An advanced systemic lesson learned knowledge model for project organisations

The research study described in this thesis was inspired by many years as a project manager, watching the failure of organisation projects, and the lessons learned. This led to the research idea of how can the lessons learned enable organisations to learn from past project experiences to drive continuous improvement. The thesis is based on five published publications that collectively make a significant contribution to knowledge of the development of the Systemic Lessons Learned Knowledge (Syllk) model (Paper One) and application of the Syllk model (Papers Two, Three and Four) and the research methodology (Paper Five). I have applied an action research study which addressed the dual imperatives of both the research and problem solving by using a series of action research cycles on three separate projects. The research method consisted of multiple spiral action research cycles. I have demonstrated how to apply the Syllk model to enable the organisations to disseminate and apply knowledge/lessons learned. The initial planning stage consisted of interviews, followed by focus groups, to identify the facilitators and barriers that impact upon the initial design of the Syllk model within the organisation. Established knowledge management practices were aligned with each of the Syllk elements to address the identified barriers and facilitate learning as the action cycles progressed. Initiatives were implemented, and actions were observed, monitored, and then evaluated after a period of reflection using an after-action review process. The results from this research showed how knowledge capability can be wired (distributed) across organisational systems (capability networked) and how the Syllk model can be used to conceptually facilitate this. The research study described in this thesis provides insights into how an organisation learns and how it can be effectively wired to acquire and accumulate knowledge, including from lessons learned. The thesis highlights that the variables of the Syllk model (learning, culture, social, technology, process and infrastructure) were found to be the most dynamic and influential for the organisation participating in the action research. The action research outcomes showed that an organisation is not a simple structure, but rather, a complex interweaving and coupling (capability network) of the Syllk elements of people and systems. Processes in the organisation need to align with the elements of the Syllk model. Using action research is one possible way forward. One needs to understand how the organisation is wired for knowledge and lessons learned. The findings from this research form a sound structure for future research studies based on the application of the Syllk model. This research supports the premise that to successfully manage projects and day-to-day business activities, the learning process is challenged by many barriers. The thesis demonstrates that action research can benefit project management and knowledge management researchers and practitioners

The contribution of musculoskeletal disorders and multimorbidity to health-related job loss among older working-age adults: a population-based study

BACKGROUND: Employment is the most important source of financial income and material well-being and therefore is the main driver of the social gradient in physical health, mental health, and mortality. In addition, good employment fulfils psychosocial needs and is fundamental for an individual’s social status, societal participation, and identity. However, work participation is known to fall steeply after the age of 50 in women and 55 in men. In the EU, musculoskeletal disorders (MSDs) account for 50% of all absences from work lasting 3 days or longer and for 60% of all permanent work incapacity. However, in those aged over 50, MSDs also commonly co-occur with other health conditions, in what is known as multimorbidity. AIMS: the overarching aims of this thesis are to investigate, among older working-aged people, a) the impact of common comorbid health conditions on work outcomes in people with MSDs, and b) the common patterns of multimorbidity and their contribution to health-related job loss. METHODS: Chapter four is a systematic review of the impact of comorbidity on work outcomes in people with musculoskeletal disease. The chapters that follow describe results from a nested matched case-control study of working-age participants, over the age of fifty. Health and Employment After Fifty (HEAF) study participants with health-related job loss (HRJL) were matched 1:1 to working control participants for age, sex, and GP practice. Participants’ health diagnoses at the time of HRJL were extracted using retrospective data from the Clinical Practice Research Datalink (CPRD). Chapter five describes a cohort of older workers with HRJL (case participants) for their known demographic, lifestyle, occupational, and health factors. Chapter six compares case participants to working controls for CPRD-defined health disorders to assess their association with HRJL. Chapter seven uses cluster analysis to describe common patterns of multimorbidity across the total study sample. In Chapter eight, these prominent clusters of health disorders were explored for their association with HRJL. Finally, in Chapter nine, multivariable conditional logistic models were constructed using purposeful selection to explore the population attributable fraction of HRJL for CPRD-defined health disorders. CONCLUSIONS: Results supported the primary importance of common mental health problems and musculoskeletal disorders for health-related job loss in the older working-age population. However, multimorbidity (classified as two or more CPRD-defined health disorders) was strongly associated with HRJL and accounted for a significantly greater proportion of HRJL than any individual health disorder. Multimorbidity clusters formed by co-occurring musculoskeletal disorders and mental health problems appeared to have a particularly strong impact on HRJL

