A package for convenient downloading fhir resources in xml format and converting to R data frames
This project is maintained by POLAR-fhiR
fhircrackr is a package designed to help analyzing HL7 FHIR1
resources.
FHIR stands for Fast Healthcare Interoperability Resources and is a standard describing data formats and elements (known as “resources”) as well as an application programming interface (API) for exchanging electronic health records. The standard was created by the Health Level Seven International (HL7) health-care standards organization. For more information on the FHIR standard, visit https://www.hl7.org/fhir/.
While FHIR is a very useful standard to describe and exchange medical data in an interoperable way, it is not at all useful for statistical analyses of data. This is due to the fact that FHIR data is stored in many nested and interlinked resources instead of matrix-like structures.
Thus, to be able to do statistical analyses a tool is needed that allows converting these nested resources into data frames. This process of tabulating FHIR resources is not trivial, as the unpredictable degree of nesting and connectedness of the resources makes generic solutions to this problem not feasible.
We therefore implemented a package that makes it possible to download FHIR resources from a server into R and to tabulate these resources into (multiple) data frames.
The package is still under development. The CRAN version of the package
contains all functions that are already stable, for more recent (but
potentially unstable) developments, the development version of the
package can be downloaded from GitHub using
devtools::install_github("POLAR-fhiR/fhircrackr").
This vignette is an introduction on the basic functionalities of the
fhircrackr and should give you a broad overview over what the package
can do. For more detailed instructions on each subtopic please have a
look the other vignettes. This introduction covers the following topics:
Prerequisites
Downloading resources from a FHIR server
Flattening resources
Multiple entries
Saving and loading downloaded bundles
The complexity of the problem requires a couple of prerequisites both
regarding your knowledge and access to data. We will shortly list the
preconditions for using the fhircrackr package here:
First of all, you need the base URL of the FHIR server you want to
access. If you don’t have your own FHIR server, you can use one of
the available public servers, such as https://hapi.fhir.org/baseR4
or http://fhir.hl7.de:8080/baseDstu3. The base URL of a FHIR
server is often referred to as [base].
To download resources from the server, you should be familiar with
FHIR
search requests. FHIR search allows you to download sets of
resources that match very specific requirements. The fhircrackr
package offers some help building FHIR search requests, for this
please see the vignette on downloading FHIR resources.
In the first step, fhircrackr downloads the resources in xml
format into R. To specify which elements from the FHIR resources you
want in your data frame, you should have at least some familiarity
with XPath expressions. A good tutorial on XPath expressions can be
found here:
https://www.w3schools.com/xml/xpath_intro.asp.
In the following we’ll go through a typical workflow with fhircrackr
step by step. The first and foremost step is of course, to install and
load the package:
install.packages("fhircrackr")
library(fhircrackr)
To download resources from a FHIR server, you need to send a FHIR search
request using fhir_search(). This introduction will not go into the
details of building a valid FHIR search request. For that, please see
the vignette on downloading FHIR resources or have a look at
?fhir_url. Here we will use a simple example of downloading all
Patient resources from a public HAPI server:
request <- fhir_url(url = "http://fhir.hl7.de:8080/baseDstu3", resource = "Patient")
patient_bundles <- fhir_search(request = request, max_bundles = 2, verbose = 0)
The minimum information fhir_search() requires is a url containing the
full FHIR search request in the argument request which you can build
by a call to fhir_url() or by providing an explicit string. In
general, a FHIR search request returns a bundle of the resources you
requested. If there are a lot of resources matching your request, the
search result isn’t returned in one big bundle but distributed over
several of them. If the argument max_bundles is set to its default
Inf, fhir_search() will return all available bundles, meaning all
resources matching your request. If you set it to 2 as in the example
above, the download will stop after the first two bundles. Note that in
this case, the result may not contain all the resources from the
server matching your request.
If you want to connect to a FHIR server that uses basic authentication,
you can supply the arguments username and password. If your server
uses some form of bearer token authorization, you can supply the token
in the argument token.
