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Sascha G. Wolf, Data in:

Sascha G. Wolf

Pharmaceutical Expenditure in Germany, page 37 - 38

Future Development, Political Influence and Economic Impact

1. Edition 2009, ISBN print: 978-3-8329-4164-2, ISBN online: 978-3-8452-2005-5 https://doi.org/10.5771/9783845220055

Series: Neue Studien zur Politischen Ökonomie, vol. 6

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37 Figure 2.8: Standardised Per Capita Age-Related Drug Consumption Pro? les (Women) for 1988 and 2003.20 0 1 2 3 4 0 - 4 30 - 34 60 - 64 ? 90 Group 1 0 1 2 3 4 0 - 4 30 - 34 60 - 64 ? 90 Group 2 0 1 2 3 4 0 - 4 30 - 34 60 - 64 ? 90 Group 4 0 1 2 3 4 0 - 4 30 - 34 60 - 64 ? 90 Age Group 5 0 1 2 3 4 0 - 4 30 - 34 60 - 64 ? 90 Age Group 6 (Group 3) Standardis ed Consumption per Capit a ----- 1988 2003 2.5. Forecasting Pharmaceutical Expenditure 2.5.1. Data The expenditure outlook has been developed by using the extracted indication groups instead of aggregated total pharmaceutical expenditure. This approach has the advantage that different developments of drug expenditure can be considered. Thus the prognosis rests upon the assumption that the members of the indication groups underlie comparable growth trends whereas the development between the indication groups varies due to their unequal characteristics concerning age-dependency and acuteness. 20 See ? gure A.2.6 in the appendix for the un-standardised pro? les. 38 Data about the future demographic development was taken from the 10th Coordinated Population Projection of the German Federal Statistical Of? ce (Statistisches Bundesamt 2003). The outlook delivers 10 variations of population development by 2050: each considers different assumptions about life expectancy and immigration. In this chapter, the medium variation 5 has been applied. Therefore the life span in 2050 of a newborn boy is predicted to be 81.1 years and 86.6 years for a girl. Remaining life expectancy of a 60-year-old increases to 23.7 years for a man and to 28.2 years for a woman by 2050. An annual immigration surplus of 200,000 persons is assumed. The birth rate is kept constant at 1.4 children per woman. On the basis of the population projection, the number of SHI insurants has been assessed, using the ratio of population to insured people of 2004. 2.5.2. Methodology For each age class of people for each drug group, a growth trend was computed by means of linear regression. This was done according to the development between 1988 and 2004.21 Since the grouped indication areas of the Red List cover only 90 % of total disbursements, the expenditure that was not considered must be added. This was done by holding the share between considered expenditure and total expenditure constant at the rate of 2004, which is the base year of the prognosis. Since disbursements in some age groups have declined during the observation period, it is possible that in the outlooks in those cases negative values accrue. Therefore a minimum level of zero for every time series was implemented to prevent negative values from distorting the results. With the objective of identifying the causes of the future drug expenditure development, special indicators are needed. Calculating these indicators necessitates a circuitous procedure: Firstly, the pharmaceutical data must be standardised by dividing the values of the single age groups by average expenditure. Consequently, the slopes do not represent the absolute age group speci? c growth rates but the changes in ratio of the development of average drug disbursements. Future per-head expenditure results from: (2.1) with: Exp = standardised per-capita drug expenditure, a = age-group, g = gender, i = indication group, c = slope parameter, t = 2005, …, 2050. Secondly, re-standardisation by means of multiplying the standardised consumption pro? les with the estimated mean values delivers the expenditure amount. Using standardisation enables the extraction of various indicators: “total effect”, 21 Following Buchner (2002). The coef? cient of determination (R2) shows almost identical values for linear and exponential approximation. It averages 0.69 (0.64) for men (women) in the case of linear approximation and 0.64 (0.61) in the exponential case.

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Zusammenfassung

Der Arzneimittelsektor der Gesetzlichen Krankenversicherung stand wiederholt im Fokus zahlreicher Gesundheitsreformen. Dennoch ist es bislang nicht gelungen, den Trend steigender Ausgaben nachhaltig zu bremsen. Die vorliegende Untersuchung leistet einen Beitrag dazu, die Ursachen dieser Entwicklung zu erklären und Lösungsansätze aufzuzeigen. Mittels Hauptkomponenten- und Cluster-Analyse wurden Gruppen von Arzneimitteln mit vergleichbaren Konsumeigenschaften gebildet. Jede Gruppe wurde auf den Einfluss der Altersabhängigkeit und des technologischen Fortschritts hin analysiert. Aufbauend auf diesen Ergebnissen wurde eine Prognose der zukünftigen Ausgabenentwicklung bis zum Jahr 2050 erstellt. Obwohl die Hauptkostenfaktoren exogen sind, steht der Gesetzgeber dem vorhergesagten ansteigenden Kostenpfad nicht hilflos gegenüber. Im Gegenteil: Anhand ökonometrischer Tests wird gezeigt, dass die Gesundheitspolitik in der Vergangenheit durch wahl- und klientelorientierte Interessendurchsetzung geprägt war. Mehr Effizienz in der Arzneimittelversorgung könnte durch die Einführung individueller Gesundheitssparkonten erzielt werden. Dies bestätigen die Resultate eines vertikal differenzierten Wettbewerbsmodells.