Segmented regression interrupted time series analysis

[SSK_011523]

Hello

I am using single ITS for one of my projects to assess the impact of a policy intervention on medication use. 

Outcome: Medication use (defined as aggregated means)

Exposure: Policy intervention

For the ITS model, I have defined the following parameters: 

Time (beta1): quarterly data (a total of 31 quarters). 

Intervention (beta2): The intervention was introduced in 12th quarter. I have defined intervention as three segments to take into account lagged effect. 0 indicates pre-intervention, 1 indicates transition/lagged period and 2 indicates post-intervention.

Time after intervention (beta 3): defined as 0 before the intervention 0 and intervention 1 and then as (1,2,3..19)

Since autocorrelation was detected in my data, I decided to use PROC AUTOREG. I used the following code:

********************************

PROC AUTOREG data = have;

model outcome = time intervention time_after_intervention/method = ml backstep nlag=5 dw=12 dwprob loglikl;

output out=want p =predicted r = residual;

run;

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OUTPUT:

Variable	Estimate	Approx Pr > t
time	0.8	<0.0001
intervention	-2.9	<0.0002
time after intervention	-1.1	<0.0003

Interpretation:

I am not sure how to interpret 'intervention' as I have defined it as three segments (pre-intervention, lagged period, and post-intervention). Do I interpret it in the same way if two segments were used to define intervention? 

I tried using class statement thinking I would get separate estimates for each segment but it did nit work.

Any help on this would be appreciated. Thanks!