As you can see in the next block of code, fhir_search() returns a
fhir_bundle_list object, which is basically a list of xml objects
where each list element represents one bundle of resources, so a list of
two xml objects in our case:
length(patient_bundles)
#> [1] 2
patient_bundles
#> An object of class "fhir_bundle_list"
#> [[1]]
#> A fhir_bundle_xml object
#> No. of entries : 20
#> Self Link: http://hapi.fhir.org/baseR4/Patient
#> Next Link: http://hapi.fhir.org/baseR4?_getpages=ce958386-53d0-4042-888c-cad53bf5d5a1 ...
#>
#> {xml_node}
#> <Bundle>
#> [1] <id value="ce958386-53d0-4042-888c-cad53bf5d5a1"/>
#> [2] <meta>\n <lastUpdated value="2021-05-10T12:12:43.317+00:00"/>\n</meta>
#> [3] <type value="searchset"/>
#> [4] <link>\n <relation value="self"/>\n <url value="http://hapi.fhir.org/b ...
#> [5] <link>\n <relation value="next"/>\n <url value="http://hapi.fhir.org/b ...
#> [6] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837602"/ ...
#> [7] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/example-r ...
#> [8] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837624"/ ...
#> [9] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837626"/ ...
#> [10] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837631"/ ...
#> [11] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837716"/ ...
#> [12] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837720"/ ...
#> [13] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837714"/ ...
#> [14] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837721"/ ...
#> [15] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837722"/ ...
#> [16] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837723"/ ...
#> [17] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837724"/ ...
#> [18] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/cfsb16116 ...
#> [19] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837736"/ ...
#> [20] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837737"/ ...
#> ...
#>
#> [[2]]
#> A fhir_bundle_xml object
#> No. of entries : 20
#> Self Link: http://hapi.fhir.org/baseR4?_getpages=ce958386-53d0-4042-888c-cad53bf5d5a1 ...
#> Next Link: http://hapi.fhir.org/baseR4?_getpages=ce958386-53d0-4042-888c-cad53bf5d5a1 ...
#>
#> {xml_node}
#> <Bundle>
#> [1] <id value="ce958386-53d0-4042-888c-cad53bf5d5a1"/>
#> [2] <meta>\n <lastUpdated value="2021-05-10T12:12:43.317+00:00"/>\n</meta>
#> [3] <type value="searchset"/>
#> [4] <link>\n <relation value="self"/>\n <url value="http://hapi.fhir.org/b ...
#> [5] <link>\n <relation value="next"/>\n <url value="http://hapi.fhir.org/b ...
#> [6] <link>\n <relation value="previous"/>\n <url value="http://hapi.fhir.o ...
#> [7] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837760"/ ...
#> [8] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837766"/ ...
#> [9] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837768"/ ...
#> [10] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837781"/ ...
#> [11] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837783"/ ...
#> [12] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837784"/ ...
#> [13] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837787"/ ...
#> [14] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837788"/ ...
#> [15] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837789"/ ...
#> [16] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837790"/ ...
#> [17] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837791"/ ...
#> [18] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837792"/ ...
#> [19] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837793"/ ...
#> [20] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837794"/ ...
#> ...
If for some reason you cannot connect to a FHIR server at the moment but
want to explore the following functions anyway, the package provides two
example lists of bundles containing Patient and MedicationStatement
resources. See ?patient_bundles and ?medication_bundles for how to
use them.
Now we know that inside these xml objects there is the patient data
somewhere. To bring it into a tabular format, we will use fhir_crack()
which creates one table per resource type requested in the design
argument. The most important argument fhir_crack() takes is bundles,
the list of bundles that is returned by fhir_search(). The second
important argument is design, an object that tells the function which
data to extract from the bundle and how. fhir_crack() returns (a list
of) data.frames or data.tables (if argument data.table = TRUE).
