Development of a Predictive Model for Induction Success of Labour

Induction of the labour process is an extraordinarily common procedure used in some pregnancies. Obstetricians face the need to end a pregnancy, for medical reasons usually (maternal or fetal requirements) or less frequently, social (elective inductions for convenience). The success of induction procedure is conditioned by a multitude of maternal and fetal variables that appear before or during pregnancy or birth process, with a low predictive value. The failure of the induction process involves performing a caesarean section. This project arises from the clinical need to resolve a situation of uncertainty that occurs frequently in our clinical practice. Since the weight of clinical variables is not adequately weighted, we consider very interesting to know a priori the possibility of success of induction to dismiss those inductions with high probability of failure, avoiding unnecessary procedures or postponing end if possible. We developed a predictive model of induced labour success as a support tool in clinical decision making. Improve the predictability of a successful induction is one of the current challenges of Obstetrics because of its negative impact. The identification of those patients with high chances of failure, will allow us to offer them better care improving their health outcomes (adverse perinatal outcomes for mother and newborn), costs (medication, hospitalization, qualified staff) and patient perceived quality. Therefore a Clinical Decision Support System was developed to give support to the Obstetricians. In this article, we had proposed a robust method to explore and model a source of clinical information with the purpose of obtaining all possible knowledge. Generally, in classification models are difficult to know the contribution that each attribute provides to the model. We had worked in this direction to offer transparency to models that may be considered as black boxes. The positive results obtained from both the information recovery system and the predictions and explanations of the classification show the effectiveness and strength of this tool

Resist, comply or workaround? An examination of different facets of user engagement with information systems

This paper provides a summary of studies of user resistance to Information Technology (IT) and identifies workaround activity as an understudied and distinct, but related, phenomenon. Previous categorizations of resistance have largely failed to address the relationships between the motivations for divergences from procedure and the associated workaround activity. This paper develops a composite model of resistance/workaround derived from two case study sites. We find four key antecedent conditions derived from both positive and negative resistance rationales and identify associations and links to various resultant workaround behaviours and provide supporting Chains of Evidence from two case studies

Prediction of mode of delivery in term pregnancies: development of scoring system

Background: The objective of the study was to develop and to validate a scoring system to predict the mode of delivery.Methods: The study involved 835 term pregnancies in labor. Backward multiple logistic regression analysis was carried out in 600 women to identify the factors independently associated with vaginal or caesarean delivery and logistic coefficients were determined to provide weightage for each of the factors. The total score was calculated for each subject. Sensitivity and specificity for vaginal/ cesarean delivery were calculated for different total scores. The validity of the scoring was studied by applying to the same data provider group retrospectively, and on other 235 laboring women prospectively recruited after the development of score.Results: Of 600 women, 61.2% had vaginal deliveries. The significant facilitating factors for vaginal delivery were found to be maternal age of 20-25 years (p=0.02), multiparity (p=0.002), unscarred uterus (p=0.05), rhesus positivity (p=0.05), expected baby weight of 2.5-3.5 kg (p=0.004), and with cephalic presentation, Bishop status> 4, spontaneous onset of labor, clear liquor, and no FHR abnormality (p=0.00).A cut off score of 21 predicted the vaginal delivery with sensitivity , specificity, positive predictive value and negative predictive values of 80%, 65%, 70% and 76%, respectively.Conclusions: The composite score of 21 suggests that woman will most probably have vaginal delivery and that a higher score does not always mean a caesarean delivery

Prediction of adverse perinatal outcomes following induction of labour

Induction of labour (IOL) is one of the most common obstetric procedures which is carried out in 20-30% of pregnancies. More than a third of women having IOL will need either an instrumental delivery or a caesarean section. Induction will fail for approximately 10% of women who undergo the process. The number of indications for IOL have increased in the last few years with guidelines from professional bodies recommending induction for a range of obstetric and medical complications. This has a significant impact on the capacity and flow on antenatal wards and delivery suites across the country. There are currently no effective methods that can accurately predict the success of IOL. The current method for assessment prior to IOL includes a vaginal examination to assess the Bishop Score, which is an objective way of defining the extent of cervical ripening. There are other methods described in the current literature such as the measurement of cervical length, posterior cervical angle and more recently the angle of progression (AOP), head to perineum distance (HPD) and cervical compression index (CCI). There is also some evidence that biochemical markers such as placental alpha macroglobulin-1 and fetal fibronectin may predict the onset of labour. This has been used in management of patients with threatened preterm birth. However, there is no composite model for the accurate prediction of adverse maternal or neonatal outcomes following IOL. The main objective of this thesis is to examine which factors amongst maternal demographics and components of obstetric history, biophysical and biochemical markers, are altered in women who have adverse outcomes following IOL. I propose to develop a model that will accurately predict the risk of caesarean section for failure to progress or for suspected fetal distress using a combination of maternal and fetal factors measured at a pre-induction clinic (PIC). This model would be of significant benefit in counselling women prior to IOL

Why is Economic Geography not an Evolutionary Science?

