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3 with link identity, distribution normal and AR (1). For binary variables, such as drug overutilisation and prohibited combinations, a probit model was used in GEE. Calculating marginal effects of policies As the interpretation of segmented regression analysis is difficult because there are many variables Selisistat mw related to time, marginal effects on dependent variables were calculated to display exact effects of policies. ��2 and ��3 were related to the drug price reduction policy. Marginal effects of only the drug price reduction in December 2012 compared to March 2012 can be calculated as (��2+��3��9). Similarly, the marginal effects of the new guidelines in October 2013 compared to January 2013 can be calculated as (��4+��5��9). The marginal effects of both policies in December 2013 compared to March 2012 can be calculated as (��2+��3��21+��4+��5��11). The coefficient estimates of drug overutilisation and prohibited combinations were calculated in the probit model, as they were needed to transform to marginal effects at the sample means of variables for interpretation. They were calculated with the margins command in Stata V.13. For example, they can be interpreted as increasing probability by amount of ��5 per unit increase. Results Table?1 shows the general participant characteristics in this study. A total of 54?295 participants were included and the highest proportion was in the over 70?years age group at 15?428. There were 24?842 (45.8%) men and 29?453 (54.3%) women. Most of the participants had health insurance (93.8%). More than half lived in rural areas (53.6%). Combinations of hypertensive agents were scored as 0, 1, 2 and over 3, with 14?000 (6.2%), 14?571 (26.8%), 10?628 (19.6%) and 15?096 (27.8%) participants. Table?1 General characteristics of study participants at baseline (March 2011) The monthly trends of dependent variables are displayed in figures 2?2�C4. We did not show the trends for all study populations because they are similar to the trends of the health insurance population which made up most of this study population (93.8%). Figure?2 Trends of monthly drug utilisation per patient. (A) Daily drug utilisation; (B) Average number of drugs; (C) Per cent of original drugs. Figure?3 Trends of monthly per cent of drug overutilisation and prohibited combination per patient (A) drug overutilisation; (B) prohibited combination. Figure?4 Trends of monthly expenditures per patient. (A) Antihypertensive drug costs; (B) Antihypertensive drug cost per prescribing day. Daily drug utilisation and number of drugs showed a decreasing trend after the guidelines. They were not affected by the drug price reduction. Number of drugs, number of drug overutilisations, and number of prohibited combinations showed decreasing trends after the new guidelines were implemented. The overall utilisation of originators did not change after the introduction of the new policies��(figures 2, and ?and3).3).