The development of an instructional unit in salesmanship

Thesis (Ed.M.)--Boston Universit

Lessons learned from using linked administrative data to evaluate the Family Nurse Partnership in England and Scotland

Introduction “Big data” – including linked administrative data – can be exploited to evaluate interventions for maternal and child health, providing time- and cost-effective alternatives to randomised controlled trials. However, using these data to evaluate population-level interventions can be challenging. Objectives We aimed to inform future evaluations of complex interventions by describing sources of bias, lessons learned, and suggestions for improvements, based on two observational studies using linked administrative data from health, education and social care sectors to evaluate the Family Nurse Partnership (FNP) in England and Scotland. Methods We first considered how different sources of potential bias within the administrative data could affect results of the evaluations. We explored how each study design addressed these sources of bias using maternal confounders captured in the data. We then determined what additional information could be captured at each step of the complex intervention to enable analysts to minimise bias and maximise comparability between intervention and usual care groups, so that any observed differences can be attributed to the intervention. Results Lessons learned include the need for i) detailed data on intervention activity (dates/geography) and usual care; ii) improved information on data linkage quality to accurately characterise control groups; iii) more efficient provision of linked data to ensure timeliness of results; iv) better measurement of confounding characteristics affecting who is eligible, approached and enrolled. Conclusions Linked administrative data are a valuable resource for evaluations of the FNP national programme and other complex population-level interventions. However, information on local programme delivery and usual care are required to account for biases that characterise those who receive the intervention, and to inform understanding of mechanisms of effect. National, ongoing, robust evaluations of complex public health evaluations would be more achievable if programme implementation was integrated with improved national and local data collection, and robust quasi-experimental designs

The Role of Coping in the Wellbeing and Work-Related Quality of Life of UK Health and Social Care Workers during COVID-19

The coronavirus disease 2019 (COVID-19) was declared a global pandemic in early 2020. Due to the rapid spread of the virus and limited availability of effective treatments, health and social care systems worldwide quickly became overwhelmed. Such stressful circumstances are likely to have negative impacts on health and social care workers’ wellbeing. The current study examined the relationship between coping strategies and wellbeing and quality of working life in nurses, midwives, allied health professionals, social care workers and social workers who worked in health and social care in the UK during its first wave of COVID-19. Data were collected using an anonymous online survey (N = 3425), and regression analyses were used to examine the associations of coping strategies and demographic characteristics with staff wellbeing and quality of working life. The results showed that positive coping strategies, particularly active coping and help-seeking, were associated with higher wellbeing and better quality of working life. Negative coping strategies, such as avoidance, were risk factors for low wellbeing and worse quality of working life. The results point to the importance of organizational and management support during stressful times, which could include psycho-education and training about active coping and might take the form of workshops designed to equip staff with better coping skills

Unconsented linkage between dormant trials and administrative data: practical and regulatory implications

Half of all infants are fed formula milk. However, attrition biases evidence on the long-term safety of formula ingredients. We used unconsented linkage between administrative education and health records of 3,500 young people who were randomised as infants to formula milks, to determine long-term safety and efficacy. We discuss the steps that were implemented to safeguard the participants' privacy and achieve ethical and multi-institutional approvals. Achieving provisional ethical approval took 41 days. Achieving agreement-in-principle to match trial data to individual-level education records took 4 months and 2 weeks, while agreement to match trial data to individual level hospital records is still underway (5.5 months so far). Delays in institutional approval were largely due to unharmonised data security certificates between the two government departments holding the health and education records. Digitising all handwritten participant identifiers prior to linkage took 9 months. Results on the success of linkage between trial and education records will be presented at the conference. While directly contributing to the evidence around infant-formula-composition, this project will also act as a proof-of-concept study. Unconsented linkage between dormant RCTs and administrative data could be a novel and cost-effective method to generate evidence on the long-term efficacy and safety of interventions

Unconsented linkage between dormant trials and administrative data: practical and regulatory implications

