Calculating Total Health Service Utilisation and Costs from Routinely Collected Electronic Health Records Using the Example of Patients with Irritable Bowel Syndrome Before and After Their First Gastroenterology Appointment

Caroline Canavan (), Joe West and Timothy Card
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Caroline Canavan: University of Nottingham
Joe West: University of Nottingham
Timothy Card: University of Nottingham

PharmacoEconomics, 2016, vol. 34, issue 2, No 11, 194 pages

Abstract: Abstract Introduction Health economic models are increasingly important in funding decisions but most are based on data, which may therefore not represent the general population. We sought to establish the potential of real-world data available within the Clinical Practice Research Datalink (CPRD) and linked Hospital Episode Statistics (HES) to determine comprehensive healthcare utilisation and costs as input variables for economic modelling. Methods A cohort of patients with irritable bowel syndrome (IBS) who first saw a gastroenterologist in 2008 or 2009, and with 3 years of data before and after their appointment, was created in the CPRD. Primary care, outpatient, inpatient, prescription and colonoscopy data were extracted from the linked CPRD and HES. The appropriate cost to the NHS was attached to each event. Total and stratified annual healthcare utilisation rates and costs were calculated before and after the gastroenterology appointment with distribution parameters. Absolute differences were calculated with 95 % confidence intervals. Results Total annual healthcare costs over 3 years increase by £935 (95 % CI £928–941) following a gastroenterology appointment for IBS. We derived utilisation and cost data with parameter distributions stratified by demographics and time. Women, older patients, smokers and patients with greater comorbidity utilised more healthcare resources, which generated higher costs. Conclusions These linked datasets provide comprehensive primary and secondary care data for large numbers of patients, which allows stratification of outcomes. It is possible to derive input parameters appropriate for economic models and their distributions directly from the population of interest.

Date: 2016
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DOI: 10.1007/s40273-015-0339-y

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