Generation of early warnings with smart monitors: the future is all about getting back to the basics!

The association between abnormal vital sign groups and undesirable patient outcomes

Introduction:

To determine the association between both abnormal individual vital signs and abnormal vital sign groups in the emergency department, and undesirable patient outcomes: hospital admission, medical emergency team calls and death.

Method:

We undertook a prospective cohort study in a tertiary referral emergency department (February–May 2015). Vital signs were collected prospectively in the emergency department and undesirable outcomes from the medical records. The primary outcomes were undesirable outcomes for individual vital signs (multivariate logistic regression) and vital sign groups (univariate analyses).

Results:

Data from 1438 patients were analysed. Admission was associated with tachycardia, tachypnoea, fever, ≥1 abnormal vital sign on admission to the emergency department, ≥1 abnormal vital sign at any time in the emergency department, a persistently abnormal vital sign, and vital signs consistent with both sepsis (tachycardia/hypotension/abnormal temperature) and pneumonia (tachypnoea/fever) (p < 0.05). Medical emergency team calls were associated with tachycardia, tachypnoea, ≥1 abnormal vital sign on admission (odds ratio: 2.3, 95% confidence interval: 1.4–3.8), ≥2 abnormal vital signs at any time (odds ratio: 2.4, 95% confidence interval: 1.2–4.7), and a persistently abnormal vital sign (odds ratio: 2.7, 95% confidence interval: 1.6–4.6). Death was associated with Glasgow Coma Score ≤13 (odds ratio: 6.3, 95% confidence interval: 2.5–16.0), ≥1 abnormal vital sign on admission (odds ratio: 2.6, 95% confidence interval: 1.2–5.6), ≥2 abnormal vital signs at any time (odds ratio: 6.4, 95% confidence interval: 1.4–29.5), a persistently abnormal vital sign (odds ratio: 4.3, 95% confidence interval: 2.0–9.0), and vital signs consistent with pneumonia (odds ratio: 5.3, 95% confidence interval: 1.9–14.8).

Conclusion:

Abnormal vital sign groups are generally superior to individual vital signs in predicting undesirable outcomes. They could inform best practice management, emergency department disposition, and communication with the patient and family.

Effect of a Real-Time Electronic Dashboard on a Rapid Response System

A rapid response system (RRS) may have limited effectiveness when inpatient providers fail to recognize signs of early patient decompensation. We evaluated the impact of an electronic medical record (EMR)-based alerting dashboard on outcomes associated with RRS activation. We used a repeated treatment study in which the dashboard display was successively turned on and off each week for ten 2-week cycles over a 20-week period on the inpatient acute care wards of an academic medical center. The Rapid Response Team (RRT) dashboard displayed all hospital patients in a single view ranked by severity score, updated in real time. The dashboard could be seen within the EMR by any provider, including RRT members. The primary outcomes were the incidence rate ratio (IRR) of all RRT activations, unexpected ICU transfers, cardiopulmonary arrests and deaths on general medical-surgical wards (wards). We conducted an exploratory analysis of first RRT activations. There were 6736 eligible admissions during the 20-week study period. There was no change in overall RRT activations (IRR = 1.14, p = 0.07), but a significant increase in first RRT activations (IRR = 1.20, p = 0.04). There were no significant differences in unexpected ICU transfers (IRR = 1.15, p = 0.25), cardiopulmonary arrests on general wards (IRR = 1.46, p = 0.43), or deaths on general wards (IRR = 0.96, p = 0.89). The introduction of the RRT dashboard was associated with increased initial RRT activations but not overall activations, unexpected ICU transfers, cardiopulmonary arrests, or death. The RRT dashboard is a novel tool to help providers recognize patient decompensation and may improve initial RRT notification.

Trends and variations in the rates of hospital complications, failure-to-rescue and 30-day mortality in surgical patients in New South Wales, Australia, 2002-2009

BACKGROUND

Despite the increased acceptance of failure-to-rescue (FTR) as an important patient safety indicator (defined as the percentage of deaths among surgical patients with treatable complications), there has not been any large epidemiological study reporting FTR in an Australian setting nor any evaluation on its suitability as a performance indicator.

METHODS

We conducted a population-based study on elective surgical patients from 82 public acute hospitals in New South Wales, Australia between 2002 and 2009, exploring the trends and variations in rates of hospital complications, FTR and 30-day mortality. We used Poisson regression models to derive relative risk ratios (RRs) after adjusting for a range of patient and hospital characteristics.

RESULTS

The average rates of complications, FTR and 30-day mortality were 13.8 per 1000 admissions, 14.1% and 6.1 per 1000 admission, respectively. The rates of complications and 30-day mortality were stable throughout the study period however there was a significant decrease in FTR rate after 2006, coinciding with the establishment of national and state-level peak patient safety agencies. There were marked variations in the three rates within the top 20% of hospitals (best) and bottom 20% of hospitals (worst) for each of the four peer-hospital groups. The group comprising the largest volume hospitals (principal referral/teaching hospitals) had a significantly higher rate of FTR in comparison to the other three groups of smaller-sized peer hospital groups (RR = 0.78, 0.57, and 0.61, respectively). Adjusted rates of complications, FTR and 30-day mortality varied widely for individual surgical procedures between the best and worst quintile hospitals within the principal referral hospital group.

CONCLUSIONS

The decrease in FTR rate over the study period appears to be associated with a wide range of patient safety programs. The marked variations in the three rates between- and within- peer hospital groups highlight the potential for further quality improvement intervention opportunities.