Accessing-FHIR-resources.ipynb•183 kB
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"# Accessing FHIR resources\n",
"\n",
"This tutorial shows two ways to access FHIR resources from a FHIR server set up with InterSystems IRIS-Health, the first using the Python package fhirpy and the second using HTTP requests. I recommend using the first (fhirpy) and the tutorial goes into much more detail here. However, if you are very familiar using HTTP requests or want to access from another application that supports HTTP requests, feel free to refer to the second method. \n",
"\n",
"Finally - note that for population level data, you might be better off creating relational tables based on the FHIR data. Lucky for you, the main demo includes a [tutorial](../Tutorial/1-Using-FHIR-SQL-Builder.ipynb) on how to do this. \n",
"\n",
"**For this tutorial, I am assuming you have set up the FHIR Server using the iris-fhir-template on github, as shown in the [main demo](../Tutorial/0-FHIR-Server-setup.md)** - There are other ways to set up a FHIR server and feel free to use them, you will just have to check the FHIR server location (URL) and system credentials.\n",
"\n",
"## Using fhirpy\n",
"\n",
"fhirpy can be installed through PyPI (`pip install fhirpy`) but hopefully it should have already been installed with the requirements.txt. \n",
"\n",
"fhirpy can be used synchronously (`SyncFHIRClient`) or asynchronously (`AyncFHIRClient`), don't worry too much about this unless you have a reason to work asynchronously. \n",
"\n",
"The steps for using fhirpy can be roughly broken down into: \n",
"1. Create link to server\n",
"2. Search for resource(s)\n",
"3. Parse data"
]
},
{
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"source": [
"#### Import Dependencies"
]
},
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"source": [
"from fhirpy import SyncFHIRClient, AsyncFHIRClient ## Used for created a link to the FHIR server\n",
"import base64 # Used for encoding the credentials"
]
},
{
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"source": [
"### Create link to Server\n",
"This creates a bridge to the client server allowing us to query the FHIR server and fetch resources using [fhirpy](https://pypi.org/project/fhirpy/) methods. This bridge means we don't have to keep typing out the server location or authorisation, we can just repeatedly query the client bridge created."
]
},
{
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"source": [
"#### Encode credentials \n",
"Note that this method is vulnerable and should be replaced with a more secure method in production code."
]
},
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"username = \"_SYSTEM\"\n",
"password = \"ISCDEMO\"\n",
"credentials = f\"{username}:{password}\".encode(\"utf-8\")\n",
"encoded = base64.b64encode(credentials).decode(\"utf-8\")"
]
},
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"source": [
"## Create client using the server location - in our case it is locally on port 32783, and authorization using our encoded credentials. \n",
"client = SyncFHIRClient(\"http://localhost:32783/csp/healthshare/demo/fhir/r4/\", authorization= f\"Basic {encoded}\")"
]
},
{
"cell_type": "markdown",
"id": "fceedc25-b5f4-4bfa-ba25-eadc230b5f88",
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"source": [
"### Example Query\n",
"\n",
"To get a specific type of resource, we can query the resource endpoint using `client.resources({resource_type_endpoint})` method. For example: "
]
},
{
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"execution_count": 4,
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"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[<SyncFHIRResource Patient/4>, <SyncFHIRResource Patient/3>, <SyncFHIRResource Patient/41>, <SyncFHIRResource Patient/45>, <SyncFHIRResource Patient/65>, <SyncFHIRResource Patient/32>]\n",
"\n",
"\n",
"The query has returned 6 patient resources\n",
"\n"
]
}
],
"source": [
"resources= client.resources(\"Patient\").fetch()\n",
"print(resources)\n",
"print(f'\\n\\nThe query has returned {len(resources)} patient resources\\n')"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "e8bf224a-0006-4e08-b2b1-4e6963dbff90",
