Daten der Spitalinfrastruktur
Datensatzen über die verfügbare medizinische Infrastrukturen und Kapazitäten in der Schweiz
Data on hospital infrastructure
Collaboration on a dataset on available infrastructure and bed capacity for medical facilities in Switzerland.
The current mitigation strategy of COVID-19 is to "flatten the curve", which means to decrease the daily case load below a threshold level. This threshold is given by the maximum capacity of the health care system. To inform models with meaningful parameters we need detailed data on hospital infrastructure and bed capacities by hospital. This challenge aims to combine data on the capacities of the Swiss health care system from different sources and to produce an open and free data set, which can be used to inform modelling and public health strategies. Current Indicators, Methods and Data sources of interest are listed below, mirrored in our repository, where we also have an Issue tracker with open tasks.
We started a collaborative effort to establish a common data set where the community can contribute data in a moderated way. To contribute, you can:
- View the crowdsourced Data Package and OGD Data Schema to check the data baseline.
- Use our Online Form to submit individual data points or corrections.
- Visit the Issue Tracker to find out how you could contribute to automation & validation.
- Explore visualizations (ETH) and models (neherlab, plotti) that use this data.
- Join our Team Chat if you have any other questions or suggestions.
Indicators of interest
- N of hospitals in CH (with name and geolocation)
- N of beds by hospital
- N of ICU beds by hospital
- N of respirators by hospital
- average % bed availability pre-COVID-19 ("Bettenauslastung") by hospital
- N ICU nurses by hospital ("IPS Pflege")
An idea of the basic workflow we have in mind:
- Kennzahlen der Schweizer Spitalen from the Federal Office of Health lists all Swiss hospitals and large clinics, including the number of beds and other indicators as of 2017. This is the open data starting point for our project, even though it is rather out of date.
- The geolocations of hospitals and other attributes is available from SWISSNAMES3D from Swisstopo. You can see this if you search for Hospital on map.geo.admin.ch, which also has an open data map of hospital landing sites. Thanks @swiss_geoportal for your support.
- The list of intensive care units (ICU) and beds from the Swiss Society or Intensive Medicine (swiss-icu-cert) has been extracted by Jonas Herzog for his visualization.
- Gesundheitsdirektorenkonferenz lists of hospitals by canton, and might be more up to date than the BAG publication.
- Spitalverband H+ likely has updated data on all hospitals - we are trying to reach out.
- OBSAN - Hospitalisierungsrate in Akutspitälern can be downloaded in Excel format.
- Zürich open data and SITG Geneva are regional data sources with some additional fields, however missing capacity numbers or any other actionable indicators. We could reach out to see if there is more behind the scenes.
- Spitalfinder.ch could be a useful reference, might even be interested to support this. See their Datenquellen
- Nationalen Verein für Qualitätsentwicklung in Spitälern und Kliniken is referenced by Spitalfinder. All hospitals are required to register with them. "Ziel des ANQ ist, die Messresultate national vergleichend darzustellen, die breite Öffentlichkeit zu informieren und den Spitälern und Kliniken einen kontinuierlichen Verbesserungsprozess (KVP) zu ermöglichen."
- Kennzahlen der Schweizer Pflegeheime and Spitex vor Ort are databases of care homes, which could play a role in an expanded version of our database.
- Health insurers (Krankenkassen) in principle should have real-time data on hospital admissions and releases. It might be worth encouraging contacts there to join forces with others and make these data available in appropriately aggregated form. The comparis.ch insurance recommendation website maintains a list of hospitals used to reference providers.
- Expatica has a high ranked private list of hospitals with links.
- The List of hospitals in Switzerland on Wikipedia is probably the first place people would go to get an overview. They currently reference 2010 data! In German Wikipedia, see Kategorie:Krankenhaus in der Schweiz.
- @philshem and @sfkeller suggested OpenStreetMap extraction via scripts or a OSM Query for Switzerland, which can be turned into an OSM API (where polygons need to be processed separately). See also taginfo via @rastrau. We got advice from the developer of water-fountains/datablue, which could be used to import OSM data.
- Healthsites.io collects and monitors data about health facilities around the world based on OpenStreetMap. They have data management workflows, a standard data model and complete OSM tag list, an API, and simple tracking of "completeness of attributes", or indicators.
Swiss Hospital Data
This is a collaborative effort to establish a common data set about Swiss public medical infrastructure, where the community can contribute and manage data in a moderated way. Our goal is to improve the transparency and efficiency of data exchange about basic indicators, expanding on the existing available open government data.
This project was started at the Monitoring COVID-19 effects (#covid19mon) hackathon. Visit our challenge page for further details and tasks, some of which are in our current notes and backed up here. Please suggest additional data sources and ideas in the issue tracker.
:mag: Use our Online Form to submit individual data points or corrections.
:floppy_disk: Visit the Issue Tracker to find out how you could contribute to automation & validation.
:personwithpouting_face: Join our Team Chat if you have any other questions or suggestions.
:construction: This README is very much Work In Progress. :construction:
There is an initial Data Package which can be previewed here.
Please see the data folder to see all the datasets that we are working on.
Instructions: Accessible data files (ideally in simple data formats such as CSV, JSON and GeoJSON), as well as the raw data, are placed in the
datafolder. In this section you should mention the files and formats included. It is good to suggest purposes for this data, such as example applications or use cases. Include any relevant background, contact points, and links that may help people to use this data. You can find examples of this at datahub.io or github.com/datasets, and further tips at frictionlessdata.io and datahub.io.
Details of what data we are using and how we are preparing it can be found in our notes.
Instructions: describe here where you obtained the data, how it was created, where and how it was extracted, and any transformation steps that took place during publication. Link to the sources, as well as to any tools that were used. If you used any scripts to extract and convert the data, add them to a
scriptfolder in your repository.
The licensing terms of this dataset have not yet been established. If you intend to use these data in a public or commercial product, check with each of the data sources for any specific restrictions.