A 'lived experienced’ tool for managing and building project delivery capability

This paper discusses a new, integrated tool-set for project managing. This tool-set is a response to calls for project managers to be able to apply new project managing thinking ‘in practice’. The tool-set integrates the project-space model and the Syllk model. Together, they bring visibility to enablers and constraints to project delivery capability, and these learnings can then be integrated into the organisation’s systems to build in a tailored manner ongoing project management capability. Specifically, the tool-set highlights the hindrances to project delivery and what capabilities need to be ‘wired’ into an organisation to remove them. This tool-set integrates into future organisational initiatives the learnings from concrete ‘lived experiences’ of project managing

The efficacy of teat sealants in dairy cows at dry-off to prevent new intra-mammary infections during the dry-period or clinical mastitis during early lactation: A protocol for a systematic review

Rationale: The majority of antibiotic use in the dairy industry is for intramammary infections (IMI), with a large portion of this aimed at treating and preventing IMI during the dry period (Lam et al., 2102). During dry off, formation of the teat-canal keratin plug plays an important role in susceptibility to IMI (Huxley et al., 2002), but there is wide variation between cows on time to complete closure of the teat-canal, or indeed if closure occurs at all (Dingwell et al., 2003). In heifers, pre-partum IMI is an important risk factor for the development of clinical mastitis in early lactation, and the impact of this disease on future udder health and productivity is far greater than in multiparous animals (Piepers et al., 2009). Moreover, the incidence of clinical mastitis at freshening in heifers is roughly double that of multiparous cows (Ali Naqvi et al., 2018). Teat sealants provide a non-antibiotic strategy to prevent IMI in the pre-calving period, which is of increasing importance due to concern for antimicrobial use and its relationship with the development of antimicrobial resistance (WHO, 2015). Understanding the efficacy of these products is essential to optimizing their use in order to decrease reliance on antibiotics for both treatment and prevention. Systematic reviews of randomized controlled trials in these areas will yield the highest level of evidence for efficacy of treatment under field conditions (Sargeant and O’Connor, 2014). Establishing the efficacy of teat sealants at dry-off, and pre-partum in heifers, to reduce the incidence of both clinical mastitis and/or IMI, will serve to improve decision makers’ ability to engage in effective stewardship of antibiotics thorough the strategic use of non-antibiotic alternatives

The efficacy of antibiotic treatments in dairy cows at dry-off to prevent new intramammary infections during the dry-period or clinical mastitis during early lactation: A protocol for a systematic review

