Register the INSPIRE dataset

INSPIRE (perioperative medicine) — `MEDS_extract-INSPIRE` from the
upstream `inspire-meds` package handles the extraction. No demo recipe
upstream, so marked `demo_available: false`.

Also lands the shared `demo_available` registry mechanism (identical
across sister per-dataset PRs).

Replicated from the closed bundled PR #299 (which itself replicated
@rvandewater's #258).

Co-Authored-By: Robin P. van de Water <rvandewater@users.noreply.github.com>
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

Author: 3 people

src/MEDS_DEV/datasets/INSPIRE/README.md

@@ -0,0 +1,38 @@
+# INSPIRE: a publicly available research dataset for perioperative medicine
+
+## Description
+
+The INSPIRE dataset is a publicly available research dataset in perioperative medicine, which includes approximately 130,000 cases (50% of all surgical cases) who underwent anesthesia for surgery at an academic institution in South Korea between 2011 and 2020. This comprehensive dataset includes patient characteristics such as age, sex, American Society of Anesthesiologists physical status classification, diagnosis, surgical procedure code, department, and type of anesthesia. It also includes vital signs in the operating theatre, general wards, and intensive care units (ICUs), laboratory results from six months before admission to six months after discharge, and medication during hospitalization. Complications include total hospital and ICU length of stay and in-hospital death.[1]
+
+## Access Requirements
+
+Taken from [PhysioNet](https://physionet.org/content/inspire/1.3/):
+
+- **Access Policy**: Complete the credentialed data access requirements on PhysioNet[1]
+- **License (for files)**: PhysioNet Credentialed Health Data License Version 1.5.0[1]
+- **Data Use Agreement**: Agreement requires verified institutional affiliation and commitment to use data solely for lawful scientific research[1]
+- **Required training**: Valid CITI training certification in human research subject protection and HIPAA regulations[1]
+- **License Term**: 3 years from account creation date[1]
+- **Code Sharing**: Agreement to contribute code associated with publications to open research repository[1]
+
+## Supported Tasks
+
+INSPIRE includes several classification tasks organized into categories such as:[1]
+
+**Operational Outcomes:**
+
+- `tasks/mortality/long_length_of_stay.yaml`
+- `tasks/readmission/30_day_readmission.yaml`
+- `tasks/transfer/icu_transfer.yaml`
+
+## MEDS-transformation
+
+The INSPIRE ETL is found at https://github.com/rvandewater/INSPIRE_MEDS.
+
+## Sources
+
+1. [INSPIRE Physionet Website](https://physionet.org/content/inspire/1.3/)
+
+## Disclaimer
+
+Please refer to the data owners and the most up-to-date information when using this dataset in your research. The INSPIRE dataset has not been reviewed or approved by the Food and Drug Administration and is for non-clinical, research and education use only.[1]

src/MEDS_DEV/datasets/INSPIRE/dataset.yaml

@@ -0,0 +1,18 @@
+metadata:
+  demo_available: false
+  description: >-
+    A MEDS version of INSPIRE.
+  links:
+    - https://github.com/rvandewater/INSPIRE_MEDS
+    - https://physionet.org/content/inspire/
+  contacts:
+    - name: "Robin P. van de Water"
+      github_username: "rvandewater"
+
+commands:
+  build_full: >-
+    MEDS_extract-INSPIRE
+    raw_input_dir="{temp_dir}/raw"
+    pre_MEDS_dir="{temp_dir}/pre_MEDS"
+    MEDS_cohort_dir="{output_dir}"
+    log_dir="{output_dir}/.pipeline_logs"

src/MEDS_DEV/datasets/INSPIRE/predicates.yaml

@@ -0,0 +1,35 @@
+predicates:
+  hospital_admission:
+    code: { regex: "^ADMISSION//.*" }
+  hospital_discharge:
+    code: { regex: "^HOSPITAL_DISCHARGE//.*" }
+
+  icu_admission:
+    code: { regex: "^ICU_ADMISSION//.*" }
+  icu_discharge:
+    code: { regex: "^ICU_DISCHARGE//.*" }
+
+  creatinine_mgdl:
+    code: { any: ["LAB//mg/dL//creatinine"] }
+
+  #TODO: convert units from mmol/L to mg/dL
+  sodium_meql:
+    code: { any: ["LAB//mmol/L//sodium"] }
+
+  wbc_kul:
+    code: { any: ["LAB///nL//wbc"] }
+
+  platelets_kul:
+    code: { any: ["LAB///nL//platelet"] }
+
+  map_mmhg:
+    code:
+      {
+        any:
+          [
+            "VITAL//pap_mbp//mmHg",
+            "VITAL//nibp_mbp//mmHg",
+            "VITAL//art_mbp//mmHg",
+            "WARD_VITAL//mmHg//nibp_mbp",
+          ],
+      }

