The purpose of this thesis is to examine the process of organizational socialization in hospital newcomers, and the effects of this process on their levels of well-being and service quality. Following a review of the literature, two original models of socialization are presented and then tested using a longitudinal mixed methods case study approach that includes quantitative and qualitative components. The models take a novel approach by viewing the psychological contract as the key mechanism through which communication and learning facilitate employee integration. The survey study revealed that during the first three months of socialization, proactively obtained useful information about the new environment led to an increase in perceived organizational promises, which in turn was related to better attitudes and well-being. Useful information provided by the organization led to an increased focus on service quality, but did not influence perceived promises. After twelve months, greater knowledge about the environment led to lower perceptions of violation, which in turn was associated with better attitudes, well-being and service quality focus. The interview study revealed that breach and fulfilment of the psychological contract, under certain circumstances, acted as turning points which caused a sharp change in well-being and service quality. Overall, there is broad support for the theoretical framework and for the role of the psychological contract as an intervening mechanism in the socialization process. Additionally, the findings suggest that socialization is not the smooth process towards integration that much previous work implies. In practical terms, the findings indicate that organizations must ensure that newcomers are provided with both functional and social information, that they are encouraged to ask questions and that existing insiders are encouraged to respond with useful information.

There is increasing interest in outcomes assessment in modern surgical research and the applicability of outcomes research to everyday clinical practice. Improving healthcare quality is a current political priority and since outcomes are the most visible and quantifiable end points of clinical care pathways, they are most frequently publicised. Standardised mortality metrics such as the Hospital Standardised Mortality Ratio are of particular interest given their current media spotlight following recent infamous failings in the quality of NHS care. Specialised mortality metrics such as the "failure-to-rescue" rate are of particular interest to clinicians given their theoretical superiority in identifying failings in standards of care but derivation of such metrics from administrative data requires identification of complications of care. However, a number of unanswered questions remain including the utility of Hospital Episode Statistics (the national administrative dataset) for providing outcomes data such as mortality and complication rates. Additionally the validity of hospital wide summary mortality measures remains incompletely defined given the lack of data on the inter-dependencies of outcomes between disparate patient groups within English hospitals. Methods Hospital Episode Statistics were used to provide national patient level data on various defined cohorts including patients undergoing emergency medical, emergency surgical, elective general surgical and elective vascular surgical care in England from 2000 - 2010. Outcomes included in hospital and longer term mortality as well as non-mortality metrics such as emergency readmission, length of stay, complication rates and "failure-to-rescue" rates. Complications data validation was performed through case note review for matched patients undergoing cholecystectomy. Novel methods were developed to manipulate the HES data, to analyse inter-provider variability in outcomes and to evaluate evidence of intra-provider inter-dependencies in outcomes amongst different clinical groups. A number of statistical methods were employed including systematic review for evidence base synthesis and multi-level regression modeling for risk-adjustment. Results 60.8% of published studies using HES data were on surgical specialties and the most common analytic theme was of inequalities and variations in treatment or outcome (27%). The volume of published studies has increased with time (r = 0.82, P < 0.0001) as has the length of study epoch (r = 0.76, P <0.001) and the number of outcomes assessed per study (r = 0.72, P = 0.0023). Generic methodologic data were better reported than those specific to HES data extraction. For the majority of parameters, there were no improvements with time. 2,406,709 admissions across 20 emergency groups, 116,596 emergency and elective vascular surgical admissions across 5 groups and 418,214 cholecystectomy procedures were considered in three separate analyses. Clinically and statistically significant variations in outcome were observed between providers (p<O.OOl). The risk-adjusted outcome in a given hospital for an individual clinical group was significantly predicted by the aggregated outcome of the other clinical groups. There were several strong correlations (r>O.s) between specific pairs of groups. The relative dearth of significant negative correlations suggested that outcomes were hospital-specific. For cholecystectomy provision, evidence was found that hospital characteristics (case volume and presence of specialized surgical units) were associated with improved processes of care (p<O.OOOl). Coding accuracy was relatively high for specific procedural complications of care following cholecystectomy at a single centre (sensitivity and specificity of 81.8% and 99.7% for conversion to open and 100% for bile duct injury). Conclusions Studies using HES data to report healthcare outcomes have increased in volume, scope and complexity with time. It is likely that the role of these studies in assessing healthcare, benchmarking practice and planning service delivery will continue to increase. Hospital-level risk-adjusted mortality and non-mortality outcomes across a range of emergency and elective specialties vary considerably. There was evidence of hospitals being globally high or low performers suggesting that hospital-level structural and process factors might influence outcomes. The implications could be far reaching, both in terms of investigating performance at individual hospitals and in the development of a hospital ratings system. Further research should be directed towards identifying structure and process factors which might underlie the findings.