Rationale: The majority of antibiotic use in the dairy industry is for the treatment and prevention of intramammary infections (IMI); in the Netherlands, approximately 60 % of all antimicrobial use in dairy is for this purpose, with two-thirds being dry cow therapy (Lam et al., 2012). In the United States, over 90 % of dairy cows receive dry cow therapy after every lactation (USDA-APHIS, 2016), with the goal of treating or preventing IMI during the dry period. These infections are strongly associated with risk of development of clinical mastitis in the first two weeks post-calving, which represents the highest risk period for this disease (Green et al., 2002). To combat this, blanket dry cow therapy (intramammary antimicrobial treatment of all quarters of all cows after the last milking of the lactation) was recommended for decades as part of a comprehensive strategy to reduce IMI in the dry period (Neave et al., 1969), and has been widely adopted in North America and the United Kingdom (Ruegg, 2017). Although cow2 level selective dry cow therapy has been in use in some regions for several decades (Schultze, 1983), interest has more recently increased worldwide, in part driven by concern for antimicrobial use and its relationship with the development of antimicrobial resistance between species (WHO, 2015), including nation-specific regulations (Santman-Berends et al., 2016). Selective dry cow therapy has been employed because it is a means to rapidly reduce the amount of antimicrobials used in dairy cattle (Vanhoudt et al., 2018), rather than because it is known to contribute importantly to antimicrobial resistance (Oliver et al., 2011). With a greater concern for prudent antibiotic use in the dairy industry, it is important that decision making with regards to dry cow therapy at both the cow and herd levels be evidencebased. Choosing ineffective antibiotics, or using antibiotic when not warranted, unnecessarily contributes to use while having little impact on controlling disease, which has substantial bearing to both profitability and animal welfare (Leslie & Petersson-Wolfe, 2012). Systematic reviews of randomized controlled trials yield the highest level of evidence for efficacy of treatment under field conditions (Sargeant and O’Connor, 2014), and comparative efficacy can be examined using network meta-analysis for multiple comparisons. Establishing the efficacy of both cow-level antibiotic therapy and herd-level dry cow antibiotic protocols for the prevention of IMI will serve to improve decision makers’ ability to engage in effective stewardship of antibiotics

Comorbidity burden in axial spondyloarthritis: a cluster analysis

Objectives To examine how comorbidities cluster in axial spondyloarthritis (axSpA) and whether these clusters are associated with quality of life, global health and other outcome measures. Methods We conducted a cross-sectional study of consecutive patients meeting ASAS criteria for axSpA in Liverpool, UK. Outcome measures included quality of life (EQ5D), global health and disease activity (BASDAI). We used hierarchical cluster analysis to group patients according to 38 pre-specified comorbidities. In multivariable linear models, the associations between distinct comorbidity clusters and each outcome measure were compared, using axSpA patients with no comorbidities as the reference group. Analyses were adjusted for age, gender, symptom duration, BMI, deprivation, NSAID-use and smoking. Results We studied 419 patients (69% male, mean age 46 years). 255 patients (61%) had at least one comorbidity, among whom the median number was 1 (range 1–6). Common comorbidities were hypertension (19%) and depression (16%). Of 15 clusters identified, the most prevalent clusters were hypertension-coronary heart disease and depression-anxiety. Compared with patients with no comorbidities, the fibromyalgia-irritable bowel syndrome cluster was associated with adverse patient-reported outcome measures; these patients reported 1.5-unit poorer global health (95%CI 0.01, 2.9), reduced quality of life (0.25-unit lower EQ5D; 95%CI −0.37, −0.12) and 1.8-unit higher BASDAI (95% CI 0.4, 3.3). Similar effect estimates were found for patients in the depression-anxiety cluster. Conclusion Comorbidity is common among axSpA patients. The two most common comorbidities were hypertension and depression. Patients in the depression-anxiety and fibromyalgia-IBS clusters reported poorer health and increased axSpA severity

Application of quantitative bias analysis for unmeasured confounding in cost-effectiveness modelling

Due to uncertainty regarding the potential impact of unmeasured confounding, health technology assessment (HTA) agencies often disregard evidence from nonrandomised studies when considering new technologies. Quantitative bias analysis (QBA) methods provide a means to quantify this uncertainty but have not been widely used in the HTA setting, particularly in the context of cost-effectiveness modelling (CEM). This study demonstrated the application of an aggregate and patient-level QBA approach to quantify and adjust for unmeasured confounding in a simulated nonrandomised comparison of survival outcomes. Application of the QBA output within a CEM through deterministic and probabilistic sensitivity analyses and under different scenarios of knowledge of an unmeasured confounder demonstrates the potential value of QBA in HTA