The object that is passed to the design argument can be of class
fhir_table_description or fhir_design. A fhir_table_description is
used when you want to extract just one resource type, resulting in a
single table. A fhir_design is basically a named list of
fhir_table_descriptions and is used when you want to extract several
resource types at once, resulting in a named list of tables.
The details of what the different elements of a fhir_table_description
or fhir_design mean are described in the vignette on flattening
resources. Please refer to this document for more information, as we
will just use one simple example here.
#define table_description
table_description <- fhir_table_description(
resource = "Patient",
cols = c(
id = "id",
use_name = "name/use",
given_name = "name/given",
family_name = "name/family",
gender = "gender",
birthday = "birthDate"
),
sep = " ~ ",
brackets = c("<<", ">>"),
rm_empty_cols = FALSE,
format = 'compact',
keep_attr = FALSE
)
#have a look
table_description
#> A fhir_table_description with the following elements:
#>
#> resource: Patient
#>
#> cols:
#> ------------ -----------------
#> column name | xpath expression
#> ------------ -----------------
#> id | id
#> use_name | name/use
#> given_name | name/given
#> family_name | name/family
#> gender | gender
#> birthday | birthDate
#> ------------ -----------------
#>
#> sep: ' ~ '
#> brackets: '<<', '>>'
#> rm_empty_cols: FALSE
#> format: 'compact'
#> keep_attr: FALSE
Each of the five style elements sep, brackets,
remove_empty_columns, format and keep_attr in table_description
can also be controlled directly by the argument of the same name of
fhir_crack(). If one of these function arguments is NULL (the
default value for each argument), the corresponding value specified from
the table_description will be used. If the argument in fhir_crack is
set, the corresponding value in fhir_table_description will be
overruled. If both the fhir_crack function argument and the
corresponding component in fhir_table_description are NULL, the
respective default value (sep = ':::', brackets = NULL,
rm_empty_cols = TRUE, format = 'compact', keep_attr = FALSE) will
be applied.
After it is defined, the fhir_table_description can be used in
fhir_crack() like this:
#flatten resources
patients <- fhir_crack(bundles = patient_bundles, design = table_description, verbose = 0)
#have look at the results
head(patients)
#> id use_name
#> 1 <<1>>2072744 <<1.1>>official
#> 2 <<1>>2431578 <<1.1>>official
#> 3 <<1>>2431568 <<1.1>>official ~ <<2.1>>usual ~ <<3.1>>maiden
#> 4 <<1>>2431577 <<1.1>>official
#> 5 <<1>>2431757 <<1.1>>old
#> 6 <<1>>2431759 <<1.1>>official
#> given_name
#> 1 <<1.1>>K ~ <<1.2>>Kari
#> 2 <<1.1>>Roman
#> 3 <<1.1>>Peter ~ <<1.2>>James ~ <<2.1>>Jim ~ <<3.1>>Peter ~ <<3.2>>James
#> 4 <<1.1>>Ganpat ~ <<1.2>>Malekar
#> 5 <NA>
#> 6 <<1.1>>ABC
#> family_name gender birthday
#> 1 <<1.1>>Nordmann <<1>>female <<1>>2018-09-12
#> 2 <<1.1>>Smith <<1>>male <<1>>2021-07-19
#> 3 <<1.1>>Chalmers ~ <<3.1>>Windsor <<1>>male <<1>>1974-12-25
#> 4 <<1.1>>Malekar <<1>>male <<1>>1996-02-07
#> 5 <<1.1>>murali <<1>>male <NA>
#> 6 <<1.1>>XYZ <<1>>male <<1>>1998-01-03
A particularly complicated problem in flattening FHIR resources is caused by the fact that there can be multiple occurrences of the same FHIR element within one resource. For a more detailed description of this problem, please see the vignette on flattening resources.
In general, fhir_crack() will paste multiple entries for the same
attribute together in the table, using the separator provided by the
sep argument.
