extract_entities_tapering: Extract Medication Entities From Phrase - Extension of...

In medExtractR: Extraction of Medication Information from Clinical Text

Extract Medication Entities From Phrase - Extension of extract_entities for Tapering application

Description

This function searches a phrase for medication dosing entities of interest. It is called within medExtractR_tapering and generally not intended for use outside that function.

Usage

extract_entities_tapering(
  phrase,
  p_start,
  d_stop,
  unit,
  frequency_fun = NULL,
  intaketime_fun = NULL,
  duration_fun = NULL,
  route_fun = NULL,
  doseschedule_fun = NULL,
  preposition_fun = NULL,
  timekeyword_fun = NULL,
  transition_fun = NULL,
  dosechange_fun = NULL,
  strength_sep = NULL,
  ...
)

Arguments

phrase	Text to search.
p_start	Start position of phrase within original text.
d_stop	End position of drug name within original text.
unit	Unit of measurement for medication strength, e.g., ‘mg’.
frequency_fun	Function used to extract frequency.
intaketime_fun	Function used to extract intake time.
duration_fun	Function used to extract duration.
route_fun	Function used to extract route.
doseschedule_fun	Function used to extract dose schedule.
preposition_fun	Function used to extract preposition.
timekeyword_fun	Function used to extract time keyword.
transition_fun	Function used to extract transition.
dosechange_fun	Function used to extract dose change.
strength_sep	Delimiter for contiguous medication strengths.
...	Parameter settings used in extracting frequency and intake time, including additional arguments to frequency_fun and intaketime_fun. Use frequency_dict to identify custom frequency dictionaries and intaketime_dict to identify custom intake time dictionaries. Similarly, for all other entities with a corresponding <entity>_fun, a custom dictionary can be supplied with the argument <entity>_dict.

Details

Various medication dosing entities are extracted within this function including the following:

strength: The amount of drug in a given dosage form (i.e., tablet, capsule).
dose amount: The number of tablets, capsules, etc. taken at a given intake time.
dose strength: The total amount of drug given intake. This quantity would be equivalent to strength x dose amount, and appears similar to strength when dose amount is absent.
frequency: The number of times per day a dose is taken, e.g., “once daily” or ‘2x/day’.
intaketime: The time period of the day during which a dose is taken, e.g., ‘morning’, ‘lunch’, ‘in the pm’.
duration: How long a patient is on a drug regimen, e.g., ‘2 weeks’, ‘mid-April’, ‘another 3 days’.
route: The administration route of the drug, e.g., ‘by mouth’, ‘IV’, ‘topical’.
dose change: Whether the dosage of the drug was changed, e.g., ‘increase’, ‘adjust’, ‘reduce’.
dose schedule: Keywords which represent special dosing regimens, such as tapering schedules, alternating doses, or stopping keywords, e.g., ‘weaning’, ‘even days’ or ‘odd_days’, ‘discontinue’.
time keyword: Whether the dosing regimen is a past dose, current dose, or future dose, e.g., ‘currently’, ‘remain’, ‘yesterday’.
transition: Words or symbols that link consecutive doses of a tapering regimen, e.g., ‘then’, ‘followed by’, or a comma ‘,’.
preposition: Prepositions that occur immediately next to another identified entity, e.g., ‘to’, ‘until’, ‘for’.
dispense amount: The number of pills prescribed to the patient.
refill: The number of refills allowed for the patient's prescription.

Similar to the basic implementation, drug name and and time of last dose are not handled by the extract_entities_tapering function. Those entities are extracted separately and appended to the extract_entities_tapering output within the main medExtractR_tapering function. In the tapering extension, however, dose change is treated the same as other dictionary-based entities and extracted within extract_entities_tapering. Strength, dose amount, dose strength, dispense amount, and refill are primarily numeric quantities, and are identified using a combination of regular expressions and rule-based approaches. All other entities use dictionaries for identification. For more information about the default dictionary for a specific entity, view the documentation file for the object <entity>_vals.

By default and when an argument <entity>_fun is NULL, the extract_generic function will be used to extract that entity. This function can also inherit user-defined entity dictionaries for each entity, supplied as arguments <entity>_dict to medExtractR or medExtractR_tapering (see documentation files for main function(s) for details).

Note that extract_entities_tapering has the argument d_stop. This differs from extract_entities, which uses the end position of the full search window. This is a consequence of medExtractR using a fixed search window length and medExtractR_tapering dynamically constructing a search window.

Value

data.frame with entities information. At least one row per entity is returned, using NA when no expression was found for a given entity.
The “entity” column of the output contains the formatted label for that entity, according to the following mapping.
strength: “Strength”
dose amount: “DoseAmt”
dose strength: “DoseStrength”
frequency: “Frequency”
intake time: “IntakeTime”
duration: “Duration”
route: “Route”
dose change: “DoseChange”
dose schedule: “DoseScheule”
time keyword: “TimeKeyword”
transition: “Transition”
preposition: “Preposition”
dispense amount: “DispenseAmt”
refill: “Refill”
Sample output for the phrase “Lamotrigine 200mg bid for 14 days” would look like:

entity	expr
IntakeTime	<NA>
Strength	<NA>
DoseAmt	<NA>
DoseChange	<NA>
DoseSchedule	<NA>
TimeKeyword	<NA>
Transition	<NA>
Preposition	<NA>
DispenseAmt	<NA>
Refill	<NA>
Frequency	bid;19:22
DoseStrength	200mg;13:18
Preposition	for;23:26
Duration	14 days;27:34

Examples

note <- "prednisone 20mg daily tapering to 5mg daily over 2 weeks"
extract_entities_tapering(note, 1, 11, "mg")
# A user-defined dictionary can be used instead of the default
my_dictionary <- data.frame(c("daily", "twice daily"))
extract_entities(note, 1, 11, "mg", frequency_dict = my_dictionary)

medExtractR documentation built on June 7, 2022, 1:08 a.m.