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PubMed1993

ADAMS: Aggregate Data Management System for epidemiologists and health-care managers.

An effective health-care policy is supported by the availability of data in the form of statistical tables for epidemiologists and health-care managers. Creation, analysis and exploitation of these data strongly support the monitoring of trends in mortality and morbidity phenomena and the evaluation of offered health services. This might imply the transformation of statistical tables to more suitable formats. A successful management, manipulation and querying of a statistical table is a complex activity requiring a considerable knowledge of statistical problems. Computerised support can be precious in this task and this led to the development of several data management systems. In this paper we sketch out the features of ADAMS (Aggregate Data Management System), a system conceived to allow an easy interaction with statistical tables, reshaping and browsing of their descriptive part. ADAMS aims at simplifying the problem of extracting information from a statistical database and performing statistical table manipulation. The following functionalities are provided: definition of a statistical database at descriptive level; storage of data in the database; manipulation of data according to the summarisation and reclassification operators; browsing between data and their descriptive part. It also supports different manipulation styles according to different user profiles.

Data Interpretation, Statistical↗

PubMed2006

Using aggregate data on dispensed drugs to evaluate the quality of prescribing in urban primary health care in Sweden.

BACKGROUND: Valuable evaluations of the quality of drug prescribing in routine health care are difficult to perform. It is even more difficult to study prescribing in a non-gatekeeping healthcare system with a variety of caregivers involved in patient care. Consequently, there is a need to develop methods for evaluation using data available in routine health care. OBJECTIVES: The aim of this study was to analyse possibilities and limitations for evaluation of the quality of drug prescribing using routinely collected aggregate data on dispensed drugs and health care provision. A secondary aim was to study the effects of allocating more resources to primary health care (PHC) on the quality of drug prescribing. METHODS: The study was performed with routinely collected data from 10 PHC centres in Stockholm, Sweden that were participating in an intervention project that aimed to decrease the number of inhabitants per PHC doctor. Time periods for analysis were October-December 1999, 2000 and 2001. Data on dispensed prescriptions were analysed by age using Anatomical Therapeutic Chemical (ATC) classification/defined daily dose (DDD) methodology. The general quality of prescribing was determined using DU90% methodology (identifying the number of drugs constituting 90% of the volume expressed in DDDs and the adherence to evidence-based recommendations) and ratios between different treatment alternatives. The total volume and cost of drugs prescribed to the population was also analysed. RESULTS: In 2001, PHC centres accounted for, on average, 27% (range 14-36%) of all doctor consultations and 32% (range 22-43%) of all prescriptions to populations in the corresponding primary care districts. There was great variation between the different PHC centres with regard to the prescribing doctors' compliance with guidelines from the regional drug and therapeutics committee, and the utilization of health care and drugs among the population in the corresponding primary care districts. No clear improvement was observed over time. CONCLUSION: Analysis of aggregated prescription and healthcare data at population level was feasible. However, the effects of allocation of increasing resources to PHC on the quality of drug prescribing need to be analysed in a broader context.

Adolescent↗

PubMed1999

The German monitoring and reporting system for the treatment of substance-related problems: a national system on the basis of aggregated data.

The German treatment monitoring and reporting system EBIS for out-patient centres treating clients with substance-related problems and disorders was set up in 1980. A parallel system for in-patient treatment was added in 1993 under the name of SEDOS. Together they are based nation-wide on more than 600 specialised treatment centres which collect diagnosis- and treatment-related data as well as information on socio-economic and family background. As part of the data relate to the end of treatment, also evaluative elements are included. In EBIS and SEDOS, aggregated data are the basis of the national and regional statistics produced, which offers a very high level of data protection for the clients treated. The revision of the national system implementing the Treatment Demand Indicator Protocol as the European Monitoring Centre for Drugs and Drug Addiction standard has already been started.

Ambulatory Care↗

PubMed1990

Expressed emotion as a predictor of schizophrenic relapse: an analysis of aggregated data.

We examine published data from 12 studies assessing the capacity of Expressed Emotion (EE) status to predict schizophrenic relapse. Analysis of aggregated data, for 908 subjects, established a 3.7 times greater likelihood of relapse in those categorized as high EE, and a somewhat waning predictive strength EE over the publication interval, 1962-88.

Data Interpretation, Statistical↗

PubMed2002

Aggregate data meta-analysis with time-to-event outcomes.

