoxemia.

    As the most common sleep disorder, the prevalence of OSA is exceedingly high (Ayas et al., 2014). The occurrence of OSA among the surgical population is greater than among the general population (Memtsoudis et al., 2013). Patients with OSA are at greater risk for perioperative complications than patients who do not have OSA (Gross et al., 2014).

    The gold standard for diagnosis of OSA is a laboratory polysomnography sleep study (Gasparini et al., 2015). This is a costly and time-consuming diagnostic procedure that involves an overnight stay at a sleep laboratory (Weingarten et al., 2011). Most patients with OSA have not been definitively diagnosed by polysomnography; therefore, the vast majority of patients with OSA remain undiagnosed and unaware that they are afflicted with this serious disorder (American Sleep Apnea Association, 2015). Consequently, it is imperative to screen patients for occult OSA during the preoperative period so that the appropriate perioperative care plan modifications can be made to optimize care and ensure safety among this vulnerable population.

    Throughout this chapter, the value of preoperative screening for OSA has been stressed. An overabundance of scholarly research concludes that a preoperative OSA screening protocol augments patient safety and promotes exceptional patient outcomes. The Joint Commission and the American Society of Perianesthesia Nurses highly recommend preoperative OSA screening, and both organizations endorse the STOP-Bang OSA screening questionnaire (ASPAN OSA Practice Recommendation Work Team, 2012; The Joint Commission, 2015). This authorís DPI project entails the implementation of a preoperative OSA screening protocol using the STOP-Bang questionnaire which is intended to advance clinician knowledge of patientsí potential risk for OSA, as well as the relevance of subsequent implementation of appropriate perioperative care plan modifications.

    The next chapter (chapter three) details the quantitative methodology for the DPI project. Sections that are expanded upon include project methodology, project design, population and sample selection, instrumentation, validity, reliability, data collection procedures, data analysis procedures, ethical considerations, and limitations. Chapter three documents how the DPI project was conducted in sufficient detail to allow for replication by others.

    Chapter 3: Methodology

    The prevalence of obstructive sleep apnea (OSA) is high (Franklin and Lindberg, 2015); however, the vast majority of patients with OSA have not been diagnosed with the disorder (American Sleep Apnea Association, 2015). A plethora of research has established OSA as a risk factor for perioperative complications. Consequently, it is important to identify patients at high-risk for OSA preoperatively.
    The purpose of this authorís Direct Practice Improvement (DPI) project was to implement a preoperative OSA screening protocol, using the STOP-Bang screening questionnaire in a 427-bed community hospital. The following was the clinical PICOT question for this project: During the one-month period following initiation of a STOP-Bang OSA screening protocol, will adult (ages 18-75) general anesthesia elective surgery patients who undergo preoperative OSA screening on the STOP-Bang questionnaire, compared to adult (ages 18-75) general anesthesia elective surgery patients who do not undergo preoperative OSA screening on the STOP-Bang questionnaire during the one-month period prior to initiation of a STOP-Bang OSA screening protocol, experience postoperative hypoxemia (defined by Liu et al. (2010) as a hemoglobin oxygen saturation ≤ 95% on pulse oximetry monitoring) less frequently in the PACU? A paper version of the STOP-Bang questionnaire was completed by the Preadmission Testing (PAT) nurses and placed on the front of the patientsí charts. Demographic data, including gender, BMI, and age were obtained from the STOP-Bang questionnaire. The occurrence, or nonoccurrence of postoperative hypoxemia in the PACU was obtained from the patientsí records in the EHR in accordance with the comparative design of the project. This chapter incorporates the following components: project methodology; project design; population and sample selection; instrumentation; validity; reliability; data collection procedures; data analysis procedures; ethical considerations; and limitations.

    Project Methodology

    On April 14, 2016, the PAT nurses were instructed by this author during a 30-minute PowerPoint presentation on the value of preoperative OSA screening and were instructed on how to conduct OSA screening using the STOP-Bang questionnaire. To ensure competency, the nurses conducted STOP-Bang screening on each other. This author verified that all 14 of the PAT nurses demonstrated proficiency in conducting STOP-Bang screening. Beginning on April 25, 2016 all adult (ages 18-75) general anesthesia elective surgery patients were screened during the preoperative interview by the PAT nurses. Prior to conducting the STOP-Bang OSA screening, patients were informed by the PAT nurses that their answers on the questionnaire would provide important medical information that would be given to their anesthesiologist and surgeon before surgery.

    This quality improvement project employed a quantitative methodology with a comparative design. With this methodology, this author observed for statistically significant differences in the proportion of postoperative hypoxemia between two sample groups. Group A (n=100) was comprised of adult (ages 18-75) general anesthesia elective surgery patients who were screened preoperatively for OSA on the STOP-Bang OSA screening instrument. Group B (n=100) was comprised of adult (ages 18-75) general anesthesia elective surgery patients who were not screened preoperatively for OSA on the STOP-Bang OSA screening instrument. The problem statement for this project was: It is unknown whether adult (ages 18-75) general anesthesia elective surgery patients who undergo preoperative screening for OSA on the STOP-Bang questionnaire (at a 427-bed community medical center) during the one-month period following implementation of an OSA screening protocol will experience postoperative hypoxemia less frequently than adult (ages 18-75) general anesthesia elective surgery patients who do not undergo preoperative screening for OSA on the STOP-Bang questionnaire during the one-month period prior to implementation of the OSA screening protocol.

    A quantitative approach for this project was selected over a qualitative or mixed methodology. The data for this project is numerical; therefore, it is well-matched to a quantitative methodology. A time intensive mixed methodology was not selected due to project time constraints.

    Quantitative research falls under the umbrella of the theory of Positivism (Ingham-Broomfield, 2014). The principle of positivism is founded on the philosophy that knowledge is derived from the positive data of observable experience, and the ideal way of achieving this is through scientific methods of inquiry (Changing Minds, 2016). This author intends to make a concerted effort to gather and report data meaningfully, objectively, and without bias.

