What is the minimum requirement for the dataset for time series forecasting? I have a dataset of patients where, for each patient, a measurement is taken 3 times per day. For example, patient 1 has recordings at 7.30 am, 12.30 pm and 8.30 pm. Patient 1 has a collection of 30 days with such data recorded thrice a day.(altogether 3 recordings per day * 30 days = 90 data points). 

Is this type of data suitable for time-series forecasting? 

Thanks in advance for the help.
Sure! A time-series is just a set of data points indexed temporally, and that's exactly what you have for each patient.

You can certainly build a forecaster using this data.  You may run into a couple wrinkles since your data is not spaced evenly, but that's not an insurmountable barrier.

If you want to quickly prototype a forecasting model, FB Prophet is incredibly easy to use and often works well out-of-the-box.