Cantonal data protection laws from Vaud and Zurich
ADONIS aimes to improve early detection and management of neonatal sepsis, a leading cause of infant mortality and long-term complications in Switzerland and worldwide. Despite its burden, neonatal sepsis remains under-addressed in Swiss research funding. ADONIS leverages a uniquely curated, high-resolution clinical dataset from neonates treated at the University Hospital of Lausanne (CHUV), the University Children's Hospital of Zurich (KiSpi), and University Hospital of Zurich (USZ). The project leverages patient demographics, clinical signs, data from support devices, point-of-care diagnostics, lab results, and treatments to develop advanced machine learning methods. Its objective is to identify subtle physiological changes that precede overt clinical signs of sepsis, thereby enabling earlier and more accurate intervention. ADONIS filles a major gap in national infrastructure by integrating neonatal data into the Swiss Personalized Health Network (SPHN), linking two existing National Data StreamsâSwissPedHealth and IICU. The project's outcomes sets the foundation for data-driven neonatal care and fosters improved sepsis management protocols, potentially reducing mortality, morbidity, and inappropriate antibiotic use among newborns.
Accelerating detection of neonatal sepsis: a machine learning-based approach (ADONIS)
General Consent and consent waiver (art. 34 HRA)
Researchers interested in accessing data can request the necessary Data Transfer and Use Agreement (DTUA), via the Principal Investigator. Upon request, the consortium executive board will evaluate the application. If accepted, access will be granted to BioMedIT under the supervision of the Principal Investigator. Researchers who wish to analyze, reproduce, or gain further insights from the data must submit a request for de-identified patient-level data to heads of the current project. Requests must clearly justify the use of the data and specify the required variables. External users or collaborators should demonstrate a proven track record in the field, provide a detailed research protocol, and explain how they will handle the data ethically and scientifically. The protocol should include: Collaborators and their affiliations, Potential conflicts of interest, Project funding details, Inclusion/exclusion criteria, Scientific questions to be addressed, Detailed analysis plan, Peer-reviewed publication in the field, Approval Process. The ADONIS executive board will review the application, recommending any necessary protocol adjustments to enhance quality and ensure alignment with project objectives. Before access to data is granted, both parties will sign the Data Transfer and Use Agreement (DTUA) based on the Swiss Personalized Health Network (SPHN) template. This agreement will define responsibilities related to data protection, management, authorship (in accordance with international standards), and the proper citation of sources and funding. Additionally, it will specify the required date for secure data destruction after analysis is completed, with confirmation of destruction submitted to the project leads. To get access to the dataset, please contact the following email: eric.giannoni@chuv.ch
Hospitalized in the neonatal ward at either CHUV, USZ, or KiSpi
Newborns, defined as inpatients aged less than 28 days for those born at a gestational age >= 37 weeks, and infants with a corrected age (gestational + postnatal age) < 44 weeks for those born < 37 weeks
Swiss Personalized Health Network (SPHN)
Centre hospitalier universitaire vaudois
Distribution of USZ clinical routine dataset (2025.1)
VOID Dataset associated with the Distribution
Distribution of Infection Radar Data Set
Due to the unique epidemiology, developmental changes, and high vulnerability of children, there is an urgent need to continuously improve health care based on real world pediatric data. The digital transformation is a unique opportunity to shape a data-driven, agile, learning health care system and deliver more efficient and personalized care to children and their families. The goal of SwissPedHealth is to build a sustainable and scalable infrastructure to make routine clinical data from pediatric hospitals in Switzerland interoperable, standardized, quality-controlled, and ready for observational research, quality assurance, trials, and health-policy creation. SwissPedHealth is one of four National Data Streams co-funded by the Swiss Personalized Health Network (SPHN) and the ETH focus area Personalized Health Related Technologies (PHRT). Dedicated catalog and dataset are provided for PHRT data. SwissPedHealth develops modular governance and regulatory strategies in collaboration with clinical data warehouses, the Data Coordination Center, Biomedical Information Technology Network, and others. The data stream contains work packages focusing on: 1) governance and implementation of standardized data collection, 2) nested projects to test the feasibility of the data stream, 3) a lighthouse project that enriches the data stream by integrating multi-omics data, aiming to improve diagnoses of rare diseases, and 4) engagement with families through patient and public involve-ment activities and interviews.
General consent (for the general cohort irrespective of consent status)
Informed consent (patients recruited through the Lighthouse Project (Prospective cohort, Phase 3))
Access to the NDS data is regulated through the SwissPedHealth infrastructure consortium agreement V2.0 18.11.2022. As brief explanation: When planning to carry out a project using data from the SwissPedHealth NDS, you will need to set up a data project consortium agreement (DPCA) involving all participating partners. Note that this should include "internal" SwissPedHealth partners and "external" partners, i.e. those not part of the SwissPedHealth NDS Infrastructure Consortium. For the DPCA, projects should consider the SwissPedHealth general terms and conditions (GTCs) and, wherever possible, try to adopt them without or with minor deviations. This will facilitate the process of legal review and signing for all "internal" partners, since the GTCs will have already been reviewed as part of the development and adoption process. If deviations are required, these will need to be specified in the DPCA, and should be highlighted during the legal review of the DPCA. Note that the following additional documentation will be required to complete the DPCA: Project funding application/Proof of funding, Study protocol and Ethical approval. In case the latter is not available it should be added as soon as available, and the DPCA cannot be executed without evidence of ethical review and approval. All parts highlighted in yellow in the DPCA template need to be completed/amended. All DPCAs will need to incorporate a data transfer and use agreement (DTUA) and data transfer and processing agreement (DTPA). These are included in the SwissPedHealth DPCA template, reflecting SPHN requirements. Please note that adaptations may be necessary in cases where the Data Processors are not one of the BioMedIT nodes (SENSA - Lausanne, SciCORE - Basel, SIS - Zurich). For the DTUA section, each project will need to describe and depict the planned data flow as well as data and metadata to be transferred. All parts highlighted in yellow in the DTUA and DTPA templates need to be completed/amended. Access to SwissPedHeath project specific data (from the lighthouse or nested projects) is regulated through their corresponding DPCAs.
