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The Effect of Financial and Educational Incentives on Rational Prescribing. A State‐Space Approach

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  • Petros Pechlivanoglou
  • Jaap E. Wieringa
  • Tim de Jager
  • Maarten J. Postma

Abstract

In 2005, a Dutch health insurer introduced a financial incentive directed to general practitioners to promote rational prescribing of statins and proton pump inhibitors (PPIs). Concomitantly, a regional institution that develops pharmacotherapeutic guidelines implemented two educational interventions also aiming at promoting rational statin and PPI prescribing. Utilizing a prescription database, we estimated the effect of the interventions on drug utilization and cost of statins and PPIs over time. We measured the effect of the interventions within an implementation and a control region. The implementation region included prescriptions from the province of Groningen where the educational intervention was implemented and where the health insurer is most active. The control region comprised all other provinces covered by the database. We modelled the effect of the intervention using a state‐space approach. Significant differences in prescribing and cost patterns between regions were observed for statins and PPIs. These differences however were mostly related to the concurrent interventions of Proeftuin Farmacie Groningen. We found no evidence indicating a significant effect of the rational prescribing intervention on the prescription patterns of statins and PPIs. Our estimates on the economic impact of the Proeftuin Farmacie Groningen interventions indicate that educational activities as such can achieve significant cost savings. Copyright © 2014 John Wiley & Sons, Ltd.

Suggested Citation

  • Petros Pechlivanoglou & Jaap E. Wieringa & Tim de Jager & Maarten J. Postma, 2015. "The Effect of Financial and Educational Incentives on Rational Prescribing. A State‐Space Approach," Health Economics, John Wiley & Sons, Ltd., vol. 24(4), pages 439-453, April.
    • Handle: RePEc:wly:hlthec:v:24:y:2015:i:4:p:439-453
    DOI: 10.1002/hec.3030
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    1. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
    2. Commandeur, Jacques J.F. & Koopman, Siem Jan, 2007. "An Introduction to State Space Time Series Analysis," OUP Catalogue, Oxford University Press, number 9780199228874.
    3. Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2004. "How Much Should We Trust Differences-In-Differences Estimates?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(1), pages 249-275.
    4. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    5. Peter Leeflang & Jaap Wieringa, 2010. "Modeling the effects of pharmaceutical marketing," Marketing Letters, Springer, vol. 21(2), pages 121-133, June.
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    1. Christoph F. Kurz & Martin Rehm & Rolf Holle & Christina Teuner & Michael Laxy & Larissa Schwarzkopf, 2019. "The effect of bariatric surgery on health care costs: A synthetic control approach using Bayesian structural time series," Health Economics, John Wiley & Sons, Ltd., vol. 28(11), pages 1293-1307, November.

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