    Project Design

    This project comprised a combined prospective/retrospective comparative design which aligned with the projectís designated quantitative methodology. Comparative studies observe the dissimilarities amid intact groups on a dependent variable of interest (Nieswiadomy, 2012). The dependent variable was the occurrence of hypoxemia in the PACU. In keeping with the condition of a comparative design, the independent variable cannot be manipulated (Nieswiadomy). The independent variable was screening for OSA on the STOP-Bang screening questionnaire (either STOP-Bang screening was conducted, or was not conducted). A combined prospective/retrospective chart audit was conducted by this author following execution of the preoperative STOP-Bang OSA screening protocol. After implementation of the protocol, the PAT nurses screened all adult elective surgery patients for OSA using the STOP-Bang tool during the preoperative interview. Subsequently, 100 postoperative charts from the STOP-Bang OSA screened group, and 100 postoperative charts from the group not screened for OSA on the STOP-Bang questionnaire, were selected using a consecutive sampling technique. The incidence of postoperative hypoxemia, which occurred in the PACU, was compared between the two groups.

    The combined prospective/retrospective comparative design was chosen by this author because of its feasibility. It was projected to work well given the amount of time and resources available to conduct and complete this project. It was also selected due to the ability to implement a small change and then have access to readily accessible data to evaluate the change. It was not the intent of this author to conduct an empirical research study. Existing research provided support for the clinical practice change and the design allowed access to data to evaluate.

    Prior to implementing the STOP-Bang OSA screening program, the PAT nurses were instructed by this author on how to conduct OSA screening using the STOP-Bang questionnaire. This education was conducted on a one-on-one basis with all 14 PAT nurses. A return demonstration ensured competency.


    Population and Sample Selection

    The setting for the population and sample selection was a community hospital, with a 427-bed capacity, located in Californiaís Central Valley. The population encompasses all of the subjects that a researcher(s) is interested in studying (Rebar, Gersch, Macnee, and McCabe, 2010). In this case, the population was comprised of all adult (ages 18-75) general anesthesia elective surgery patients who presented to the facility in which 10,000 surgeries are performed annually.

    Following Institutional Review Board (IRB) approval, a subset of the overall population was selected to comprise the sample. The sample for this project was 100 adult (ages 18-75) postoperative elective surgery patients who had their surgical procedures performed under general anesthesia and were screened preoperatively for OSA on the STOP-Bang questionnaire and 100 adult (ages 18-75) postoperative elective surgery patients who had their surgical procedures performed under general anesthesia and were not screened preoperatively for OSA on the STOP-Bang questionnaire. Patients included in the sample were obtained through a consecutive sampling technique. In a consecutive sampling technique all subjects who meet inclusion criteria are selected until the required sample size is achieved (Lundsford and Lundsford, 1995). Only the charts of patients who had elective surgery, as noted by the operating room schedules, were examined. No distinction between types of surgery was considered in this project.

    Instrumentation

    The instrument that was used to collect the data for categorizing patients into either the OSA screened, or OSA not screened, group was the STOP-Bang OSA screening questionnaire. The STOP-Bang tool is proprietary to the University Health Network (UHN) in Toronto, Canada. Permission to use the tool was granted to this author (Appendix C).

    The STOP-Bang OSA screening instrument (Appendix A) was developed in 2008 by Dr. Frances Chung and her team. It is comprised of eight yes or no questions. The questions are built in to the acronym (Yang and Chung, 2013). The acronym, STOP-Bang, represents S- snoring (loud enough to be heard through a closed door?); T- tiredness (feeling fatigued during the daytime?); O- observed (observed by another to stop breathing or gasping/choking while asleep?); P- pressure (diagnosed hypertension?); B- body mass index (BMI) (more than 35?); A- age (over 50-years-old?); N- neck circumference (≥ 41 centimeters for women, and ≥ 43 centimeters for men?); and G- gender (male?). An affirmative response to up to two questions is indicative of low risk for OSA; an affirmative response to three to four questions is indicative of intermediate risk for OSA; and an affirmative response to five to eight questions is indicative of a high risk of OSA (Yang and Chung).

    The STOP-Bang tool is remarkably simple to use because of its yes or no design (Acar et al., 2014). STOP-Bang screening is efficient, and requires less than a minute to accomplish (Spence et al., 2015). The STOP-Bang OSA screening questionnaire is one of the OSA screening tools recommended by The Joint Commission for preoperative OSA screening (The Joint Commission, 2015). Currently, the STOP-Bang OSA screening questionnaire is one of two OSA screening tools recommended by the American Society of Perianesthesia Nurses (ASPAN) (ASPAN OSA Practice Recommendation Work Team, 2012).

    Validity

    The concept of validity is a facet of a measurement which reflects how precisely the measure produces information about the variable being studied (Rebar et al., 2010). If a measure accurately measures what it intended to measure, it is valid (Macnee and McCabe, 2008). The validity of the STOP-Bang screening instrument is concerned with what it measures, and how soundly it does so.

    The STOP-Bang questionnaire has been validated by multiple studies as a reliable instrument for the detection of individuals who have a high OSA index of suspicion (Chung et al., 2012). In terms of predictive value, Luo et al. (2014) found the STOP-Bang OSA screening tool to be superior to other validated OSA screening instruments, including both the venerated Berlin questionnaire and the Epworth Sleepiness Scale. A study by Abrishami et al. (2010) determined that the STOP-Bang OSA screening questionnaire exhibited reasonable accuracy along with high methodological validity. Vasu et al. (2010) found that when using a cut-off score of ≥ three, the STOP-Bang OSA screening instrument had a 91.7% sensitivity, a 63.4% specificity, as well as a high negative predictive capability. Kulkarni et al. (2014) found the positive predictive value of the STOP-Bang instrument to be 76%, with a sensitivity of 92.1%. Kulkarni et al. also found that the sensitivity for STOP-Bang OSA identification increased to 96% when OSA was diagnosed by polysomnography as moderate-severe (as evidenced by an apnea hypopnea index (AHI) > 15 hourly events), and 100% when OSA was diagnosed by polysomnography as severe (as evidenced by and AHI > 30 hourly events).

    The STOP-Bang instrument itself has been validated; however, it still must be administered correctly in order to yield valid results. Therefore, the PAT nurses were instructed by this author on how to accurately use the tool. Prior to conducting OSA screening with the STOP-Bang questionnaire, the PAT nurses gave a return demonstration to ensure competency. The STOP-Bang questionnaire was placed on the front of the patientsí paper charts for ease of preoperative review by the anesthesiologist and surgical services healthcare providers. This author provided all surgical services staff members with information about the STOP-Bang questionnaire by email and during a surgical services staff meeting prior to implementing the STOP-Bang OSA screening protocol.

