Christian P. Subbe

The impact of the introduction of critical care outreach services in England: a multicentre interrupted time-series analysis

IntroductionCritical care outreach services (CCOS) have been widely introduced in England with little rigorous evaluation. We undertook a multicentre interrupted time-series analysis of the impact of CCOS, as characterised by the case mix, outcome and activity of admissions to adult, general critical care units in England.MethodsData from the Case Mix Programme Database (CMPD) were linked with the results of a survey on the evolution of CCOS in England. Over 350,000 admissions to 172 units between 1996 and 2004 were extracted from the CMPD. The start date of CCOS, activities performed, coverage and staffing were identified from survey data and other sources. Individual patient-level data in the CMPD were collapsed into a monthly time series for each unit (panel data). Population-averaged panel-data models were fitted using a generalised estimating equation approach. Various potential outcomes reflecting possible objectives of the CCOS were investigated in three subgroups of admissions: all admissions to the unit, admissions from the ward, and unit survivors discharged to the ward. The primary comparison was between periods when a formal CCOS was and was not present. Secondary analyses considered specific CCOS activities, coverage and staffing.ResultsIn all, 108 units were included in the analysis, of which 79 had formal CCOS starting between 1996 and 2004. For admissions from the ward, CCOS were associated with significant decreases in the proportion of admissions receiving cardiopulmonary resuscitation before admission (odds ratio 0.84, 95% confidence interval 0.73 to 0.96), admission out of hours (odds ratio 0.91, 0.84 to 0.97) and mean Intensive Care National Audit & Research Centre physiology score (decrease in mean 1.22, 0.31 to 2.12). There was no significant change in unit mortality (odds ratio 0.97, 0.87 to 1.08) and no significant, sustained effects on outcomes for unit survivors discharged alive to the ward.ConclusionThe observational nature of the study limits its ability to infer causality. Although associations were observed with characteristics of patients admitted to critical care units, there was no clear evidence that CCOS have a big impact on the outcomes of these patients, or for characteristics of what should form the optimal CCOS.

Failure to rescue: using rapid response systems to improve care of the deteriorating patient in hospital:

“Failure to rescue” is the inadequate or delayed response to clinical deterioration in hospitalized patients. Rapid response systems are a set of hospital-wide interventions that attempt to reduce failure to rescue by improving patient monitoring on general wards (the afferent component) and the reliability of the response to deterioration by a dedicated Critical Care Outreach Team, Rapid Response Team or Medical Emergency Team (the efferent component). The reliability of such systems depends on the faultless functioning of a “chain of survival” consisting of: (1) high-quality recording of vital signs; (2) the education and mind-set of staff at the bedside to recognize pathological patterns; (3) the reporting of abnormality to the efferent team; (4) a timely and appropriate response by the latter. Repeated feedback loops are crucial for an effective functioning of the chain.

Timing and teamwork--an observational pilot study of patients referred to a Rapid Response Team with the aim of identifying factors amenable to re-design of a Rapid Response System.

BACKGROUND Rapid Response Teams aim to accelerate recognition and treatment of acutely unwell patients. Delays in delivery might undermine efficiency of the intervention. Our understanding of the causes of these delays is, as yet, incomplete. AIM To identify modifiable causes of delays in the treatment of critically ill patients outside intensive care with a focus on factors amenable to system design. METHODS Review of care records and direct observation with process mapping of care delivered to 17 acutely unwell patients attended by a Rapid Response Team in a District General Hospital in the United Kingdom. Delays were defined as processes with no added value for patient care. RESULTS Essential diagnostic and therapeutic procedures accounted for only 31% of time of care processes. Causes for delays could be classified into themes as (1) delays in call-out of the Rapid Response Team, (2) problems with team cohesion including poor communication and team efficiency and (3) lack of resources including lack of first line antibiotics, essential equipment, experienced staff and critical care beds. CONCLUSION We identified a number of potentially modifiable causes for delays in care of acutely ill patients. Improved process design could include automated call-outs, a dedicated kit for emergency treatment in relevant clinical areas, increased usage of standard operating procedures and staff training using crew resource management techniques.

Better ViEWS ahead?: It is high time to improve patient safety by standardizing Early Warning Scores