In a meta-analysis of randomized controlled trials with time-to-event outcomes, an aggregate data approach may be required for some or all included studies. Variation in the reporting of survival analyses in journals suggests that no single method for extracting the log(hazard ratio) estimate will suffice. Methods are described which improve upon a previously proposed method for estimating the log(HR) from survival curves. These methods extend to life-tables. In the situation where the treatment effect varies over time and the trials in the meta-analysis have different lengths of follow-up, heterogeneity may be evident. In order to assess whether the hazard ratio changes with time, several tests are proposed and compared. A cohort study comparing life expectancy of males and females with cerebral palsy and a systematic review of five trials comparing two anti-epileptic drugs, carbamazepine and sodium valproate, are used for illustration.

Anticonvulsants↗

PubMed1983

Estimation in Markov models from aggregate data.

In this paper, situations in which individuals move through a finite set of states according to a continuous-time Markov process are considered. Only aggregate data are available: these consist of the number of individuals in each state at specified observation times. We develop conditional least squares and approximate maximum-likelihood-estimation procedures for time-homogeneous models, and extend the methods so that they can handle immigration of individuals into the system during observation. Asymptotic covariance estimates are presented, and some problems for future study are noted.

Animals↗

PubMed2005

An overview of methods and empirical comparison of aggregate data and individual patient data results for investigating heterogeneity in meta-analysis of time-to-event outcomes.

Combining the results of individual studies using meta-analysis may be undertaken using either aggregate data (AD) or individual patient data (IPD). In any meta-analysis it is important to consider statistical heterogeneity between studies. Potential sources of heterogeneity can be explored using regression models with either AD or IPD. An overview of approaches and empirical assessment of how the results and conclusions differ from these analyses is undertaken using a meta-analysis of five randomized controlled trials comparing two antiepileptic drugs with time-to-event outcomes. Alternative meta-regression models using AD are compared to stratified Cox regression models using IPD. Age as a potential cause of heterogeneity is detected by both AD and IPD regression models. Time from first ever seizure to randomization is only identified by some AD models. A more thorough explanation of heterogeneity is obtained from the model using IPD but further empirical evidence comparing IPD and AD results are needed.

Clinical Trials as Topic↗

PubMed2003

Estimating the induction period of pleural mesothelioma from aggregate data on asbestos consumption.

This study aimed to estimate the induction period from causal action of asbestos exposure to the manifestation of mesothelioma. We included the 9 countries for which we could find published aggregate data on the use of raw asbestos for a relevant time period. We extracted the annual numbers of cases of pleural cancer among men from the World Health Organization mortality database for those years using the International Classification of Diseases, 9th revision, classification. For the Scandinavian countries, we used published national cancer incidence data. In autoregressive Poisson regression modeling, we invoked different time lags of the mean annual use of asbestos to specify which time span produced the best correlation between the 2 time series. The ecologic analysis suggested that the most probable estimate for the mean induction period (use versus morbidity at society level) is approximately 25 years.

Asbestos↗

PubMed1988

Deriving relative risks from aggregate data. 2. An application to the relationship between unemployment and suicide.

In Part 1 of this study, the mathematical relations between micro and macro measures of effect were derived. The formulas thus obtained can be used for cross level comparisons of findings concerning the effect of some specific risk factor on, eg, mortality. The approach is illustrated by means of an empirical example relating to the association between unemployment and suicide. This relationship is estimated on micro data as well as on aggregate time series data. The findings from the two levels are fairly consistent.

Adult↗

PubMed2002

A method for meta-analysis where the level of data aggregation differs between studies.

BACKGROUND: This paper presents a statistical method that was used to assess haemoglobin levels world-wide among women, based on a combination of over 400 studies. METHODS: The methodology is easy to implement and is specifically adapted to the case where mean observations are taken, although the subgroups represented by the mean values may differ from study to study. That is, the level of data aggregation is not consistent between studies. RESULTS: In this example some studies report average haemoglobin levels for a sample of the population, while others give averages by urban/rural classification and/or pregnancy status. Though the method is based on likelihood principles, computation is straightforward. CONCLUSIONS: The methodology can be applied to a variety of meta-analytic situations where assessments are based on combining data from several sources. We provide an example of how the method was implemented in a study of haemoglobin levels among women undertaken at the World Health Organisation.

Data Collection↗

PubMed1993

Community types, socio-economic structure and IHD mortality--a contextual analysis based on Swedish aggregate data.