    Reliability

    The concept of reliability means that a measure can be trusted to consistently give the same result, provided that the aspect being measured has not changed (Macnee and McCabe, 2008). The reliability of a measure becomes harder to guarantee as the measurement procedure becomes more complex, because complexity allows for more chances for error (Macnee and McCabe). The sheer simplicity of conducting STOP-Bang screening lends itself to consistently yielding correct and accurate results.
    Assuming that nothing changes, reliability has to do with how far a specific procedure, test, or instrument will produce similar results under different circumstances (Roberts, Priest, and Traynor, 2006). Acar et al. (2014) note that the design of the STOP-Bang OSA screening questionnaire is exceedingly simple. Similarly, Vasu et al. (2010) tout the ease of administering the STOP-Bang OSA screening questionnaire. Therefore, it is reasonable to assume that when a PAT nurse conducts STOP-Bang OSA screening, the results would be the same if another PAT nurse had conducted the screening. Sadeghniiat-Haghighi et al. (2015) note that the STOP-Bang questionnaire is a reliable and valid instrument for OSA screening.

    Data Collection Procedures

    The STOP-Bang OSA screening protocol was implemented for a one-month period at the selected 427-bed community hospital. During that time frame, the PAT nurses conducted OSA screening, using the STOP-Bang instrument, for all adult (ages 18-75) general anesthesia elective surgery patients. The PAT nurses used a paper copy of the STOP-Bang questionnaire.

    One hundred EHRs of patients who were screened for OSA preoperatively and 100 EHRs of patients who were not screened for OSA preoperatively were selected using a consecutive sampling technique. One hundred records of adult (ages 18-75) general anesthesia elective surgery patients not screened for OSA who were on the OR schedule during the second and third week of April, 2016, prior to implementation of the OSA screening program, were retrospectively audited in the order that they were listed on the OR schedule until the sample size of 100 charts was obtained. The charts of 100 adult (ages 18-75) general anesthesia elective surgery patients who were screened for OSA on the STOP-Bang tool following implementation of the OSA screening program, during the last week of April and first week of May, 2016, were prospectively audited in the order they were received by this investigator until the required sample size of 100 was obtained.

    All 200 charts were examined by this author. Descriptive data for age, gender, and BMI were obtained from the summary section of the EHRs. Data for the dependent variable, the occurrence of postoperative hypoxemia in the PACU, was retrieved from the PACU flowsheet section of the EHR. The incidence of hypoxemia that occurred in the OSA screened group was compared to the group who were not screened for OSA. The proportion of patients in the group screened for OSA who experienced hypoxemia in the PACU was less than the proportion of patients in the group who were not screened for OSA by a clinically significant margin. Of the 100 patients who were screened for OSA, 40 experienced hypoxemia in the PACU compared to 54 out of 100 patients who experienced hypoxemia in the PACU who were not screened for OSA. This data was statistically analyzed using SPSS version 18.
    Data collected on the incidence of hypoxemia in the STOP-Bang OSA screened and STOP-Bang OSA not screened groups was kept by this author and stored in a secure, password-protected computer file for the duration of the project period, and will remain there for three-years following project completion. No identifiers, such as name, date-of-birth, or medical record number were associated with the statistics. Only demographic data on gender, age, and BMI, OSA screening or lack of OSA screening, and the occurrence or lack of occurrence of postoperative hypoxemia was recorded.

    Data Analysis Procedures

    This DPI project employed a combined prospective/retrospective comparative design. The project sought to determine if adult (ages 18-75) general anesthesia elective surgery patients who were not screened preoperatively for OSA would experience hypoxemia more frequently in the PACU than adult (ages 18-75) general anesthesia elective surgery patients who were screened preoperatively for OSA. Data was collected through a prospective/retrospective chart audit of 100 patients who were screened preoperatively for OSA on the STOP-Bang instrument and 100 patients who were not screened preoperatively for OSA on the STOP-Bang instrument.

    The projectís supposition that the incidence of hypoxemia in the STOP-Bang OSA screened group would be less than in the STOP-Bang OSA not screened group was tested using Pearsonís Chi-Square (Goodness of Fit) test (Salkind, 2011). This author postulated that the proportion of patients who experienced postoperative hypoxemia in the PACU before implementation of the STOP-Bang OSA screening program would not be equal to the proportion of patients who experienced postoperative hypoxemia in the PACU after implementation of the STOP-Bang OSA screening program. Chi-Square analysis conducted using SPSS version 18 revealed a p-value of 0.149, which was not indicative of statistical significance because the p-value was greater than 0.05. However, there was a greater incidence of hypoxemia in the group who were not screened for OSA and this was clinically significant.
    Ethical Considerations

    Approval to conduct this project was sought and granted from the IRB at the facility where the project was conducted, as well as from the IRB at Grand Canyon University. This quality improvement project was deemed IRB exempt by Grand Canyon University and IRB expedited by the site organization. The procedures, rules, and regulations dictated by the IRB were strictly followed.

    This project intended to improve patient care and promote quality outcomes of surgical patients in the perioperative period by identifying patients who were at increased risk for OSA. STOP-Bang OSA screening results were provided to the anesthesiologist and surgical services healthcare team by placing the completed STOP-Bang OSA questionnaire on the front of the patientís paper chart, which then followed the patient into the OR theater. Heightened clinician awareness of the patientís probability of having undiagnosed/untreated OSA may lead to perioperative care plan modifications designed to enhance patient safety within this vulnerable population. Therefore, the intent of the project was to implement a new care practice; not to conduct empirical research to test a hypothesis. Research actions mandate full patient consent and IRB authorization; however, practice actions are held to a different standard (Macnee and McCabe, 2008).

    Patient privacy was rigorously safeguarded. As described in the section on data collection procedures, all statistical data abstracted from the EHR was stored in a secure computer file that is password-protected while the project was conducted, and will remain there for a three-year period following completion of the project, at which time it will be destroyed. All HIPAA regulations were adhered to stringently. No conflict of interest exists.

    Limitations

    This project had several limitations. One limitation was the relatively small sample size. A larger sample size would have been more likely to produce significant results; however, program time constraints prohibited collecting and analyzing additional records.