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{
"name": "stdout",
"output_type": "stream",
"text": [
"[{'use': 'official', 'family': 'Hoeger474', 'given': ['Aurora248']}]\n",
"[{'use': 'official', 'family': 'Ziemann98', 'given': ['Alisia5'], 'prefix': ['Mrs.']}, {'use': 'maiden', 'family': 'Dietrich576', 'given': ['Alisia5'], 'prefix': ['Mrs.']}]\n",
"[{'use': 'official', 'family': 'Wolff180', 'given': ['Miquel905'], 'prefix': ['Mr.']}]\n",
"[{'use': 'official', 'family': 'Jacobson885', 'given': ['Lakita48'], 'prefix': ['Mrs.']}, {'use': 'maiden', 'family': 'Bartell116', 'given': ['Lakita48'], 'prefix': ['Mrs.']}]\n",
"[{'use': 'official', 'family': 'Spinka232', 'given': ['Sherry479'], 'prefix': ['Mrs.']}, {'use': 'maiden', 'family': 'Windler79', 'given': ['Sherry479'], 'prefix': ['Mrs.']}]\n",
"[{'use': 'official', 'family': 'Lemke', 'given': ['Tish'], 'prefix': ['Mrs.']}, {'use': 'maiden', 'family': 'Johnston', 'given': ['Tish'], 'prefix': ['Mrs.']}]\n"
]
}
],
"source": [
"for resource in resources:\n",
" print(resource.name)"
]
},
{
"cell_type": "markdown",
"id": "2f8ace88-c009-4381-a7d3-d712a8b6c4f5",
"metadata": {},
"source": [
"### Adding search parameters\n",
"We can add search parameters into our fetch methods, for example if we want to find a specific patient we could query by their first name:"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "0956aa86-4fd7-474c-9a04-255dae567f3d",
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{
"name": "stdout",
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"text": [
"45 ['Lakita48'] Jacobson885\n"
]
}
],
"source": [
"lakita = client.resources(\"Patient\").search(name=\"Lakita\").fetch()\n",
"if len(lakita)==1: \n",
" lakita = lakita[0]\n",
"print(lakita.id, lakita.name[0].given, lakita.name[0].family)"
]
},
{
"cell_type": "markdown",
"id": "55d3b128-dcd2-4649-8080-5c7f6b4a8061",
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"source": [
"You can see that this is a fuzzy search - neither of the results are of a man called John - instead patient 12724 has the surname \"Johns\" and patient 25319 has the maiden surname \"Johnson\".\n",
"\n",
"We could be more specific in our original search:"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "b8e6add8-99dc-444d-b5a0-1aa76ba7c86f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[<SyncFHIRResource Patient/32>]\n"
]
}
],
"source": [
"tish = client.resources(\"Patient\").search(family=\"Lemke\", given=\"Tish\", birthDate=\"1975-05-26\").fetch()\n",
"print(tish)"
]
},
{
"cell_type": "markdown",
"id": "6da37e32-d0ad-48b9-901c-7f77e9c8a4ae",
"metadata": {},
"source": [
"We can add many search parameters to our search which we will come across later on. For every resource type, there is a list of search parameters on the FHIR documentation pages, for example, we can access [patient search parameters](https://build.fhir.org/patient-search.html). \n",
"\n",
"Lets see if any of our *fictional* patients are deceased:"
]
},
{
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"id": "c99014c6-31ca-448e-9ed7-ade2e9b8ce50",
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{
"data": {
"text/plain": [
"[]"
]
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],
"source": [
"deceased = client.resources(\"Patient\").search(deceased=True).fetch()\n",
"deceased"
]
},
{
"cell_type": "markdown",
"id": "7a504824-27ff-4772-a4b5-de775917ea5a",
"metadata": {},
"source": [
"See how we can add search parameters to improve our search? For now though, lets return to the patient we found earlier and find out a bit more about her. \n",
"\n",
"Our searches have so far returned lists of resources that match, even if there is only one match. For simplicity, I am going to extract the patient resource from the list of matches:"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "2cdefb40-dd72-4ed1-a02d-4c1a856d8113",
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"outputs": [],
"source": [
"tish = tish[0] # set tish to be the first (and only) resource returned by our search "
]
},
{
"cell_type": "markdown",
"id": "7448523f-3e24-45a5-b91a-e23ab18eb62c",
"metadata": {},
"source": [
"## Parsing the resource\n",
"\n",