Patients attended in pediatric hospitals
N/A (The SwissPedHealth Dataset is a registry - not analyzed at this level)
for the Nested Projects, exception NP4 administered inpatients between 2021-2022 only
for patients recruited through the Lighthouse Project (Prospective cohort, Phase 3
Code Frequency associated with the distribution
ÃuÃere Ursachen von Morbidität und Mortalität
Observable entity (observable entity)
Operationen am Bewegungsapparat (76â84)
Krankheiten der Haut und der Unterhaut
Operationen an den Augen (08â16)
Angeborene Fehlbildungen, Deformitäten und Chromosomenanomalien
Schlüsselnummern für besondere Zwecke
Krankheiten des Muskel-Skelett-Systems und des Bindegewebes
Operationen am Integument (85â86)
SNOMED CT Model Component (metadata)
Bestimmte infektiöse und parasitäre Krankheiten
BLOOD AND BLOOD FORMING ORGANS
RESPIRATORY SYSTEM
Operationen an den Ohren (18â20)
Krankheiten des Ohres und des Warzenfortsatzes
Staging and scales (staging scale)
Substance (substance)
SYSTEMIC HORMONAL PREPARATIONS, EXCL. SEX HORMONES AND INSULINS
Environment or geographical location (environment / location)
Respiratory measures and Ventilator management
Messinstrumente und Messungen (AA)
SENSORY ORGANS
Bestimmte Zustände, die ihren Ursprung in der Perinatalperiode haben
Verletzungen, Vergiftungen und bestimmte andere Folgen äuÃerer Ursachen
Verschiedene diagnostische und therapeutische Massnahmen (87â99)
Procedure (procedure)
Schwangerschaft, Geburt und Wochenbett
Krankheiten des Blutes und der blutbildenden Organe sowie bestimmte Störungen mit Beteiligung des Immunsystems
Symptome und abnorme klinische und Laborbefunde, die anderenorts nicht klassifiziert sind
Faktoren, die den Gesundheitszustand beeinflussen und zur Inanspruchnahme des Gesundheitswesens führen
ANTIPARASITIC PRODUCTS, INSECTICIDES AND REPELLENTS
Rehabilitation (BA-BB)
Krankheiten des Auges und der Augenanhangsgebilde
Qualifier value (qualifier value)
Operationen an den weiblichen Geschlechtsorganen (65â71)
Operationen am endokrinen System (06â07)
Organism (organism)
DERMATOLOGICALS
Krankheiten des Verdauungssystems
Clinical finding (finding)
VARIOUS
MUSCULO-SKELETAL SYSTEM
GENITO URINARY SYSTEM AND SEX HORMONES
Operationen am Verdauungstrakt (42â54)
Krankheiten des Nervensystems
Neubildungen
Operationen am hämatopoetischen und lymphatischen System (40â41)
Operationen am respiratorischen System (30â34)
Krankheiten des Urogenitalsystems
Operationen an den Harnorganen (55â59)
Krankheiten des Kreislaufsystems
ANTIINFECTIVES FOR SYSTEMIC USE
Operationen am Nervensystem (01â05)
Endokrine, Ernährungs- und Stoffwechselkrankheiten
CARDIOVASCULAR SYSTEM
NERVOUS SYSTEM
Psychische und Verhaltensstörungen
Specimen (specimen)
Geburtshilfliche Operationen (72â75)
Operationen an den männlichen Geschlechtsorganen (60â64)
ALIMENTARY TRACT AND METABOLISM
Krankheiten des Atmungssystems
Operationen an Nase, Mund und Pharynx (21â29)
Massnahmen und Interventionen nicht anderswo klassifizierbar (00)
ANTINEOPLASTIC AND IMMUNOMODULATING AGENTS
Body structure (body structure)
Operationen am kardiovaskulären System (35â39)
This is a combined dataset which contains clinical routine data for (a) SPAC participants via SPHN which was used to compare with manually collected data saved in the study database, to assess if routine healthcare data could supplement or replace traditional data collection methods, and for (b) children who visited the collaborating clinics in SPAC but did not participate in the study, which was used to compare with data from SPAC participants to evaluate the generalizability of the results from the SPAC cohort.
Clinical routine data for SPAC participants and for non-participants
Reuse of data of SPHN-SPAC is described in the SPHN-SPAC Data Project Consortium Agreement. Briefly, data may be shared under the prerequisites listed in the SwissPedHealth General Terms and Conditions (GTC), if they meet the following conditions: 1. the Project Executive Board must approve the sharing the data, 2. If the data includes personal information, each person or group that provided the data must give their individual, written consent, 3. Only parties or third parties who have signed an agreement with all project members (and approved by the Project Executive Board) can access the data.4. The sharing of data must follow all relevant laws, particularly those about human research and data usage, 5. The data cannot be used for profit or commercial purposes, 6. If required by law, the sharing must have approval from ethical committees or other relevant authorities. Contact point: claudia.kuehni@unibe.ch.
Enrolled in SPAC study during the above period
Patients who visited the pneumology clinics between the period and at the age described above and did not participate in the SPAC study or refuse the general consent.
Institute of Social and Preventive Medicine, University of Bern
The identification of underlying genetic and molecular mechanisms is an essential prerequisite for personalized medicine. Building on our preliminary data created in Phase 1, we aim to develop (Phase 2) and test (Phase 3) a Swiss multi-omics workflow to identify rare diseases in children with extreme phenotypes. This will be performed in two further phases. In Phase 2, we will include children from existing cohorts and re-use samples and data to develop novel computational methods to integrate multi-omics data into a diagnostic workflow. This will be based on samples and data with ethical approval already in place. In Phase 3, we will prospectively recruit children with extreme phenotypes from Swiss hospitals to test the multi-omics workflow (done in addition to routine diagnostic procedures) and identify rare diseases causing extreme phenotypes. We will also recruit patient's relatives (healthy parents and siblings) as controls for genomic analysis
SwissPedHealth: Development of a multi-omics workflow to discover rare diseases in children with extreme phenotypes - MOMIC
Age > 20 years, Insufficient quality of language communication or cognitive capacity to understand study procedures and to give consent, Documented refusal of MOMIC informed consent (Phase 3)
We will exclude samples, for which a documented refusal of further use is available (Phase 2)
Re-use of patient samples and data from existing cohorts (MMA Study: BASEC Nr. PB_2020_00053, SPSS: KEK-Nr. 029/2011, GIS: KEK Nr. 2015-0555, EUCLIDS: UK Research Ethics Committee Nr. 11/LO/1982). Only for samples, for which ethics approval and consent is available (Phase 2)
Patients attended in pediatric hospitals, All pediatric divisions, Age < 20 years, Male and female, In- and outpatients, acceped and signed MOMIC informed consent (Phase 3)
Prospective, observational study (Phase 3)
Personalized Health and Related Technologies
human genetic, epigenomic and genomic data
Distribution of Drug Plasma Level Data and associated Clinical Data of Fludarabine
The SPHN ADONIS dataset is a high-resolution, multi-center clinical dataset designed to support research on the early detection of neonatal sepsis using machine learning. It includes data from over 15'000 neonates admitted to the neonatal intensive care units of three major Swiss hospitalsâCHUV, USZ, and KiSpiâbetween 2007 and 2022. The dataset comprises >400 confirmed sepsis cases, >90 necrotizing enterocolitis cases, and a large control group. Data are collected at one-minute intervals and cover more than 800 variables, including vital signs, laboratory results, treatments, and device outputs. All data are semantically harmonized using SPHN standards and mapped to international ontologies such as SNOMED CT, LOINC, and ICD-10. Stored in RDF format and hosted on the secure BioMedIT infrastructure, the dataset is interoperable, pseudonymized, and ethically approved for research use.