    Another limitation was that a retrospective chart audit was conducted. Any time data is abstracted retrospectively, there is the chance that the data might have been miscoded or missed (Liu et al., 2010). This limitation is typical of retrospective data collection procedures (Liu et al.).
    Confounding variables may also have contributed to this projectís limitations. Confounding variables, also known as extraneous variables, are variables the researcher is unable, or chooses not to control which may impact the results of the study (Nieswiadomy, 2012). In this case, there may have been patients in the group not screened for OSA who had a preexisting diagnosis of OSA. Additionally, the wide age range of adults (ages 18-75 years-old) could have influenced the development of postoperative hypoxemia for reasons other than the presence, or absence, of undiagnosed OSA. Elderly patients could reasonably be expected to have diminished renal and hepatic function when compared to younger patients; therefore, elderly patients may have developed postoperative hypoxemia in the PACU due to their diminished ability to metabolize and excrete sedatives, opioids, and other anesthetic agents administered in the perioperative period irrespective of whether or not they suffered from undiagnosed OSA. Demographic data on age and gender are presented in chapter 4.

    Summary

    Obstructive sleep apnea is a highly prevalent disorder (Franklin and Lindberg, 2015), yet the vast majority of people who have OSA remain undiagnosed (American Sleep Apnea Association, 2015). An abundance of research has established OSA as a risk factor for perioperative complications; therefore, the preoperative recognition of patients at high risk for OSA is a priority. This authorís DPI project involved the implementation of a preoperative OSA screening protocol using the validated STOP-Bang OSA instrument.

    In this chapter, the methodology that was used for the DPI project was described. The quality improvement STOP-Bang OSA screening protocol project used a quantitative methodology with a comparative design. The authorís rationale for selecting a quantitative methodology, as opposed to a qualitative or mixed methodology, was explained.

    The project design was a combined prospective/retrospective comparative design. This design aligned well with the projectís quantitative methodology. The rationale for the chosen project design was detailed in this chapter.

    The setting for the population and sample selection was described. The population and sample, previously acknowledged in the project design section of the paper, was detailed. The way in which patients, and patient privacy, was protected was addressed.

    For this authorís DPI project, the STOP-Bang OSA screening questionnaire was the instrument that was used to categorize patients into either the OSA screened, or the OSA not screened group. This validated tool is proprietary to the University Health Network (UHN) in Toronto, CA. Permission to use the tool was granted to this author (Appendix C). In this chapter, the STOP-Bang questionnaire was described in detail. The specific scale of measurement for the questionnaire was identified.
    The ASA recommends preoperative screening for OSA (Gross et al., 2014). The STOP-Bang OSA screening questionnaire is one of the OSA screening tools that is recommended by The Joint Commission for preoperative OSA screening (The Joint Commission, 2015). Currently, the STOP-Bang OSA screening questionnaire is one of two OSA screening tools recommended by the American Society of Perianesthesia Nurses (ASPAN) (ASPAN OSA Practice Recommendation Work Team, 2012).
    In this chapter, the concepts of validity and reliability were discussed. Procedures employed to assess the validity and reliability of the data that were collected was described. The validity and reliability of the STOP-Bang OSA screening instrument were detailed.

    Data collection, and the subsequent data analysis procedures that were used were described in detail. Each step of the data collection and data analysis procedures were outlined. The expectation is that other investigators are able to replicate this DPI project.

    Ethical considerations were discussed. Safe storage of the statistical data that was abstracted from the EHRs was described. Throughout this project, patient privacy was rigorously protected. HIPPA guidelines were closely followed.

    The final section of this chapter discussed the limitations related to the project. Several limitations were identified. An explanation of the limitations was given.

    The next chapter (chapter four) summarizes the data collected. The analysis of the data are described. Finally, the results of the data are presented and thoroughly explained.

    Chapter 4: Data Analysis and Results

    This Direct Practice Improvement (DPI) project aimed to answer a clinical PICOT question. The PICOT question asked was: During the one-month period following initiation of a STOP-Bang obstructive sleep apnea (OSA) screening protocol, will adult (ages 18-75) general anesthesia elective surgery patients who undergo preoperative OSA screening on the STOP-Bang questionnaire, compared to adult (ages 18-75) general anesthesia elective surgery patients who do not undergo preoperative OSA screening on the STOP-Bang questionnaire during the one-month period prior to initiation of a STOP-Bang OSA screening protocol, experience postoperative hypoxemia (defined by Liu et al. (2010) as a hemoglobin oxygen saturation ≤ 95% on pulse oximetry monitoring) less frequently in the Post Anesthesia Care Unit (PACU)? The problem statement for this project was: It is unknown whether adult (ages 18-75) general anesthesia elective surgery patients who undergo preoperative screening for OSA on the STOP-Bang questionnaire (at a 427-bed community medical center) during the one-month period following implementation of an OSA screening protocol will experience postoperative hypoxemia less frequently than adult (ages 18-75) general anesthesia elective surgery patients who do not undergo preoperative screening for OSA on the STOP-Bang questionnaire during the one-month period prior to implementation of the OSA screening protocol.

    This DPI project was conducted at a 427-bed community hospital located in the Central Valley of California. A quantitative methodology with a comparative design was utilized. The independent variable was STOP-Bang OSA screening and the dependent variable was postoperative hypoxemia in the PACU. Pearsonís Chi-Square test was used to determine the association between the variables and to establish the probability that the STOP-Bang OSA screening intervention affected the incidence of postoperative hypoxemia in the PACU. This chapter summarizes the data that has been collected and shows how the data was analyzed statistically. The results of the data are presented and explained.

    Descriptive Data

    The population for this project was comprised of all adult (ages 18-75) patients who presented to the 427-bed community medical center for an elective surgical procedure under general anesthesia. A subset of the overall population was selected to comprise the sample. The sample for this project consisted of 100 postoperative elective surgery patients who had their surgical procedures performed under general anesthesia and were screened preoperatively for OSA on the STOP-Bang questionnaire and 100 postoperative elective surgery patients who had their surgical procedures performed under general anesthesia and were not screened preoperatively for OSA on the STOP-Bang questionnaire.
    The design for this project was a combined prospective/retrospective comparative design. One hundred electronic health records (EHRs) of patients who were screened for OSA preoperatively and 100 EHRs of patients who were not screened for OSA preoperatively were selected using a consecutive sampling technique. Following site organization and Grand Canyon University IRB approval, the charts of adult (ages 18-75) general anesthesia patients who were on the OR schedule for an elective surgical procedure during the period between April 12, 2016 Ė April 20, 2016 were retrospectively audited in the order that they were listed on the OR schedule until the sample size of 100 charts was obtained. This time frame was prior to implementation of STOP-Bang OSA screening by the PAT nurses. Screening for OSA by the PAT nurses commenced on April 25, 2016. Between the period of April 26 Ė May 5, 2016, the charts of 100 adult (ages 18-75) general anesthesia elective surgery patients who were screened for OSA on the STOP-Bang tool were prospectively audited in the order they were received by this investigator until the required sample size of 100 was obtained. The incidence of postoperative hypoxemia which occurred in the PACU was compared between the two groups.
    Descriptive statistical data obtained from the sample of 200 EHRs revealed that most patients were within the age range of: 65 to 75 years old (27.5%), female (57%), and had a body mass index (BMI) range of 25.1 Ė 30 kg/m2 (32.5%). Of the 100 patients in the group who were screened for OSA on the STOP-Bang questionnaire, 39% (n = 39) were male and 61% (n = 61) were female. The age range was 25 Ė 75 years old. The body mass index (BMI) range was 18 Ė 50 kg/m2. Of the 100 patients in the group who were not screened for OSA on the STOP-Bang questionnaire, 47% (n = 47) were male and 53% (n = 53) were female. The age range was 18 Ė 75 years old. The BMI range was 17 Ė 47 kg/m2 (Table 1).