"Once we have our resource, we can find the data we need from the resource. The different parts of the resource can be accessed as properties: \n",
"\n",
"Please note our subject for this part, Tish Lemke, is completely fictional. The data is synthetic and generated using [Synthea](https://synthetichealth.github.io/synthea/).\n"
]
},
{
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"id": "c59a4e99-662f-486d-a654-95d160910508",
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"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ID: 32\n",
"Date of Birth: 1978-06-25\n"
]
}
],
"source": [
"print(\"ID: \", tish.id)\n",
"print(\"Date of Birth: \", tish.birthDate)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "7c9c34d1-3771-41bf-8fc9-afd4c1cc9c85",
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{
"name": "stdout",
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"text": [
"[{'use': 'official', 'family': 'Lemke', 'given': ['Tish'], 'prefix': ['Mrs.']}, {'use': 'maiden', 'family': 'Johnston', 'given': ['Tish'], 'prefix': ['Mrs.']}]\n"
]
}
],
"source": [
"## Some properties are more complex than others: \n",
"print(tish.name)"
]
},
{
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"id": "4a8de4fa-be4e-4817-a190-805cd9cf56a3",
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{
"name": "stdout",
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"text": [
"LastName,FirstName: Lemke,Tish\n"
]
}
],
"source": [
"print(\"LastName,FirstName: \", f\"{tish.name[0].family},{tish.name[0].given[0]}\") "
]
},
{
"cell_type": "markdown",
"id": "efd135f2-1e83-413b-aece-1e7ecb7463b0",
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"source": [
"We can see all the data in the resource with: "
]
},
{
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"execution_count": 17,
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"outputs": [
{
"data": {
"text/plain": [
"{'resourceType': 'Patient',\n",
" 'id': '32',\n",
" 'text': {'status': 'generated',\n",
" 'div': '<div xmlns=\"http://www.w3.org/1999/xhtml\">Generated by <a href=\"https://github.com/synthetichealth/synthea\">Synthea</a>.Version identifier: synthea-java . Person seed: 7070811051044420006 Population seed: 1597764932523</div>'},\n",
" 'extension': [{'url': 'http://hl7.org/fhir/StructureDefinition/patient-mothersMaidenName',\n",
" 'valueString': 'Lisabeth Zboncak'},\n",
" {'url': 'http://hl7.org/fhir/StructureDefinition/patient-birthPlace',\n",
" 'valueAddress': {'city': 'Nahant',\n",
" 'state': 'Massachusetts',\n",
" 'country': 'US'}},\n",
" {'url': 'http://synthetichealth.github.io/synthea/disability-adjusted-life-years',\n",
" 'valueDecimal': 0.07941261291993779},\n",
" {'url': 'http://synthetichealth.github.io/synthea/quality-adjusted-life-years',\n",
" 'valueDecimal': 40.92058738708006}],\n",
" 'identifier': [{'system': 'https://github.com/synthetichealth/synthea',\n",
" 'value': 'e362ce59-b198-4296-b01e-109fa6b44fe5'},\n",
" {'type': {'coding': [{'system': 'http://terminology.hl7.org/CodeSystem/v2-0203',\n",
" 'code': 'MR',\n",
" 'display': 'Medical Record Number'}],\n",
" 'text': 'Medical Record Number'},\n",
" 'system': 'http://hospital.smarthealthit.org',\n",
" 'value': 'e362ce59-b198-4296-b01e-109fa6b44fe5'},\n",
" {'type': {'coding': [{'system': 'http://terminology.hl7.org/CodeSystem/v2-0203',\n",
" 'code': 'SS',\n",
" 'display': 'Social Security Number'}],\n",
" 'text': 'Social Security Number'},\n",
" 'system': 'http://hl7.org/fhir/sid/us-ssn',\n",
" 'value': '999-13-4626'},\n",
" {'type': {'coding': [{'system': 'http://terminology.hl7.org/CodeSystem/v2-0203',\n",
" 'code': 'DL',\n",
" 'display': \"Driver's License\"}],\n",
" 'text': \"Driver's License\"},\n",
" 'system': 'urn:oid:2.16.840.1.113883.4.3.25',\n",
" 'value': 'S99931949'},\n",
" {'type': {'coding': [{'system': 'http://terminology.hl7.org/CodeSystem/v2-0203',\n",
" 'code': 'PPN',\n",
" 'display': 'Passport Number'}],\n",
" 'text': 'Passport Number'},\n",
" 'system': 'http://standardhealthrecord.org/fhir/StructureDefinition/passportNumber',\n",
" 'value': 'X76326389X'}],\n",
" 'name': [{'use': 'official',\n",
" 'family': 'Lemke',\n",
" 'given': ['Tish'],\n",
" 'prefix': ['Mrs.']},\n",
" {'use': 'maiden',\n",
" 'family': 'Johnston',\n",