ADONIS Cohort: High-Resolution Clinical Data for Neonatal Sepsis Detection
SwissPedHealth MOMIC Phase 3 Clinical Data (2025.1)
The dataset contains drug plasma level data of busulfan and complementary clinical data of patients receiving busulfan-based conditioning regimens for stem cell transplantation. The data will be used in pharmacokinetic models to better understand the pharmacokinetics of this drug and therefore be able to optimise the dosage regimens for children.
Drug Plasma Level Data and associated Clinical Data of Busulfan
Access to the SwissPedDW Demonstrator project data is regulated by the SwissPedDW governance bodies. Approval is given by the SwissPedDW Reuse and Access Committee. Contact: paolo.paioni@kispi.uzh.ch.
Routinely measured drug levels (TDM: Therapeutic Drug Monitoring) for Busulfan
SwissPedDW Data Access and Re-Use Committee
The dataset contains drug plasma level data of fludarabine and complementary clinical data. The data will be used in pharmacokinetic models to better understand the pharmacokinetics of this drug and therefore be able to optimise dosage regimens.
Drug Plasma Level Data and associated Clinical Data of Fludarabine
Any coexisting medical or psychological condition that would preclude participation in the required study procedures, as judged by the treating physician
Any condition which precludes initiation of treatment (e.g. breast feeding, pregnancy, infections etc.)
Routinely measured drug levels (TDM: Therapeutic Drug Monitoring) for Fludarabine
HLA-identical and related haplotypical donors
healthcare-related administrative data, including on dispensations, reimbursement claims and reimbursements
The Swiss Paediatric Airway Cohort (SPAC) is an ongoing study that includes children seen at pediatric pulmonology clinics across Switzerland, where we collect questionnaires and clinical data from hospital records. However, manual collection of clinical data is time-consuming, and frequent updates are needed to track patients across multiple visits, increasing the risk of missing data. In the SPHN-SPAC project, we obtained clinical data for SPAC participants via SPHN and compared it with manually collected data to determine whether routine healthcare data could supplement or replace traditional data collection methods. Additionally, we obtained clinical information from children who visited the clinics but did not participate and compare it with the data from SPAC participants to evaluate the generalizability of the SPAC cohort results. Lastly, we aimed to leverage routine healthcare data to obtain complete longitudinal information, including test results (e.g., lung function) and healthcare utilization details (e.g., emergency visits, hospitalizations).
Using routine health care data to facilitate clinical cohort studies (SPAC)
Enrolled in SPAC for the SPAC data, or patients who visited the pneumology clinics between the period and at the age described above and did neither participate in the SPAC study nor refuse the general consent for the non-SPAC data.
A subset of the LUCID registry including only concepts required for monitoring on low value care indicators.
Use of the data set is currently restricted to member institutions of the project consortium.
For included patients, only administrative cases (stays) with the following criteria should be included. If a given administrative case follows the criteria, all its associated data for the list of reused SPHN concepts should be included: Age >= 18 years at admission, Inpatient setting, Acute care (Hospital stay "Class A"), Period: from the beginning of hospital stay after 01/01/2014 until the current day of cohort creation, Length of stay >= 24h consecutively in at least one units/subunits of interest. For included patients, patient-associated data from the following concepts should be included regardless of their association with an administrative case (i.e. including before 2014 and regardless of the unit): Allergy, Administrative Sex, Birth Date, Death, Billed Diagnosis.
Infections show a range of diverse phenotypes with variable impact on clinical course and outcomes. Our NDS proposal focuses on this heterogeneity within critically ill patients with severe infections using a combined clinical- and data-driven approach for an improved personalized assessment, characterization and outcome prediction on patients with infections. We will integrate rich and diverse data sources to predict outcomes relevant in the lighthouse project and nested projects
Personalized, data-driven prediction and assessment of Infection related outcomes in Swiss ICUs
Use of the dataset is currently restricted to member institutions of the project consortium.
Non-ICU patients, patients under 18 years of age, or patients who have declined consent for data use
ICU patients aged 18 and older who have provided general consent (GC) or whose consent status for data use is unknown
Concept Availability associated with the distribution
Glasgow coma score (observable entity)
Richmond Agitation Sedation Scale score (observable entity)
Paediatric Index of Mortality 3 (assessment scale)
Paediatric Index of Mortality 2 (assessment scale)
Sequential Organ Failure Assessment score (observable entity)
Serum specimen (specimen)
Deoxyribonucleic acid specimen (specimen)
Plasma specimen with citrate (specimen)
Urine specimen (specimen)
Plasma specimen (specimen)
Cerebrospinal fluid specimen (specimen)
Plasma specimen with ethylenediamine tetraacetic acid (specimen)
Buffy coat (specimen)
Gleason grading system for prostatic cancer (staging scale)
Gleason scoring system for malignant neoplasm of prostate (staging scale)
World Health Organization grading system for urothelial carcinoma (staging scale)
World Health Organization classification of tumors histologic grading system (staging scale)
Radiographic imaging procedure (procedure)
Magnetic resonance imaging (procedure)
Computed tomography (procedure)
Positron emission tomography (procedure)
This dataset includes a small paediatric clinical reference data pool (PCRDP) with clinical, whole genome sequencing and metabolomics data of healthy children. The data will be used to identify biomarkers which provide information on the activity of drug metabolising enzymes and drug transporters between birth and adolescence.
Genomics and Metabolomics Data of a Healthy Children Cohort
Any diagnosis of severe injuries/diseases or chronic conditions (judged by Kispi clinician)
Measurement of specific IgE (rAra h 2, rCor a 9/rCor a 14, rAna o3, rJug r 1)
data on pathogens that impact human health
data from research cohorts, questionnaires and surveys related to health, after the first publication of the related results
Melanoma retrospective cohort of the SPO-NDS
Currently restricted to the use within the consortium. Anyone considering reuse of data from the SPO-NDS project must comply with the SPO-NDS CA, in particular sections 6.1, 6.2. 6.4, 6.5 and 6.6.