    Table 1

    Descriptive Statistics of Demographic Variables
    Measure É % M SD

    Gender
    Female
    Pre STOP-Bang 53 53
    Post STOP-Bang 61 61
    Male
    Pre STOP-Bang 47 47
    Post STOP-Bang 39 39
    Age-Pre STOP-Bang 51.36 15.13
    18-27 years 7 7
    28-37 years 14 14
    38-47 years 20 20
    48-57 years 21 21
    58-67 years 18 18
    68-75 years 20 20
    Age-Post STOP-Bang 56.56 13.89
    18-27 years 2 2
    28-37 years 13 13
    38-47 years 9 9
    48-57 years 22 22
    58-67 years 29 29
    68-75 years 25 25
    BMI-Pre STOP-Bang 30.14 6.04
    10-20 3 3
    21-30 54 54
    31-40 36 36
    41-50 7 7
    BMI-Post STOP-Bang 30.64 8.10
    10-20 6 6
    21-30 52 52
    31-40 30 30
    41-50 12 12



    Data Analysis Procedures

    Following expedited Institutional Review Board (IRB) approval from the site organization and IRB exempt approval from Grand Canyon University (GCU) data collection commenced. Data was retrospectively extrapolated from 100 consecutively procured EHRs within the one-month period prior to the implementation of the STOP-Bang OSA screening program. Dates of retrospective data collection were from April 12, 2016 through April 20, 2016. Data was prospectively extrapolated from 100 consecutively procured EHRs beginning on April 26, 2016, which was the first day of prospective data collection, and ended on May 5, 2016 when the 100th EHR was audited. Data on the incidence of postoperative hypoxemia in the group who were screened preoperatively for OSA and the group who were not screened preoperatively for OSA were analyzed using Pearsonís Chi-Square (Goodness of Fit) test (Salkind, 2011) conducted by SPSS version 18 software.

    Results

    After screening patients with the STOP-Bang questionnaire, the PAT nurses placed the completed and scored STOP-Bang questionnaires on the front of the patientsí paper charts. Subsequently, the paper charts accompanied the patients to the preoperative holding area and into the operating room theater. Patientsí anesthesiologists and surgeons reviewed the STOP-Bang results prior to surgery.
    For this quality improvement project, a single PICOT question was asked. The question was: During the one-month period following initiation of a STOP-Bang OSA screening protocol, will adult (ages 18-75) general anesthesia elective surgery patients who undergo preoperative OSA screening on the STOP-Bang questionnaire, compared to adult (ages 18-75) general anesthesia elective surgery patients who do not undergo preoperative OSA screening on the STOP-Bang questionnaire during the one-month period prior to initiation of a STOP-Bang OSA screening protocol, experience postoperative hypoxemia (defined by Liu et al. (2010) as a hemoglobin oxygen saturation ≤ 95% on pulse oximetry monitoring) less frequently in the Post Anesthesia Care Unit (PACU)? To answer the PICOT question, data obtained from patientsí EHRs were analyzed by Chi Square analysis using SPSS version 18. It was noted that there was a statistically nonsignificant, but clinically significant, difference in the proportion of patients who experienced hypoxemia in the PACU between the two groups. The occurrence of postoperative hypoxemia was greater in the group not screened preoperatively for OSA on the STOP-Bang questionnaire.

    April 12, 2016 marked the date when initial data collection commenced. The retrospective chart audit of the 100 EHRs from the one-month period prior to the initiation of the STOP-Bang OSA screening program was conducted first. The first record retrospectively audited was from April 12, 2016 and the last record audited was from April 20, 2016. The prospective chart audit of the 100 EHRs from the one-month period following initiation of the STOP-Bang OSA screening program was conducted second. The first record prospectively audited was from April 26, 2016. The last record prospectively audited was from May 5, 2016.

    A Chi-square analysis using SPSS version 18 software was conducted comparing the proportion of positive postoperative hypoxemia occurrences in the PACU. In support of this investigatorís theory, the proportion of patients who experienced hypoxemia in the PACU pre implementation of the STOP-Bang screening program was not equal to the proportion of patients who experienced hypoxemia in the PACU post implementation of the STOP-Bang screening program, χ2 (1, N = 94) = 2.085, p = .149. There was an observed frequency of 40 occurrences of postoperative hypoxemia in the PACU in the post STOP-Bang implementation group, compared to 54 occurrences of postoperative hypoxemia in the PACU in the pre STOP-Bang implementation group (Table 2). Given an expected proportion of 47 patients to experience hypoxemia in the PACU for both pre and post implementation of the STOP-Bang screening program, there was a statistically nonsignificant shift toward fewer patients who experienced hypoxemia in the PACU post implementation of the STOP-Bang screening program.
    Table 2

    Pearson Chi-Square Goodness of Fit Between Implementation of the STOP-Bang Screening Program and Proportion of Patients who Experience Hypoxemia in the PACU

    Proportion who Experienced Hypoxemia in the PACU

    Implementation O E χ2 df



    Pre STOP-Bang screening 54 47 2.085 1

    Post STOP-Bang screening 40 47
    p = .149


    Figure 1 shows STOP-Bang frequencies, percentages, and total score breakdown. This figure reflects the STOP-Bang scores for the project population of the 100 patients who were screened preoperatively for OSA. It is striking that nearly one out of five adult (ages 18-75) general anesthesia elective surgery patients screened at high risk for OSA on the STOP-Bang questionnaire. These results underscore the importance of preoperative OSA screening.

