orders

A dataset containing 59 blood culture orders for 27 unique synthetic
 patients. There is only 1 order for blood cultures. Patient-level sampling
 rate, mean numeric value, standard deviation, and number of measurements
 per patient follow patterns observed in real electronic health record data.
 This dataset is included to demonstrate sepsis identification.

datasets

Examine any number of time series data frames to identify
instances in which various criteria are met within specified time
frames. In clinical medicine, these types of events are often
called "constellations of signs and symptoms", because a single
condition depends on a series of events occurring within a certain
amount of time of each other. This package was written to work with
any number of time series data frames and is optimized for speed
to work well with data frames with millions of rows.

Mark Sendak

constellation

Identify Event Sequences Using Time Series Joins

orders function

A data frame with 59 rows and 3 variables:<dl class="dl-horizontal">
 <dt>PAT_ID</dt><dd>patient identification number, randomly generated integer</dd>
 <dt>ORDER_TIME</dt><dd>order datetime of blood culture, character</dd>
 <dt>VARIABLE</dt><dd>categorical variable specifying the blood culture order
 name, character</dd>
</dl>

Format

Synthesized blood culture orders for cohort of 100 synthetic patients — orders

A data frame with 59 rows and 3 variables:<dl class='dl-horizontal'>
 <dt>PAT_ID</dt><dd>patient identification number, randomly generated integer</dd>
 <dt>ORDER_TIME</dt><dd>order datetime of blood culture, character</dd>
 <dt>VARIABLE</dt><dd>categorical variable specifying the blood culture order
 name, character</dd>
</dl>

orders: Synthesized blood culture orders for cohort of 100 synthetic patients

Description

Usage

Arguments

Format

Examples