Cluster-randomized trial to evaluate the effects of a quality improvement program on management of non-ST-elevation acute coronary syndromes: The European Quality Improvement Programme for Acute Coronary Syndromes (EQUIP-ACS).

BACKGROUND: Registries have shown that quality of care for acute coronary syndromes (ACS) often falls below the standards recommended in professional guidelines. Quality improvement (QI) is a strategy to improve standards of clinical care for patients, but the efficacy of QI for ACS has not been tested in randomized trials. METHODS: We undertook a prospective, cluster-randomized, multicenter, multinational study to evaluate the efficacy of a QI program for ACS. Participating centers collected data on consecutive admissions for non-ST-elevation ACS for 4 months before the QI intervention and 3 months after. Thirty-eight hospitals in France, Italy, Poland, Spain, and the United Kingdom were randomized to receive the QI program or not, 19 in each group. We measured 8 in-hospital quality indicators (risk stratification, coronary angiography, anticoagulation, ß-blockers, statins, angiotensin-converting enzyme inhibitors, and clopidogrel loading and maintenance) before and after the intervention and compared composite changes between the QI and non-QI groups. RESULTS: A total of 2604 patients were enrolled. The absolute overall change in use of quality indicators in the QI group was 8.5% compared with 0.8% in the non-QI group (odds ratio for achieving a quality indicator in QI versus non-QI 1.66, 95% CI 1.43-1.94; P < .001). The main changes were observed in the use of risk stratification and clopidogrel loading dose. CONCLUSIONS: The QI strategy resulted in a significant improvement in the quality indicators measured. This type of QI intervention can lead to useful changes in health care practice for ACS in a wide range of settings.

Abdominal aortic aneurysm expansion: risk factors and time intervals for surveillance.

BACKGROUND: Intervention to reduce abdominal aortic aneurysm (AAA) expansion and optimization of screening intervals would improve current surveillance programs. The aim of this study was to characterize AAA growth in a national cohort of patients with AAA both overall and by cardiovascular risk factors. METHODS AND RESULTS: In this study, 1743 patients were monitored for changes in AAA diameter by ultrasonography over a mean follow-up of 1.9 years. Mean initial AAA diameter and growth rate were 43 mm (range 28 to 85 mm) and 2.6 mm/year (95% range, -1.0 to 6.1 mm/year), respectively. Baseline diameter was strongly associated with growth, suggesting that AAA growth accelerates as the aneurysm enlarges. AAA growth rate was lower in those with low ankle/brachial pressure index and diabetes but higher for current smokers (all P<0.001). No other factor (including lipids and blood pressure) was associated with AAA growth. Intervals of 36, 24, 12, and 3 months for aneurysms of 35, 40, 45, and 50 mm, respectively, would restrict the probability of breaching the 55-mm limit at rescreening to below 1%. CONCLUSIONS: Annual, or less frequent, surveillance intervals are safe for all AAAs < or =45 mm in diameter. Smoking increases AAA growth, but atherosclerosis plays a minor role.

Detection, management, and prospects for the medical treatment of small abdominal aortic aneurysms.

Small abdominal aortic aneurysms, up to 5.5 cm in diameter, are very common. Ultrasonography is the most cost-effective method of detecting these aneurysms and keeping them under surveillance, because the natural history is 1 of continued expansion. The expansion rate is in the range 0.25 to 0.35 cm/y and is fastest in current smokers. From a study of expansion rates, it has been possible to formulate guidelines for the intervals at which surveillance should occur. Although the evidence from randomized trials indicates that early, open, elective surgery for small aneurysms does not save lives, when aneurysms exceed 5.5 cm in diameter, either open or endovascular surgery is recommended. To prevent small aneurysms reaching the 5.5-cm threshold, new treatments to reduce the expansion rate by >50% need to be designed, based on the underlying pathologic processes: proteolysis and inflammation. Any proposed treatments, including statins, will need to be tested in clinical trials.

Winter excess mortality in intensive care in the UK: an analysis of outcome adjusted for patient case mix and unit workload.