Introduction Half of all infants are fed formula milk. However, attrition biases evidence on the long-term safety of formula ingredients. We used unconsented linkage between administrative education and health records of young people who were randomised as infants to formula milks, to determine long-term safety and efficacy. Objectives and Approach We used record level data from a series of 9 historical randomised controlled trials (RCTs) conducted in 1982-2002 (n=3,500 participants), which are key to the evidence-base around formula-composition. All later follow-ups are biased by attrition leading to limited evidence around the long-term effects of formula ingredients on cognition and metabolic and cardiovascular health. We sought permissions from data providers and regulatory agencies for unconsented linkage to education and hospital records, as proxy measures for cognitive and health development. We discuss the steps that were implemented to safeguard the participants' privacy and achieve ethical and multi-institutional approval for this project. Results Achieving provisional ethical approval took 41 days. Achieving agreement in principle to match trial data to individual level education records took 4 months and 2 weeks, while agreement to match trial data to individual level hospital records is still underway (5.5 months in February 2018). Delays in institutional approval were largely due to unharmonised data security certificates between the two government departments holding the health and education records. Digitising and cleaning all handwritten RCT participant identifiers prior to linkage took 9 months of full-time researcher time. Maintaining separation of identifiers and attribute data required specific secure haven provision. Results on the success of linkage between RCTs and education records will be presented at the conference. Conclusion/Implications While directly contributing to the evidence around infant-formula-composition, this project will also act as a proof-of-concept study. Unconsented linkage between dormant RCTs and administrative data could be a novel and cost-effective method to generate evidence on the long-term efficacy and safety of interventions

Lessons learned from using linked administrative data to evaluate the Family Nurse Partnership in England and Scotland

Introduction “Big data” – including linked administrative data – can be exploited to evaluate interventions for maternal and child health, providing time- and cost-effective alternatives to randomised controlled trials. However, using these data to evaluate population-level interventions can be challenging. Objectives We aimed to inform future evaluations of complex interventions by describing sources of bias, lessons learned, and suggestions for improvements, based on two observational studies using linked administrative data from health, education and social care sectors to evaluate the Family Nurse Partnership (FNP) in England and Scotland. Methods We first considered how different sources of potential bias within the administrative data could affect results of the evaluations. We explored how each study design addressed these sources of bias using maternal confounders captured in the data. We then determined what additional information could be captured at each step of the complex intervention to enable analysts to minimise bias and maximise comparability between intervention and usual care groups, so that any observed differences can be attributed to the intervention. Results Lessons learned include the need for i) detailed data on intervention activity (dates/geography) and usual care; ii) improved information on data linkage quality to accurately characterise control groups; iii) more efficient provision of linked data to ensure timeliness of results; iv) better measurement of confounding characteristics affecting who is eligible, approached and enrolled. Conclusions Linked administrative data are a valuable resource for evaluations of the FNP national programme and other complex population-level interventions. However, information on local programme delivery and usual care are required to account for biases that characterise those who receive the intervention, and to inform understanding of mechanisms of effect. National, ongoing, robust evaluations of complex public health evaluations would be more achievable if programme implementation was integrated with improved national and local data collection, and robust quasi-experimental designs

Challenges and lessons learned from two countries using linked administrative data to evaluate the Family Nurse Partnership.

Objectives We describe the challenges and lessons learned from two studies using linked administrative data from health, education and social care sectors to evaluate the Family Nurse Partnership (FNP), an intervention supporting adolescent mothers in England(E) and Scotland(S). We present recommendations for studies using linked administrative data to evaluate complex interventions. Approach We constructed two cohorts of all mothers aged 13-19 giving birth in NHS hospitals in England and Scotland between 2010-2016/17 using linkage of mothers and babies in hospital admissions data (E:Hospital Episode Statistics/S:Maternity Inpatient and Day Case), and identified FNP participation through linkage to FNP programme data. We additionally linked to health, educational and social care data for mothers and their babies (E:National Pupil Database/S:eDRIS). We used these data to identify key risk factors for enrolment in the FNP, assess the effect of the FNP on maternal and child outcomes, and determine programme characteristics modifying the effect of the FNP. Results Key challenges: characterising the intervention and usual care, understanding quality of multi-sector data linkage, data access delays, constructing appropriate comparator groups and interpreting outcomes captured in administrative data. Lessons learned: evaluations require detailed data on intervention activity (dates/geography), and assessment of usual care, which are rarely readily available and are time-consuming to gather; data linkage quality is variable/not available, making defining denominators challenging; data access delays impeded on data analysis time; unmeasured confounders not captured in administrative data may prevent generation of an appropriate comparator group. Recommendations: Characteristics informing targeting should be explicitly documented, and could be enhanced using linked primary care data and information on household members (e.g. fathers). Process evaluation and qualitative research could help to provide better understanding of mechanisms of effect. Conclusion Linkage of administrative data presents exciting opportunities for efficient evaluation of large-scale, complex public health interventions. However, sufficient information is needed on programme meta-data, targeting and important confounders in order to generate meaningful results. Study findings should help stimulate exploration with practitioners about how programmes can be improved