Overall criteria: patients treated for multiple cancers
Melanoma-specific criteria: Uveal melanoma (ICD-10 C69)
Overall criteria: age at first date (incidence datetime) of diagnosis older than 18 years, approval of general consent, treated within the UH, biopsy assessed by NGS, date of NGS on or after 1st of January 2015
Melanoma-specific criteria: ICD-10 code C43 or diagnosis text contains 'melanoma|melanom|melanome', treated with anti-PD-1 based or anti-PDL-1 based therapies
Special concept (special concept)
Physical object (physical object)
RNA/DNA/Metabolomics/Proteomics/Transcriptomics Data (Phase 3)
Access to MOMIC phase 3 specific data is regulated through its corresponding DPCA
Insufficient quality of language communication or cognitive capacity to understand study procedures and to give consent
Documented refusal of MOMIC informed consent
acceped and signed MOMIC informed consent
Research project involving human subjects, prospective, observational study (Phase 3)
Distribution of SwissPedHealth Nested Project 1: Anthropometric routine data in Switzerland (SwissPedGrowth)
ADONIS 2024.1 Retrospective Cohort Phase 3 Clinical Data (2024.1)
Distribution of Personalized, data-driven prediction and assessment of Infection related outcomes in Swiss ICUs
National Data Streams (NDS) are set to play an important role in making Swiss healthcare more effective, cost-efficient, data-driven, and evidence-based. Our project focuses on hospital inpatient quality of care and will attempt to find ways of improving healthcare processes in Swiss hospitals. As both the number of patients and the cost of acute care are expected to increase in the future, avoiding healthcare waste, while satisfying inpatients expectations, is key for the Swiss health system. Since value-based healthcare aims at preventing low-value healthcare processes while keeping costs under control through a patient-centered outcome orientation, and within an evidence-based and data-informed framework, our broad objective is to build an NDS permitting to monitor and study the quality of care in Swiss hospitals using existing hospital data and Patient Reported Outcomes (PROs). While the current project will focus on hospitalized patients in medicine who represent the largest part of hospitalizations, the project's infrastructure and processes are applicable for hospitalized patients from other specialties.
Low Value of Care in Hospitalized Patients - a National Data Stream on Quality of Care in Swiss university hospitals (LUCID)
The Cohort Demonstrator project facilitates the secure and efficient transfer of routine clinical data from multiple University Hospital Clinical Data Warehouses (CDWHs) to the Swiss Transplant Cohort Study (STCS). To facilitate patient selection and linkage, the project implemented dedicated tools (IDEAL) for managing study participants. IDEAL (and Horus, at CHUV) supports the identification and secure linking of patient identifiers between the study and the hospital, ensuring compliance with data protection requirements and enabling seamless downstream data transfer. A key outcome of the project is the development of the Cohort Hospital Integration Layer (CHIL). CHIL ingests multisite RDF data using consistent terminology across hospitals and provides a user-friendly interface for querying study-specific datasets. This data is then integrated into the STCS research database, enhancing the data granularity, completeness, and usability of STCS data, unlocking new possibilities for real-world data analyses, AI-based research, and embedded sub-studies. This project also highlights the need for harmonised procedures and infrastructure across institutions to support sustainable data sharing practices. The solutions developed are designed to be reusable and adaptable, offering a blueprint for other cohorts and research initiatives aiming to harness routine clinical data across institutional boundaries.
Cohort demonstrator: Full integration of a national cohort into the SPHN infrastructure
STCS data enriched with hospital CDWH data, will be available to researchers following approval of an application ('nested STCS project') by the STCS Data Center, STCS scientific committee, data governance board, and the competent ethics committee. The data provider agreed to the re-use of the CDWH data by agreeing with the DTUA/DTPA between Hospital (as the data provider), STCS (as the data recipient), and BioMedIT network (as the data processor).
STCS patients (solid organ transplants recipients) at USB, CHUV and Inselspital
1.83 (1791 Male, 978 Female). Note: gender information missing for 158 patients
Distribution of INSEL clinical routine dataset (2025.1)
This dataset describes the data, which is available in SPHN format for HUG.
Access is given by internal validation pursuant to institutional guidelines and processes and approval by the Data Access Body.
Data available in the Clinical Data Platform of all patients with administrative cases since 2018 and general consent is accepted.
The SwissPedGrowth dataset is a comprehensive collection of routinely gathered pediatric clinical data from participating Swiss children's hospitals. It includes anthropometric measurements (height, weight, head circumference), clinical parameters, and laboratory values obtained from both inpatient and outpatient visits. Data are collected from January 2017 to December 2025 and are enriched with socioeconomic information (Swiss-SEP) via linkages with federal datasets (Swiss National Cohort, FSO). This pseudonymized dataset - excluding patients who rejected general consent - aims to use multi-institutional pediatric EHR data from Switzerland (SwissPedHealth) and compare them internationally to assess the feasibility of retrieving anthropometric data from EHRs in Switzerland, investigate data quality and validity, and answer simple research questions.
SwissPedHealth Data Repository (NDS SPH Registry)
SwissPedHealth Nested Project 1: Anthropometric routine data in Switzerland (SwissPedGrowth)
Access to the NDS data is regulated through the SwissPedHealth infrastructure consortium agreement V2.0 18.11.2022. As brief explanation: · When planning to carry out a project using data from the SwissPedHealth NDS, you will need to set up a data project consortium agreement (DPCA) involving all participating partners. Note that this should include "internal" SwissPedHealth partners and "external" partners, i.e. those not part of the SwissPedHealth NDS Infrastructure Consortium. · For the DPCA, projects should consider the SwissPedHealth general terms and conditions (GTCs) and, wherever possible, try to adopt them without or with minor deviations. This will facilitate the process of legal review and signing for all "internal" partners, since the GTCs will have already been reviewed as part of the development and adoption process. If deviations are required, these will need to be specified in the DPCA, and should be highlighted during the legal review of the DPCA. · Note that the following additional documentation will be required to complete the DPCA: Project funding application/Proof of funding, Study protocol and Ethical approval. In case the latter is not available it should be added as soon as available, and the DPCA cannot be executed without evidence of ethical review and approval. All parts highlighted in yellow in the DPCA template need to be completed/amended. · All DPCAs will need to incorporate a data transfer and use agreement (DTUA) and data transfer and processing agreement (DTPA). These are included in the SwissPedHealth DPCA template, reflecting SPHN requirements. Please note that adaptations may be necessary in cases where the Data Processors are not one of the BioMedIT nodes (SENSA - Lausanne, SciCORE - Basel, SIS - Zurich). For the DTUA section, each project will need to describe and depict the planned data flow as well as data and metadata to be transferred. All parts highlighted in yellow in the DTUA and DTPA templates need to be completed/amended. Access to SwissPedHeath project specific data (from the lighthouse or nested projects) is regulated through their corresponding DPCAs.
Patients treated between 01.01.2017-28.02.2023: if active general consent refusal was given
thus those informed are included. Patients treated after 28.02.2023: if general consent was not signed.