OBJECTIVE: To investigate whether mortality in UK intensive care units is higher in winter than in non-winter and to explore the importance of variations in case mix and increased pressure on ICUs. DESIGN AND SETTING: Cohort study in 115 adult, general ICUs in England, Wales and Northern Ireland. PATIENTS AND PARTICIPANTS: 113,389 admissions from 1995 to 2000. MEASUREMENTS AND RESULTS: Hospital mortality following admission to ICU was compared between winter (December-February) and non-winter (March-November). The causes of any observed differences were explored by adjusting for the case mix of admissions and the workload of the ICUs. Crude hospital mortality was higher in winter. After adjusting for case mix using the APACHE II mortality probability this effect was reduced but still significant. When additional factors reflecting case mix and workload were introduced into the model, the overall effect of winter admission was no longer significant. Factors reflecting both the case mix of the individual patient and of the patients in surrounding beds were found to be significantly associated with outcome. After adjustment for other factors, the occupancy of the unit (proportion of beds occupied) was not significantly associated with mortality. CONCLUSIONS: The excess winter mortality observed in UK ICUs can be explained by variation in the case mix of admissions. Unit occupancy was not associated with mortality.

Case mix, outcome and length of stay for admissions to adult, general critical care units in England, Wales and Northern Ireland: the Intensive Care National Audit & Research Centre Case Mix Programme Database.

INTRODUCTION: The present paper describes the methods of data collection and validation employed in the Intensive Care National Audit & Research Centre Case Mix Programme (CMP), a national comparative audit of outcome for adult, critical care admissions. The paper also describes the case mix, outcome and activity of the admissions in the Case Mix Programme Database (CMPD). METHODS: The CMP collects data on consecutive admissions to adult, general critical care units in England, Wales and Northern Ireland. Explicit steps are taken to ensure the accuracy of the data, including use of a dataset specification, of initial and refresher training courses, and of local and central validation of submitted data for incomplete, illogical and inconsistent values. Criteria for evaluating clinical databases developed by the Directory of Clinical Databases were applied to the CMPD. The case mix, outcome and activity for all admissions were briefly summarised. RESULTS: The mean quality level achieved by the CMPD for the 10 Directory of Clinical Databases criteria was 3.4 (on a scale of 1 = worst to 4 = best). The CMPD contained validated data on 129,647 admissions to 128 units. The median age was 63 years, and 59% were male. The mean Acute Physiology and Chronic Health Evaluation II score was 16.5. Mortality was 20.3% in the CMP unit and was 30.8% at ultimate discharge from hospital. Nonsurvivors stayed longer in intensive care than did survivors (median 2.0 days versus 1.7 days in the CMP unit) but had a shorter total hospital length of stay (9 days versus 16 days). Results for the CMPD were comparable with results from other published reports of UK critical care admissions. CONCLUSIONS: The CMP uses rigorous methods to ensure data are complete, valid and reliable. The CMP scores well against published criteria for high-quality clinical databases.

Characteristics and outcome for admissions to adult, general critical care units with acute severe asthma: a secondary analysis of the ICNARC Case Mix Programme Database.

INTRODUCTION: This report describes the case mix, outcome and activity (duration of intensive care unit [ICU] and hospital stay, inter-hospital transfer, and readmissions to the ICU) for admissions to ICUs for acute severe asthma, and investigates the effect of case mix factors on outcome. METHODS: We conducted a secondary analysis of data from a high-quality clinical database (the Intensive Care National Audit and Research Centre [ICNARC] Case Mix Programme Database) of 129,647 admissions to 128 adult, general critical care units across England, Wales and Northern Ireland over the period 1995-2001. RESULTS: Asthma accounted for 2152 (1.7%) admissions, and in 57% mechanical ventilation was employed during the first 24 hours in the ICU. A total of 147 (7.1%) patients died in intensive care and 199 (9.8%) died before discharge from hospital. The mean age was 43.6 years, and the ratio of women to men was 2:1. Median length of stay was 1.5 days in the ICU and 8 days in hospital. Older age, female sex, having received cardiopulmonary resuscitation (CPR) within 24 hours before admission, having suffered a neurological insult during the first 24 hours in the ICU, higher heart rate, and hypercapnia were associated with greater risk for in-hospital death after adjusting for Acute Physiology and Chronic Health Evaluation II score. CPR before admission, neurological insult, hypoxaemia and hypercapnia were associated with receipt of mechanical ventilation after adjusting for Acute Physiology and Chronic Health Evaluation II score. CONCLUSION: ICU admission for asthma is relatively uncommon but remains associated with appreciable in-hospital mortality. The greatest determinant of poor hospital survival in asthma patients was receipt of CPR within 24 hours before admission to ICU. Clinical management of these patients should be directed at preventing cardiac arrest before admission.