The strategic implementation process is a mystery to many businessmen and consultants, and due to its complexity, only limited strategic management research has actually focused on implementation. However, a clear understanding of the factors influencing the implementation process in terms of the industrial context, and the implementation factors needs to be considered. Thus, the ultimate aim of this research is to build a framework facilitating the implementation process. Initially, based on factors identified through the comprehensive review of the literature, a framework was developed. Then, relationships between the factors were proposed and tested within the study in order to validate the framework. Data was collected using both qualitative and quantitative. In the first stage, mini case studies were performed to explore the factors during the implementation process, aiming at validating the factors that have been extracted from the literature review. Then, a pilot study was performed to authenticate the questionnaire which would be used in the final stage. This research will employ four types of statistical data analysis, namely: partial correlation analysis, ANOV A analysis, hierarchical regression analysis, and structural equation modelling (AMOS application). Results of the study have verified that these implementation factors and influencer factors are critical to implementation process. The inter-relationship among these complex factors is essential in impacting the outcome. Results also demonstrated that there were recognized differences between successful and less successful hospitals in implementing this policy., However, results did not reveal much difference in implementing this policy, between the public and the private hospitals. Finally, different types of interaction in the different proposed contexts (public and private) have been revealed. Hence, a fully mediated model is best used to explain the relationship among the factors in public hospitals, indicating a significant impact that the external factors have on the outcome. As for private hospitals, a partially mediated model is best used to describe the relationship among the factors due to its ability to control the external environment.

No description available.

Literature has established FM as a global business model that continues to explore how organisation can grow faster through expansion into new markets, find new ways of fostering innovation through collaborative outsourcing that will achieve right balance between the decision to outsource, risks and legal requirements embedded in the service level agreement (SLA) between client organisations and their FM outsourcing vendors. The study aims to develop and test a framework for outsourcing facilities management services using data from Nigeria’s public hospitals. The specific objectives are among others; to determine a set of key factors that influence the decision to outsource facilities management services in public hospitals; to conduct an empirical survey of facilities management services outsourced in public hospitals; to access the satisfaction of users of outsourced FM services and model the satisfaction of users on quality of outsourced facilities management services using SEM; and assess the probability and severity of risks associated with outsourcing of facilities management services in public hospitals. Data for this study were collected using a cross sectional 2-strand questionnaire survey and case study. During the first strand of questionnaire survey, a total of 85 responses were received from the six states comprising the study area while 11 of them were discarded due to missing data resulting in 74 usable responses. This gave an overall response rate of 45.4%. A total of 246 survey responses were received during the second strand of questionnaire survey. Of these, 38 were not fully completed and therefore discarded leaving 208 as usable responses. This resulted in an overall response rate of 25.1%. The case study component involved semi-structured interview section with 4 participants representing 4 cases (3 hospitals and 1 FM organisation). Findings revealed that 25 of the 31 factors were significant in explaining the decision to outsource FM service in Nigeria’s public hospitals; while 15 of them grouped into 5 broad categories were recommended for framework construction based on their factor loadings during analysis. Also, 6 facilities management services including plant management and repairs; general cleaning services; waste disposal and environmental management; landscape maintenance; security; and catering/restroom management are completely outsourced in all the 74 hospitals. Findings additionally revealed that service quality in relation to catering, plant maintenance, waste management, security, landscape maintenance, and cleaning services received very high satisfaction ratings from respondents. Findings also established 24 out of the 35 risk factors as critical, 4 factors as somehow critical, and 5 factors as not critical. Besides, 9 risk factors were selected based on their factor loadings from PCA to develop the outsourcing framework. Drawing on theoretical analysis and input from the questionnaire survey and case study, an outsourcing framework comprising 4 components was developed to assist public hospitals administrators achieve sustainable best practice resource management. It is recommended among others that further research be conducted to develop standardised criteria for vendor selection processes.