" 'given': ['Tish'],\n",
" 'prefix': ['Mrs.']}],\n",
" 'telecom': [{'system': 'phone', 'value': '555-640-1130', 'use': 'home'}],\n",
" 'gender': 'female',\n",
" 'birthDate': '1978-06-25',\n",
" 'address': [{'extension': [{'url': 'http://hl7.org/fhir/StructureDefinition/geolocation',\n",
" 'extension': [{'url': 'latitude', 'valueDecimal': 41.78651253516297},\n",
" {'url': 'longitude', 'valueDecimal': -70.69785375801584}]}],\n",
" 'line': ['400 Cartwright Knoll'],\n",
" 'city': 'Wareham',\n",
" 'state': 'Massachusetts',\n",
" 'country': 'US'}],\n",
" 'maritalStatus': {'coding': [{'system': 'http://terminology.hl7.org/CodeSystem/v3-MaritalStatus',\n",
" 'code': 'M',\n",
" 'display': 'M'}],\n",
" 'text': 'M'},\n",
" 'multipleBirthBoolean': False,\n",
" 'communication': [{'language': {'coding': [{'system': 'urn:ietf:bcp:47',\n",
" 'code': 'en-US',\n",
" 'display': 'English'}],\n",
" 'text': 'English'}}],\n",
" 'meta': {'lastUpdated': '2025-10-08T16:01:02Z', 'versionId': '1'}}"
]
},
"execution_count": 17,
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"source": [
"tish.serialize() ## The result is the resource in Python Dictionary format (essentially JSON format)"
]
},
{
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"execution_count": 54,
"id": "77f1b60c-2b7b-408b-bfa3-30817497a0a3",
"metadata": {},
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"source": [
"## As a challenge - see if you can find Tish's phone number using . properties! "
]
},
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"
}
},
"cell_type": "markdown",
"id": "0674efa2-040a-4f03-b42f-13aff6709126",
"metadata": {},
"source": [
"## Other resources\n",
"\n",
"While the patient resource is vital for knowing the personal details of the patient in focus, clinical information is kept in other resources. There are many supported resources - the [Official FHIR resource list](https://build.fhir.org/resourcelist.html) has 159, each with a specific role. Many of these are adminstrative and handle orgnisations, payments and general management, but a subset might be useful for clinical means: \n",
"\n",
"\n",
"\n",
"When using a new resource, I highly recommend using the .serialize() method to look at the resource structure and help you locate the data you need! \n",
"\n",
"We can find information about our (*fictional*) patient using her id: "
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "555a3fd7-34fd-45de-964c-b54f285a6f48",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[<SyncFHIRResource Condition/3426>, <SyncFHIRResource Condition/1806>, <SyncFHIRResource Condition/1784>, <SyncFHIRResource Condition/1802>, <SyncFHIRResource Condition/1803>, <SyncFHIRResource Condition/1804>, <SyncFHIRResource Condition/1805>, <SyncFHIRResource Condition/1777>, <SyncFHIRResource Condition/1778>, <SyncFHIRResource Condition/1779>, <SyncFHIRResource Condition/1780>, <SyncFHIRResource Condition/1781>, <SyncFHIRResource Condition/1782>, <SyncFHIRResource Condition/1783>, <SyncFHIRResource Condition/1486>, <SyncFHIRResource Condition/1478>, <SyncFHIRResource Condition/1474>, <SyncFHIRResource Condition/1435>, <SyncFHIRResource Condition/1002>, <SyncFHIRResource Condition/985>, <SyncFHIRResource Condition/690>, <SyncFHIRResource Condition/484>]\n"
]
}
],
"source": [
"patient_id = tish.id\n",
"\n",
"## Here I am adding a 'sort' method to the search to return the results in order of most recent. \n",
"## The '-' character in the sort search parameter means reverse order (in this case ascending, or most recent first). \n",
"## The search parameters have different syntax to the resource serialization. \n",
"## To find search parameters for a specific resource, look on the build.fhir.org documneation\n",
"## see https://build.fhir.org/condition-search.html for condition resource search parameters\n",
"conditions = client.resources(\"Condition\").search(patient=patient_id).sort(\"-recorded-date\").fetch()\n",
"\n",
"print(conditions)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "79ab8761-d560-49cb-9a62-151031e13398",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'resourceType': 'Condition',\n",
" 'id': '3426',\n",
" 'clinicalStatus': {'coding': [{'system': 'http://terminology.hl7.org/CodeSystem/condition-clinical',\n",
