Which algorithm can i use for predicting length of stay in coming year based on historical claims data? I have two years historical health claims data of one thousand members. Based on this two years data, I have to predict length of stay in hospital in 3rd year for all members. here is the data sample.

Year MembID x1 x2 x3 x4 x5 x6 x7 LengthOfStay

2010 1 6 35 0 3 0 0 4 1

2010 1 8 35 0 5 0 0 3 0

2009 1 5 35 0 5 0 0 3 3

2009 1 3 35 0 8 2 0 8 0

2010 2 6 30 0 3 3 2 4 0

2010 2 8 30 0 5 0 0 3 0

2009 2 5 30 0 5 0 0 3 0

2010 2 5 30 1 5 0 2 2 0

2009 3 5 55 1 5 1 2 2 0

2010 3 10 55 1 5 0 2 2 0

2010 3 5 55 1 5 1 2 2 0

2009 3 10 55 1 5 0 0 2 0

2010 4 5 24 1 5 0 0 2 0

2009 4 3 24 1 8 0 0 2 0

2009 5 10 65 1 5 1 2 4 5

2009 5 5 65 1 5 0 2 3 0

2010 5 6 65 1 3 0 0 4 1

2010 5 4 65 1 5 0 0 4 0
2010 6 10 44 1 5 1 2 4 5 
2011--- i expect------ 1 


I did the classification with randomforest. How can I proceed further for prediction on 2011?
If you want to do prediction using 2011 features, the answer is yes, you can do that.

However, as you don't want to use these features, the answer might be no.

Without using 2011 features, your dataset will have only 2 samples(2009 and 2010) under the assumption that every memberID is different. Prediction from two samples is neither reliable nor feasible.