A Remote Surveillance Platform to Monitor General Care Ward Surgical Patients for Acute Physiologic Deterioration.

BACKGROUND: The traditional paradigm of hospital surgical ward care consists of episodic bedside visits by providers with periodic perusals of the patient's electronic health record (EHR). Vital signs and laboratory results are directly pushed to the EHR but not to providers themselves. Results that require intervention may not be recognized for hours. Remote surveillance programs continuously monitor electronic data and provide automatic alerts that can be routed to multidisciplinary providers. Such programs have not been explored in surgical general care wards. METHODS: We performed a quality improvement observational study of otolaryngology and ophthalmology patients on a general care ward from October 2017 to March 2019 during nighttime hours (17:00-07:00). The study was initiated due to the loss of on-site anesthesiology resources that historically helped respond to acute physiologic deterioration events. We implemented a remote surveillance software program to continuously monitor patients for severe vital signs and laboratory abnormalities and automatically alert the ward team and a remote critical care anesthesiology team. The primary end point was the true positive rate, defined as the proportion of alerts that were associated with a downstream action that changed the care of the patient. This was determined using systematic chart review. The secondary end point, as a measure of alarm fatigue, was the average number of alerts per clinician shift. RESULTS: The software monitored 3926 hospital visits and analyzed 1,560,999 vitals signs and 16,635 laboratories. It generated 151 alerts, averaging 2.6 alerts per week. Of these, 143 (94.7%) were numerically accurate and 8 (5.3%) were inaccurate. Hypoxemia with oxygen saturation <88% was the most common etiology (92, 63%) followed by tachycardia >130 beats per minute (19, 13.3%). Among the accurate alerts, 133 (88.1%) were true positives with an associated clinical action. Actions included a change in management 113 (67.7%), new diagnostic test 26 (15.6%), change in discharge planning 20 (12.0%), and change in level of care to the intensive care unit (ICU) 8 (4.8%). As a measure of alarm fatigue, there were 0.4 alerts per clinician shift. CONCLUSIONS: In a surgical general care ward, a remote surveillance software program that continually and automatically monitors physiologic data streams from the EHR and alerts multidisciplinary providers for severe derangements provided highly actionable alarms at a rate that is unlikely to cause alarm fatigue. Such programs are feasible and could be used to change the paradigm of monitoring.

Effects of obstructive sleep apnoea risk on postoperative respiratory complications: protocol for a hospital-based registry study.

INTRODUCTION: Obstructive sleep apnoea (OSA), the most common type of sleep-disordered breathing, is associated with significant immediate and long-term morbidity, including fragmented sleep and impaired daytime functioning, as well as more severe consequences, such as hypertension, impaired cognitive function and reduced quality of life. Perioperatively, OSA occurs frequently as a consequence of pre-existing vulnerability, surgery and drug effects. The impact of OSA on postoperative respiratory complications (PRCs) needs to be better characterised. As OSA is associated with significant comorbidities, such as obesity, pulmonary hypertension, myocardial infarction and stroke, it is unclear whether OSA or its comorbidities are the mechanism of PRCs. This project aims to (1) develop a novel prediction score identifying surgical patients at high risk of OSA, (2) evaluate the association of OSA risk on PRCs and (3) evaluate if pharmacological agents used during surgery modify this association. METHODS: Retrospective cohort study using hospital-based electronic patient data and perioperative data on medications administered and vital signs. We will use data from Partners Healthcare clinical databases, Boston, Massachusetts. First, a prediction model for OSA will be developed using OSA diagnostic codes and polysomnography procedural codes as the reference standard, and will be validated by medical record review. Results of the prediction model will be used to classify patients in the database as high, medium or low risk of OSA, and we will investigate the effect of OSA on risk of PRCs. Finally, we will test whether the effect of OSA on PRCs is modified by the use of intraoperative pharmacological agents known to increase upper airway instability, including neuromuscular blockade, neostigmine, opioids, anaesthetics and sedatives. ETHICS AND DISSEMINATION: The Partners Human Research Committee approved this study (protocol number: 2014P000218). Study results will be made available in the form of manuscripts for publication and presentations at national and international meetings.