Nova Publishers
My Account Nova Publishers Shopping Cart
HomeBooksSeriesJournalsReference CollectionseBooksInformationSalesImprintsFor Authors
            
  Top » Catalog » Journals » International Public Health Journal » Volume 3 Issue 2 Articles » My Account  |  Cart Contents  |  Checkout   
Quick Find
  
Use keywords to find the product you are looking for.
Advanced Search
What's New? more
Theory of Literature
$270.00
Shopping Cart more
0 items
Information
Shipping & Returns
Privacy Notice
Conditions of Use
Contact Us
Bestsellers
01.Best Practice in Using Evidence for Health Policy: Do we know what it is?
02.What is Translational Research? Background, Concepts, and a Definition
03.Vertical Integration of Health Insurance and Care Provision: Does it Improve Service Delivery?
Notifications more
NotificationsNotify me of updates to Evaluating Pharmaceutical Policy Impacts Using Interrupted Time Series Analysis: An Australian Case Study
Tell A Friend
 
Tell someone you know about this product.
Evaluating Pharmaceutical Policy Impacts Using Interrupted Time Series Analysis: An Australian Case Study $0.00
Authors:  Anna Kemp, David B. Preen, Frank M. Sanfilippo, John Glover, James Semmens and Elizabeth E. Roughead
Abstract:
Determining the impacts of policy on health outcomes is important for policy makers, clinicians and consumers. Interrupted time series analysis is a powerful quasi-experimental method for quantifying change in an outcome after policy implementation. We illustrate the use of interrupted time series analysis for policy evaluation with an Australian case study. Use of prescription medicines in Australia were examined before and after the implementation of pharmaceutical-subsidy changes. Methods: Interrupted time series analysis compares longitudinal data, aggregated into time-units, before and after a change-point. A line of best fit is calculated for the period before and after the change-point and the differences in the level (i.e. height) and trend (i.e. slope) of these lines are quantified. In our case study, dispensings of specified medicines in Australia were compared for 60 months before and 33 months after a substantial increase in prescription costs in January 2005. Results: Interrupted time series analysis quantifies level and trend changes occurring after a change-point and indicates when, and for how long, changes occur. Significant change in the level of a series indicates an immediate policy impact while a significant trend change indicates an on-going impact on an outcome. We found significant decreases in the level or trend of dispensings for 12 medicine classes indicating both immediate and on-going declines in use. Declines were largest for low income patients and for medicines used preventatively to treat asymptomatic conditions. Conclusions: Interrupted time series analysis provides a simple and feasible method of evaluating the impact of already-implemented policies on health outcomes. Findings from the case study, suggested that the January 2005 increase patient co-payments had affected the use of medicines, and that the largest impacts were on low income patients and medicines used to prevent disease progression. These findings had implications for patient care and health service planning. Interrupted time series can be adapted to a range of settings to provide feedback important for future policy formulation. 


Available Options:
Version:

  Open Access item.
  Click below PDF icon for free download.

  

This is an Open Access item. Click above PDF icon for free download.
Special Focus Titles
01.Violent Communication and Bullying in Early Childhood Education
02.Cultural Considerations in Intervention with Women and Children Exposed to Intimate Partner Violence
03.Chronic Disease and Disability: The Pediatric Lung
04.Fruit and Vegetable Consumption and Health: New Research
05.Fire and the Sword: Understanding the Impact and Challenge of Organized Islamism. Volume 2

Nova Science Publishers
© Copyright 2004 - 2020

Evaluating Pharmaceutical Policy Impacts Using Interrupted Time Series Analysis: An Australian Case Study