The contribution by Prytherch et al.1 in this issue represents a ajor advance in the way early warning scores2 are used to identify atients at risk of catastrophic deterioration and cardiorespiratory rrest on general wards. In turn, this will impact the efficiency of apid response systems (RRS). In the absence of continuous central monitoring, deterioation of in-patients is often slow to be recognized. This is espite the fact that it is possible to recognize most deteriorating atients by changes in the pattern of basic physiological bedside bservations.3,4 This has enabled the development of structured ssessments of bedside observations using ‘track and trigger’ tools nd the creation of protocols for escalation of care. In this way the isk to patients is quantified and patient safety improved.5 In 2007, a review identified 25 distinct ‘track and trigger’ tools ith very different sensitivity and specificity for the detection of hese at risk patients.6 Why is there such a large number? The cretion of early warning scores has been hampered by the absence of rospective cohort studies of a size that enables simulation of rare onstellations of physiology and their impact on outcomes. Hospials rely on subjective preferences and have rarely looked beyond heir own institutions for creation of scoring tools. Databases used or creation of the tools were typically limited in their size and id therefore need to rely on composite endpoints including intenive care admission, an endpoint that is highly dependent on local esources and style of medicine. The sheer fact that there are many tools undermines a relible response to abnormal values. It also means medical staff is ot confident that these tools are trustworthy or safe. It would e unimaginable that the diagnosis of acute myocardial ischemia ould rely on local methods to attach the electrocardiogram ECG) electrodes and interpret the results. The standardization of he interpretation of the ECG enabled completion of large-scale andomized controlled trials of patients with acute myocardial nfarctions, thus producing a steady reduction in mortality rates.7 Rapid response teams depend on reliable identification of bnormal observations. Reliability is linked to the statistical proprties of the track and trigger tools as much as to perceptions and ttitudes of users.8 The multitude of systems therefore undermines he efficiency of rapid response systems. The Royal College of Physicians (London) has recognized this fact n its recent report on acute medical care and has recommended he establishment of a National Early Warning Score (NEWS) in he United Kingdom (UK).9 A NEWS would facilitate training in the se of this important patient safety tool. Given that established abits and beliefs are difficult to change, it offers an opportunity

Effect of an automated notification system for deteriorating ward patients on clinical outcomes.

BackgroundDelayed response to clinical deterioration of ward patients is common.MethodsWe performed a prospective before-and-after study in all patients admitted to two clinical ward areas in a district general hospital in the UK. We examined the effect on clinical outcomes of deploying an electronic automated advisory vital signs monitoring and notification system, which relayed abnormal vital signs to a rapid response team (RRT).ResultsWe studied 2139 patients before (control) and 2263 after the intervention. During the intervention the number of RRT notifications increased from 405 to 524 (p = 0.001) with more notifications triggering fluid therapy, bronchodilators and antibiotics. Moreover, despite an increase in the number of patients with “do not attempt resuscitation” orders (from 99 to 135; p = 0.047), mortality decreased from 173 to 147 (p = 0.042) patients and cardiac arrests decreased from 14 to 2 events (p = 0.002). Finally, the severity of illness in patients admitted to the ICU was reduced (mean Acute Physiology and Chronic Health Evaluation II score: 26 (SD 9) vs. 18 (SD 8)), as was their mortality (from 45% to 24%; p = 0.04).ConclusionsDeployment of an electronic automated advisory vital signs monitoring and notification system to signal clinical deterioration in ward patients was associated with significant improvements in key patient-centered clinical outcomes.Trial registrationClinicalTrials.gov, NCT01692847. Registered on 21 September 2012.

Collaborative Audit of Risk Evaluation in Medical Emergency Treatment (CARE-MET I) — An international pilot

BACKGROUND The absence of an accepted model for risk-adjustment of acute medical admissions leads to suboptimal clinical triage and serves as a disincentive to compare outcomes in different hospitals. The Simple Clinical Score (SCS) is a model based on 16 clinical parameters affecting hospital mortality. METHODS We undertook a feasibility pilot in 21 hospitals in Europe and New Zealand each collecting data for 12 or more consecutive medical emergency admissions. Data from 281 patients was analysed. RESULTS Severity of illness as estimated by SCS was related to risk of admission to the Intensive Care Unit (p<0.001) but not to the Coronary Care Unit. Mortality increased from 0% in the Very Low Risk group to 22% in the Very High Risk Group (p<0.0001). Very low scores were associated with earlier discharge as opposed to very high scores (mean length of stay of 2.4 days vs 5.6 days, p<0.001). There were differences in the pattern of discharges in different hospitals with comparable SCS data. Clinicians reported no significant problems with the collection of data for the score in a number of different health care settings. CONCLUSION The SCS appears to be a feasible tool to assist clinical triage of medical emergency admissions. The ability to view the profile of the SCS for different clinical centres opens up the possibility of accurate comparison of outcomes across clinical centres without distortion by different regional standards of health care. This pilot study demonstrates that the adoption of the SCS is practical across an international range of hospitals.

Relationship between input and output in acute medicine - secondary analysis of the Society for Acute Medicine's benchmarking audit 2013 (SAMBA '13).

The performance of acute medical units (AMUs) against published quality indicators is variable. We aimed to identify the impact of case-mix and unit resources on timely assessment and discharge of patients admitted to 43 AMUs on a single day in June 2013, as part of the Society for Acute Medicines benchmarking audit 2013. Performance against quality indicators was at its worst in the early evening hours. Units admitting fewer than 40 patients performed better. Patients who were more frail, as measured by the Clinical Frailty Scale, were also more likely to have significant physiological abnormalities and a higher risk of death, as measured by the National Early Warning Score. Our analysis suggests that resource allocation at the front door is related to quality indicators. Teams will need strengthening in the evening hours and if looking after higher numbers of frail patients.