src/MEDS_DEV/datasets/INSPIRE/refs.bib

@@ -0,0 +1,31 @@
+@article{limINSPIREPubliclyAvailable2024,
+  title = {{{INSPIRE}}, a Publicly Available Research Dataset for Perioperative Medicine},
+  author = {Lim, Leerang and Lee, Hyeonhoon and Jung, Chul-Woo and Sim, Dayeon and Borrat, Xavier and Pollard, Tom J. and Celi, Leo A. and Mark, Roger G. and Vistisen, Simon T. and Lee, Hyung-Chul},
+  year = 2024,
+  month = jun,
+  journal = {Scientific Data},
+  volume = {11},
+  number = {1},
+  pages = {655},
+  publisher = {Nature Publishing Group},
+  issn = {2052-4463},
+  doi = {10.1038/s41597-024-03517-4},
+  urldate = {2024-11-06},
+  abstract = {We present the INSPIRE dataset, a publicly available research dataset in perioperative medicine, which includes approximately 130,000 surgical operations at an academic institution in South Korea over a ten-year period between 2011 and 2020. This comprehensive dataset includes patient characteristics such as age, sex, American Society of Anesthesiologists physical status classification, diagnosis, surgical procedure code, department, and type of anaesthesia. The dataset also includes vital signs in the operating theatre, general wards, and intensive care units (ICUs), laboratory results from six months before admission to six months after discharge, and medication during hospitalisation. Complications include total hospital and ICU length of stay and in-hospital death. We hope this dataset will inspire collaborative research and development in perioperative medicine and serve as a reproducible external validation dataset to improve surgical outcomes.},
+  copyright = {2024 The Author(s)},
+  langid = {english},
+  keywords = {Outcomes research,Public health,Risk factors},
+}
+
+@misc{robinvandewaterRvandewaterINSPIRE_MEDSZenodo2025,
+  title = {Rvandewater/{{INSPIRE}}\_{{MEDS}}: {{Zenodo}}},
+  shorttitle = {Rvandewater/{{INSPIRE}}\_{{MEDS}}},
+  author = {{Robin van de Water}},
+  year = 2025,
+  month = feb,
+  doi = {10.5281/ZENODO.14891940},
+  urldate = {2025-10-16},
+  abstract = {First Zenodo release.},
+  copyright = {MIT License},
+  howpublished = {Zenodo}
+}

src/MEDS_DEV/datasets/INSPIRE/requirements.txt

@@ -0,0 +1 @@
+INSPIRE-MEDS==0.0.11

src/MEDS_DEV/datasets/__init__.py

@@ -38,23 +38,28 @@ class DatasetMetadata(Metadata):
         access_policy: The level of accessibility of the dataset. Limited to the values in the AccessPolicy
             enum.
         access_details: A string describing the access policy in more detail. May be empty.
+        demo_available: Whether the dataset has a usable ``build_demo`` recipe. Datasets where the upstream
+            extractor offers no public demo set this to False; integration tests skip them and they are
+            excluded from the CI dataset matrix.
 
     Examples:
         >>> DatasetMetadata(description="foo", contacts=[{"name": "bar"}]) # doctest: +NORMALIZE_WHITESPACE
         DatasetMetadata(description='foo',
                         contacts=[Contact(name='bar', email=None, github_username=None)],
                         links=None,
                         access_policy=<AccessPolicy.PRIVATE_SINGLE_USE: 'private_single_use'>,
-                        access_details=None)
+                        access_details=None,
+                        demo_available=True)
         >>> DatasetMetadata(
         ...     description="foo", contacts=[{"name": "bar"}], access_policy="public_unrestricted",
-        ...     access_details="baz"
+        ...     access_details="baz", demo_available=False
         ... ) # doctest: +NORMALIZE_WHITESPACE
         DatasetMetadata(description='foo',
                         contacts=[Contact(name='bar', email=None, github_username=None)],
                         links=None,
                         access_policy=<AccessPolicy.PUBLIC_UNRESTRICTED: 'public_unrestricted'>,
-                        access_details='baz')
+                        access_details='baz',
+                        demo_available=False)
         >>> DatasetMetadata(
         ...     description="foo", contacts=[{"name": "bar"}], access_policy="foo"
         ... ) # doctest: +NORMALIZE_WHITESPACE
@@ -74,6 +79,7 @@ class DatasetMetadata(Metadata):
 
     access_policy: AccessPolicy = AccessPolicy.PRIVATE_SINGLE_USE
     access_details: str | None = None
+    demo_available: bool = True
 
     def __post_init__(self):
         super().__post_init__()

tests/conftest.py

@@ -325,6 +325,9 @@ def get_opts(config, opt: str) -> list[str]:
     if isinstance(out, dict):
         out = list(out.keys())
 
+    if opt == "dataset":
+        out = [name for name in out if DATASETS[name]["metadata"].demo_available]
+
     return out
 
 

tests/test_registry_validation.py

@@ -31,6 +31,10 @@ def test_all_datasets_have_commands():
     for name, dataset in DATASETS.items():
         commands = dataset.get("commands")
         assert commands is not None, f"Dataset {name} missing commands"
+        metadata = dataset.get("metadata")
+        if metadata is not None and not metadata.demo_available:
+            # Datasets that explicitly opt out of a demo recipe don't need build_demo.
+            continue
         assert "build_demo" in commands, f"Dataset {name} missing build_demo command"