    Figure 2 shows the percentages of level of OSA risk in pie chart format. The prevalence of low risk for OSA within the projectís STOP-Bang screened adult (ages 18-75) general anesthesia elective surgery patient population was 39%. The prevalence of intermediate risk for OSA within this population was 42%. The prevalence of high risk for OSA within this population was 19%. The level of intermediate-high risk classification for this population was 61%. These figures highlight the significance of preoperative OSA screening.

    Figure 3 shows the incidence of postoperative hypoxemia in the PACU within the group who were screened preoperatively for OSA on the STOP-Bang screening questionnaire, compared to the group who were not screened preoperatively for OSA on the STOP-Bang screening questionnaire. There were 54/100 occurrences of hypoxemia in the group not screened for OSA, compared to 40/100 occurrences of hypoxemia in the group who were screened for OSA. Although not statistically significant, this is clinically significant. These results underline the value of preoperative OSA screening.

    Figures in attached document

    The incidence of postoperative hypoxemia in the STOP-Bang OSA screened group and the incidence of postoperative hypoxemia in the STOP-Bang OSA not screened group is illustrated in bar chart format.



    Summary

    This DPI quality improvement project sought to answer a clinical PICOT question to determine if the incidence of postoperative hypoxemia in the PACU experienced by adult (ages 18-75) general anesthesia elective surgery patients who were screened preoperatively on the STOP-Bang OSA screening questionnaire would be significantly less than incidence of postoperative hypoxemia in the PACU experienced by adult (ages 18-75) general anesthesia elective surgery patients who were not screened preoperatively on the STOP-Bang OSA screening questionnaire. Descriptive data was collected and analyzed. Results of patientsí gender, age, and BMI were reported in narrative and table format.

    The retrospective chart review of 100 EHRs from the one-month period prior to implementation of the STOP-Bang OSA screening protocol was conducted between April 12, 2016 and April 20, 2016. The prospective chart review of 100 EHRs from the one-month period following implementation of the STOP-Bang OSA screening protocol was conducted between April 26, 2016 and May 5, 2016. Data on the incidence of postoperative hypoxemia in the group who were screened preoperatively for OSA and the group who were not screened preoperatively for OSA were a

    The results of the retrospective and prospective chart audits provided the answer to the clinical PICOT question. The proportion of patients who experienced postoperative hypoxemia in the PACU prior to implementation of the STOP-Bang screening program was not equal to the proportion of patients who experienced hypoxemia in the PACU after implementation of the STOP-Bang screening program. A Chi-square analysis was calculated comparing the proportion of positive postoperative hypoxemia in the PACU occurrences and a statistically nonsignificant difference was found between the two groups. Although the difference between the two groups was statistically nonsignificant, the implementation of the STOP-Bang OSA screening program has noteworthy clinical significance. Anesthesiologists, surgeons, and perioperative nurses have shown support for the OSA screening program and have applauded the value of promoting clinician awareness of the potential existence of OSA among surgical patients. The STOP-Bang OSA screening program is a valued patient safety initiative at the site facility.
    The next chapter, chapter five, will comprehensively summarize the project in its entirety. The importance of the preoperative screening for OSA will be reiterated in chapter five. An explanation of how the project will contribute to the body of knowledge already in existence regarding the merit of preoperative screening for OSA will be clarified. Finally, plans to disseminate salient information gleaned from the project will be discussed.



    Chapter 5: Summary, Conclusions, and Recommendations

    Obstructive sleep apnea (OSA) is a serious and ubiquitous condition (Franklin and Lindberg, 2015). Approximately 25 million people are afflicted with OSA in the United States, according to the American Academy of Dental Sleep Medicine (2016). It is projected that about 80% of individuals who currently suffer from OSA are unaware of it (American Sleep Apnea Association, 2015). This is particularly concerning for surgical patients because individuals with OSA are often afflicted with comorbidities that have the potential to elevate their risk of perioperative complications (Kim, Koo, Lee, and Lee, 2016). Patients who suffer from OSA are at heightened risk for problematical airway management, including difficult endotracheal intubation and difficult mask ventilation (Auckley and Bolden, 2012; Porhomayon, El-Solh, Chhangani, and Nader, 2011). Moreover, patients with OSA are highly sensitive to medications and anesthetics which could conceivably result in perioperative airway compromise (Gross et al., 2014).

    Preoperative screening for OSA stands as an essential measure to help promote clinician identification of patients who are possibly at risk for this serious syndrome (Diffee, Beach, and Cuellar, 2012). Ensuing modifications by clinicians to the perioperative care plan for patients with known, or suspected, OSA can augment the safety of this susceptible population (Vasu, Grewal, and Doghramji, 2012). Screening for OSA preoperatively is in alliance with The Joint Commissionsí, the American Society of Anesthesiologistsí, and the American Society of Perianesthesia Nursesí recommendations (ASPAN OSA Practice Recommendation Work Team, 2012; Gross et al., 2014; The Joint Commission, 2015). For this authorís DPI project, the STOP-Bang OSA screening tool was specifically selected over other validated OSA screening instruments due to its simplicity and ease of use, as well as its endorsement by The Joint Commission and the American Society of Perianesthesia Nurses.

    This quality improvement project was designed to implement a preoperative OSA screening program using the validated STOP-Bang OSA screening tool at a 427-bed community hospital. Preceding program implementation, the Preadmission Testing (PAT) nurses were educated by this author on the value of preoperative OSA screening by a 30-minute PowerPoint presentation and were successively instructed on how to conduct OSA screening by means of the STOP-Bang OSA screening questionnaire. Following implementation of the program, all adult (ages 18-75) general anesthesia elective surgery patients were screened for OSA on the STOP-Bang questionnaire. Prior to surgery, anesthesiologists and surgeons were informed of the patients STOP-Bang scores which were noted on the front of the patientsí paper charts. The quality improvement project was chosen due to its prospective to promote patient well-being and safety during the perioperative phase.

    The most common complication encountered by surgical patients who have OSA is hypoxemia (Pereira et al., 2013). Postoperative hypoxemia in the PACU was selected as the dependent variable for the project. This author postulated that the incidence of postoperative hypoxemia would be less in the group of patients who were screened preoperatively for OSA on the STOP-Bang questionnaire, when compared to the group not screened preoperatively for OSA on the STOP-Bang questionnaire, due to healthcare provider awareness of the potential for OSA.