Impact of exclusion criteria on case mix, outcome, and length of stay for the severity of disease scoring methods in common use in critical care.

OBJECTIVE: To identify the exclusion criteria for the major severity of disease scoring methods in critical care and to investigate the impact of the exclusion criteria on the case mix, outcomes and length of stay for admissions to intensive care units (ICUs) in England, Wales and Northern Ireland. DESIGN: Cohort study-analysis of prospectively collected data. SETTING: 127 adult, general (mixed medical/surgical) ICUs in England, Wales and Northern Ireland. PATIENTS: 120,503 admissions between 1995 and 2001. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Thirteen different exclusion criteria were identified from the original methodological/validation papers and data collection manuals for APACHE II, APACHE III, SAPS II and MPM II. Application of the original exclusion criteria for the four, major severity of disease scoring methods resulted in exclusion of between 11.5% and 14.6% of admissions. Hospital mortality for the overall cohort was 29.0% but ranged from 4.7% to 50.1% among those groups excluded. After application of the exclusion criteria for each scoring method, there was little difference in overall hospital mortality or median ICU and hospital length of stay for the included admissions when compared with the original cohort. At the level of individual ICUs, there were differences in hospital mortality before and after exclusions-minimum -3.1% to maximum 9.5% (APACHE II), minimum -2.8% to maximum 9.4% (APACHE III), minimum -3.1% to maximum 16.1% (SAPS II) and minimum -3.1% to maximum 16.5% (MPM II). The mean difference across individual ICUs was -0.5 % (95% CI -0.7% to -0.2%) for APACHE II, -0.2% (95% CI -0.2% to 0.1%) for APACHE III, 2.0% (95% CI 1.7% to 2.4%) for SAPS II and 2.1% (95% CI 1.7% to 2.5%) for MPM II. SAPS II and MPM II showed systematic variation. A survey of the literature found wide variation in the exclusion criteria reported in subsequent, published research using a single severity of disease scoring method (APACHE II). CONCLUSIONS: Exclusion criteria used in critical care research are often ill-defined and poorly reported. More attention to the choice of exclusion criteria and their effect on the reported results is essential. We hope this study will raise the need for both better reporting of exclusion criteria applied in studies and promote the need for a common set of explicit exclusion criteria for these methods.

Improving the management of non-ST elevation acute coronary syndromes: systematic evaluation of a quality improvement programme European QUality Improvement Programme for Acute Coronary Syndrome: the EQUIP-ACS project protocol and design.

