By John Zaleski, Chief Analytics Officer of Bernoulli Enterprise, Inc.

March 2018 – In high-acuity patient settings, data often speak for the patient, particularly those that are unconscious, recuperating from invasive surgical procedures, or heavily sedated on pain medication. Yet, of the 40 million plus surgeries performed annually in the United States, a significant potential threat to patient safety is unforeseen — respiratory events and missed alarms associated with cardiorespiratory monitoring.

Patients admitted with pre-existing respiratory ailments have high mortality rates. The frequency of emergency mechanical ventilation has been estimated at higher than 44,000 patients per year in the United States alone, with mortality of nearly 40% for patients that develop in-hospital respiratory failure. It also has been estimated that the death rate in patients with respiratory failure is more than twice the estimate for patients experiencing heart attacks, and higher than in those diagnosed with cancer, stroke or renal failure. [1][2]

A study of 92 closed insurance claims (i.e., claims that have been settled) between 1990 and 2009 concluded that patients who had experienced inadequate postoperative ventilation necessary to support adequate gas exchange (i.e., respiratory depression, or RD) was a significant cause of death and brain damage, with as high as 88% of cases estimated to occur within the first day after surgery. Almost all of these cases–97%–were deemed preventable. Forty-two percent of patients identified with RD were done so within 2 hours of the last nursing check, and 16% were within15 minutes of the last nursing check. [3]

These findings and statistics are substantial and startling. As recently as this year, the Anesthesia Patient Safety Foundation (APSF) called attention to these and further findings, citing that opioid-induced ventilatory impairment (OIVI) affects as many as 1 in 200 postoperative patients, with 75% of cases occurring within 24 hours of surgery. [4][5]

RD and opioid-induced ventilatory impairment (OIVI) are often caused by postoperative pain medication depressing pulmonary function, and they result in a significant number of emergent intubations, post-operative mortality, and causal conditions leading to mortality. Many conditions exacerbate or aggravate respiratory compromise, such as congestive heart failure, some lung ailments, pulmonary embolism and edema, and airway obstruction.

Recommendations from APSF, the Association for the Advancement of Medical Instrumentation (AAMI) and others advocate for the use of continuous cardiorespiratory monitoring of patients throughout the postoperative period to improve the surveillance of all patients and to ameliorate the risks associated with RD, and particularly those patients at risk for cessation of breathing. Patients diagnosed with or at risk for central or obstructive sleep apnea fall into this category.

Continuous monitoring enables earlier clinical detection of onset of inadequate ventilation, which can lead to RD in patients. Measurements such as heart rate, blood oxygenation content, and blood pressure can indicate the evolution of patient state from stability to instability, including conditions that may result in patient suffering and death.

Continuous monitoring provides real-time and sustained cardiorespiratory patient measurements. Through these measurements, their trajectories, and the expected evolution of patient states, it is possible to identify earlier when patients are beginning a downward spiral. This provides the safety net so often absent in intensive care units, medical surgical units, emergency wards and other locations in and around the hospital. Yet, many hospitals only employ continuous monitoring in the highest acuity settings: the intensive care units and emergency wards. It is time to reevaluate extending continuous monitoring to every location in the hospital setting, on every patient, all the time.

The continuous monitoring model can be extended to the home, such as for patients struggling with diabetes, chronic obstructive pulmonary disease (COPD), or congestive heart failure (CHF). Here too this monitoring adds a safety net to patients at home, particularly those who live alone, so that adverse events can be detected and early interventions can be initiated on patients at risk for RD.

ABOUT THE AUTHOR

John Zaleski, PhD, CAP, CPHIMS, is Chief Analytics Officer of Bernoulli Enterprise, Inc. (http://bernoullihealth.com), a leader in real-time connected healthcare and clinical surveillance. Dr. Zaleski has been researching medical device interoperability and clinical decision support since 1996. He received his Ph.D. from the University of Pennsylvania, with a dissertation that describes a novel approach for modeling and prediction of post-operative respiratory behavior in post-surgical cardiac patients. Dr. Zaleski has a particular expertise in designing, developing, and implementing clinical and non-clinical point-of-care applications for hospital enterprises. Dr. Zaleski is the named inventor or co-inventor on eight issued U.S. patents related to medical device interoperability and clinical informatics. He is the author of peer-reviewed articles and conference papers on clinical use of medical device data, information technology and medical devices and wrote three seminal books on integrating medical device data into electronic health records and the use of medical device data for clinical decision making, including the #1 best seller of HIMSS 2015 on connected medical devices. Dr. Zaleski is also a member of the Board of Directors of Health Solutions Research (http://healthsolutionsresearch.org) and posts to his personal weblog on topics ranging from medical device integration, medical informatics and his personal passion related to rowing and sculling at http://johnrzaleski.com.

REFERENCES

[1] Morris, Timothy A; Gay Peter C; MacIntyre, Neil R; Hess, Dean R; Hanneman, Sandra K; Lamberti, James P; Doherty, Dennis E; Chang, Lydia; Seckel, Maureen A. “Respiratory Compromise As a New Paradigm for the Care of Vulnerable Hospitalized Patients.” Respiratory Care | April 2017 | Vol 62 | No 4.

[2] Curry, J Paul; Jungquist, Carla R. “A critical assessment of monitoring practices, patient deterioration, and alarm fatigue on inpatient wards: a review.” Patient Safety in Surgery | 2014 | Vol 8 | No 29.

[3] Lee, Lorri A; Caplan, Robert A; Stephens, Linda S; Posner, Karen L; Terman, Gregory W; Voepel-Lewis, Terri; Domino, Karen B. “Postoperative Opioid-induced Respiratory Depression.” Anesthesiology | 2015 | Vol 122 | pp 659-65.

[4] Greenberg, Steven. “Opioid-Induced Ventilatory Impairment: An Ongoing APSF Initiative.” APSF Newsletter | February 2018 | Vol 32 | No 3.

[5] Gupta, Rajnish K; Edwards, David A. “Monitoring for Opioid-Induced Respiratory Depression.” APSF Newsletter | February 2018 | Vol 32 | No 3.