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PubMed · 10751975

Evaluation methods for social intervention.

Abstract

Experimental design is the method of choice for establishing whether social interventions have the intended effects on the populations they are presumed to benefit. Experience with field experiments, however, has revealed significant limitations relating chiefly to (a) practical problems implementing random assignment, (b) important uncontrolled sources of variability occurring after assignment, and (c) a low yield of information for explaining why certain effects were or were not found. In response, it is increasingly common for outcome evaluation to draw on some form of program theory and extend data collection to include descriptive information about program implementation, client characteristics, and patterns of change. These supplements often cannot be readily incorporated into standard experimental design, especially statistical analysis. An important advance in outcome evaluation is the recent development of statistical models that are able to represent individual-level change, correlates of change, and program effects in an integrated and informative manner.

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M W Lipsey, D S Cordray. 2000. Evaluation methods for social intervention.. https://doi.org/10.1146/annurev.psych.51.1.345

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Data Collection↗

[Exchange of paraclinical information between the primary and secondary health sectors].

INTRODUCTION: The purpose of the study was to investigate the extent to which, biochemical test results obtained in the primary health sector could be regarded as valid information in the clinical assessment of patients admitted to hospital. METHODS: The study was based on a questionnaire, which was designed to assess the value of historical biochemical data in the initial diagnostic process. The data was transferred from the laboratory of Copenhagen general practitioners (KPLL) database to a computer terminal in the emergency medical ward at H:S Bispebjerg Hospital. RESULTS: It was possible to assess historical KPLL data on close to 80% of all hospitalised patients. In 50% of these patients, doctors indicated that the data always (96%) contributed to the diagnosis. In 70%, the data further contributed to the subsequent planning of diagnostic strategy. With regard to the initial diagnosis, comparison of KPLL data with data obtained on admission always resulted in a further classification of at least one condition. The comparison of KPLL data with admission data always led to a more precise plan for further diagnostic strategy. CONCLUSION: The comparison of KPLL data with admission data, significantly contributes to differentiate the initial diagnostic strategy. In turn, this seems to have a significant bearing on the planning of further diagnostic strategy. It is postulated that a computer-based information system, through which the primary and secondary health sectors can exchange patient-related clinical data, would lead to a more focused use of resources, and hold significant advantages for the patient.

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