Design of a novel multifunction decision support/alerting system for in-patient acute care, ICU and floor (AlertWatch AC).

BACKGROUND: Multifunction surveillance alerting systems have been found to be beneficial for the operating room and labor and delivery. This paper describes a similar system developed for in-hospital acute care environments, AlertWatch Acute Care (AWAC). RESULTS: A decision support surveillance system has been developed which extracts comprehensive electronic health record (EHR) data including live data from physiologic monitors and ventilators and incorporates them into an integrated organ icon-based patient display. Live data retrieved from the hospitals network are processed by presenting scrolling median values to reduce artifacts. A total of 48 possible alerts are generated covering a broad range of critical patient care concerns. Notification is achieved by paging or texting the appropriated member of the critical care team. Alerts range from simple out of range values to more complex programing of impending Ventilator Associated Events, SOFA, qSOFA, SIRS scores and process of care reminders for the management of glucose and sepsis. As with similar systems developed for the operating room and labor and delivery, there are green, yellow, and red configurable ranges for all parameters. A census view allows surveillance of an entire unit with flashing or text to voice alerting and enables detailed information by windowing into an individual patient view including live physiologic waveforms. The system runs via web interface on desktop as well as mobile devices, with iOS native app available, for ease of communication from any location. The goal is to improve safety and adherence to standard management protocols. CONCLUSIONS: AWAC is designed to provide a high level surveillance view for multi-bed hospital units with varying acuity from standard floor patients to complex ICU care. Alerts are generated by algorithms running in the background and automatically notify the selected member of the patients care team. Its value has been demonstrated for low acuity patients, further study is required to determine its effectiveness in high acuity patients.

Design of a Novel Multifunction Decision Support Display for Anesthesia Care: AlertWatch® OR.

BACKGROUND: This paper describes the design of a multifunction alerting display for intraoperative anesthetic care. The design was inspired by the multifunction primary flight display used in modern aviation. RESULTS: The display retrieves live data from multiple sources; the physiologic monitors, the anesthesia information management system, the laboratory values and comorbidities from patient's problem summary list, medical history or history & physical. This information is integrated into a display composed of readily identifiable icons of organ systems, which are color coded to signify normal range, marginal range, abnormal range (by green, yellow, red respectively) and orange outlines for comorbidities/risk factors. There are dozens of text alerts, which can be presented as black text (informational), red text (important information) and red scrolling text (highest importance information). The alerts are derived from current standards in the literature and some involve complex calculations being conducted in the background. CONCLUSIONS: The goal of such a system is to improve the quality and safety of anesthetic care by providing enhanced situational awareness in a fashion analogous to the "glass cockpit" and its primary flight display which has improved aviation safety.

Variability of Automated Intraoperative ST Segment Values Predicts Postoperative Troponin Elevation.

BACKGROUND: Intraoperative electrocardiographic monitoring is considered a standard of care. However, there are no evidence-based algorithms for using intraoperative ST segment data to identify patients at high risk for adverse perioperative cardiac events. Therefore, we performed an exploratory study of statistical measures summarizing intraoperative ST segment values determine whether the variability of these measurements was associated with adverse postoperative events. We hypothesized that elevation, depression, and variability of ST segments captured in an anesthesia information management system are associated with postoperative serum troponin elevation. METHODS: We conducted a single-institution, retrospective study of intraoperative automated ST segment measurements from leads I, II, and III, which were recorded in the electronic anesthesia record of adult patients undergoing noncardiac surgery. The maximum, minimum, mean, and SD of ST segment values were entered into logistic regression models to find independent associations with myocardial injury, defined as an elevated serum troponin concentration during the 7 days after surgery. Performance of these models was assessed by measuring the area under the receiver operator characteristic curve. The net reclassification improvement was calculated to quantify the amount of information that the ST segment values analysis added regarding the ability to predict postoperative troponin elevation. RESULTS: Of 81,011 subjects, 4504 (5.6%) had postoperative myocardial injury. After adjusting for patient characteristics, the ST segment maximal depression (e.g., lead I: odds ratio [OR], 1.66; 95% confidence interval [CI], 1.26-2.19; P = 0.0004), maximal elevation (e.g., lead I: OR, 1.70; 95% CI, 1.34-2.17; P < 0.0001), and SD (e.g., lead I: OR, 0.16; 95% CI, 0.06-0.42; P = 0.0002) were found to have statistically significant associations with myocardial injury. Increased SD was associated with decreased risk when accounting for the maximal amount of ST segment depression and elevation and for patient characteristics. The ST segment summary statistics model had fair discrimination, with an area under the receiver operator characteristic curve of 0.71 (95% CI, 0.68-0.73). Addition of ST segment data produced a net reclassification improvement of 0.0345 (95% CI, 0.00016-0.0591; P = 0.0474). CONCLUSIONS: Analysis of automated ST segment values obtained during anesthesia may be useful for improving the prediction of postoperative troponin elevation.

Association of high body mass index in children with early post-tonsillectomy pain.

BACKGROUND: The purpose of this investigation was to determine whether there is an association between high body mass index (BMI) in children and the occurrence of early post-tonsillectomy pain (PTP). The hypothesis tested was that high BMI is associated with increased severity of early PTP. METHODS: We extracted data on all children aged 3-17 years that underwent adeno-tonsillectomy (T&A) over a 2-year period from our anesthesia clinical information system. Patients were classified into normal or high BMI group and early PTP scores were compared between the groups. Clinically significant (moderate-severe) early PTP was defined as pain score ≥ 4 within the first 15 min of admission to the post-anesthesia care unit (PACU). RESULTS: Among 462 patients, 35.1% were overweight or obese. The overall incidence of moderate to severe early PTP was 23.6%. All the patients received at least one or more intraoperative opioid (morphine 94.2% and fentanyl 21.9%). Compared to those in the normal BMI group, children with moderate-severe PTP were older, female and more likely to be overweight or obese. Children with high BMI had significantly higher unadjusted odds of having moderate-severe early post-tonsillectomy pain (48.9% vs. 14.1%, OR=7.01, 95% CI=3.9-12.8, p<0.001). After controlling for several clinically relevant covariates, high BMI was the most consistent risk factor for moderate to severe early PTP in this cohort of children. CONCLUSION: These results indicate that high BMI in children is associated with increased early PTP. The mechanism(s) underlying this association deserve further elucidation.