This paper explains the main commonalities and differences between neoclassical, institutional and evolutionary approaches that have been influential in economic geography during the last couple of decades. For all three approaches, we argue that they are in agreement in some respects and in conflict in other respects. While explaining to what extent and in what ways the Evolutionary Economic Geography approach differs from the Neoclassical (or ‘new’) Economic Geography and the Institutional Economic Geography, we can specify the value-added of economic geography as an evolutionary science. Finally, we briefly outline a research agenda of the Evolutionary Economic Geography we like to explore.

The Two Methods of Economics

A Teoria Econômica Emprega Dois Métodos: o Método Hipotético-Dedutivo, Utilizado Principalmente Pelos Economistas Neoclássicos, e o Método Histórico-Dedutivo, Adotado Pelos Economistas Clássicos e Keynesianos. Ambos são Legítimos, Mas, Desde que a Economia é Substantiva, não uma Ciência Metodológica, Onde o Objeto é o Sistema Econômico, o Método Histórico-Dedutivo é o Mais Apropriado. o Método Hipotético-Dedutivo Permite que o Economista Desenvolva Ferramentas para Analisar o Sistema Econômico, Mas Falha ao Analisar o Sistema como um Todo. em Contrapartida, o Método Histórico-Dedutivo Parte da Observação Empírica da Realidade e da Busca por Regularidades e Tendências. é um Método Empírico, Apropriado para as Ciências Substantivas que Tratam de Sistemas Abertos, como é o Caso da Economia.

Prediction of Caesarean Delivery

For expectant parents, a first birth is notable for its unpredictability, and the path to safe labour and delivery is commonly complicated by a requirement for unplanned caesarean delivery. The ability to anticipate an uncomplicated vaginal birth, or to predict the requirement for unplanned caesarean delivery, carries the potential to facilitate optimal birth choices. For example, elective caesarean delivery confers substantially less risk than unplanned caesarean delivery performed during the course of labour. Pre-delivery knowledge of a high predictive risk of requiring intrapartum caesarean delivery could lead to women opting to deliver by elective caesarean delivery, thereby lowering associated risks. Equally, pre-labour knowledge of a high prospect of achieving a successful and uncomplicated vaginal birth could result in enhanced motivation for women to deliver in a less medicalised environment. Predictive risk models have been utilised to good effect in other areas of medicine. The incorporation of a risk predictive tool for intrapartum caesarean delivery would enable women and their caregivers to choose the most appropriate management plan for each woman

Human resource management in India: strategy, performance and complementarity

This study seeks to explore which types of HR practice are associated with better organisational performance (OP). Whilst the core finding—that specific HR practices lead to better organisational outcomes may not be surprising—we also found an absence of complementarity. Normally, the absence of complementarities would suggest limitations in institutional supports; on the one hand, however, institutional shortfalls are not unique to India and may be encountered in many emerging market settings. In contrast, the great internal diversity of the Indian setting, with strong variations recognised amongst institutions, along with enforcement capabilities, might suggest that these tendencies are particularly pronounced. We also found a strong link between the intrinsic rewards and performance—an unexpected result in a low-income country, where wages are generally low. We suggest that this may reflect the nature of the labour market and the limited (and possibly proportionately shrinking) pool of good jobs, making exit a difficult option for all but the best qualified. Whilst this puts employees in a poor bargaining position in bidding-up pay (making pay rises seem unfeasible), the intrinsic attributes of the job become more important

Towards optimal caesarean practice

This dissertation focuses on improving caesarean section care. The goal was to identify groups of women for whom guidelines are not always followed and for whom improved care can be realised. This research shows improved care is possible in women with a previous caesarean section, women who are pregnant with a first child with signs of foetal distress, women who are pregnant with a first child when birth does not progress and in the continuous guidance of the birth. Strategies were developed to improve caesarean section care after identifying the factors which promote or impede optimal care, as well as those that influence the chance of an unplanned caesarean section. For example, continuous guidance results in fewer assisted births, fewer requests for pain relief and increased satisfaction of the woman postpartum. Partially financed by zonMW (grant number 17100.3006)

Re-reengineering the dream: agility as competitive adaptability

Organizational adaptation and transformative change management in technology-based organizations is explored in the context of collaborative alliances. A Re-reengineering approach is outlined in which a new Competitive Adaptability Five-Influences Analysis approach under conditions of collaborative alliance, is described as an alternative to Porter’s Five-Forces Competitive Rivalry Analysis model. Whilst continuous change in technology and the associated effects of technology shock (Dedola & Neri, 2006; Christiano, Eichenbaum & Vigfusson, 2003) are not new constructs, the reality of the industrial age was and is a continuing reduction in timeline for relevance and lifetime for a specific technology and the related skills and expertise base required for its effective implementation. This, combined with increasing pressures for innovation (Tidd & Bessant, 2013) and at times severe impacts from both local and global economic environments (Hitt, Ireland & Hoskisson, 2011) raises serious challenges for contemporary management teams seeking to strategically position a company and its technology base advantageously, relative to its suppliers, competitors and customers, as well as in predictive readiness for future technological change and opportunistic adaptation. In effect, the life-cycle of a technology has become typically one of disruptive change and rapid adjustment, followed by a plateau as a particular technology or process captures and holds its position against minor challenges, eventually to be displaced by yet another alternative (Bower & Christensen, 1995)