" 'code': 'resolved'}]},\n",
" 'verificationStatus': {'coding': [{'system': 'http://terminology.hl7.org/CodeSystem/condition-ver-status',\n",
" 'code': 'confirmed'}]},\n",
" 'code': {'coding': [{'system': 'http://snomed.info/sct',\n",
" 'code': '301011002',\n",
" 'display': 'Escherichia coli urinary tract infection'}],\n",
" 'text': 'Escherichia coli urinary tract infection'},\n",
" 'subject': {'reference': 'Patient/32'},\n",
" 'encounter': {'reference': 'Encounter/3425'},\n",
" 'onsetDateTime': '2020-07-31T05:02:07-04:00',\n",
" 'abatementDateTime': '2020-08-07T05:02:07-04:00',\n",
" 'recordedDate': '2020-07-31T05:02:07-04:00',\n",
" 'meta': {'lastUpdated': '2025-10-08T16:01:06Z', 'versionId': '1'}}"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"## Again, we can view the full resource using: \n",
"conditions[0].serialize()"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "6a2e66f6-cd8e-4143-a265-3e25dbaffc0e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"id: 3426 , patient: Patient/32\n",
"Date: 2020-07-31T05:02:07-04:00\n",
"Condition: Escherichia coli urinary tract infection \n",
"\n",
"id: 1806 , patient: Patient/32\n",
"Date: 2020-03-12T05:41:07-04:00\n",
"Condition: Acute pulmonary embolism (disorder) \n",
"\n",
"id: 1784 , patient: Patient/32\n",
"Date: 2020-03-04T04:41:07-05:00\n",
"Condition: COVID-19 \n",
"\n",
"id: 1802 , patient: Patient/32\n",
"Date: 2020-03-04T04:41:07-05:00\n",
"Condition: Pneumonia (disorder) \n",
"\n",
"id: 1803 , patient: Patient/32\n",
"Date: 2020-03-04T04:41:07-05:00\n",
"Condition: Hypoxemia (disorder) \n",
"\n"
]
}
],
"source": [
"## Or iterate through the first 5 results: \n",
"for condition in conditions[:5]: \n",
" print(f'id: {condition.id} , patient: {condition.subject.reference}')\n",
" print(\"Date: \", condition.recordedDate)\n",
" print(\"Condition: \", condition.code.text, \"\\n\") \n",
" "
]
},
{
"cell_type": "markdown",
"id": "56a6cba4-948b-42e0-ac97-9b4070f73617",
"metadata": {},
"source": [
"Note each resource has an ID value, this is not the same as the patient ID! \n",
"\n",
"We can do the same with other resources: "
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "4c1dbad5-0120-4168-a3e1-bb80ceb69d6b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['Standard pregnancy test', 'Ultrasound scan for fetal viability', 'Counseling for termination of pregnancy', 'Induced termination of pregnancy', 'Pregnancy termination care', 'Physical exam following abortion', 'Depression screening', 'Standard pregnancy test', 'Ultrasound scan for fetal viability', 'Evaluation of uterine fundal height', 'Auscultation of the fetal heart', 'Blood typing, RH typing', 'Hemoglobin / Hematocrit / Platelet count', 'Hepatitis B Surface Antigen Measurement', 'Human immunodeficiency virus antigen test', 'Chlamydia antigen test', 'Gonorrhea infection test', 'Syphilis infection test', 'Urine culture', 'Cytopathology procedure, preparation of smear, genital source', 'Urine screening test for diabetes', 'Hepatitis C antibody test', 'Rubella screening', 'Measurement of Varicella-zoster virus antibody', 'Skin test for tuberculosis', 'Urine protein test', 'Physical examination of mother', 'Evaluation of uterine fundal height', 'Auscultation of the fetal heart', 'Screening for chromosomal aneuploidy in prenatal amniotic fluid', 'Physical examination', 'Depression screening', 'Bilateral tubal ligation', 'Sputum examination (procedure)', 'Medication Reconciliation (procedure)', 'Throat culture (procedure)', 'Suture open wound', 'Medication Reconciliation (procedure)', 'Face mask (physical object)', 'Plain chest X-ray (procedure)', 'Oxygen administration by mask (procedure)', 'Placing subject in prone position (procedure)', 'Oxygen administration by mask (procedure)', 'Placing subject in prone position (procedure)', 'Oxygen administration by mask (procedure)', 'Placing subject in prone position (procedure)', 'Oxygen administration by mask (procedure)', 'Placing subject in prone position (procedure)', 'Oxygen administration by mask (procedure)', 'Placing subject in prone position (procedure)', 'Oxygen administration by mask (procedure)', 'Placing subject in prone position (procedure)', 'Oxygen administration by mask (procedure)', 'Placing subject in prone position (procedure)', 'Oxygen administration by mask (procedure)', 'Placing subject in prone position (procedure)', 'Oxygen administration by mask (procedure)', 'Placing subject in prone position (procedure)', 'Oxygen administration by mask (procedure)', 'Placing subject in prone position (procedure)']\n",
