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Peter Congdon

Publications and source records attributed to Peter Congdon.

9 recordsLinked to original sources
PubMed2006

Modelling multiple hospital outcomes: the impact of small area and primary care practice variation.

BACKGROUND: Appropriate management of care--for example, avoiding unnecessary attendances at, or admissions to, hospital emergency units when they could be handled in primary care--is an important part of health strategy. However, some variations in these outcomes could be due to genuine variations in health need. This paper proposes a new method of explaining variations in hospital utilisation across small areas and the general practices (GPs) responsible for patient primary care. By controlling for the influence of true need on such variations, one may identify remaining sources of excess emergency attendances and admissions, both at area and practice level, that may be related to the quality, resourcing or organisation of care. The present paper accordingly develops a methodology that recognises the interplay between population mix factors (health need) and primary care factors (e.g. referral thresholds), that allows for unobserved influences on hospitalisation usage, and that also reflects interdependence between hospital outcomes. A case study considers relativities in attendance and admission rates at a North London hospital involving 149 small areas and 53 GP practices. RESULTS: A fixed effects model shows variations in attendances and admissions are significantly related (positively) to area and practice need, and nursing home patients, and related (negatively) to primary care access and distance of patient homes from the hospital. Modelling the impact of known factors alone is not sufficient to produce a satisfactory fit to the observations, and random effects at area and practice level are needed to improve fit and account for overdispersion. CONCLUSION: The case study finds variation in attendance and admission rates across areas and practices after controlling for need, and remaining differences between practices may be attributable to referral behaviour unrelated to need, or to staffing, resourcing, and access issues. In managerial terms, the analysis points to the utility of formal statistical analysis of hospitalisation rates as a prelude to non-statistical investigation of primary care resourcing and organisation. For example, there may be implications for the location of staff involved in community management of chronic conditions; health managers may also investigate whether some practices have unusual populations (homeless, asylum seekers, students) that explain different hospital use patterns.

Aged, 80 and over↗
PubMed2006

Psychological distress among adolescents, and its relationship to individual, family and area characteristics in East London.

This paper identifies factors associated with variation in psychosocial distress among adolescents in a relatively deprived and ethnically diverse inner city setting in London, UK. The research draws on literature which discusses whether neighbourhood socio-economic conditions are associated with mental health, as well as attributes of individual adolescents and their families. We report an analysis of data from the Research with East London Adolescents: Community Health Survey (RELACHS). The survey collected data on mental health measured by the Strengths and Difficulties Questionnaire (SDQ), and on various aspects of individual and family circumstances. These data were linked with information about social and economic conditions in 'middle layer standard output areas' (MSOA) used for the population Census 2001, having a mean total population of 6767 in the study area. Census statistics including the Indices of Deprivation for 2004 proposed by the Office of the Deputy Prime Minister, were used to describe the socio-economic conditions within these areas. Although the socio-economic disparities among small areas were not typical of those across the whole of the country, there were differences in levels of deprivation and crime, social fragmentation, and ethnic composition. A Bayesian regression analysis using Gibbs sampling in the programme WinBugs investigated whether there was variability in SDQ at both individual and area (MSOA) level, and whether the predictor variables at both levels were significantly associated with SDQ. Individuals from Asian or Black ethnic groups, and those in families with harmonious relationships and no financial stress had significantly lower SDQ scores, i.e. better health. Those who had special educational needs or long standing illness, or were from reconstituted families had significantly worse SDQ scores. About 6% of the variation in SDQ was associated with area differences. However, this area variation was not related to differences in area indicators of socio-economic deprivation, crime or social fragmentation. There was a complex association between SDQ and ethnic composition of neighbourhoods.

Adolescent↗
PubMed2006

Estimating diabetes prevalence by small area in England.