The importance of social and economic conditions for people's health has been receiving more and more attention during the past 10 years. The question that is raised in this study is if the link between socio-economic factors in society, seen in the more composite sense, and cardiovascular mortality are dependent on different socio-geographical contexts? Two contextual situations are used; one concerns the dimension which places the analysis in an urban-rural context and the other, the dimension placing it in a context which describes people's forms of work. The study is based on aggregated data on the social and economic conditions for men in the municipalities in Sweden for the period 1983-1987. The results show that the link between various dimensions of the socio-economic structure and IHD rates is more pronounced in the urban and white-collar community types than in rural and blue-collar communities. In the community type where the links are more pronounced the IHD rate is lower and in the type where the links are less pronounced the IHD rate is higher. The results are discussed in relation to different theoretical perspectives.

Cardiovascular Diseases↗

PubMed1987

Testing equality of relative survival patterns based on aggregated data.

The relative survival rate is defined as the ratio of the survival rate observed in a patient group under consideration to the survival rate expected in a group of people similar to the patient group at the beginning of the follow-up interval, with respect to all possible factors (e.g., age and sex) affecting survival, except the disease under study. Survival from cancer and other chronic diseases is often measured by this quantity, which is adjusted for the effect of mortality attributable to competing risks of death. In this paper, maximum likelihood ratio tests are constructed on the basis of aggregated data for testing the equality of relative survival rates between patient groups against proportional hazards and general alternative hypotheses. The tests are applied to the Finnish nationwide data on colon cancer patients with nonlocalized tumors as reported to the Finnish Cancer Registry. Simulation studies show that the maximum likelihood ratio tests compare favorably with alternative methods proposed earlier. Moreover, the maximum likelihood ratio tests are more extensive in coverage and are based on more applicable alternative hypotheses than the other test statistics. Finally, an extension to proportional hazards regression models of the relative survival rates is suggested.

Biometry↗

PubMed1990

"Avoidable" mortality and health services: a review of aggregate data studies.

STUDY OBJECTIVE: The aim of the study was to review published work reporting mortality from conditions amenable to medical intervention and compare the methods used and the results obtained. SOURCE MATERIAL: Two types of analysis were examined: (1) analyses of time trends, relating decline in mortality from amenable conditions to improvements in medical care (3 papers); (2) analyses of geographical variation, either between or within countries, in which mortality was related to the availability of health care resources and to other factors (8 papers). RESULTS: Time-trend studies have in general shown that mortality from amenable causes has declined faster over the past decades than most other causes of death. Studies of geographical variation have shown that mortality from amenable causes is consistently associated with socioeconomic factors, and that the association with the provision of health care resources is rather weak and inconsistent. CONCLUSIONS: (1) The low levels of mortality from amenable causes which presently prevail in industrialised countries are likely to reflect, at least in part, the increased effectiveness of health services; (2) geographical variation in mortality from amenable causes has not yet been shown to reflect differences in effectiveness of health services; and (3) if geographical variation in avoidable mortality does reflect such differences, they must arise from circumstances other than the level of supply, for example from more specific aspects of health care delivery, and are probably closely related to socioeconomic circumstances. In depth studies at the individual level are now more likely to produce information about factors limiting the effectiveness of health services than further studies of aggregate data.

Health Resources↗

PubMed1985

The ability of aggregate data to predict self-sufficiency levels in subsidized rural primary care practices.

American rural health policy has as its long-term goal the reallocation of health facilities and manpower to permit equitable access to primary care for all citizens. Rural health centers subsidized by governmental and philanthropic programs frequently have been placed in places of high need for their services. Yet both government and philanthropic policymakers expect these primary care practices to become economically self-sufficient within a few years of practice. The problem is how to assign rural practices to communities with a planning process that will enhance the likelihood that these conflicting goals of serving need and financial self-sufficiency will be achieved. This study uses actual 1980 self-sufficiency data from 167 randomly selected rural primary care clinics as the dependent variable. Independent variables for the corresponding communities five or more years earlier were taken from a database often used by policymakers to make site evaluations. These data tend to be selected from aggregate county level measures. Regression analysis were used to determine how well these data could predict actual self-sufficiency in later years. The result of the analysis is that these aggregate level data have little capacity to predict the ability of rural primary care practices to achieve self-sufficiency. Much better predictions can be made on the basis of local, practice-specific variables. Therefore, planning for economically viable rural practices calls for a much different forecasting approach.