The rationale for carrying out this research was to address the clear lack of knowledge surrounding the measurement of public hospital performance in Ireland. The objectives of this research were to develop a comprehensive model for measuring hospital performance and using this model to measure the performance of public acute hospitals in Ireland in 2007. Having assessed the advantages and disadvantages of various measurement models the Data Envelopment Analysis (DEA) model was chosen for this research. DEA was initiated by Charnes, Cooper and Rhodes in 1978 and further developed by Fare et al. (1983) and Banker et al. (1984). The method used to choose relevant inputs and outputs to be included in the model followed that adopted by Casu et al. (2005) which included the use of focus groups. The main conclusions of the research are threefold. Firstly, it is clear that each stakeholder group has differing opinions on what constitutes good performance. It is therefore imperative that any performance measurement model would be designed within parameters that are clearly understood by any intended audience. Secondly, there is a lack of publicly available qualitative information in Ireland that inhibits detailed analysis of hospital performance. Thirdly, based on available qualitative and quantitative data the results indicated a high level of efficiency among the public acute hospitals in Ireland in their staffing and non pay costs, averaging 98.5%. As DEA scores are sensitive to the number of input and output variables as well as the size of the sample it should be borne in mind that a high level of efficiency could be as a result of using DEA with too many variables compared to the number of hospitals. No hospital was deemed to be scale efficient in any of the models even though the average scale efficiency for all of the hospitals was relatively high at 90.3%. Arising from this research the main recommendations would be that information on medical outcomes, survival rates and patient satisfaction should be made publicly available in Ireland; that despite a high average efficiency level that many individual hospitals need to focus on improving their technical and scale efficiencies, and that performance measurement models should be developed that would include more qualitative data.

No description available.

Background: Performance-based contracting (PBC) and similar approaches to tie funding to measured performance have become major characteristics of innovative financing mechanisms. The World Bank and Uganda's Ministry of Health pilot tested PBC in five districts for a period 2003 to 2006. This PhD examines the response to this pilot among private-not-for-profit (PNFP) hospitals. Methods: A multi-level analysis was undertaken to explore essential up-stream and downstream institutional relationships and functions for PBC success. Agency-based and processbased organisational theories were used as alternative frameworks to build explanations of the response actions. In -depth case studies were carried out using mixed methods among PNFP hospitals that were assigned to different mix of PBC pilot components (performance targets, service output metering, performance feedback and financial bonuses). Seven PNFP hospitals participated in the PBC pilot while an additional three non-participating public hospitals provided opportunity for comparative analysis. In-depth interviews (28) covered hospital management teams (HMTs) and members of their Board of Governors (BOG) in all the ten hospitals. Five district health officials, two implementers of PBC pilots and two officials from Uganda Catholic Medical Bureau (UCMB) were also interviewed. A survey of 560 hospital staff at baseline and 741 after 12 months was undertaken among the 10 hospitals to measure changes in perceptions relevant to hospital performance. Participant observations were undertaken during meetings for PBC pilot activities as well as meetings for reviewing the performance of health activities at national and district levels. Major findings: Upstream support functions like financial disbursement, staff movements and costs of service provision formed contextual constraints for the hospitals to respond to PBC. Likewise, governance relationships between HMT and BOG provided additional constraints for PBC success. Hospital managers were expected to respond to several performance-focused interventions - many of which were contradictory to the PBC targets. Among the difficulties observed during the PBC pilot implementation, poor metering of performance and inadequate financing for the essential pilot elements were particularly problematic. The implementation arrangements generated unanticipated negative performance influences especially among the control group -a situation that may overestimate the pilot effectiveness. Findings show that financial bonuses at the organization level can create either motivation or demotivation among staff depending on the hygiene of the bonus allocation processes within an organization. Results from the staff surveys indicate that the drivers for performance improvements in the hospitals were related to job satisfaction, performance governance of work teams, availability of medicines and supplies, as well as staff satisfaction with their financial benefits. Conclusions: PBC may not achieve optimal effectiveness in settings without a package of supplementary interventions for improving resource inputs, performance governance and motivating the workforce. Financial incentives as predicted from agency theory were not sufficient for PBC success. Micro-care approaches aimed at improving the organisational processes (process-based theory) for better performance will be required for greater effectiveness of PBC initiatives and policies. Policy prescriptions and implementation arrangements for PBC interventions need to provide for on-going monitoring of mechanisms and consequences as a basis for mitigating harmful effects on health systems and optimizing the good.

No description available.

This piece of work describes a hospital's Critical Care Unit and uses different mathematical techniques to model the behaviour seen there. The main factor that is included in these models is the problem of bed blocking in the Unit. Blocking is defined as patients who are well enough not to be in the Critical Care Unit, but remain there, for any number of reasons. These patients are using up an expensive and limited resource. The mathematical techniques that the models are built on are extensively reviewed and analysed. These are the Coxian Phase Type Distribution and Networks of Queues with Blocking Equations. Both techniques are described in detail and their distributions analysed under different circumstances. The final chapter shows how the two distributions can be used to model a complex situation such as the one found in the Critical Care Unit. The models are tested and compared. Finally, the models are tested under a number of 'what if scenarios to predict the effect of changing certain factors on the actual Unit.