All children and adolescents (<20 years) who visited participating SwissPedHealth clinics (both inpatient and outpatient) during the study period
Observational, retrospective cohort study
Pharmaceutical / biologic product (product)
Distribution of Genomics and Metabolomics Data of a Healthy Children Cohort
data on factors impacting on health, including socioeconomic, environmental and behavioural determinants of health
General information on all patients allowing to identify t-MN patients
Therapy-related myeloid neoplasms after cytotoxic treatment
(i) Approved protocol, (ii) DTUA with CHUV, HUG, Insel and USB, and (iii) approval of Main Project Leader Prof. Sabine Blum based on a joint decision with project parties. Contact: Sabine.Blum@chuv.ch
Patients younger than 18 years old at time of protocol approval
Patients with documented refusal of subsequent use of their data for research
Cancers patients treated with chemotherapy or radiotherapy
Neoplasms after cytotoxic treatment dataset
Distribution of Drug Plasma Level Data and associated Clinical Data of Gentamicin, Vancomycin, Voriconazole
Distribution of SwissPedHealth Main Dataset
The dataset was derived from a data extraction of the USB CDWH for STCS patients followed at the USB. Corresponding patient records were identified using the linking log (STCS person IDs linked with Hospital person ID) of IDEAL provided to the CDWH. The extraction process was guided by an RDF schema covering 23 SPHN re-used concepts, such as 'Lab test', which included 17 different lab tests identified via LOINC codes. Transformation into RDF using the SPHN connector and transferred to CHIL after encryption with sett. Authorized researchers can browse and query this dataset on CHIL. From this dataset, approximately 500,000 records were processed and imported into the STCS research database, significantly enhancing the granularity of data available for research purposes.
Cohort Demonstrator USB dataset (2012-2024)
STCS patients (solid organ transplants recipients) at USB
STCS Scientific Committee and Data Governance Board
Neoplasm After Cytotoxic Treatment Cohort (2023.1)
Distribution of Multi Omics Data (Phase 2)
Kinderspital Zurich (KISPI), Margarete von Wantoch
Distribution of Paediatric clinical hospital dataset
Distribution of Therapy-related myeloid neoplasms after cytotoxic treatment
Myelodysplastic/Myeloproliferative Neoplasm Post Cytotoxic Therapy
Distribution of Cohort Demonstrator USB dataset (2012-2024)
Distribution of Cohort Demonstrator CHUV dataset (2007-2025)
Leveraging the potential of the routine health data for translational clinical data-driven research projects and real-world use cases through embedding the SPHN principles of interoperability and system permeability. The principal goal of the proposed INFRA project is to integrate the different data types, e.g. laboratory, physiological values, and clinical symptoms and visualize the patients' current status. It will be developed aiming at an improvement of the detection of risk factors and patterns of surgical infections and a multidimensional visualization of severity and periodicity.
In accordance with a Data Governance Working Group strategy considering institutional data governance and researchers' interest in compliance with Swiss legal and ethical regulations. Access is given upon approval of the Data Givernance Commission Insel Gruppe, directorate of research at Inselgruppe AG. Contact point: Forschungssupport.DLF@insel.ch
The exclusion criteria that were applied for excluding patients from the project. These are specific characteristics or attributes of members of the target population which render them unsuitable to contribute data to the project. For the observational study "Prediction of postoperative infections by strategic data imputation and explainable machine learning", the data from patients with a documented rejection for the use of healthcare data were excluded.
The inclusion criteria that were applied for including patients as viable data points into the project. These are specific characteristics or attributes that members of the target population must possess such that their data can be considered for the project. While the goal was to build a generalisable semantic layer in our cDWH, we didn't restrict the inclusion, but tried to integrate a broad patient cohort to represent the comprehensive Insel patient cohort. All valid patients records available in the Insel Data Platform with a discharge between 2020-01-01 - 2024-12-31 were included into the project-specific data mart in order to build a project-specific ontology and test the validation rules. For the observational study "Prediction of postoperative infections by strategic data imputation and explainable machine learning", a data set of 91,794 patient cases with surgeries recorded in the Bern University Hospital from May 2014 to September 2022 was analysed, Inclusion criteria: Presence of a surgical procedure and at least one laboratory value in the first 30 days after surgery. For the Data Driven Diagnosis Sepsis Cohort, the cases of the patients treated at Insel Group 2020-01-01 - 2024-12-31 were used for the calculation of the SOFA and Phoenix score.
Distribution of Clinical gait analysis data for cerebral palsy and toe walking patients
Index of activities of daily living (assessment scale)
Visual analog pain scale (assessment scale)
Katz activities of daily living (assessment scale)
Mini-mental state examination (assessment scale)
Richmond Agitation Sedation Scale (assessment scale)
Mini-Cog brief cognitive screening test (assessment scale)
Finnegan Neonatal Abstinence Scoring Tool (assessment scale)
National Early Warning Score (assessment scale)
Confusion Assessment Method (assessment scale)
Eastern Cooperative Oncology Group scale for physical assessment (assessment scale)
Apgar score (assessment scale)
Frailty Index (assessment scale)
Glasgow coma scale (assessment scale)
Montreal Cognitive Assessment version 8.1 (assessment scale)
Montreal Cognitive Assessment version 7.1 (assessment scale)
Verbal Rating Scale for pain intensity (assessment scale)
Nutritional Risk Screening 2002 (assessment scale)
Abbreviated injury scale (assessment scale)
Braden Scale (assessment scale)
Simplified Acute Physiology Scale III (assessment scale)
Charlson Comorbidity Index (assessment scale)
Neonatal Infant Pain Scale (assessment scale)
Instrumental activities of daily living (assessment scale)
Tinetti assessment scale (assessment scale)
Geriatric depression scale 4 item form (assessment scale)
Simplified acute physiology scale II (assessment scale)
Sequential Organ Failure Assessment (assessment scale)
Blood specimen (specimen)
Tissue specimen (specimen)
Positron emission tomography with computed tomography (procedure)
Mammography (procedure)
Nuclear medicine imaging procedure (procedure)
Ultrasonography (procedure)
Orthopantogram (procedure)
Therapy-related myeloid neoplasms (t-MNs) are hematologic cancers that are caused by treatments administered for another primary cancer and are among the most feared side effects of chemotherapy or radiotherapy. Incidence of t-MNs is of the order of a few percent, which makes them difficult to study in a single hospital. Here, we take advantage of the Swiss Personalized Health Network initiative, and in particular the Swiss Personalized Oncology network, to screen a large population of patients (100,000 to 200,000) that have received chemotherapy in four university hospitals in Switzerland. We leverage the SPHN infrastructure to be able to access their data quickly and securely and detect possible t-MNs. After local validation and data completion for the 100-200 expected cases, we will be able to calculate t-MN risk and describe t-MN patient characteristics and outcomes. Since results will be based on real-world data collected in Switzerland with local standard of care and clinical context, the results will be directly relevant to Swiss patients, authorities, as well as the scientific and medical community.