BACKGROUND: Acute coronary syndromes, including myocardial infarction and unstable angina, are important causes of premature mortality, morbidity and hospital admissions. Acute coronary syndromes consume large amounts of health care resources, and have a major negative economic and social impact through days lost at work, support for disability, and coping with the psychological consequences of illness. Several registries have shown that evidence based treatments are under-utilised in this patient population, particularly in high-risk patients. There is evidence that systematic educational programmes can lead to improvement in the management of these patients. Since application of the results of important clinical trials and expert clinical guidelines into clinical practice leads to improved patient care and outcomes, we propose to test a quality improvement programme in a general group of hospitals in Europe. METHODS/DESIGN: This will be a multi-centre cluster-randomised study in 5 European countries: France, Spain, Poland, Italy and the UK. Thirty eight hospitals will be randomised to receive a quality improvement programme or no quality improvement programme. Centres will enter data for all eligible non-ST segment elevation acute coronary syndrome patients admitted to their hospital for a period of approximately 10 months onto the study database and the sample size is estimated at 2,000-4,000 patients. The primary outcome is a composite of eight measures to assess aggregate potential for improvement in the management and treatment of this patient population (risk stratification, early coronary angiography, anticoagulation, beta-blockers, statins, ACE-inhibitors, clopidogrel as a loading dose and at discharge). After the quality improvement programme, each of the eight measures will be compared between the two groups, correcting for cluster effect. DISCUSSION: If we can demonstrate important improvements in the quality of patient care as a result of a quality improvement programme, this could lead to a greater acceptance that such programmes should be incorporated into routine health training for health professionals and hospital managers. TRIAL REGISTRATION: Clinicaltrials.gov NCT00716430.

Recalibration of risk prediction models in a large multicenter cohort of admissions to adult, general critical care units in the United Kingdom.

OBJECTIVE: To assess the performance of published risk prediction models in common use in adult critical care in the United Kingdom and to recalibrate these models in a large representative database of critical care admissions. DESIGN: Prospective cohort study. SETTING: A total of 163 adult general critical care units in England, Wales, and Northern Ireland, during the period of December 1995 to August 2003. PATIENTS: A total of 231,930 admissions, of which 141,106 met inclusion criteria and had sufficient data recorded for all risk prediction models. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The published versions of the Acute Physiology and Chronic Health Evaluation (APACHE) II, APACHE II UK, APACHE III, Simplified Acute Physiology Score (SAPS) II, and Mortality Probability Models (MPM) II were evaluated for discrimination and calibration by means of a combination of appropriate statistical measures recommended by an expert steering committee. All models showed good discrimination (the c index varied from 0.803 to 0.832) but imperfect calibration. Recalibration of the models, which was performed by both the Cox method and re-estimating coefficients, led to improved discrimination and calibration, although all models still showed significant departures from perfect calibration. CONCLUSIONS: Risk prediction models developed in another country require validation and recalibration before being used to provide risk-adjusted outcomes within a new country setting. Periodic reassessment is beneficial to ensure calibration is maintained.

Assessment and optimization of mortality prediction tools for admissions to pediatric intensive care in the United kingdom.

OBJECTIVE: To assess the Pediatric Risk of Mortality (PRISM, PRISM III-12, and PRISM III-24) systems and the Pediatric Index of Mortality (PIM and PIM2) systems for use in comparing the risk-adjusted mortality of children after admission for pediatric intensive care in the United Kingdom. METHODS: All PICUs in the United Kingdom were invited to participate. Predicted probability of PICU mortality was calculated using the published algorithms for PIM, PIM2, and PRISM and compared with observed mortality. These scores, along with PRISM III-12 and PRISM III-24, whose algorithms are not published, were optimized for the United Kingdom. RESULTS: Of 26 PICUs in the United Kingdom, 22 (85%) were recruited, and sufficient prospective data were collected from 18 (69%) units on 10,197 (98%) of 10,385 admissions between March 2001 and February 2002. All published tools were found to have poor calibration but provided good discriminatory power. After estimation of UK-specific coefficients, only PIM2, PRISM III-12, and PRISM III-24 had satisfactory calibration. All models provided good discriminatory power. Funnel plots for all of the recalibrated models indicated that the risk-adjusted mortality for all units was consistent with random variation. CONCLUSIONS: PIM2, PRISM III-12, and PRISM III-24 all were found to be suitable for use in a UK PICU setting. All tools provided similar conclusions in assessing the distribution of risk-adjusted mortality in UK PICUs. It now is important that these tools be used to monitor outcome and improve the quality of pediatric intensive care within the United Kingdom.

Simplifying a prognostic model: a simulation study based on clinical data.