    Summary of the Project


    This Direct Practice Improvement (DPI) project intended to answer an important clinical PICOT question. The PICOT question that framed this project was: During the one-month period following initiation of a STOP-Bang OSA screening protocol, will adult (ages 18-75) general anesthesia elective surgery patients who undergo preoperative OSA screening on the STOP-Bang questionnaire, compared to adult (ages 18-75) general anesthesia elective surgery patients who do not undergo preoperative OSA screening on the STOP-Bang questionnaire during the one-month period prior to initiation of a STOP-Bang OSA screening protocol, experience postoperative hypoxemia (defined by Liu et al. (2010) as a hemoglobin oxygen saturation ≤ 95% on pulse oximetry monitoring) less frequently in the PACU? The results of this DPI projectís relation to the clinical PICOT question will be discussed herein.
    Patients at the site facility were not screened for OSA prior to implementation of the STOP-Bang OSA screening program. Following implementation of the STOP-Bang OSA screening protocol, clinicians were made aware of surgical patientsí risk for OSA by STOP-Bang questionnaire results that were placed on the front of the patientsí paper charts. This author postulated that pertinent perioperative care plan alterations made by clinicians, for patients at risk for OSA according to STOP-Bang OSA screening results, would potentially result in a reduced occurrence of postoperative hypoxemia in the PACU. The frequency of postoperative hypoxemia in the PACU prior to implementation of the preoperative STOP-Bang OSA screening protocol, compared to the frequency of postoperative hypoxemia in the PACU following implementation of the preoperative STOP-Bang OSA screening protocol is expounded on in the next section of this chapter. This chapter will also address the summary of the project findings and conclusions; practical, future, and theoretical implications; recommendation for future projects; and recommendations for future practice. This DPI project was carried out by implementation of the following steps: Site approval procured; IRB approval from GCU (Appendix D) and the site facility (Appendix E) was obtained; data was collected from April 12 - May 5, 2016; data was analyzed by Chi Square analysis using SPSS version 18; and project results were summarized and explained.

    Summary of Findings and Conclusions

    An abundance of evidence subsists in the literature which underscores the existence of heightened risk for adverse outcomes during the perioperative phase amongst surgical patients afflicted with OSA. According to Pereira, Xara, Mendonca, Santos, and Abelha (2013), hypoxemia is the most frequently encountered complication by OSA patients. Hypoxemia, as well as other perioperative complications can be mitigated, or evaded, when the perioperative care plan is designed to meet the distinct needs of the patient with known or suspected OSA. Therefore, clinician awareness of patientsí risk for OSA is paramount.

    A noteworthy clinical question outlined this DPI project. The question was: During the one-month period following initiation of a STOP-Bang OSA screening protocol, will adult (ages 18-75) general anesthesia elective surgery patients who undergo preoperative OSA screening on the STOP-Bang questionnaire, compared to adult (ages 18-75) general anesthesia elective surgery patients who do not undergo preoperative OSA screening on the STOP-Bang questionnaire during the one-month period prior to initiation of a STOP-Bang OSA screening protocol, experience postoperative hypoxemia (defined by Liu et al. (2010) as a hemoglobin oxygen saturation ≤ 95% on pulse oximetry monitoring) less frequently in the PACU? The specific findings of the project are subsequently conveyed.

    Analysis of data from this DPI project answered the clinical PICOT question. The results are clinically, but not statistically significant. The occurrence of postoperative hypoxemia in the PACU was tallied by this author during the chart audits. It was determined that the proportion of patients who experienced postoperative hypoxemia in the PACU before implementation of the STOP-Bang OSA screening program was not equal to the proportion of patients who experienced postoperative hypoxemia in the PACU after implementation of the STOP-Bang OSA screening program. Analysis of the recorded incidence of postoperative hypoxemia in the PACU documented in the electronic health record (EHR) revealed that the pre-STOP-Bang screening group experienced 54/100 incidences of postoperative hypoxemia in the PACU, while the post-STOP-Bang screening group experienced 40/100 incidences of postoperative hypoxemia in the PACU. A Chi-square analysis using SPSS version 18 software was conducted comparing the proportion of positive postoperative hypoxemia in the PACU occurrences and a nonsignificant difference was found between the two groups, χ2 (1, N = 94) = 2.085, p = .149. A cross-tabulation analysis showed that the proportion of patients who experienced hypoxemia in the PACU pre-implementation of the STOP-Bang screening program was greater than the proportion of patients who experienced hypoxemia in the PACU post implementation of the STOP-Bang screening program. Although the difference between the groups was statistically insignificant, the implementation of the STOP-Bang OSA screening program was clinically significant because it served as an important patient safety initiative. An abundance of evidence-based, peer-reviewed research literature has been presented in this manuscript to support the benefit of preoperative screening for OSA.

    There is a surplus of literature that corroborates the significance of preoperative recognition of OSA by clinicians (STOP-Bang.ca, 2016). A plethora of research on the perioperative risks associated with OSA has been conducted, primarily within the last twenty years (Memtsoudis, Besculides, and Mazumdar, 2013). According to the Agency for Healthcare Research and Quality (2001), it is well accepted that the translation of research into evidence-based clinical practice may take up to twenty years. This authorís quality improvement project helped lessen the gap between research and clinical practice.
    A fundamental goal of this project was to amplify clinician cognizance of the impact of OSA in the perioperative period with the intention of promoting patient safety. The conceptual framework for this DPI project was provided by the Iowa Model for Evidence-Based Practice to Promote Quality Care (Iowa model). The Iowa Model served as the foundation to implement a preoperative OSA screening protocol at a 427-bed community hospital, an EBP change. The Iowa model encompasses seven steps: Problem-focused and knowledge-focused triggers; Priority of the topic; Formation of a team; Obtaining sufficient research to guide practice; Piloting the change in practice; Adoption of the practice; and Analysis, evaluation, and dissemination (Brown, 2014). The first six steps of the Iowa model have been implemented. Analysis, evaluation, and dissemination of the project results will continue on an ongoing basis by this author. The implementation of the preoperative STOP-Bang OSA screening protocol effectively decreased the chasm between the plethora of concrete research that recommends preoperative OSA screening and a worthwhile evidence-based clinical practice change.

