dupl.readm: Identify Duplicates and Re-admissions

In rSPARCS: Sites, Population, and Records Cleaning Skills

Identify Duplicates and Re-admissions

Description

Identify the duplicates and re-admissions in hospital data with subject identifications.

Usage

dupl.readm(data,UniqueID,date,period)

Arguments

data	a data.frame containing "UniqueID" and "date"
UniqueID	the name of the variable in the data indicating case ID.
date	the name of the variable in the data indicating the admission/onset date.
period	the time period used to define an re-admission; period=365 by default.

Details

Not limited to hospital data, but also applicable to other surveillance data with "UniqueID" and "date".

Value

id.dupl	indicating whether it is a duplicated record with exactly the same "UniqueID" and "date" as a previous record. In some hospital data,some patients may be reported twice or even more due to insurance issues. For most studies, researchers may remove this kind of duplicates to avoid potential overcounting problems.
onlyone	indicating whether this is the only record with this ID.
Period	the time period between the current visit and the previous one for a patient; 0 for the 1st visit; and NA for those with only one record.
Nadmission	indicating the times of admission, e.g. 1st, 2nd admission; a patient may have more than one 1st admissions if some periods between two visits are greater than e.g. 365 days.

Examples

dataset=data.frame(
  ID=c(1,3,4,2,4,6,3,5,7,1),
  onset=c("2015/1/1","2016/1/2","2015/5/9",
          "2015/12/1","2016/8/2","2015/5/9",
		  "2015/11/1","2016/3/2","2016/5/9","2015/9/9")
)

out.data=dupl.readm(data=dataset,
                    UniqueID="ID",date="onset",period=365)
head(out.data)

rSPARCS documentation built on Nov. 21, 2023, 9:07 a.m.