"\n",
"\n"
]
}
],
"source": [
"procedures = client.resources(\"Procedure\").search(patient=patient_id).fetch()\n",
"print([f'{procedure.code.text}' for procedure in procedures])\n",
"\n",
"print('\\n')"
]
},
{
"cell_type": "markdown",
"id": "0e7e032a-a60a-4005-a006-c2a6bf744780",
"metadata": {},
"source": [
"There might be a particular value we are interested in. For example, maybe we want to track how a patient's weight has changed over time. Here we can use the coding systems to search for a particular category of resource. Here, I've looked up the code for patient weight from https://www.findacode.com and used this code (29463-7) as a search parameter:"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "71220c93-7461-4569-acbf-fbc622a34d25",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The search returned 16 results!\n",
"Resource structure: \n"
]
},
{
"data": {
"text/plain": [
"{'resourceType': 'Observation',\n",
" 'id': '3409',\n",
" 'status': 'final',\n",
" 'category': [{'coding': [{'system': 'http://terminology.hl7.org/CodeSystem/observation-category',\n",
" 'code': 'vital-signs',\n",
" 'display': 'vital-signs'}]}],\n",
" 'code': {'coding': [{'system': 'http://loinc.org',\n",
" 'code': '29463-7',\n",
" 'display': 'Body Weight'}],\n",
" 'text': 'Body Weight'},\n",
" 'subject': {'reference': 'Patient/32'},\n",
" 'encounter': {'reference': 'Encounter/3406'},\n",
" 'effectiveDateTime': '2020-07-05T05:02:07-04:00',\n",
" 'issued': '2020-07-05T05:02:07.383-04:00',\n",
" 'valueQuantity': {'value': 55.8,\n",
" 'unit': 'kg',\n",
" 'system': 'http://unitsofmeasure.org',\n",
" 'code': 'kg'},\n",
" 'meta': {'lastUpdated': '2025-10-08T16:01:06Z', 'versionId': '1'}}"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"observations = client.resources(\"Observation\").search(patient=patient_id, code=\"29463-7\").sort(\"-date\").fetch()\n",
"print(f'The search returned {len(observations)} results!')\n",
"print(\"Resource structure: \")\n",
"observations[0].serialize()"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "8653bf9d-e2bc-49d6-b61b-d96f86adf706",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"('2020-07-05T05:02:07-04:00', 55.8, 'kg')\n",
"('2020-03-13T05:41:07-04:00', 55.8, 'kg')\n",
"('2020-03-12T05:41:07-04:00', 55.8, 'kg')\n",
"('2020-03-11T05:41:07-04:00', 55.8, 'kg')\n",
"('2020-03-10T05:41:07-04:00', 55.8, 'kg')\n",
"('2020-03-09T05:41:07-04:00', 55.8, 'kg')\n",
"('2020-03-08T05:41:07-04:00', 55.8, 'kg')\n",
"('2020-03-07T04:41:07-05:00', 55.8, 'kg')\n",
"('2020-03-06T04:41:07-05:00', 55.8, 'kg')\n",
"('2020-03-05T04:41:07-05:00', 55.8, 'kg')\n",
"('2020-03-04T04:41:07-05:00', 55.8, 'kg')\n",
"('2020-03-04T04:02:07-05:00', 55.8, 'kg')\n",
"('2018-07-01T05:02:07-04:00', 55.8, 'kg')\n",
"('2015-09-13T05:02:07-04:00', 55.8, 'kg')\n",
"('2014-11-09T04:02:07-05:00', 55.8, 'kg')\n",
"('2012-09-09T05:02:07-04:00', 55.8, 'kg')\n"
]
}
],
"source": [
"datapoints = []\n",
"for observation in observations: \n",
" point = (observation.effectiveDateTime, observation.valueQuantity.value, observation.valueQuantity.unit)\n",
" datapoints.append(point)\n",
" print(point) \n"
]
},
{
"cell_type": "markdown",
"id": "a46898c3-ec97-4ce4-a37d-9777ae5aa7d4",
"metadata": {},
"source": [
"Now somewhat unexpectedly, the patient has stayed at exactly the same weight for 8 years and across two pregnancies! There are limits to the realism of synthetic data... \n",
"\n",
"I was planning to demonstrate making a basic graph of weight-vs-time, but on second thoughts, I think you can use your imagination! However, you can hopefully see how you can use FHIR resources to build a picture of a patient's medical history. "
]
},
{
"cell_type": "markdown",
"id": "a6fadde4-5bf6-4202-ae32-ec6510f96d8f",
"metadata": {},
"source": [
"# Querying the FHIR Server with HTTP requests\n",
"\n",