A pragmatic triage system to reduce length of stay in medical emergency admission: Feasibility study and health economic analysis

BACKGROUND Departments of Internal Medicine tend to treat patients on a first come first served basis. The effects of using triage systems are not known. METHODS We studied a cohort in an Acute Medical Unit (AMU). A computer-assisted triage system using acute physiology, pre-existing illness and mobility identified five distinct risk categories. Management of the category of very low risk patients was streamlined by a dedicated Navigator. Main outcome parameters were length of hospital stay (LOS) and overall costs. Results were adjusted for the degree of frailty as measured by the Clinical Frailty Scale (CFS). A six month baseline phase and intervention phase were compared. RESULTS 6764 patients were included: 3084 in the baseline and 3680 in the intervention phase. Patients with very low risk of death accounted for 40% of the cohort. The LOS of the 1489 patients with very low risk of death in the intervention group was reduced by a mean of 1.85days if compared with the 1276 patients with very low risk in the baseline cohort. This was true even after adjustment for frailty. Over the six month period the cost of care was reduced by £250,158 in very low patients with no increase in readmissions or 30day mortality. CONCLUSIONS Implementation of an advanced triage system had a measurable impact on cost of care for patients with very low risk of death. Patients were safely discharged earlier to their own home and the intervention was cost-effective.

Clinical outcomes of patients seen by Rapid Response Teams: A template for benchmarking international teams ☆

AIM The study was developed to characterize short-term outcomes of deteriorating ward patients triggering a Rapid Response Team (RRT), and describe variability between hospitals or groups thereof. METHODS We performed an international prospective study of Rapid Response Team (RRT) activity over a 7-day period in February 2014. Investigators at 51 acute hospitals across Australia, Denmark, the Netherlands, USA and United Kingdom collected data on all patients triggering RRT review concerning the nature, trigger and immediate outcome of RRT review. Further follow-up at 24h following RRT review focused on patient orientated outcomes including need for admission to critical care, change in limitations of therapy and all cause mortality. RESULTS We studied 1188 RRT activations. Derangement of vital signs as measured by the National Early Warning Score (NEWS) was more common in non-UK hospitals (p=0.03). Twenty four hour mortality after RRT review was 10.1% (120/1188). Urgent transfer to ICU or the operating theatre occurred in 24% (284/1188) and 3% (40/1188) of events, respectively. Patients in the UK were less likely to be admitted to ICU (31% vs. 22%; p=0.017) and their median (IQR) time to ICU admission was longer [4.4 (2.0-11.8) vs. 1.5 (0.8-4.4)h; p<0.001]. RRT involvement lead to new limitations in care in 28% of the patients not transferring to the ICU; in the UK such limitations were instituted in 21% of patients while this occurred in 40% of non-UK patients (p<0.001). CONCLUSION Among patients triggering RRT review, 1 in 10 died within 24h; 1 in 4 required ICU admission, and 1 in 4 had new limitations in therapy implemented. We provide a template for an international comparison of outcomes at RRT level.

Patients’ and providers’ perceptions of the preventability of hospital readmission: a prospective, observational study in four European countries

Objectives Because of fundamental differences in healthcare systems, US readmission data cannot be extrapolated to the European setting: To investigate the opinions of readmitted patients, their carers, nurses and physicians on predictability and preventability of readmissions and using majority consensus to determine contributing factors that could potentially foresee (preventable) readmissions. Design Prospective observational study. Readmitted patients, their carers, and treating professionals were surveyed during readmission to assess the discharge process and the predictability and preventability of the readmission. Cohen’s Kappa measured pairwise agreement of considering readmission as predictable/preventable by patients, carers and professionals. Subsequently, multivariable logistic regressionidentified factors associated with predictability/preventability. Setting 15 hospitals in four European countries Participants 1398 medical patients readmitted unscheduled within 30 days Main Outcome(s) and Measure(s) (1) Agreement between the interviewed groups on considering readmissions likely predictable or preventable;(2) Factors distinguishing predictable from non-predictable and preventable from non-preventable readmissions. Results The majority deemed 27.8% readmissions potentially predictable and 14.4% potentially preventable. The consensus on predictability and preventability was poor, especially between patients and professionals (kappas ranged from 0.105 to 0.173). The interviewed selected different factors as potentially associated with predictability and preventability. When a patient reported that he was ready for discharge during index admission, the readmission was deemed less likely by the majority (predictability: OR 0.55; 95% CI 0.40 to 0.75; preventability: OR 0.35; 95% CI 0.24 to 0.49). Conclusions There is no consensus between readmitted patients, their carers and treating professionals about predictability and preventability of readmissions, nor associated risk factors. A readmitted patient reporting not feeling ready for discharge at index admission was strongly associated with preventability/predictability. Therefore, healthcare workers should question patients’ readiness to go home timely before discharge.