An optimistic outlook on the use of evidence syntheses to inform environmental decision-making

Practitioners and policymakers working in environmental arenas make decisions that can have large impacts on ecosystems. Basing such decisions on high‐quality evidence about the effectiveness of different interventions can often maximize the success of policy and management. Accordingly, it is vital to understand how environmental professionals working at the science‐policy interface view and use different types of evidence, including evidence syntheses that collate and summarize available knowledge on a specific topic to save time for decision‐makers. We interviewed 84 senior environmental professionals in Canada working at the science‐policy interface to explore their confidence in, and use of, evidence syntheses within their organizations. Interviewees value evidence syntheses because they increase confidence in decision‐making, particularly for high‐profile or risky decisions. Despite this enthusiasm, the apparent lack of available syntheses for many environmental issues means that use can be limited and tends to be opportunistic. Our research suggests that if relevant, high quality evidence syntheses exist, they are likely to be used and embraced in decision‐making spheres. Therefore, efforts to increase capacity for conducting evidence syntheses within government agencies and/or funding such activities by external bodies have the potential to enable evidence‐based decision‐making.Additional co-authors: Karen E. Smokorowski, Steven M. Alexander, Steven J. Cook

Sources of potential bias when combining routine data linkage and a national survey of secondary school-aged children: a record linkage study

Background Linking survey data to administrative records requires informed participant consent. When linkage includes child data, this includes parental and child consent. Little is known of the potential impacts of introducing consent to data linkage on response rates and biases in school-based surveys. This paper assessed: i) the impact on overall parental consent rates and sample representativeness when consent for linkage was introduced and ii) the quality of identifiable data provided to facilitate linkage. Methods Including an option for data linkage was piloted in a sub-sample of schools participating in the Student Health and Wellbeing survey, a national survey of adolescents in Wales, UK. Schools agreeing to participate were randomized 2:1 to receive versus not receive the data linkage question. Survey responses from consenting students were anonymised and linked to routine datasets (e.g. general practice, inpatient, and outpatient records). Parental withdrawal rates were calculated for linkage and non-linkage samples. Multilevel logistic regression models were used to compare characteristics between: i) consenters and non-consenters; ii) successfully and unsuccessfully linked students; and iii) the linked cohort and peers within the general population, with additional comparisons of mental health diagnoses and health service contacts. Results The sub-sample comprised 64 eligible schools (out of 193), with data linkage piloted in 39. Parental consent was comparable across linkage and non-linkage schools. 48.7% (n = 9232) of students consented to data linkage. Modelling showed these students were more likely to be younger, more affluent, have higher positive mental wellbeing, and report fewer risk-related behaviours compared to non-consenters. Overall, 69.8% of consenting students were successfully linked, with higher rates of success among younger students. The linked cohort had lower rates of mental health diagnoses (5.8% vs. 8.8%) and specialist contacts (5.2% vs. 7.7%) than general population peers. Conclusions Introducing data linkage within a national survey of adolescents had no impact on study completion rates. However, students consenting to data linkage, and those successfully linked, differed from non-consenting students on several key characteristics, raising questions concerning the representativeness of linked cohorts. Further research is needed to better understand decision-making processes around providing consent to data linkage in adolescent populations