The dataset comprises both raw and processed data across various omics types, including RNA, DNA, metabolomics, proteomics, and transcriptomics. These samples, originating from the retrospective phase (Phase 2) of the project, were biobanked by the SwissPedHealth Lighthouse Project, with purified materials prepared by the Lighthouse team. The samples were subsequently sent to the Swiss Multi-Omics Center (SMOC) for processing, such as DNA sequencing. The resulting multi-omics data were transferred to BioMedIT, typically in formats such as FASTQ. Both raw and processed data are stored within the BioMedIT infrastructure
0 - 16 years (for the Immune cohort); N/A (at the moment for the other cohorts)
Consent for reuse of samples must be available.
Samples and data of children with extreme phenotypes in Phase 2 arise from existing cohorts where consent to perform omics in stored biospecimens are already available. Conditions for data reuse must be determined with the cohort's responsible PI (not within SwissPedHealth)
Samples with a documented refusal for further use is excluded
Phase 2 Cohort (metabolic cohort: elevated homocysteine in plasma)
89:61 (the number is available for the metabolic cohort)
Retrospective study from existing cohort (Phase 2)
This dataset describes the data, which is available in SPHN format for USB.
Access is given by internal validation pursuant to institutional guidelines and processes and approval by the Data Access Body. A request can be made using the DKFonline form (exceptional) https://dolphin.dkfbasel.ch/contactform#en
Distribution of Federated SPHN clinical routine dataset (2025.1)
personal electronic health data automatically generated through medical devices
Continuity Assessment Record and Evaluation (CARE) survey
Children's Preventative Health System Attachments
The SPHN Federated Clinical Routine Dataset consists of standardized and semantically encoded clinical data available in the SPHN format at participating hospitals. Currently, it includes data from six Swiss hospitals. The dataset covers all patients with a clinical case since 2018 who have signed the general consent. Each hospital retains its data locally and publishes corresponding metadata in the SPHN Metadata Catalog for discoverability. For research projects, subsets of this dataset can be requested through the respective hospital-specific governance processes.
Dataset including routinely reported and documented primary care data from children a three Swiss paeditric practices
Access is regulated by the PREPP consortium and upon approval by its Executive Board. Contact point: jan.bonhoeffer@ukbb.ch
Patients from the children's hospitals in Basel, Bern, Geneva
Distribution of Manually collected clinical data and questionnaire data for SPAC participants
Distribution of Analysis of low value care indicators
PREPP Paediatric Clinical Hospital and Primary Care Data (2024.1)
Distribution of KISPI clinical routine dataset (2025.1)
The SwissPedGrowth dataset is a comprehensive collection of routinely gathered pediatric clinical data from participating Swiss children's hospitals. It includes anthropometric measurements (height, weight, head circumference), clinical parameters, and laboratory values obtained from both inpatient and outpatient visits. Data are collected from January 2017 to December 2025 and are enriched with socioeconomic information (Swiss-SEP) via linkages with federal datasets (Swiss National Cohort, FSO). This pseudonymized datasetâexcluding patients who rejected general consentâaims to use multi-institutional pediatric EHR data from Switzerland (SwissPedHealth) and compare them internationally to assess the feasibility of retrieving anthropometric data from EHRs in Switzerland, investigate data quality and validity, and answer simple research questions.
Patients treated after 28.02.2023: if general consent was not signed.
Patients treated between 01.01.2017-28.02.2023: if active general consent refusal was given, thus those informed are included
Stroke risk (assessment scale)
Intensive Care Delirium Screening Checklist (assessment scale)
Tinetti balance and gait scale (assessment scale)
Patient satisfaction score (assessment scale)
Generalized Anxiety Disorder 7 item scale (assessment scale)
Health of the Nation Outcome Scale for children (assessment scale)
Strength, Assistance walking, Rising from chair, Climbing stairs and Falls questionnaire (assessment scale)
National Institutes of Health stroke scale (assessment scale)
Sexual health inventory for men (assessment scale)
Pain Assessment in Advanced Dementia scale (assessment scale)
Health of the Nation Outcome Scale (generic version) (assessment scale)
EuroQoL five dimension five level questionnaire (assessment scale)
Clinical chronic obstructive pulmonary disease questionnaire (assessment scale)
ABC behavioral checklist (assessment scale)
Functional independence measure (assessment scale)
Barthel index (assessment scale)
Edmonton Symptom Assessment System (assessment scale)
Clinical opiate withdrawal scale (assessment scale)
Short falls efficacy scale - international (assessment scale)
Pain intensity rating scale (assessment scale)
Edinburgh postnatal depression scale (assessment scale)
Quality of life scale (assessment scale)
Revised Face, Legs, Activity, Cry, Consolability scale (assessment scale)
Hospital anxiety and depression scale (assessment scale)
Positive and negative syndrome scale (assessment scale)
Short Physical Performance Battery (assessment scale)
Mini Nutritional Assessment (assessment scale)
Modified checklist for autism in toddlers (assessment scale)
Impact of event scale (assessment scale)
Health of the Nation Outcome Scales (assessment scale)
Hamilton Anxiety Rating Scale (assessment scale)
Nine Equivalents of Nursing Manpower Use Score (assessment scale)
Braden Q assessment scale (assessment scale)
Montgomery-Ã sberg depression rating scale (assessment scale)
Harvey and Bradshaw index (assessment scale)
Timed up and go mobility test (assessment scale)
Medical outcomes study short form general health survey (assessment scale)
Ãchelle de Douleur et d'Inconfort du Nouveau-né (assessment scale)
Karnofsky performance status (assessment scale)
Medical Research Council motor power scale (assessment scale)
Epworth Sleepiness Scale (assessment scale)
Beck depression inventory (assessment scale)
Symptom checklist (assessment scale)
Amyotrophic Lateral Sclerosis Functional Rating Scale Revised (assessment scale)
Faces Pain Scale - Revised (assessment scale)
Addiction Research Foundation Clinical Institute Withdrawal Assessment for Alcohol (assessment scale)
Geriatric depression scale short form (assessment scale)
Fagerstrom test for nicotine dependence (assessment scale)
Falls risk assessment score for the elderly (assessment scale)
International Consultation on Incontinence questionnaire (assessment scale)
Borg scale (assessment scale)
Postural Assessment Scale for Stroke Patients (assessment scale)
Gugging Swallowing Screen (assessment scale)
Acute physiology and chronic health evaluation II (assessment scale)
Frontal assessment battery (assessment scale)
Voice handicap index (assessment scale)
Distribution of ADONIS Cohort: High-Resolution Clinical Data for Neonatal Sepsis Detection
The goal of the Swiss Personalized Oncology (SPO)-NDS is to build and extend the existing infrastructure, datasets, and know-how developed over the first 3 years of the Swiss Personalized Oncology SPHN Driver project. The SPO-NDS will aim to consolidate the clinical data acquisition, finalizing the extraction of the core data set at the 5 University Hospitals and at the Swiss Group for Clinical Cancer Research (SAKK), and pursuing the natural language processing applications to enrich the data set. In addition, high value cohorts have been and will be assembled in cancer types treated with immuno-oncology (IO) therapies that will allow comparative immunomics between highly IO sensitive tumors (e.g., melanoma, lung-cancer, triple-negative breast cancer (TNBC)) to less sensitive (e.g., MSI-CRC, hormone receptor-positive breast cancer). Using the momentum of the Tumor Profiler (TuPro) initiative, single-cell and -omics data will now be at the center of the program including NGS, IMC, digital pathology, as well as functional drug screening to drive therapeutic decisions within the existing molecular tumor boards.
