Have you tried the Split Function?

Thanks for your quick response. There is no specific delimiter as in the example. Sometimes it is a comma, and sometimes it is a semi-colon, and sometime it is a space. So it would be difficult to create an array of dates. Also, the last date is not always in the same format. It may be m/d/yy, or m/d/yyyy ormm/dd/yy, or mm/dd/yyyy. And the text field contains other text such as "updated" or "new". I feel it may not be possible.

Where is the list of dates coming from?
Can that be standardised?

You could split by all the delimiters.
Then you could get the last item.
Then you could split by /
And use DatePart

Hi Stephen,  
Is this your database? Why are you not storing the dates in a child table?

You could use the Replace Function to make all delimiters the same.
Then use some String Functions to remove the last semi-colon.
Then Split the split the string based on the delimiter.

The screenshot below shows this process for a single field based on the information given.
If you need to do this for multiple records you will need a Recordset loop.

>> There is no specific delimiter as in the example. Sometimes it is a comma, and sometimes it is a semi-colon, and sometime it is a space. <<

If it is totally free-form text, you need to consider other possibilities: what if a comma (or any delimiter) is followed by one space, no space, or multiple spaces?  What if the user typed space-ccomma-space, space-space-comma, comma-space-space, etc.?  What if the user typed invalid dates due to typos: 10//18/24, 10/1 8/24, etc.  The more irregularities like these, the more difficult it would be (if not impossible) to write code to extract data from the text.  You need to have a better way to control user input instead of allowing free-form text entry with no validation nor control.

Sami asked a very important question that Stephen should address.

John

You might also check out InStrRev and be prepared to do some manual data scrubbing.  

Long term, you might check out Normalizing Data.  As you are probably aware, this is the cost of not Normalizing data in the beginning.

You are not alone in dealing with non-Normalized data.  It requires an evaluation of the data and an application of the recommended topics to clean as much data as you can.  It will likely require some manual scrubbing of the rest.

Sorry for not getting back to everyone sooner. Other issues came up. To answer Sami's question, No it is not my Database. It belongs to a Food Pantry/Thrift Store where I volunteer.  Their programmer retired and I told them I did some Access programming throughout my career. And now that I am their programmer (also volunteer work) I am tasked with converting their flat file Database into a truly relational Database.

Thank you all for your help.

After considering my options and realizing that this field of data is too abnormal (it starts out being 1 date, sometimes represented  as "New " + the date the client becomes a member), I have decided that it will be a manual process and changed to just one date: LastUpdate on the client's record and it only gets updated once a year due to federal regulations.There is no need to keep all the previous updates. Once again, Thank you everyone for your input.