Let’s have a look at the following simple example, where we have a
bundle containing just two Patient resources. The example is part of the
fhircrackr package and you can make it available like this:
bundles <- fhir_unserialize(bundles = example_bundles1)
This represents a bundle list with only one very simple bundle of just two Patient resources which looks like this:
<Bundle>
<Patient>
<id value='id1'/>
<address>
<use value='home'/>
<city value='Amsterdam'/>
<type value='physical'/>
<country value='Netherlands'/>
</address>
<name>
<given value='Marie'/>
</name>
</Patient>
<Patient>
<id value='id3'/>
<address>
<use value='home'/>
<city value='Berlin'/>
</address>
<address>
<type value='postal'/>
<country value='France'/>
</address>
<address>
<use value='work'/>
<city value='London'/>
<type value='postal'/>
<country value='England'/>
</address>
<name>
<given value='Frank'/>
</name>
<name>
<given value='Max'/>
</name>
</Patient>
</Bundle>
The first resource has just one entry for the address attribute. The second Patient resource has an address attribute with three entries containing different elements and also two entries for the name attribute.
This is where the style elements of the table_description comes into
play:
table_description <- fhir_table_description(
resource = "Patient",
brackets = c("[", "]"),
sep = " | ",
rm_empty_cols = FALSE,
format = 'compact',
keep_attr = FALSE
)
df <- fhir_crack(bundles = bundles, design = table_description, verbose = 0)
df
#> address.city address.country
#> 1 [1.1]Amsterdam [1.1]Netherlands
#> 2 [1.1]Berlin | [3.1]London [2.1]France | [3.1]England
#> address.type address.use id name.given
#> 1 [1.1]physical [1.1]home [1]id1 [1.1]Marie
#> 2 [2.1]postal | [3.1]postal [1.1]home | [3.1]work [1]id3 [1.1]Frank | [2.1]Max
Multiple entries are pasted together with the specified separator string
(in this case: " | ") in between and the indices (inside the specified
bracket strings (here: "[" and "]")) display the entry the value
belongs to. That way you can see that Patient resource 2 had three
entries for the attribute address and you can also see which
attributes belong to which entry.
If you know beforehand that you only need home addresses, you can use predicates in your XPath expressions that filter for that and avoid multiple entries in your table:
table_description <- fhir_table_description(
resource = "Patient",
cols = c(
id = "id",
city = "address[use[@value='home']]/city",
type = "address[use[@value='home']]/type",
country = "address[use[@value='home']]/country",
name = "name/given"
)
)
df_filtered <- fhir_crack(bundles = bundles, design = table_description, verbose = 0)
df_filtered
#> id city type country name
#> 1 id1 Amsterdam physical Netherlands Marie
#> 2 id3 Berlin <NA> <NA> Frank:::Max
If you can’t filter during cracking, there are several options to deal with the resulting multiple entries in your table.
If the table produced by fhir_crack() contains multiple entries,
you’ll probably want to divide these entries into distinct observations
at some point. This is where fhir_melt() comes into play.
fhir_melt() takes an indexed table with multiple entries in one or
several columns and spreads (aka melts) these entries over several
rows.
fhir_melt(
indexed_data_frame = df,
columns = "address.city",
brackets = c("[", "]"),
sep = " | ",
all_columns = FALSE
)
#> resource_identifier address.city
#> 1 1 [1]Amsterdam
#> 2 2 [1]Berlin
#> 3 2 <NA>
#> 4 2 [1]London
The new variable resource_identifier maps which rows in the created
table belong to which row (usually equivalent to one resource) in the
original table. brackets and sep have to be the same character
vectors that have been used to build the indices with fhir_crack().
