Multiple Imputations in a Dataset

Dear all,

I'm a student working on a dataset based on a cross-sectional survey. The dataset includes around 200participants. The main analysis will involve a linear regression involving 3 predictors and an outcome continuous variable. Unfortunately, the data I have was collected over a long period of time and there was a systematic fault in data collection: the outcome variable in my analysis was not collected for a subset within my dataset. This subset is 40 participants. As such, my data isn't missing at random. Also, the missing subset is around 20% of my whole sample!

For such a huge percentage of missing data, I was wondering if multiple imputations can be done? Also, what would be a recommended number of imputations to make? Is there a specific reference or book that you recommend.

Thank you