Swiss Personalized Oncology National Data Stream (SPO-NDS)
Retrospective cohort study and prospective cohort study
EPFL - Swiss Federal Technology Institute of Lausanne
Swiss Group for Clinical Cancer Research
HES-SO University of Applied Sciences and Arts Western Switzerland
Distribution of Drug Plasma Level Data and associated Clinical Data of Busulfan
Fluoroscopy (procedure)
Imaging guided biopsy (procedure)
Needle biopsy using ultrasonographic guidance (procedure)
Imaging (procedure)
Point of care diagnostic ultrasonography (procedure)
Angiography (procedure)
Computed tomography guidance for needle biopsy (procedure)
Plain X-ray (procedure)
Biopsy using fluoroscopic guidance (procedure)
Nine Equivalents of Nursing Manpower Use Score (observable entity)
Paediatric Index of Mortality 3 score (observable entity)
Personalized, data-driven prediction and assessment of Infection related outcomes in Swiss ICUs (IICU)
Due to the unique epidemiology, developmental changes, and high vulnerability of children, there is an urgent need to continuously improve health care based on real world pediatric data. The digital transformation is a unique opportunity to shape a data-driven, agile, learning health care system and deliver more efficient and personalized care to children and their families. The goal of SwissPedHealth is to build a sustainable and scalable infrastructure to make routine clinical data from pediatric hospitals in Switzerland interoperable, standardized, quality-controlled, and ready for observational research, quality assurance, trials, and health-policy creation. SwissPedHealth is one of four National Data Streams co-funded by the Swiss Personalized Health Network (SPHN) and the ETH focus area Personalized Health Related Technologies (PHRT). SwissPedHealth develops modular governance and regulatory strategies in collaboration with clinical data warehouses, the Data Coordination Center, Biomedical Information Technology Network, and others. The data stream contains work packages focusing on: 1) governance and implementation of standardized data collection, 2) nested projects to test the feasibility of the data stream, 3) a lighthouse project that enriches the data stream by integrating multi-omics data, aiming to improve diagnoses of rare diseases, and 4) engagement with families through patient and public involvement activities and interviews.
Pediatric Personalized Research Network Switzerland (SwissPedHealth) - a Joint Pediatric National Data Stream
informed consent for patients recruited through the Lighthouse Project (Prospective cohort, Phase 3)
Retrospective cohort study (Nested Projects, Lighthouse Project Phase 2)
Prospective, observational study (Lighthouse Project Phase 3)
for the Nested Projects, exception NP4 administered in-patients between 2021-2022 only
for patients recruited through the Lighthouse Project (Prospective cohort, Phase 3)
This dataset describes the data, which is available in SPHN format for CHUV.
CHUV Clinical Routine Dataset SPHN (2025.1)
This dataset contains clinical data collected at baseline and during follow-up visits for SPAC participants enrolled through Insel Gruppe AG, University of Bern Children's Hospital, University Children's Hospital Zurich - Eleonore Foundation and Luzerner Kantonspital . The data was manually extracted from the hospital electronic health record and entered into the study database. In addition to clinical information, the dataset includes selected baseline characteristics and variables related to self-reported emergency department visits and hospitalizations due to respiratory issues, which was reported in questionnaires answered by the participants.
Manually collected clinical data and questionnaire data for SPAC participants
Enrolled in SPAC study during the above period through the pneumology clinics at Insel Gruppe AG, University of Bern Children's Hospital, University Children's Hospital Zurich - Eleonore Foundation and Luzerner Kantonspital
The dataset contains clinical gait analysis data for two populations, cerebral palsy and toe walking patients, that were collected at two different centers, the clinical gait analysis services at UKBB and HUG. The dataset contains physical examination data (anthropometric measurements, range of motion measurements, muscle strength assessments and spasticity assessments), surgical procedure data, and instrumented gait analysis data (spatio-temporal parameters, gait scores, kinematics, kinetics and electromyography data), as well as SOP for both centers.
Clinical gait analysis data for cerebral palsy and toe walking patients
The data can be accessed and used by the persons authorized to access the BioMedIT space of the EVIGAITCP project. Other interested parties may contact the project leader (morgan.sangeux@ukbb.ch) to discuss reuse conditions.
A documented refusal from the patient or the legal representative(s) is the main exclusion criteria. In addition, cases with missing or inaccurate data will be excluded.
The project will include all data available from UKBB and HUG, with the following inclusion criteria: male or female, children and adults with a neuromuscular disorder, including cerebral palsy and toe walking. It is important to include the maximum time span for both centres in order to maximise our capacity to assemble treatment and control groups from unicentric and multicentric datasets whenever possible. By control group, we mean the group of patients who did not undergo any treatment between two gait data acquisitions.
EVIGAITCP project partners, UKBB as responsible organization. Contact point: mor-gan.Sangeux@ukbb.c
Acute Myeloid Leukemia Post Cytotoxic Therapy
This dataset describes the data, which is available in SPHN format for USZ.
Data available in the Clinical Data Platform of all patients with administrative cases since 2012 and general consent is accepted.
University Hospital Zurich, Data Governance Board
Dataset including routinely reported and documented hospital data from children in three Swiss hopsitals
All patients from the children's hospitals in Basel, Bern, Geneva
Distribution of USB clinical routine dataset (2025.1)
The dataset consists of phenotypes extracted from free-text clinical reports collected over 30 years, where individuals were referred to with suspicion of a remethylation disorder (RD). All individuals presented with elevated plasma homocysteine levels. Phenotype annotations were extracted using a semi-automated pipeline and reviewed by at least two annotators in consultation with medical experts. The dataset is structured in RDF format and serves as a benchmark for the newly developed SPH Concept 'Phenotypic Observation'
Phenotypic Observation Remethylation Disorder (Phase 2)
Samples excluded for which a documented refusal of further use is available
Phase 2 metabolic cohort: Elevated homocysteine in Plasma, Phenotypic Observation connected to the patient
Distribution of MOMIC RDF Dataset (Phase 3)
The dataset contains drug plasma level data of gentamicin, fludarabine and vancomycin and complementary clinical data. These data will be used in pharmacokinetic models to better understand the pharmacokinetics of these drugs and therefore be able to optimise the dosage regimens for children.
