Monitoring for Opioid Induced Respiratory Depression: Paradigm Shift from Threshold Monitoring to Trend Monitoring Carla R. Jungquist, ANP BC, PhD Assistant Professor University at Buffalo J. Paul Curry, MD Past Chief of Staff Hoag Memorial Hospital and Clinical Professor UCLA Dept. Anesthesiology Conflict of Interest Disclosure Authors Conflicts of Interest: A. Jungquist Serve as expert witness for cases of personal injury or death from opioid induced respiratory depression B. Curry Consultant with Lyntek Medical Technologies that holds patents on real time advanced clinical pattern recognition Objectives Describe current monitoring practices and possible legal consequences from adverse events Describe the physiology of respiration as it relates to identifying impending respiratory depression Identify disease and conditions associated with increased risk of opioid induced respiratory depression Describe best practices for the use of electronic monitoring. 1
Why we care Postoperative hypoxemia, defined as oxygen saturation (SpO 2 ) below 90%, is a multifactorial problem affecting as many as 76% of our patients. (Curry, 2003) Opioid related adverse events in post surgical populations is associated with: increased length of hospitalization greater hospital costs higher likelihood for 30 day readmissions higher mortality rates Why we care In an extensive review of 24 legal cases associated with Obstructive Sleep Apnea that went to jury decisions, all cases (11) that occurred on post surgical units involved opioids and resulted in either severe anoxic brain injury or death. Settlements ranged from $650,000 $7.7 million. The incidence has been progressively increasing since 1991. (Fouladpour, 2015) How Nurses Recognize Patients at Risk 2
2009 & 2013 Monitoring Practices High Risk Only All Patients 2013 (n=102) 2009 (n=90) 2013 (n=102) 2009 (n=90) Intermittent Pulse Oximetry Epidural 30% 21% 38% 36% IV PCA 36% 22% 42% 36% Oral/IV 34% 20% 40% 37% Continuous Pulse Oximetry Epidural 41% 25% 37% 31% IV PCA 41% 32% 28% 20% Oral/IV 17% 27% 5% 13% End Tidal Carbon Dioxide Epidural 10% 6% 7% 2% IV PCA 14% 8% 11% 2% Oral/IV 8% - 1% - Use of sedation scales 2013 (n=102) 2009 (n=90) Pasero Opioid Scale 53% 21% Aldrete Scale 39% 30% Ramsey Scale 17% 15% Modified Ramsay Scale 13% 13% Richmond Agitation-Sedation Scale 42% 12% Riker Scale/Modified Riker Scale 6% 8% Scale developed at your institution 8% <1% Motor Activity Assessment Scale 1% <1% Glasgow Coma Scale 37% <1% University of Michigan Scale 4% <1% Best Practice for IV PCA Every 2.5 hours for the first 24 hours: respiratory rate level of sedation and SpO 2 with pulse oximetry 3
2012 Hospital Practice Comparing Best Practice to the hospital monitoring practices, we found that: 8.3% of the patients on opioid IV PCA were being monitored per best practice. If we changed the timeframe to every 4.5 hours 26.8% of the patients were monitored using the 3 parameters of RR, PO, SS. Scratch, the Cat 4
Orion, the Hunter Review of respiratory physiology Review of respiratory physiology 5
Three Patterns Of Respiratory Dysfunction Type I A healthy male who had just undergone elective surgery develops shortness of breath that s noticed by his family who express concern to the nurse. The nurse, citing a normal oxygen saturation reading on his oximeter, reassures the family that the monitor indicates he s okay. Eventually his respiratory rate does rise to a critical value, but by this time it s too late to effectively respond to his rapidly deteriorating clinical condition and the patient, with sepsis, dies. Framework of three patterns of respiratory dysfunction Three patterns of respiratory dysfunction Type II A healthy female who is receiving routine post op nasal oxygen has been up all night complaining of severe post op pain, but is now finally asleep after yet another dose of IV opioid. The nurse, noticing on rounds the patient s oxygen saturation is perfect on the monitor, decides not to awaken her. She is found dead in bed 4 hours later. 6
Framework of three patterns of respiratory dysfunction Math Counts! The alveolar gas equation: [PA02 = FIO2(PATM PH2O) PaCO2/RQ] PAO2 PaO2 (A a gradient) = (Pt. age + 10)/4 Henderson Hasselbach equation (ph=6.1+log(hco3/(0.03xpaco2)) Automated mathematical models like HbO.Dash are used by blood gas laboratories, correlating reliable saturation values off any known PaO2 How Nurses Recognize Patients at Risk Simulated SPO 2 values associated with FIO 2 and PaCO 2 /arterial ph FIO 2 PaCO 2 55mmHg (ph 7.26) Oximeter 90% alarm breach SPO 2 drift PaCO 2 70mmHg (CO 2 Narcosis) Oximeter 90% alarm breach SPO 2 drift 30yo Patient Model.21 SPO 2 91% + + +.24 SPO 2 95% SPO 2 89% + +.27 SPO 2 93% +.30 SPO 2 98% SPO 2 95% 7
