Solving Bayes Theorem equation -> I can't calculate proper result

Question

I am solving questions for an edx course on Machine Learning. One particular question is giving me a problem:

Assume a patient comes into the doctor’s office to test whether they have a particular disease. The test is positive 85% of the time when tested on a patient with the disease (high sensitivity): P(test+|disease)=0.85 The test is negative 90% of the time when tested on a healthy patient (high specificity): P(test−|heathy)=0.90 The disease is prevalent in about 2% of the community: P(disease)=0.02 Using Bayes' theorem, calculate the probability that you have the disease if the test is positive.

My solution:

I have created a table

   sick   |   healthy
     2%   |   98%
+   90%   |   15%
-   10%   |   85%

From this I calculated bayes theorem like this:

                      (0,02*0,9)
P(A|B) = -----------------------------------------------------
               (0,02*0,9) + (0,15*0,98)

I get P(A|B)=0,109 however this answer is wrong, where did I do mistake?