columns is a character vector with the names of the variables/columns
you want to melt. You can provide more than one column here but it makes
sense to only have variables from the same repeating attribute together
in one call to fhir_melt():
cols <- c("address.city", "address.use", "address.type", "address.country")
fhir_melt(
indexed_data_frame = df,
columns = cols,
brackets = c("[", "]"),
sep = " | ",
all_columns = FALSE
)
#> resource_identifier address.city address.use address.type address.country
#> 1 1 [1]Amsterdam [1]home [1]physical [1]Netherlands
#> 2 2 [1]Berlin [1]home <NA> <NA>
#> 3 2 <NA> <NA> [1]postal [1]France
#> 4 2 [1]London [1]work [1]postal [1]England
With the argument all_columns you can control whether the resulting
table contains only the molten columns or all columns of the original
table:
molten <- fhir_melt(
indexed_data_frame = df,
columns = cols,
brackets = c("[", "]"),
sep = " | ",
all_columns = TRUE
)
molten
#> address.city address.country address.type address.use id
#> 1 [1]Amsterdam [1]Netherlands [1]physical [1]home [1]id1
#> 2 [1]Berlin <NA> <NA> [1]home [1]id3
#> 3 <NA> [1]France [1]postal <NA> [1]id3
#> 4 [1]London [1]England [1]postal [1]work [1]id3
#> name.given resource_identifier
#> 1 [1.1]Marie 1
#> 2 [1.1]Frank | [2.1]Max 2
#> 3 [1.1]Frank | [2.1]Max 2
#> 4 [1.1]Frank | [2.1]Max 2
Values on the other variables will just repeat in the newly created rows. For more information please see the vignette on flattening resources.
Once you have sorted out the multiple entries, you might want to get rid
of the indices in your data frame. This can be achieved using
fhir_rm_indices():
fhir_rm_indices(indexed_data_frame = molten, brackets = c("[", "]"))
#> address.city address.country address.type address.use id name.given
#> 1 Amsterdam Netherlands physical home id1 Marie
#> 2 Berlin <NA> <NA> home id3 Frank | Max
#> 3 <NA> France postal <NA> id3 Frank | Max
#> 4 London England postal work id3 Frank | Max
#> resource_identifier
#> 1 1
#> 2 2
#> 3 2
#> 4 2
Again, brackets should be given the same character vector that was
used for fhir_crack() and fhir_melt() respectively.
Since fhir_crack() ignores all data that are not specified in
design, it makes sense to store the original search result for
reproducibility and in case you realize later on that you need elements
from the resources that you haven’t extracted at first.
There are two ways of saving the FHIR bundles you downloaded: Either you save them as R objects, or you write them to an xml file.
If you want to save the list of downloaded bundles as an .rda or
.RData file, you can’t just use R’s save() or save_image() on it,
because this will break the external pointers in the xml objects
representing your bundles. Instead, you have to serialize the bundles
before saving and unserialize them after loading. For single xml objects
the package xml2 provides serialization functions. For convenience,
however, fhircrackr provides the functions fhir_serialize() that can
be used directly on the bundles returned by fhir_search() and
fhir_unserialize():
#serialize bundles
serialized_bundles <- fhir_serialize(bundles = patient_bundles)
#have a look at them
head(serialized_bundles[[1]])
#> [1] 58 0a 00 00 00 03
#create temporary directory for saving
temp_dir <- tempdir()
#save
saveRDS(serialized_bundles, file = paste0(temp_dir, "/bundles.rda"))
If you reload this bundle, you have to unserialize it before you can work with it:
#load bundles
serialized_bundles_reloaded <- readRDS(paste0(temp_dir, "/bundles.rda"))
#unserialize
bundles <- fhir_unserialize(bundles = serialized_bundles_reloaded)
#have a look
bundles
#> An object of class "fhir_bundle_list"
#> [[1]]
#> A fhir_bundle_xml object
#> No. of entries : 20
#> Self Link: http://hapi.fhir.org/baseR4/Patient
#> Next Link: http://hapi.fhir.org/baseR4?_getpages=ce958386-53d0-4042-888c-cad53bf5d5a1 ...