How Nurses Recognize Patients at Risk Simulated SPO 2 values associated with FIO 2 and PaCO 2 /arterial ph FIO 2 PaCO 2 55mmHg (ph 7.26) Oximeter 90% alarm breach SPO 2 drift PaCO 2 70mmHg (CO 2 Narcosis) Oximeter 90% alarm breach SPO 2 drift 50yo Patient Model.21 SPO 2 89% + + + +.24 SPO 2 94% + SPO 2 87% + +.27 SPO 2 93% +.30 SPO 2 95% How Nurses Recognize Patients at Risk Simulated SPO 2 values associated with FIO 2 and PaCO 2 /arterial ph FIO 2 PaCO 2 55mmHg (ph 7.26) Oximeter 90% alarm breach SPO 2 drift PaCO 2 70mmHg (CO 2 Narcosis) Oximeter 90% alarm breach SPO 2 drift 75yo Patient Model.21 SPO 2 87% + + + +.24 SPO 2 93% + SPO 2 84% + +.27 SPO 2 96% SPO 2 91% +.30 SPO 2 95% Framework of three patterns of respiratory dysfunction Type III An otherwise healthy male with unrecognized sleep apnea receives a post operative opioid. His alarm sounds repeatedly but lasts only for about 30 seconds before it stops, only to repeat again and again. When the nurse awakens the patient he feels fine and is completely alert, asking for more pain medication, which the nurse gives in a normal dose. The nurse, suffering from alarm fatigue, stops responding to the same alarming. Later that night the patient is found dead in bed. 8
Framework of three patterns of respiratory dysfunction Framework of three patterns of respiratory dysfunction Pulse Oximetry Perhaps all patients in the first 48 hours post op should be continuously monitored, but remember we have a lot of patients on IV opioids for acute pain control that are not undergoing a procedure. Patients are in the hospital because they need us to take care of them!!! Letting your patient get a good night of sleep is not taking good care of them. Intermittent timing and technique is the problem 9
Respiration is the most vulnerable during sleep We missed the desaturations!! What is wrong with this picture??? 10
ETCO2 Minute Volume Recommendations for best monitoring practices Regardless of the type of electronic monitoring or nurse monitoring, the most important point I want you to take from this talk is that patient s have individual response to opioids and the only way we will be able to figure out if they are in trouble is to compare their parameters to their baseline. Keep in mind the different patterns of dysfunction. Know your patient s risks and how best to provide safe and effective pain control. 11
References 1. Samuels & Rabinov (1986 ) Difficulty Reversing Drug induced Coma in a Patient with Sleep Apnea. Anesthesia Analgesia. 2. Khoo, Mukherjee, Phua & Xia Shi (2009) Obstructive Sleep Apnea Presenting as Recurrent Cardiopulmonary Arrest. Sleep Breath. 3. APSF NEWSLETTER (2002) Sleep Apnea and Narcotic Postoperative Pain Medication: A Morbidity and Mortality Risk. 4. Chung et al. (2015) Postoperative Sleep Disordered Breathing in Patients Without Preoperative Sleep Apnea: Anesthesia Analgesia. 5. Taenzer, Pyke, McGrath, Blike (2010) Impact of Pulse Oximetry Surveillance on Rescue Events and Intensive Care Unit Transfers: Anesthesiology. 6. Foulapour, Jesudoss, Bolden, Sharman, & Auckley (2015) Perioperative Complications in Obstructive Sleep Apnea Patients Undergoing Surgery: A Review of the Legal Literature. Anesthesa Analgesia. 7. Jarzyna, D., Jungquist, C.R., Pasero, C., Willens, J.S., Nisbet, A., Oakes, L., Dempsey, S., Santangelo, D., & Polomano, R.C. (2011). American society for pain management nursing: Expert consensus panel on monitoring for opioid induced sedation and respiratory depression. Journal of Pain Management Nursing, 12(3), 118 145. 8. Willens J, Jungquist CR, Polomano, R (2013) ASPMN Monitoring Survey Results, Journal of Pain Management Nursing, available online 1/2013. http://dx.doi.org/10.1016/j.pmn.2013.01.002 9. Jungquist CR, Willens JS, Dunwoody DR, Klingman KJ, Polomano RC (2013) Monitoring for Opioid Induced Advancing Sedation and Respiratory Depression: ASPMN membership survey of current practice. Pain Management Nursing. Available online May, 2014. Vol 14, No 1 (March), 2013: pp 60 65. http://dx.doi.org/10.1016/j.pmn.2013.01.002. 10. Jungquist CR, Pasero C, Tripoli N, Gorodetsky R, Metersky M, Polomano RC (2014) Instituting Best Practice for Monitoring for Opioid Induced Advancing Sedation in Hospitalized Patients. Worldviews on Evidence Based Nursing. 00:00, 1 11. Available online 9/24/14. 11. Curry JP, Jungquist CR (2014). A critical assessment of monitoring practices, patient deterioration, and alarm fatigue on inpatient wards: a review. Patient Safety in Surgery. 2014, 8:29 http://www.pssjournal.com/content/8/1/29. 12