cohort_processing: Patient Cohort Re-Identification Processing

In SangerTools: Tools for Population Health Management Analytics

Patient Cohort Re-Identification Processing

Description

Population Health Management commonly leads practitioners to identify a cohort that will have an intervention applied. As a rule of thumb most analysts will work with pseudonymised data sets. For targeted interventions patients require re-identification; this process is generally carried out by a third party organisation. As third party organisations work with many health care providers they have a strict set of requirements. This has been based around SW CSU's required formatting.

Usage

cohort_processing(
  df,
  Split_by,
  path,
  prefix = "DSCRO",
  com_code = "11M",
  date_format = "%Y%m%d",
  suffix = "_REID_V01"
)

Arguments

df	a tidy dataframe in standard Master Patient Index format ie SangerTools::PopHealthData.
Split_by	A column within df that will be used to split the patients and will also appear in the file name. Ideally should be a health organisation code such as GP Practice Code or Hospital Trust Code. Should only have alpha-numeric values
path	A file path to which the CSV files will be written
prefix	File name prefix, default is "DSCRO" See more here: NHS DSCRO
com_code	Commissioner Code, default is "11M"; Gloucestershire.
date_format	A date format passed internally to 'format(Sys.Date())'; will form part of file name to denote date of generation. You can read more about date formatting in R from R lang
suffix	A file name suffix, default is "_REID_V01", To be left as blank use "", without spaces.

Value

n number of CSV files written to the location specified by path argument.

SangerTools documentation built on March 18, 2022, 6:45 p.m.