This paper investigates the relationship between team performance and managerial change in English football using a data set containing information on all match results and managerial job changes in the English Football League between 1972 and 1993. We find that poor recent form drives many managerial terminations, while managerial turnover is more rapid in the lower divisions. Significantly, managerial change appears to have a harmful effect on team performance immediately following a managerial termination.

ObjectivesWe aimed to estimate how many children were attending a universal preschool health screen and to identify characteristics associated with non-participation.DesignAnalysis of population-level linked administrative data.ParticipantsChildren were considered eligible for a B4 School Check for a given year if:(1) they were ever resident in New Zealand (NZ),(2) lived in NZ for at least 6 months during the reference year, (3) were alive at the end of the reference year, (4) either appeared in any hospital (including emergency) admissions, community pharmaceutical dispensing or general practitioner enrolment datasets during the reference year or (5) had a registered birth in NZ. We analysed 252 273 records over 4 years, from 1 July 2011 to 30 June 2015.ResultsWe found that participation rates varied for each component of the B4 School Check (in 2014/2015 91.8% for vision and hearing tests (VHTs), 87.2% for nurse checks (including height, weight, oral health, Strengths and Difficulties Questionnaire [SDQ] and parental evaluation of development status) and 62.1% for SDQ – Teacher [SDQ-T]), but participation rates for all components increased over time. Māori and Pacific children were less likely to complete the checks than non-Māori and non-Pacific children (for VHTs: Māori: OR=0.60[95% CI 0.61 to 0.58], Pacific: OR=0.58[95% CI 0.60 to 0.56], for nurse checks: Māori: OR=0.63[95% CI 0.64 to 0.61], Pacific: OR=0.67[95% CI 0.69 to0.65] and for SDQ-T: Māori: OR=0.76[95% CI 0.78 to 0.75], Pacific: OR=0.37[95% CI 0.38 to 0.36]). Children from socioeconomically deprived areas, with younger mothers, from rented homes, residing in larger households, with worse health status and with higher rates of residential mobility were less likely to participate in the B4 School Check than other children.ConclusionThe patterns of non-participation suggest a reinforcing of existing disparities, whereby the children most in need are not getting the services they potentially require. There needs to be an increased effort by public health organisations, community and whānau/family to ensure that all children are tested and screened.

Background: In a novel endeavour we aimed to develop a clinically relevant case identification method for use in research about the mental health of children and young people in New Zealand using the Integrated Data Infrastructure (IDI). The IDI is a linked individual-level database containing New Zealand government and survey microdata. Methods: We drew on diagnostic and pharmaceutical information contained within five secondary care service use and medication dispensing datasets to identify probable cases of mental health and related problems. A systematic classification and refinement of codes, including restrictions by age, was undertaken to assign cases into 13 different mental health problem categories. This process was carried out by a panel of eight specialists covering a diverse range of mental health disciplines (a clinical psychologist, four child and adolescent psychiatrists and three academic researchers in child and adolescent mental health). The case identification method was applied to the New Zealand youth estimated resident population for the 2014/15 fiscal year. Results: Over 82,000 unique individuals aged 0-24 with at least one specified mental health or related problem were identified using the case identification method for the 2014/15 fiscal year. The most prevalent mental health problem subgroups were emotional problems (31,266 individuals), substance problems (16,314), and disruptive behaviours (13,758). Overall, the pharmaceutical collection was the largest source of case identification data (59,862). Conclusion: This study demonstrates the value of utilising IDI data for mental health research. Although the method is yet to be fully validated, it moves beyond incidence rates based on single data sources, and provides directions for future use, including further linkage of data to the IDI.

Health administrative data provide a potentially robust information source regarding the substantial burden chronic pain exerts on individuals and the health care system. This study aimed to use health administrative data to estimate comorbidity prevalence and annual health care utilization associated with chronic pain in Newfoundland and Labrador, Canada. Applying the validated Chronic Pain Algorithm to provincial Fee-for-Service Physician Claims File data (1999-2009) established the Chronic Pain (n = 184,580) and No Chronic Pain (n = 320,113) comparator groups. Applying the Canadian Chronic Disease Surveillance System coding algorithms to Claims File and Provincial Discharge Abstract Data (1999-2009) determined the prevalence of 16 comorbidities. The 2009/2010 risk and person-year rate of physician and diagnostic imaging visits and hospital admissions were calculated and adjusted using the robust Poisson model with log link function (risks) and negative binomial model (rates). Results indicated a significantly higher prevalence of all comorbidities and up to 4 times the odds of multimorbidity in the Chronic Pain Group (P-value < 0.001). Chronic Pain Group members accounted for 58.8% of all physician visits, 57.6% of all diagnostic imaging visits, and 54.2% of all hospital admissions in 2009/2010, but only 12% to 16% of these were for pain-related conditions as per recorded diagnostic codes. The Chronic Pain Group had significantly higher rates of physician visits and high-cost hospital admission/diagnostic imaging visits (P-value < 0.001) when adjusted for demographics and comorbidities. Observations made using this methodology supported that people identified as having chronic pain have higher prevalence of comorbidities and use significantly more publicly funded health services.

New Zealand has few estimates of the prevalence of autism spectrum disorder and no national registry. The use of administrative data sources is expanding and could be useful in autism spectrum disorder research. However, the extent to which autism spectrum disorder can be captured in these data sources is unknown. In this study, we utilised three linked administrative health data sources from the Integrated Data Infrastructure to identify cases of autism spectrum disorder among New Zealand children and young people. We then investigated the extent to which a range of mental health, neurodevelopmental and related problems co-occur with autism spectrum disorder. In total, 9555 unique individuals aged 0–24 with autism spectrum disorder were identified. The identification rate for 8-year-olds was 1 in 102. Co-occurring mental health or related problems were noted in 68% of the autism spectrum disorder group. The most common co-occurring conditions were intellectual disability, disruptive behaviours and emotional problems. Although data from the Integrated Data Infrastructure may currently undercount cases of autism spectrum disorder, they could be useful for monitoring service and treatment-related trends, types of co-occurring conditions and for examining social outcomes. With further refinement, the Integrated Data Infrastructure could prove valuable for informing the national incidence and prevalence of autism spectrum disorder and the long-term effectiveness of clinical guidelines and interventions for this group. Lay abstract New Zealand has few estimates of the prevalence autism spectrum disorder and no national registry or data set to identify and track cases. This hinders the ability to make informed, evidence-based decisions relating to autism spectrum disorder. In this study, we utilised linked health and non-health data to develop a method for identifying cases of autism spectrum disorder among children and young people in New Zealand. In addition, we examined rates of co-occurring mental health, neurodevelopmental and related conditions among this cohort and compared these to the general population. The method identified almost 10,000 children and young people with autism spectrum disorder in New Zealand. Co-occurring mental health or related problems were found in over 68% of this group (nearly seven times higher than the general population), and around half were identified with multiple co-occurring conditions. The most frequently identified conditions were intellectual disability, disruptive behaviours and emotional problems. We have developed a useful method for monitoring service and treatment-related trends, number and types of co-occurring conditions and examining social outcomes among individuals with autism spectrum disorder. While the method may underestimate the prevalence of autism spectrum disorder in New Zealand, it provides a significant step towards establishing a more comprehensive evidence base to inform autism spectrum disorder–related policy.