Is there a way to combine multiple MatchIt objects together in R

Question

I have a dataset that I'm performing a match on that is a repeated cross section with overlapping membership:

MemberID	Treatment	StudyMonth	Age	Sex	RiskScore	COPD	CHF	Diabetes	ComplexProviderFLG
123	1	1	54	M	1.45	0	1	1	0
201	0	1	55	M	1.54	0	1	1	0
205	0	1	85	M	.8	1	0	0	0
155	1	2	56	M	1.58	0	1	1	0
201	0	2	55	M	1.54	0	1	1	0
208	0	2	58	M	1.68	0	0	1	0

NOTE how Member 201 was in the first month cross-section and the second. So when I match on one StudyMonth, I need to remove the individuals matched for that cross section from the potential match pool for future cross sections.In the toy example above even though 201 is the best control for both 123 in month 1 and 155 in month 2, I don't want him in the control pool twice.

It's pretty straight forward to do a for loop and rerun the match, eliminating previously chosen individuals and then bind the results of each loop together into a final treatment/control group like this:

for (MatchMonth in 0:11){
WorkingMatchedCohort <- matchit(Treatment ~ Age + Sex + RiskScore +
                       CHF + COPD + Diabetes + Depression + ComplexProviderFLG,
                       data= filter(WorkingSet,(Treatment==0 | Treatment==1) & StudyMonth==MatchMonth))

    if(exists("unionedmatches")) {
      unionedmatches<-bind_rows(unionedmatches,match.data(WorkingMatchedCohort))
    }else{
      unionedmatches<-match.data(WorkingMatchedCohort)
    }
  ##Flag members so that they're not reused 
  WorkingSet$Treatment[WorkingSet$Treatment==0 & WorkingSet$MemberID %in% unionedmatches$MemberID] <-2
}

This gives me combined results in the unionedmatches tibble using match.data . But how would I go about combining the actual MatchIt objects WorkingMatchedCohort so that I can use the built in MatchIt tools for plotting the goodness of fit?