    Practical, Future, and Theoretical Implications

    This DPI project is in accordance with the recommendation for preoperative OSA screening by The Joint Commission as well as other prominent professional organizations, including the American Society of Anesthesiologists and the American Society of Perianesthesia Nurses (ASPAN OSA Practice Recommendation Work Team, 2012; Gross et al., 2014; The Joint Commission, 2015). The results of this DPI project revealed a decrease in the incidence of postoperative hypoxemia in the PACU in the STOP-Bang OSA screened group compared to the group not screened for OSA on the STOP-Bang questionnaire. Although not statistically significant, these results highlight the practical importance of continuing the STOP-Bang OSA screening program the site facility as an important patient safety initiative.

    Another positive practical outcome of this quality improvement project is that some patients identified at high risk for OSA, according to the STOP-Bang questionnaire results, were subsequently referred for a polysomnography study to conclude if a definitive diagnosis of OSA exists. When a definitive diagnosis of OSA is determined by a polysomnography study, ensuing treatment with continuous positive airway pressure can mitigate or avert the long-term deleterious effects of OSA on health outcomes (Yang, Huang, Lan, Wu, and Huang, 2015). Therefore, sleep study referrals that resulted from this project theoretically have the potential to considerably improve the future long-term health outcomes of patients with OSA. It will be important to track the polysomnography results of patients referred for the sleep study based on STOP-Bang questionnaire scores to support continuation of the STOP-Bang OSA screening program.

    Recommendations for Future Projects

    This DPI project encompassed a quantitative methodology with a comparative design. Using this methodological approach, this author looked at the proportion of postoperative hypoxemia that occurs among two sample groups. One group was comprised of 100 adult (ages 18-75) general anesthesia elective surgery patients who were screened preoperatively for OSA with the STOP-Bang OSA screening questionnaire while the other group was comprised of 100 adult (ages 18-75) general anesthesia elective surgery patients who were not screened preoperatively for OSA with the STOP-Bang OSA screening questionnaire. A single dependent variable, the incidence of postoperative hypoxemia in the PACU was observed.

    It is a recommendation of this author that future projects with similar methodologies and designs as this DPI project be conducted. Potential dependent variables to be observed following implementation of a preoperative OSA screening program include prolonged PACU admission time, unexpected admissions of ambulatory surgical patients, and/or unanticipated admission to a higher level of care such as to an intensive care unit. Results of such projects could support the permanent adoption of a preoperative OSA screening program.

    A limitation present in this project was that the sample size of 200 subjects was relatively small. A future project identical to this DPI project, except for the use of a much larger sample size is recommended. With a quantitative methodology, the larger the sample size, the higher the probability that the sample will accurately represent the population of interest (Macnee and McCabe, 2008). The ability to achieve statistical significance would be enhanced with larger sample sizes. However, for this DPI project, it was not feasible to use a large sample size due to the limited time allotted to complete the project.

    Another recommendation for a future project involves using a qualitative methodology. The recommended project would entail surveying anesthesia providers regarding their attitudes and practice patterns related to OSA patients in the perioperative venue, similar to the study conducted by Auckley, Cox, Bolden, and Thornton (2015). Auckley et al. concluded that most physicians felt that OSA is a significant risk factor for complications in the perioperative period and most had experience with an adverse outcome related to OSA. The results of the suggested project could provide the necessary support to promote the development and utilization of evidence-based OSA perioperative management guidelines; thereby promoting perioperative patient safety.

    This incidence of obesity is greater in Californiaís Central Valley compared to other geographical locations in the United States (National Public Radio, 2014). Obesity is a significant risk factor for OSA (Diffee et al., 2012). Therefore, it is this authorís recommendation that a project matching this DPI be conducted in a geographic area outside of Californiaís Central Valley.

    Recommendations for Future Practice

    This evidence-based practice DPI project underscored the significance of preoperative OSA screening. Patients who were screened preoperatively for OSA on the STOP-Bang OSA screening tool experienced a lower incidence of postoperative hypoxemia in the PACU. Therefore, it is the recommendation of this author that the site facility continue to screen patients for OSA preoperatively with the STOP-Bang OSA screening instrument. It is also recommended that the site facility affiliates adopt a similar OSA screening program.

    Another recommendation for future practice is that the site facility conduct OSA screening for all patients who present to the facility. This practice would potentially increase the number of patients who are identified at high-risk for OSA. Subsequent referrals to a sleep center for polysomnography studies could lead to better long-term health outcomes for individuals definitively diagnosed with OSA.
    Currently, most institutions lack OSA management guidelines (Auckley et al., 2015). A recommendation for future practice is the development of standardized EBP clinical perioperative OSA management guidelines. Implementation of such guidelines could serve to promote safe, high quality, perioperative care delivery.

    Conclusion

    It is well-documented that the prevalence of OSA is greater in the surgical population than in general population (Memtsoudis et al., 2013). Patients with OSA are at greater risk for perioperative complications than patients who do not have OSA (Kaw et al., 2012). Consequently, the significance of preoperative OSA screening cannot be over-stressed.

    Hypoxemia is the most frequently encountered perioperative complication in patients who have OSA (Pereira et al., 2013). Hypoxemia, as well as other perioperative complications may be mitigated, or circumvented, when the perioperative care plan is aimed to meet the distinct needs of the patient with OSA. Preoperative screening for OSA by means of the STOP-Bang questionnaire intends to heighten clinician awareness of patients at high risk for OSA and allows for appropriate perioperative care plan modifications to promote patient safety among this at risk population.

    Conducting this DPI project was worthwhile. The project heightened surgical services cliniciansí and administratorsí recognition of the unique perioperative considerations that pertain to patients with known or suspected OSA. When patients screen positive for OSA on the STOP-Bang tool, the importance of a referral to the primary care provider for possible definitive OSA testing by a polysomnography sleep study was underscored by this project. Based on the recommendation of the Chief of Anesthesia at the site facility, hospital administrators have unanimously decided to implement the OSA screening protocol introduced by this project on a permanent basis. That is a testimony to the success of this DPI project in leading to an important evidence-based clinical practice change designed to promote patient safety and well-being.











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    I am looking for any kind of advice for choosing between the Midwestern

    Carna 2 Days Ago Go to last post
    doubleA

    How do I look?

    On paper you look awesome! Have you figured out what program you like best? Pick 1 or 2 programs and shadow a class. Meeting current students and showing

    doubleA 3 Days Ago Go to last post
    perezs13

    How do I look?

    I'm not a SRNA, but I am definitely interested in applying soon. From the research I've gathered, it definitely seems like you are competitive! I think

    perezs13 6 Days Ago Go to last post
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