#>
#> {xml_node}
#> <Bundle>
#> [1] <id value="ce958386-53d0-4042-888c-cad53bf5d5a1"/>
#> [2] <meta>\n <lastUpdated value="2021-05-10T12:12:43.317+00:00"/>\n</meta>
#> [3] <type value="searchset"/>
#> [4] <link>\n <relation value="self"/>\n <url value="http://hapi.fhir.org/b ...
#> [5] <link>\n <relation value="next"/>\n <url value="http://hapi.fhir.org/b ...
#> [6] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837602"/ ...
#> [7] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/example-r ...
#> [8] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837624"/ ...
#> [9] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837626"/ ...
#> [10] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837631"/ ...
#> [11] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837716"/ ...
#> [12] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837720"/ ...
#> [13] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837714"/ ...
#> [14] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837721"/ ...
#> [15] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837722"/ ...
#> [16] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837723"/ ...
#> [17] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837724"/ ...
#> [18] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/cfsb16116 ...
#> [19] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837736"/ ...
#> [20] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837737"/ ...
#> ...
#>
#> [[2]]
#> A fhir_bundle_xml object
#> No. of entries : 20
#> Self Link: http://hapi.fhir.org/baseR4?_getpages=ce958386-53d0-4042-888c-cad53bf5d5a1 ...
#> Next Link: http://hapi.fhir.org/baseR4?_getpages=ce958386-53d0-4042-888c-cad53bf5d5a1 ...
#>
#> {xml_node}
#> <Bundle>
#> [1] <id value="ce958386-53d0-4042-888c-cad53bf5d5a1"/>
#> [2] <meta>\n <lastUpdated value="2021-05-10T12:12:43.317+00:00"/>\n</meta>
#> [3] <type value="searchset"/>
#> [4] <link>\n <relation value="self"/>\n <url value="http://hapi.fhir.org/b ...
#> [5] <link>\n <relation value="next"/>\n <url value="http://hapi.fhir.org/b ...
#> [6] <link>\n <relation value="previous"/>\n <url value="http://hapi.fhir.o ...
#> [7] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837760"/ ...
#> [8] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837766"/ ...
#> [9] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837768"/ ...
#> [10] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837781"/ ...
#> [11] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837783"/ ...
#> [12] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837784"/ ...
#> [13] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837787"/ ...
#> [14] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837788"/ ...
#> [15] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837789"/ ...
#> [16] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837790"/ ...
#> [17] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837791"/ ...
#> [18] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837792"/ ...
#> [19] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837793"/ ...
#> [20] <entry>\n <fullUrl value="http://hapi.fhir.org/baseR4/Patient/1837794"/ ...
#> ...
After unserialization, the pointers are restored and you can continue to
work with the bundles. Note that the example bundles
medication_bundles and patient_bundles that are provided with the
fhircrackr package are also provided in their serialized form and have
to be unserialized as described on their help page.
If you want to store the bundles in xml files instead of R objects, you
can use the functions fhir_save() and fhir_load(). fhir_save()
takes a list of bundles in form of xml objects (as returned by
fhir_search()) and writes them into the directory specified in the
argument directory. Each bundle is saved as a separate xml-file. If
the folder defined in directory doesn’t exist, it is created in the
current working directory.
#save bundles as xml files
fhir_save(bundles = patient_bundles, directory = temp_dir)
To read bundles saved with fhir_save() back into R, you can use
fhir_load():
bundles <- fhir_load(directory = temp_dir)
fhir_load() takes the name of the directory (or path to it) as its
only argument. All xml-files in this directory are read into R and
returned as a list of bundles in xml format just as returned by
fhir_search().
This work was carried out by the SMITH consortium and the cross-consortium use case POLAR_MI; both are part of the German Initiative for Medical Informatics and funded by the German Federal Ministry of Education and Research (BMBF), grant no. 01ZZ1803A , 01ZZ1803C and 01ZZ1910A.
FHIR is the registered trademark of HL7 and is used with the permission of HL7. Use of the FHIR trademark does not constitute endorsement of this product by HL7 ↩