Drug Plasma Level Data and associated Clinical Data of Gentamicin, Vancomycin, Voriconazole
Renal replacement therapy (Haemodialysis, -filtration, Peritoneal dialysis)
Routinely measured drug levels (TDM: Therapeutic Drug Monitoring) for one of the three drugs requested for the main project
The SPHN Metadata Catalog provides an overview of health research datasets available in Switzerland. It describes standardized metadata of each dataset, including the scope of the data, creation date, and access conditions. While the underlying data come from diverse sources and domains, the metadata comply with the HealthDCAT-AP (https://healthdataeu.pages.code.europa.eu/healthdcat-ap/releases/release-6) standard of the European Health Data Space (EHDS). To make your data findable in the catalog, write an email to: fair-data-team@sib.swiss
This dataset was obtained from a data extraction from CHUV CDWH, for STCS patients followed at CHUV. Corresponding patient records were identified using the linkage log (STCS person IDs linked with Hospital person ID) of HORUS. The RDF Schema used to extract the data re-used 23 SPHN concepts, such as 'Lab Test', which included 17 different types of laboratory tests identified by LOINC codes. Transformation into RDF using the SPHN connector and transferred to CHIL after encryption with sett. This data can be browsed and queried on CHIL by authorized researchers. By the end of the current week (06/08/2025), this data will be integrated into 3LC, the STCS research database. This data will increase the granularity of the data available for research.
Cohort Demonstrator CHUV dataset (2007-2025)
STCS patients (solid organ transplants recipients) at CHUV
1.83 Male (967 Male, 526 Female). Note: gender information is missing for 158 patients.
SPO-NDS Melanoma Retrospective Cohort (2024.1)
Distribution of Phenotypic Observation Remethylation Disorder (Phase 2)
American Society of Anesthesiologists physical status classification (assessment scale)
Geriatric depression scale (assessment scale)
Numeric Pain Rating Scale (assessment scale)
Neonatal Pain Assessment and Sedation Scale (assessment scale)
Verbal rating scale (assessment scale)
Endoscopic ultrasonography (procedure)
Single photon emission computed tomography (procedure)
Optical coherence tomography (procedure)
External camera medical photography (procedure)
Echocardiography (procedure)
Ocular fundus photography (procedure)
Intracranial intravascular ultrasound (procedure)
other human molecular data such as proteomic, transcriptomic, metabolomic, lipidomic and other omic data
This dataset describes the data, which is available in SPHN format for INSEL.
SPHN Federated Clinical Routine Dataset (2025.1)
Centre Hospitalier Universitaire Vaudois (CHUV)
Distribution of CHUV clinical routine dataset (2025.1)
Distribution of HUG clinical routine dataset (2025.1)
The PREPP project aimed to demonstrate the value of integrating paediatric primary care data with the national SwissPedHealth hospital data stream. Operating in pilot sites in Bern, Basel, and Geneva, the project extracted and linked data from primary care databases to hospital Clinical Data Warehouses (CDWs). An essential precondition for linking data from different healthcare providers, was pseudonymising the data through a two-stage hashing process. The project consolidated datasets using existing SPHN infrastructure to provide integrated data for research and public health.
PReparing PERsonalizEd PEdiatRic PRimaRy caRE (PREPP)
Distribution of Clinical routine data for SPAC participants and for non-participants
Distribution of Paediatric primary care dataset
Distribution of Melanoma Retrospective Cohort Dataset
Containing information to case, patient, procedures, diagnoses, comorbidities, microbiology, lab values, vitals, SOFA, MEWS score. The INFRA dataset conforms to the OMOP CDM v5.4 standard and can be exported through various means, such as OHDSI tools, R packages or as an CSV export. For the existing SPHN Concepts, the dataset can also be exported as a knowledge graph (.TTL) compliant to the SPHN RDF Schema.
This project aims to leverage existing observational cohort data from multiple centres to improve clinical decision making in persons with neuromuscular disorders, including cerebral palsy and those toe walking. The SPHN infrastructure will be used to merge rich datasets from two pilot centres: the clinical gait analysis services at UKBB and HUG. From this unique combined dataset, the project will determine the best possible treatments to improve walking in persons with neuromuscular disorders, by determining the causal effect of treatments.
Getting high level of evidence for surgical treatments from routine clinical data. A real-world testing of the SPHN infrastructure (EVIGAITCP)
SwissPedDW Fludarabine substudy (2024.1)
SPHN Federated Clinical Routine Dataset schema (2025.1)
This dataset describes the data, which is available in SPHN format for KISPI.
Phase 3: Development of a multi-omics workflow to discover rare diseases in children with extreme phenotypes. This study is a national multi-center prospective cohort study of n=140 patients aged from birth up to 20 years with extreme phenotypes admitted or referred to Swiss Children's Hospitals. We will obtain written consent and assent (if applicable) for all subjects taking part. We will collect blood samples from patients at presentation, alongside with routine clinical tests, and a skin biopsy. We will perform a buccal swab to patient's parents and siblings
This dataset describes the data which is available in SPHN across the participating hospitals.
Data available in the Clinical Data Platforms of all patients with administrative cases since 2018 and which accepted the general consent.
Refer to the Data Access Body for each individual hospital
In our previous SPHN infrastructure project SwissPKcdw, we successfully established a clinical data warehouse (CDW) to enhance access to clinical data of pediatric patients cared for at the University Children's Hospital Zurich (Kispi) and Basel (UKBB). We collected and pseudonymized drug plasma concentrations from routine drug monitoring together with the respective clinical information. These data were analyzed by population pharmacokinetic modelling to identify factors (e.g., age, weight, endogenous metabolites) which influence or correlate with the fate of a particular drug in the body. The resulting models allow to optimize and individualize drug dosage regimens. In the current demonstrator project, we aim to expand the previously built infrastructure to the remaining university children's hospitals in Switzerland. In addition to the drug plasma concentrations and clinical information we will include data on relevant genes involved in the metabolism of the drugs and on molecules that give information on chemical processes within the cells. These data will allow searching for additional endogenous metabolites with predictive potential for the pharmacokinetics of a drug in pediatric patients.
Optimising paediatric dosing regimens based on a clinical data warehouse (SwissPedDW)