
Introduction
Determining vital signs correctly is the first hurdle in early recognition of at-risk patients. Respiratory rate is often inaccurately reported, yet one of the most important parameters of critical illness. Measuring vital signs correctly, and expanding them with additional easy to measure bedside metrics can improve sensitivity and specificity detection of at-risk patients.
Efforts to reduce failure to rescue by multiable societies and agencies now emphasized the importance of early event detection. Mature robust successful RRS, that improve outcomes, allocate significant resources for afferent arm/ bedside nurse for early recognition of subtitle clinical decline.
Overview

In the US in late 90s, Rapid Response Systems(RRS) were being independently developed and implemented at the University of Pittsburgh and Redding Medical Center in Redding California among other locations. In approximately 2004-5, SCCM RRS task force headed by Dr Dan Terries was formed and included Drs Michael DeVita and Marie Baldisseri from Pittsburgh, Randy Wax from Toronto, Geoffrey Lighthall from Stanford, Frank Sebat from Reddin, California along with others which helped highlight the RRS initiative in the United States. During this time SCCM allocated resources for earlier recognition of at-risk patient’s and promotion of RRS. This included presentations at subsequent Congresses and a RRS textbook published in 2009. Following this both the Institute of Health Improvement and Joint Commission identified failure to rescue at-risk patients on the general hospital wards as a significant problem and requested hospital address this issue with a “suitable method” of early identification and treatment of this population (Patient safety Goal 16A). IHI created Rapid Response System tool kits and measuring RRTs and cardiac arrest rate/1000 discharges to address this problem. Agency for Healthcare Research and Quality joined efforts to reduce in-hospital failure to rescue events and estimated in total to be 13% of hospital admissions. These efforts continue and has been joined by the Society of Hospitals.
RRS continue to dominate the in-hospital environment and have been nearly universally implemented in hospitals throughout the developed world, at times with limited success. Even with mature successful systems, system processes and procedures that positively affect patient outcomes are not well described or understood. However, this is changing with recent work and publications describing successful system components that are not difficult to implement and if widely disseminated could positively affect the lives of thousands of hospitalized patients.
Efforts to reduce failure to rescue by multiaple societies and agencies now emphasized the importance of early event detection. Mature robust successful RRS, that improve outcomes, allocate significant resources for afferent arm/ bedside nurse for early recognition of subtitle clinical decline. To do this hospitals need a comprehensive education programs coupled with easy to audit compliance procedure for bedside clinicians, to assure that they accurately obtain and understand easily measured bedside parameters. These parameters are used singularly or in combination (scoring systems) to increase concern for at-risk patients and to prompt mobilization of appropriate resources. These key Vital Signs (VS) reflect early subtle physiologic abnormalities that herald clinical deterioration which, if recognized early, will prevent failure to rescue.
Problem

As a result of new innovative technology, clinicians, particularly the bedside nurse and physician, rely less on physical exam and more on expensive but often less valuable assessments. No one would dispute that vital signs are vital. However, little or no resources are devoted to accurately obtaining some of the key VS on the general wards. A primary example of this is respiratory rate, the sentinel vital sign of clinical decline, which is frequently inaccurately obtained and recorded in the EMR of general ward patients yet this incorrect information is relied upon by all clinicians and at-risk patient scoring systems. Inaccurate vital patient data in the EMR is compounded by the absence of focus on the bedside nurse’s ability to recognize other subtle early physiologic alterations. For example, level of consciousness scales commonly used i.e. Glasgow Coma Scale (GCS) or AVPU scale (Spontaneously alert, to verbal, to pain or unresponsive) do not pick up agitation and anxiety or apathy all of which are early signs of clinical deterioration. Capillary refill >3 which all nurses have been taught and know how to preform has been shown to be the single best predictor for transfer to ICU once a RRT alert has been called and has previously been shown to be a good predictor of progressing to subsequent organ failure. It is easy to accurately obtain, if the threshold trigger used is > 3 sec, and is very predictive. Despite all of these benefits only a few hospitals use this parameter to assist in early detection of clinical decline. Increasing awareness and attention to these fundamental patient assessment measures will reduce failure to rescue. The benefit of focusing on the basics is likely much greater than that obtained from EMR machine learning Early Warning Scores currently under development; given that some vital patient assessment is not present or correct in the EMR (respiratory rate , capillary refill or accurate LOC assessment).
Goal

Increase the awareness, acceptance and subsequent compliance in obtaining, understanding and appropriately acting on in near real-time easily measured expanded bedside parameters/vital signs on general wards, to reduce failure to rescue.
Proposed Methods

- Initiate discussion with Medical and Nursing professional societies regarding synergies between their goals and that of other organizations that are reducing in-hospital failure to rescue events i.e. Society of Critical Care medicine, Society of Hospital, Medicine, International Society of Rapid Response Systems. Kritikus Foundation and others.
- Institution of a multidisciplinary RRS task force involving; nursing, physicians, respiratory therapy, scoring system experts, a media specialist and other disciplines, as deemed appropriate. This should include current developers in the field of highly effective RRS with demonstrated improved outcomes. This for example could include experts from multible institutions i.e University of California San Diego which has designed a novel system of at-risk patient’s pattern recognition that has decreased hospital mortality and currently has the lowest reported cardiac arrest rate of any hospital in the country at just under 1/1000 Hospital admissions . Leading experts on advanced scoring systems in recognizing at-risk patient early; media specialist in internet education, social media and PR to assist in getting the message out, among others as appropriate.