Prognostic models are designed to predict a clinical outcome in individuals or groups of individuals with a particular disease or condition. To avoid bias many researchers advocate the use of full models developed by prespecifying predictors. Variable selection is not employed and the resulting models may be large and complicated. In practice more parsimonious models that retain most of the prognostic information may be preferred. We investigate the effect on various performance measures, including mean square error and prognostic classification, of three methods for estimating full models (including penalized estimation and Tibshirani's lasso) and consider two methods (backwards elimination and a new proposal called stepdown) for simplifying full models. Simulation studies based on two medical data sets suggest that simplified models can be found that perform nearly as well as, or sometimes even better than, full models. Optimizing the Akaike information criterion appears to be appropriate for choosing the degree of simplification.

Epidemiology of severe sepsis occurring in the first 24 hrs in intensive care units in England, Wales, and Northern Ireland.

OBJECTIVE: To investigate the numbers, clinical characteristics, resource use, and outcomes of admissions who met precise clinical and physiologic criteria for severe sepsis (as defined in the PROWESS trial) in the first 24 hrs in the intensive care unit. DESIGN: Observational cohort study, with retrospective analysis of prospectively collected data. SETTING: Ninety-one adult general intensive care units in England, Wales, and Northern Ireland between 1995 and 2000. PATIENTS: Patients were 56,673 adult admissions. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We found that 27.1% of adult intensive care unit admissions met severe sepsis criteria in the first 24 hrs in the intensive care unit. Most were nonsurgical (67%), and the most common organ system dysfunctions were seen in the cardiovascular (88%) and respiratory (81%) systems. Modeling the data for England and Wales for 1997 suggested that 51 (95% confidence interval, 46-58) per 100,000 population per year were admitted to intensive care units and met severe sepsis criteria in the first 24 hrs.Of the intensive care unit admissions who met severe sepsis criteria in the first 24 hrs, 35% died before intensive care unit discharge and 47% died during their hospital stay. Hospital mortality rate ranged from 17% in the 16-19 age group to 64% in those >85 yrs. In England and Wales in 1997, an estimated 24 (95% confidence interval, 21-28) per 100,000 population per year died after intensive care unit admissions with severe sepsis in the first 24 hrs. For intensive care unit admissions who met severe sepsis criteria in the first 24 hrs, median intensive care unit length of stay was 3.56 days (interquartile range, 1.50-9.32) and median hospital length of stay was 18 days (interquartile range, 8-36 days). These admissions used 45% of the intensive care unit and 33% of the hospital bed days used by all intensive care unit admissions. CONCLUSIONS: Severe sepsis is common and presents a major challenge for clinicians, managers, and healthcare policymakers. Intensive care unit admissions meeting severe sepsis criteria have a high mortality rate and high resource use.

Randomised controlled trial assessing the impact of a nurse delivered, flow monitored protocol for optimisation of circulatory status after cardiac surgery.

OBJECTIVE: To assess whether a nurse led, flow monitored protocol for optimising circulatory status in patients after cardiac surgery reduces complications and shortens stay in intensive care and hospital. DESIGN: Randomised controlled trial. SETTING: Intensive care unit and cardiothoracic unit of a university teaching hospital. PARTICIPANTS: 174 patients who underwent cardiac surgery between April 2000 and January 2003. INTERVENTIONS: Patients were allocated to conventional haemodynamic management or to an algorithm guided by oesophageal Doppler flowmetry to maintain a stroke index above 35 ml/m2. RESULTS: 26 control patients had postoperative complications (two deaths) compared with 17 (four deaths) protocol patients (P = 0.08). Duration of hospital stay in the protocol group was significantly reduced from a median of nine (interquartile range 7-12) days to seven (7-10) days (P = 0.02). The mean duration of hospital stay was reduced from 13.9 to 11.4 days, a saving in hospital bed days of 18% (95% confidence interval -12% to 47%). Usage of intensive care beds was reduced by 23% (-8% to 59%). CONCLUSION: A nurse delivered protocol for optimising circulatory status in the early postoperative period after cardiac surgery may significantly shorten hospital stay.