"While fhirpy can make certain syntax easier, we can also query the server with standard HTTP requests, this is the standard way to query FHIR servers from different applications and may be more familiar to people who have used FHIR a lot. \n"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "ed462c1d-98fc-48b4-95fd-8c6840ca7282",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<Response [200]>\n"
]
}
],
"source": [
"import requests\n",
"from requests.auth import HTTPBasicAuth\n",
"\n",
"## Credentials\n",
"username = \"_System\"\n",
"password = \"ISCDEMO\"\n",
"\n",
"## FHIR server location\n",
"baseURL = \"http://localhost:32783/csp/healthshare/demo/fhir/r4/\"\n",
"\n",
"headers ={ \"Accept\": \"application/fhir+json\"}\n",
"\n",
"endpoint = \"Patient\"\n",
"\n",
"\n",
"res = requests.get(baseURL+endpoint, headers=headers, auth=HTTPBasicAuth(username, password))\n",
"print(res)"
]
},
{
"cell_type": "markdown",
"id": "0a15785b-0ff6-4e46-bf5c-4721cd724a2b",
"metadata": {},
"source": [
"Response 200 means we have successfully recieved the expected response, in this case, it will be a bundle of all patient resources. You will likely be aware of some of the other response codes - 404 means resource not found, 403 is authorisation error, 400 is bad request. \n",
"\n",
"We can access this bundle using res.json(). This can be quite annoying to parse, but the data is there! For example: "
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "f25c8691-740f-4eba-9784-d6a035d56280",
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"4 [{'use': 'official', 'family': 'Hoeger474', 'given': ['Aurora248']}] female\n",
"3 [{'use': 'official', 'family': 'Ziemann98', 'given': ['Alisia5'], 'prefix': ['Mrs.']}, {'use': 'maiden', 'family': 'Dietrich576', 'given': ['Alisia5'], 'prefix': ['Mrs.']}] female\n",
"41 [{'use': 'official', 'family': 'Wolff180', 'given': ['Miquel905'], 'prefix': ['Mr.']}] male\n",
"45 [{'use': 'official', 'family': 'Jacobson885', 'given': ['Lakita48'], 'prefix': ['Mrs.']}, {'use': 'maiden', 'family': 'Bartell116', 'given': ['Lakita48'], 'prefix': ['Mrs.']}] female\n",
"65 [{'use': 'official', 'family': 'Spinka232', 'given': ['Sherry479'], 'prefix': ['Mrs.']}, {'use': 'maiden', 'family': 'Windler79', 'given': ['Sherry479'], 'prefix': ['Mrs.']}] female\n",
"32 [{'use': 'official', 'family': 'Lemke', 'given': ['Tish'], 'prefix': ['Mrs.']}, {'use': 'maiden', 'family': 'Johnston', 'given': ['Tish'], 'prefix': ['Mrs.']}] female\n",
"3596 [{'use': 'official', 'family': 'Kent', 'given': ['Clark']}] None\n",
"3597 [{'use': 'official', 'family': 'Kent', 'given': ['Clark']}] None\n",
"3598 [{'family': 'Wayne', 'given': ['Bruce']}] None\n"
]
}
],
"source": [
"#print(res.json())\n",
"data = res.json() \n",
"\n",
"for entry in data.get(\"entry\", [])[:10]: ## Get the first 10 entries\n",
" patient = entry.get('resource', {}) ## Get the patient resource\n",
" print(patient.get('id'), patient.get('name'), patient.get('gender')) ## Print the patient info\n"
]
},
{
"cell_type": "markdown",
"id": "9167e862-1374-4d23-9634-113baefb33c0",
"metadata": {},
"source": [
"We can add search parameters to the URL we are quering, for example: "
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "6eadf846-df89-4a96-85eb-eddd0d800651",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"http://localhost:32783/csp/healthshare/demo/fhir/r4/Patient/?name=Tish\n",
"<Response [200]>\n"
]
}
],
"source": [
"search_params = \"?name=Tish\"\n",
"\n",
"url = baseURL + endpoint+ \"/\"+ search_params\n",
"print(url)\n",
"res = requests.get(url, headers=headers, auth=HTTPBasicAuth(username, password))\n",
"print(res)"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "c162da2a-4e5e-4dd5-91fe-5bf360c5a141",
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"{'resourceType': 'Bundle',\n",
" 'id': 'f4e33c5a-a4e9-11f0-a38b-126f8db0efdb',\n",
" 'type': 'searchset',\n",
" 'timestamp': '2025-10-09T08:28:39Z',\n",
" 'total': 1,\n",
" 'link': [{'relation': 'self',\n",
" 'url': 'http://localhost:32783/csp/healthshare/demo/fhir/r4/Patient?name=Tish'}],\n",
" 'entry': [{'fullUrl': 'http://localhost:32783/csp/healthshare/demo/fhir/r4/Patient/32',\n",
" 'resource': {'resourceType': 'Patient',\n",
