Measuring and predicting the use of evidence-based management

Evidence-based management (EBM) is an increasingly essential framework to bolster informed decision-making. Amid a complex and uncertain environment, combined with an ever-increasing volume of relevant yet contradictory evidence, EBM aids managers to use the best available evidence from multiple sources to make decisions. Despite the potential benefits of EBM, and the general lack of EBM use among practitioners, little is known about the factors and mechanisms that enable its practice. This thesis presents three papers that aim to shed light on the factors that facilitate EBM. I first explore the literature and use meta-analyses to identify multi-level factors that are likely to facilitate EBM use. The findings highlight organisational-level and individual-level enablers of EBM that should be prioritised in future research. Following this, I draw on the Ability-Motivation-Opportunity framework to conduct two experimental laboratory studies which examine the effect of these three predictors. I rely on a novel measure of EBM use, which I develop and validate as objective measures of evidence collection and evidence-based decision-making. The results support rational thinking ability and social norms as significant predictors of EBM. The final study focuses on the influence of rational thinking ability in predicting the adaptive use of EBM, and specifically evidence collection. One online experiment and two additional laboratory experiments investigate whether individuals high on rational thinking ability adapt evidence collection under cognitive load and emotional load. The findings provide support that under cognitive load, individuals high on rational thinking ability refrain from collecting more evidence. However, under emotional load, rational thinking ability helps mitigate these effects and predicts more evidence collection. The findings advance empirical knowledge and theoretical insights on EBM. I highlight enablers of EBM at multiple levels of analysis and shed light on the mechanisms through which rational thinking ability influences EBM use and decision-making

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Towards a process model of evidence based decision-making

This thesis aims to develop a process model that explains why some managers engage in evidence based decision-making (EBDM) more than others. This process model is developed by drawing on the work of van Hooft and Noordzij (2009), and views Learning Goal Orientation (LGO) and Theory of Planned Behaviour (TPB) as complementary perspectives to explain intentions and behaviours. The model is then quantitatively tested with a sample of 203 senior managers from the built environment sector (i.e., inception, design and development of office buildings). To complement the cross-sectional survey, 17 in-depth interviews were conducted to ensure the relevant facilitating conditions and barriers to EBDM were captured in the model. The quantitative results support the proposed process model of EBDM. LGO is a higher order construct of TPB in predicting EBDM. LGO and TPB also explain unique additional variance in EBDM. The strongest predictors of the intention to adopt EBDM and its consequent practice are LGO and subjective norms. The qualitative results expand on the importance of the latter, by explaining how, beyond the expectations of the immediate work group, the norms embedded in organisations and industries create collective routinisation, which is when a decision-making process carried out by multiple actors is simplified and standardized. I outline why collective routinisation is important for EBDM and explore the differences between how practitioners and academics view EBDM. This thesis makes theoretical contributions by integrating LGO, TPB and the organisational learning literatures to develop a process model of EBDM. This process model identifies important barriers that must be overcome if EBDM is to be more widely practiced. The findings suggest that organisations can increase the practice of EBDM by fostering a LGO amongst employees, and balancing both exploitative and exploratory activities within their routines.

Evidence Based Practice for the Built Environment: Can Systematic Reviews Close the Research - Practice Gap?

© 2017 The Authors. A high performance building is designed and operated to minimise environmental impact whilst providing an indoor environment that maximises occupant health and comfort. The wealth of academic research into technical and non-technical solutions for high performance building continues to grow. However, industry utilisation of academic research is limited and inconsistent due to a number of factors. This situation is compounded by academics using a broad range of methodologies, which prevents a consistent and widely accepted body of knowledge being developed. These factors contribute to a widening research-practice gap. Evidence based (EB) practice is a potential avenue to close this gap. Applied in medicine, EB practice uses a rigorous, more systematic approach on which to base decisions and increase the likelihood of the desired outcome. This paper will outline an approach being used to introduce evidence based practice to the built environment by a research project of the CRC for Low Carbon Living, an Australian based, industry focussed research collaboration. This paper will detail results from the first stage of the research, which assesses the applicability and suitability of using a systematic review process for built environment research. The paper will discuss the difficulties with such an approach to the built environment field, and proposes a 'realist synthesis' adaptation

Evolution over Time of Ventilatory Management and Outcome of Patients with Neurologic Disease∗

OBJECTIVES: To describe the changes in ventilator management over time in patients with neurologic disease at ICU admission and to estimate factors associated with 28-day hospital mortality. DESIGN: Secondary analysis of three prospective, observational, multicenter studies. SETTING: Cohort studies conducted in 2004, 2010, and 2016. PATIENTS: Adult patients who received mechanical ventilation for more than 12 hours. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Among the 20,929 patients enrolled, we included 4,152 (20%) mechanically ventilated patients due to different neurologic diseases. Hemorrhagic stroke and brain trauma were the most common pathologies associated with the need for mechanical ventilation. Although volume-cycled ventilation remained the preferred ventilation mode, there was a significant (p &lt; 0.001) increment in the use of pressure support ventilation. The proportion of patients receiving a protective lung ventilation strategy was increased over time: 47% in 2004, 63% in 2010, and 65% in 2016 (p &lt; 0.001), as well as the duration of protective ventilation strategies: 406 days per 1,000 mechanical ventilation days in 2004, 523 days per 1,000 mechanical ventilation days in 2010, and 585 days per 1,000 mechanical ventilation days in 2016 (p &lt; 0.001). There were no differences in the length of stay in the ICU, mortality in the ICU, and mortality in hospital from 2004 to 2016. Independent risk factors for 28-day mortality were age greater than 75 years, Simplified Acute Physiology Score II greater than 50, the occurrence of organ dysfunction within first 48 hours after brain injury, and specific neurologic diseases such as hemorrhagic stroke, ischemic stroke, and brain trauma. CONCLUSIONS: More lung-protective ventilatory strategies have been implemented over years in neurologic patients with no effect on pulmonary complications or on survival. We found several prognostic factors on mortality such as advanced age, the severity of the disease, organ dysfunctions, and the etiology of neurologic disease