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Longitudinal Analysis of Market Utilization / Pharmaceutical Sales Data Christine Lu Harvard Medical School and Harvard Pilgrim Health Care Institute WHO.

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Presentation on theme: "Longitudinal Analysis of Market Utilization / Pharmaceutical Sales Data Christine Lu Harvard Medical School and Harvard Pilgrim Health Care Institute WHO."— Presentation transcript:

1 Longitudinal Analysis of Market Utilization / Pharmaceutical Sales Data Christine Lu Harvard Medical School and Harvard Pilgrim Health Care Institute WHO Collaborating Center in Pharmaceutical Policy ICIUM 2011 (Poster 878) WHO Collaborating Center in Pharmaceutical Policy

2 Acknowledgements  Co-investigators: Dennis Ross-Degnan, Anita Wagner, Bao Liu, Peter Stephens  IMS Health for providing the data  Location of work: Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute  Conflict of interest: None

3 Overview  Background / Context  The data  Challenges  Opportunities

4 Background – China  Country: China Most medicines sold in hospitals (80%) Hospitals rely on profits from pharmaceutical sales to cover operating costs  Policy of interest: Medicine price regulations for antidiabetic products Set product’s maximum retail price

5 Study aim To examine the effects of two targeted price regulations on purchasing of insulin and oral hypoglycemics in Chinese hospitals Dec 2001 Dec 2006

6 IMS data  Longitudinal, quarterly data  Volume data: standard units sold (e.g. one tablet) Individual product-level, can be rolled up to Drug level e.g. metformin Drug class level e.g. biguanides Categories: price regulated vs. non-regulated Adjust for population Calculate percentage market share

7 IMS data: Data elements Variable nameExample Country_ctyChina hospital Time of procurement2003 q1 Anatomical Therapeutic Class 2A10 (drugs used in diabetes) Anatomical Therapeutic Class 4A10H0 (sulphonylureas A-diabs) MoleculeGliclazide International packTablet 30mg 30 Launch date ProductDiamicron ManufacturerSERVIER-TIANJIN Licensing statusOriginal brand Further details see “IMS MIDAS Quantum Data Elements, Measures and Statistics”

8 Interrupted Time Series  Prior to using this method: Understanding the policy Sufficient data points before and after the time of the policy  Segmented regression: Estimate changes in level and trend (slope) post-policy Control for pre-existing level and trend Wagner AK et al. J Clin Pharm Ther 2002

9 Organizing data for time series plot

10 Organizing data for segmented regression

11 Some results Increase in trend of sales volume (0.18 standard units sold/1000 people/quarter) Price regulation

12 Summary of the study  China’s price regulations for antidiabetics were associated with: Increase in utilization of antidiabetics No meaningful change in market share of price- regulated antidiabetic products  ? Impact of price regulation on medicine costs for Patients Hospitals The system

13 Challenges  IMS data-related Only capture hospital data in China BUT most medicines are sold in hospitals Come from a sample of Chinese hospitals ( ≥ 100 beds) Volume data more reliable than pricing data  Non IMS data-related Relative drug prices

14 Opportunities  Clean, well-structured data from IMS Health  Data specifics well documented  Longitudinal data so can use ITS method  A large sample of hospitals across the country  Volume data available at the individual-product level  Small data file size manageable in MS Excel (& SAS)  Building a good collaboration


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