Catchment Area, Health↗

PubMed1995

Data aggregation: criteria for psychometric evaluation.

Criteria for the examination of data collected at the individual level and aggregated to the group are proposed. These four empirical criteria relate to content validity, representativeness, reliability, and validity of the aggregated scores as indicators of group phenomena. An example of the use of the criteria is provided using data from a large research project on the implementation of a professional practice model on nine nursing units. The use of the criteria proposed provide a systematic approach to the evaluation of individual data for use at the group level.

Data Collection↗

PubMed2005

The strengths and limitations of meta-analyses based on aggregate data.

BACKGROUND: Properly performed systematic reviews and meta-analyses are thought by many to represent among the highest level of evidence addressing important clinical issues. Few would disagree that meta-analyses based on individual patient data (IPD) offer several advantages and represent the standard to which all other systematic reviews should be compared. METHODS: All cancer-related meta-analyses cited in Medline were classified as based on aggregate or individual patient data. A review was then undertaken of all reports comparing the comparative strengths and limitations of meta-analyses using either aggregate or individual patient data. RESULTS: The majority of published meta-analyses are based on summary or aggregate patient data (APD). Reasons suggested for this include the considerable resources, years of study and often, broad international cooperation required for IPD meta-analyses. Many of the most important features of systematic reviews including formal meta-analyses are addressed by both IPD and APD meta-analyses. The need for defining an explicit and relevant clinical question, exhaustively searching for the totality of evidence, meticulous and unbiased data transfer or extraction, assessment of between study heterogeneity and the use of appropriate statistical methods for estimating summary effect measures are essentially the same for the two approaches. CONCLUSION: IPD offers advantages and, when feasible, should be considered the best opportunity to summarize the results of multiple studies. However, the resources, time and cooperation required for such studies will continue to limit their use in many important areas of clinical medicine which can be meaningfully and cost-effectively approached by properly performed APD meta-analyses. APD meta-analyses continue to be the mainstay of systematic reviews utilized by the US Preventive Services Task Force, the Cochrane Collaboration and many professional societies to support clinical practice guidelines.

Bias↗

PubMed1995

Disease risk near point sources: statistical issues for analyses using individual or spatially aggregated data.

STUDY OBJECTIVE: To examine the statistical issues involved in the analysis of disease risk near point sources of environmental pollution, where data are held at both the individual and group (areal) level. To explore these issues with reference to possible socioeconomic confounding. DESIGN: Statistical review. SETTING: Point sources of environmental pollution. MAIN RESULTS: Except in very specific circumstances unlikely to hold in practice, aggregation of data to the areal level will lead to bias in the estimation of disease risk. CONCLUSIONS: There is no easy solution to the analysis of spatial data when some covariates (for example, age and sex of cases) are known at individual level, whereas others (for example, populations, age-sex distributions, small area deprivation indices) are known only at the areal (ecological) level. The underlying assumptions inherent in the analysis of these data need to be explicitly recognised in order to understand better the limitations of the available methodology as well as to inform interpretation of results. Ideally, the data should be kept as disaggregated as possible, to maximise the information available and minimise potential for bias.

Bias↗

PubMedDate not supplied

The interpretation of intensity and aggregation data for infections of Schistosoma haematobium.

The relationships between mean intensities of infection, the aggregation of infection among hosts, and host age are analysed using data from 2 large (> 3000 individuals) field studies of Schistosoma haematobium infection. The data show a convex relationship between mean intensity and age, a convex relationship between an inverse index of aggregation and age, and an age-dependent relationship between the mean and aggregation of infection intensity when levels of infection are high. These patterns are qualitatively compared with the output of mathematical models based on an immigration-death process (model I), and incorporating age-dependent changes in the distribution of exposure to infection as suggested by field data (model II), or reductions in the rate of infection as a function of either current (model III) or cumulative (model IV) parasite burdens, that is, density-dependent processes without or with memory, respectively. Models II and III were able to reproduce observed patterns, but model IV, which is a possible representation of acquired immunity, was not. These results are consistent with the following assumptions: (i) age-related patterns of aggregation can be generated without recourse to density-dependent processes; (ii) the epidemiological impact of density-dependent processes depends on whether these act with or without memory; and (iii) any acquired immunity to human S. haematobium infection may be significantly less than life-long.

Adolescent↗