BACKGROUND: Diabetes risk is linked to both deprivation and ethnicity, and so prevalence will vary considerably between areas. Prevalence differences may partly account for geographic variation in health performance indicators for diabetes, which are based on age standardized hospitalization or operation rates. A positive correlation between prevalence and health outcomes indicates that the latter are not measuring only performance. METHODS: A regression analysis of prevalence rates according to age, sex and ethnicity from the Health Survey for England (HSE) is undertaken and used (together with census data) to estimate diabetes prevalence for 354 English local authorities and 8000 smaller areas (electoral wards). An adjustment for social factors is based on a prevalence gradient over area-deprivation quintiles. A Bayesian estimation approach is used allowing simple inclusion of evidence on prevalence from other or historical sources. RESULTS: The estimated prevalent population in England is 1.5 million (188 000 type 1 and 1.341 million type 2). At strategic health authority (StHA) level, prevalence varies from 2.4 (Thames Valley) to 4 per cent (North East London). The prevalence estimates are used to assess variations between local authorities in adverse hospitalization indicators for diabetics and to assess the relationship between diabetes-related mortality and prevalence. In particular, rates of diabetic ketoacidosis (DKA) and coma are positively correlated with prevalence, while diabetic amputation rates are not. CONCLUSIONS: The methodology developed is applicable to developing small-area-prevalence estimates for a range of chronic diseases, when health surveys assess prevalence by demographic categories. In the application to diabetes prevalence, there is evidence that performance indicators as currently calculated are not corrected for prevalence.

Age Factors↗
PubMed2006

A model framework for mortality and health data classified by age, area, and time.

This article sets out a modeling framework for modeling health outcomes over area, age, and time dimensions that takes account of spatial correlation, interactions between dimensions, and cohort as well as age effects. The goals of the framework include parsimony and parameter interpretability. Multivariate extensions may be made allowing interdependent or shared effects between different outcomes (e.g., ill health and mortality). A particular focus is on assessing the proportionality assumption whereby separate age and area effects multiply to produce age-area mortality or illness rates, and age-area interactions are assumed not to exist. A trivariate (mortality-health) application of the framework involves cross-sectional data in the 33 London boroughs, while a longitudinal univariate application involves deaths for the same areas over four 5-year periods starting in 1979.

Age Factors↗
PubMed2005

Estimating population prevalence of psychiatric conditions by small area with applications to analysing outcome and referral variations.

This paper considers the development of estimates of mental illness prevalence for small areas and applications in explaining psychiatric outcomes and in assessing service provision. Estimates of prevalence are based on a logistic regression analysis of two national studies that provides model based estimates of relative morbidity risk by demographic, socio-economic and ethnic group for major psychiatric conditions; household/marital and area status also figure in the regression. Relative risk estimates are used, along with suitably disaggregated census populations, to make prevalence estimates for 354 English local authorities (LAs). Two applications are considered: the first involves analysis of variations in schizophrenia referrals and suicide mortality over English LAs that takes account of prevalence differences, and the second involves assessing hospital referral and bed use in relation to prevalence (for ages 16-74) for a case study area, Waltham Forest in NE London.

Adolescent↗
PubMed2004

The ecological relationship between deprivation, social isolation and rates of hospital admission for acute psychiatric care: a comparison of London and New York City.

We report on comparative analyses of small area variation in rates of acute hospital admissions for psychiatric conditions in Greater London around the year 1998 and in New York City (NYC) in 2000. Based on a theoretical model of the factors likely to influence psychiatric admission rates, and using data from the most recent population censuses and other sources, we examine the association with area indicators designed to measure access to hospital beds, socio-economic deprivation, social fragmentation and ethnic/racial composition. We report results on admissions for men and women aged 15-64 for all psychiatric conditions (excluding self-harm), drug-related substance abuse/addiction, schizophrenia and affective disorders. The units of analysis in NYC were 165 five-digit Zip Code Areas and, in London, 760 electoral wards as defined in 1998. The analysis controls for age and sex composition and, as a proxy for access to care, spatial proximity to hospitals with psychiatric beds. Poisson regression modeling incorporating random effects was used to control for both overdispersion in the counts of admissions and for the effects of spatial autocorrelation. The results for NYC and London showed that local admission rates for all types of condition were positively and significantly associated with deprivation and the association is independent of demographic composition or 'access' to beds. In NYC, social fragmentation showed a significant association with admissions due to affective disorders and schizophrenia, and for drug dependency among females. Racial minority concentration was significantly and positively associated with admissions for schizophrenia. In London, social fragmentation was associated positively with admissions for men and women due to schizophrenia and affective disorders. The variable measuring racial/ethnic minority concentration for London wards showed a negative association with admission rates for drug dependency and for affective disorders. We discuss the interpretation of these results and the issues they raise in terms of the potential and limitations of international comparison.

