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HERALD (Health Economics using Routine Anonymised Linked Data) / Muhammad J Husain; Sinead Brophy; Steven Macey; Leila M Pinder; Mark D Atkinson; Roxanne Cooksey; Ceri J Phillips; Stefan Siebert

BMC Medical Informatics and Decision Making, Volume: 12, Issue: 1

Swansea University Author: Cooksey, Roxanne

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Abstract

AbstractBackground: Health economic analysis traditionally relies on patient derived questionnaire data, routine datasets and outcome data from experimental randomised control trials or clinical studies. These datasets are generally used as distinct datasets. Herein, we outline the potential of link...

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Published in: BMC Medical Informatics and Decision Making
ISSN: 1472-6947
Published: 2012
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URI: https://cronfa.swan.ac.uk/Record/cronfa12638
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Abstract: AbstractBackground: Health economic analysis traditionally relies on patient derived questionnaire data, routine datasets and outcome data from experimental randomised control trials or clinical studies. These datasets are generally used as distinct datasets. Herein, we outline the potential of linking these datasets to give a unified, joined-up data-resource to be used in health economic analysis.Method: The linkage of individual level data from questionnaires with routinely-captured health care data allows the entire patient journey to be mapped both retrospectively and prospectively. We illustrate this with examples from an Ankylosing Spondylitis (AS) cohort by linking patient reported study data with the routinely collected general practitioner (GP) data, inpatient (IP), outpatient (OP) and Accident and Emergency datasets in Wales. The linked data system allows (1) retrospective and prospective tracking of patient pathways through multiple healthcare facilities; (2) validation and clarification of patient-reported recall data, complementing the questionnaire/routine data information; (3) obtaining objective measures of the costs of chronic conditions for a longer time period, and during the pre-diagnosis period; (4) assessment of health service usage, referral histories, prescribed drugs and co-morbidities; and (5) profiling and stratification of patients relating to disease manifestation, lifestyles, co-morbidities, and associated costs.Results: Using the GP data system we tracked 183 AS patients retrospectively and prospectively from the date of questionnaire completion to gather the following information: (a) number of GP events; (b) presence of a GP ‘drug’ read codes; and (c) the presence of a GP ‘diagnostic’ read codes. We tracked 236 and 296 AS patients through the OP and IP data systems respectively to count the number of OP visits and IP admissions and duration.Results are presented under several patient stratification schemes based on disease severity, functions, age, sex and disease symptom onsetConclusion: The linked data system offers unique opportunities for enhanced longitudinal health economic analysis not possible through the use of traditional isolated datasets. Additionally, this data linkage provides important information to improve diagnostic and referral pathways and thus maximises clinical efficiency.
College: Swansea University Medical School
Issue: 1