" 'id': '32',\n",
" 'text': {'status': 'generated',\n",
" 'div': '<div xmlns=\"http://www.w3.org/1999/xhtml\">Generated by <a href=\"https://github.com/synthetichealth/synthea\">Synthea</a>.Version identifier: synthea-java . Person seed: 7070811051044420006 Population seed: 1597764932523</div>'},\n",
" 'extension': [{'url': 'http://hl7.org/fhir/StructureDefinition/patient-mothersMaidenName',\n",
" 'valueString': 'Lisabeth Zboncak'},\n",
" {'url': 'http://hl7.org/fhir/StructureDefinition/patient-birthPlace',\n",
" 'valueAddress': {'city': 'Nahant',\n",
" 'state': 'Massachusetts',\n",
" 'country': 'US'}},\n",
" {'url': 'http://synthetichealth.github.io/synthea/disability-adjusted-life-years',\n",
" 'valueDecimal': 0.07941261291993779},\n",
" {'url': 'http://synthetichealth.github.io/synthea/quality-adjusted-life-years',\n",
" 'valueDecimal': 40.92058738708006}],\n",
" 'identifier': [{'system': 'https://github.com/synthetichealth/synthea',\n",
" 'value': 'e362ce59-b198-4296-b01e-109fa6b44fe5'},\n",
" {'type': {'coding': [{'system': 'http://terminology.hl7.org/CodeSystem/v2-0203',\n",
" 'code': 'MR',\n",
" 'display': 'Medical Record Number'}],\n",
" 'text': 'Medical Record Number'},\n",
" 'system': 'http://hospital.smarthealthit.org',\n",
" 'value': 'e362ce59-b198-4296-b01e-109fa6b44fe5'},\n",
" {'type': {'coding': [{'system': 'http://terminology.hl7.org/CodeSystem/v2-0203',\n",
" 'code': 'SS',\n",
" 'display': 'Social Security Number'}],\n",
" 'text': 'Social Security Number'},\n",
" 'system': 'http://hl7.org/fhir/sid/us-ssn',\n",
" 'value': '999-13-4626'},\n",
" {'type': {'coding': [{'system': 'http://terminology.hl7.org/CodeSystem/v2-0203',\n",
" 'code': 'DL',\n",
" 'display': \"Driver's License\"}],\n",
" 'text': \"Driver's License\"},\n",
" 'system': 'urn:oid:2.16.840.1.113883.4.3.25',\n",
" 'value': 'S99931949'},\n",
" {'type': {'coding': [{'system': 'http://terminology.hl7.org/CodeSystem/v2-0203',\n",
" 'code': 'PPN',\n",
" 'display': 'Passport Number'}],\n",
" 'text': 'Passport Number'},\n",
" 'system': 'http://standardhealthrecord.org/fhir/StructureDefinition/passportNumber',\n",
" 'value': 'X76326389X'}],\n",
" 'name': [{'use': 'official',\n",
" 'family': 'Lemke',\n",
" 'given': ['Tish'],\n",
" 'prefix': ['Mrs.']},\n",
" {'use': 'maiden',\n",
" 'family': 'Johnston',\n",
" 'given': ['Tish'],\n",
" 'prefix': ['Mrs.']}],\n",
" 'telecom': [{'system': 'phone', 'value': '555-640-1130', 'use': 'home'}],\n",
" 'gender': 'female',\n",
" 'birthDate': '1978-06-25',\n",
" 'address': [{'extension': [{'url': 'http://hl7.org/fhir/StructureDefinition/geolocation',\n",
" 'extension': [{'url': 'latitude', 'valueDecimal': 41.78651253516297},\n",
" {'url': 'longitude', 'valueDecimal': -70.69785375801584}]}],\n",
" 'line': ['400 Cartwright Knoll'],\n",
" 'city': 'Wareham',\n",
" 'state': 'Massachusetts',\n",
" 'country': 'US'}],\n",
" 'maritalStatus': {'coding': [{'system': 'http://terminology.hl7.org/CodeSystem/v3-MaritalStatus',\n",
" 'code': 'M',\n",
" 'display': 'M'}],\n",
" 'text': 'M'},\n",
" 'multipleBirthBoolean': False,\n",
" 'communication': [{'language': {'coding': [{'system': 'urn:ietf:bcp:47',\n",
" 'code': 'en-US',\n",
" 'display': 'English'}],\n",
" 'text': 'English'}}],\n",
" 'meta': {'lastUpdated': '2025-10-08T16:01:02Z', 'versionId': '1'}},\n",
" 'search': {'mode': 'match'}}]}"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"res.json()"
]
},
{
"cell_type": "markdown",
"id": "ddcf1a41-70da-4df3-944e-68d14527beed",
"metadata": {},
"source": [
"An advantage of using HTTP requests is that there is much better documentation and examples on using search parameters, making complex queries easier to create. \n",
"\n",
"Disadvantages of HTTP requests include that you have to include the headers and authentication information each time you make a request, and the process for creating simple queries is much more complicated. The bundle output is also complete in the JSON (or python dict) format, making it harder to parse than lists of fhirpy `<SyncFHIRResource>` object. \n",
"\n",
"Depending on experience and usage, you may prefer one over the other, but so feel free to use whichever. "
]
}
],
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