Adolescent↗
PubMed2004

Geographical variation in acute psychiatric admissions within New York City 1990-2000: growing inequalities in service use?

The paper analyses geographical variations in use of acute psychiatric inpatient services within New York City and how these have changed from 1990 to 2000. We review literature suggesting reasons for the variations observed. Data from the New York State Department of Health Statewide Planning Research and Cooperative System were combined with population census data to produce age standardized ratio indicators of admissions and of bed days, as measures of use of general hospitals for psychiatric conditions, by males aged 15-64, in Zip Code Areas of New York City, in 1990 and 2000. Geographical variations in hospital use were related to proximity to general hospitals with psychiatric beds and to socio-economic status of local populations (as recorded in the 1990 and 2000 population censuses). Areas close to psychiatric hospitals areas show high admission levels. Controlling for this, Zip Code Areas with higher concentrations of poverty, of African American residents or of persons living alone were associated with relatively high admission ratios. These relationships vary somewhat between diagnostic groups. Area inequalities in standardized admission ratios persisted and widened between 1990 and 2000, and the highest hospital admission ratios were increasingly concentrated where social and economic disadvantage was greatest. Various possible reasons for this trend are explored. We conclude that increasing intensity of poverty in disadvantaged areas is not likely to provide an explanation and that the trends are more likely to result from changes in hospital management and funding affecting access to hospital services.

Acute Disease↗
PubMed2003

Rasch techniques for detecting bias in performance assessments: an example comparing the performance of native and non-native speakers on a test of academic English.

The use of common tasks and rating procedures when assessing the communicative skills of students from highly diverse linguistic and cultural backgrounds poses particular measurement challenges, which have thus far received little research attention. If assessment tasks or criteria are found to function differentially for particular subpopulations within a test candidature with the same or a similar level of criterion ability, then the test is open to charges of bias in favour of one or other group. While there have been numerous studies involving dichotomous language test items (see e.g. Chen and Henning, 1985 and more recently Elder, 1996) few studies have considered the issue of bias in relation to performance based tasks which are assessed subjectively, via analytic and holistic rating scales. The paper demonstrates how Rasch analytic procedures can be applied to the investigation of item bias or differential item functioning (DIF) in both dichotomous and scalar items on a test of English for academic purposes. The data were gathered from a pilot English language test administered to a representative sample of undergraduate students (N= 139) enrolled in their first year of study at an English-medium university. The sample included native speakers of English who had completed up to 12 years of secondary schooling in their first language (L1) and immigrant students, mainly from Asian language backgrounds, with varying degrees of prior English language instruction and exposure. The purpose of the test was to diagnose the academic English needs of incoming undergraduates so that additional support could be offered to those deemed at risk of failure in their university study. Some of the tasks included in the assessment procedure involved objectively-scored items (measuring vocabulary knowledge, text-editing skills and reading and listening comprehension) whereas others (i.e. a report and an argumentative writing task) were subjectively-scored. The study models a methodology for estimating bias with both dichotomous and scalar items using the programs Quest (Adams and Khoo, 1993) for the former and ConQuest (Wu, Adams and Wilson, 1998) for the latter. It also offers answers to the practical questions of whether a common set of assessment criteria can, in an academic context such as this one, be meaningfully applied to all subgroups within the candidature and whether analytic criteria are more susceptible to biased ratings than holistic ones. Implications for test fairness and test validity are discussed.

Australia↗