Identify encounters with disability

This function identifies whether or not an encounter had any ICD-10-CA diagnosis code(s) indicating a physical, sensory, or intellectual/ developmental disability as defined by Brown et al., 2021.

Broadly, this includes any diagnosis codes for conditions that are likely to result in functional limitations and are considered to be chronic (see Supplemental eTable 2 in Brown et al., 2021 for a full list of diagnosis codes). However, note that this function only searches for relevant diagnosis codes at the encounter level and does not check whether chronic conditions are coded consistently across different encounters for a given patient.

By setting component_wise to TRUE, users can choose to return all identified diagnosis codes for encounters with a disability, together with the disability category each code was matched with (e.g., physical/sensory/ developmental disability - see below).

Usage

disability(cohort, ipdiag, erdiag, component_wise = FALSE)

Arguments

cohort

(data.frame or data.table) Cohort table with all relevant encounters of interest, where each row corresponds to a single encounter. Must contain GEMINI Encounter ID (genc_id).

ipdiag

(data.table) ipdiagnosis table as defined in the GEMINI Data Repository Dictionary. This table must contain genc_id and diagnosis_code (as ICD-10-CA alphanumeric code) in long format.

erdiag

(data.table) erdiagnosis table as defined in the GEMINI Data Repository Dictionary. This table must contain genc_id and er_diagnosis_code (as ICD-10-CA alphanumeric code) in long format. Typically, ER diagnoses should be included when deriving disability in order to increase sensitivity. However, in certain scenarios, users may choose to only include IP diagnoses by specifying erdiag = NULL. This may be useful when comparing cohorts with different rates of ER admissions.

component_wise

(logical) If component_wise == FALSE (default), the function calculates a single (global) disability flag indicating whether each genc_id was diagnosed with any disability.

If component_wise == TRUE, for each genc_id with a disability, all identified disability diagnosis codes are returned, together with one of the following 7 disability categories:

• Physical disability - Congenital Anomalies

• Physical disability - Musculoskeletal disorders

• Physical disability - Neurological disorders

• Physical disability - Permanent Injuries

• Sensory disabilities - Hearing impairments

• Sensory disabilities - Vision impairments

• Developmental Disabilities

Value

data.table If component_wise == FALSE, returns a table with all encounters identified by the cohort table input and an additional derived field disability (logical) indicating whether any diagnosis code for a disability was identified. If a genc_id does not have any entry in the diagnosis table at all, disability = NA. Note that this is very rare: If no additional filtering was performed, >99.9% of genc_ids should have an entry in the ipdiagnosis (and >99.9% of genc_ids that were admitted via ER should have an entry in the erdiagnosis table).

If component_wise == TRUE, will only return genc_ids with a disability. The output is returned in long format, where each row corresponds to a disability diagnosis (diagnosis_code) and its corresponding disability_category (character).

Notes

This function does not differentiate between diagnosis types. That is, the disability flags are derived based on all diagnosis codes that are provided as input to this function. By default, users should include all diagnosis types to identify disabilities. However, if users wish to include only certain diagnosis types (e.g., type-M for most responsible discharge diagnosis), the ipdiag and erdiag input tables should be filtered accordingly based on diagnosis_type prior to running this function (for more details, see CIHI diagnosis type definitions.

References

Brown HK, et al. JAMA Netw Open, 2021. https://doi.org/10.1001/jamanetworkopen.2020.34993

Examples

if (FALSE) { # \dontrun{
drv <- dbDriver("PostgreSQL")
dbcon <- DBI::dbConnect(drv,
  dbname = "db",
  host = "domain_name.ca",
  port = 1234,
  user = getPass("Enter user:"),
  password = getPass("password")
)

ipadmdad <- dbGetQuery(dbcon, "select * from admdad") %>% data.table()
ipdiagnosis <- dbGetQuery(dbcon, "select * from ipdiagnosis") %>% data.table()
erdiagnosis <- dbGetQuery(db, "select * from erdiagnosis") %>% data.table()

# including ER diagnosis codes
disability(cohort = ipadmdad, ipdiag = ipdiagnosis, erdiag = erdiagnosis)

# not including ER diagnosis codes
disability(cohort = ipadmdad, ipdiag = ipdiagnosis, erdiag = NULL)

# returning component-wise disability categories
disability(ipadmdad, ipdiagnosis, erdiagnosis, component_wise = TRUE)
} # }