> dat <- data.frame("ID" = c(6,6,6,7,7,10,11,11),
                      "Admit_Dt" = c('2013-08-12', '2013-12-12', '2016-01-03','2011-04-01', '2011-09-20','2012-02-19','2014-06-24','2014-08-12'),
                      "Urgent" = c(0,1,1,1,0,0,1,1))
   > dat

| ID | Admit_Dt   | Urgent|
|  6 | 2013-08-12 |      1|
|  6 | 2013-12-12 |      0|
|  6 | 2016-01-03 |      1|
|  7 | 2011-04-01 |      1|
|  7 | 2011-09-20 |      0|
| 10 | 2012-02-19 |      0|
| 11 | 2014-06-24 |      1|
| 11 | 2014-08-12 |      1|

> dat$Urgent_1yrSum <- unlist(sapply(1:length(unique(dat$ID)), function(i) {
    grouped <-  subset(dat, ID == unique(dat$ID)[i])
      output <- do.call(rbind, lapply(1:nrow(grouped), function(y){
    urgent_sum_1year <- sum(grouped[grouped$Admit_Dt < grouped$Admit_Dt[y] & grouped$Admit_Dt > (grouped$Admit_Dt[y] - dyears(1)), "Urgent"])
     }))
      return(output)
}
))

> dat
| ID | Admit_Dt   | Urgent| Urgent_1yrSum|
|  6 | 2013-08-12 |      1|          0|
|  6 | 2013-12-12 |      0|          1|
|  6 | 2016-01-03 |      1|          0|
|  7 | 2011-04-01 |      1|          0|
|  7 | 2011-09-20 |      0|          1|
| 10 | 2012-02-19 |      0|          0|
| 11 | 2014-06-24 |      1|          0|
| 11 | 2014-08-12 |      1|          1|