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Description Catalogue of design guides and best practices for developing Telemetric solutions on using the eHealth infrastructure. |
The design guides outline rules, standards, and recommendations for designing Telemedicine solutions. The design guides provide a consistent framework for design, ensuring uniformity and coherence across Telemedicine Solutions.
Best practices are general strategies, methods, or techniques that should be used to achieve desired results effectively and efficiently.
Content
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Design guidelines
Design the operation and content of the user interfaces to microservice architecture
Avoid designing a single monolithic User Interface that collects data from many the eHealth microservices into one table or view.
A better option, is to separate different user interfaces and workflows in such a way that there is no need to combine large amounts of data in e.g. the same table view.
Target user interface and workflows to only require data from one (or a few) microservices.
Target the workflows and so that data is only retrieved when they are to be used.
A suggested approach is the use the same microservices strategy to the user interface itself by e.g. introduce micro-apps or micro frontend pattern.
Use of ”Backend for frontend” or API Gateway patterns
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#1 Develop your own API Gateway (or BFF) to aggregate multiple downstream calls
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The “API Gateway” pattern can be a useful pattern for the eHealth architectures where there are a small number of backend services.
BFF is a variation of the API Gateway pattern and defines a separate API gateway optimized for each kind of client.
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Isolate the clients from how the application is partitioned into microservices
Isolated the clients from the problem of determining the locations of service instances
Simplifies the client by moving logic for calling multiple services from the client to the API gateway
Reduces the number of requests/roundtrips. For example,
The API gateway enables clients to retrieve data from multiple services with a single round-trip. Fewer requests also means mean less overhead and improves improve the user experience.
Translates from a “standard” public web-friendly API protocol to whatever protocols are used internally
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#2 Minimize the amount of data that the application (or backend-for-frontend
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) has to calculate on
If the a telemedicine solution or application requires a BFF try Try to minimize the amount of data that the telemedicine solution (or backend-for-frontend (BFF) has to calculate on
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, as fetching too much and unnecessary data
...
puts an extra load on the BFF, and complicates the BFF.
Minimize the amount of data can by be done by:
Target user interface design to microservices (see above Design Guide)
Avoid prefetch of data for e.g. details view in a master-detail pattern
Prefer calling eHealth services directly, only use BFF pattern if really needed
Only do caching in telemedicine solutions or applications if really needed
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#3 Use caching of administrative data in application as a mechanism for achieving better performance
Caching is provided by the eHealth Infrastructure that performs server-side caching but can also be done in solutions or applications.
Guide:
Use caching in applications as a mechanism for achieving better performance
Enforce “eHealth access control” for access information in the cache
Use ”Backend for frontend” or API Gateway patterns to share the cache between clients
Recommendation:
Cache ‘static’ data (e.g., administrative data) such as
PlanDefinition
ActivityDefinitions
Organisations
etc.
Avoid cache ‘live’ data (e.g. clinical information)
Use eHealth domain events for cache invalidation.
See Telemedicine Solutions caching of information from the infrastructure for recommendations on caching in telemedicine solutions and applications.
See https://ehealth-dk.atlassian.net/wiki/spaces/EDTW/pages/1034354702/Technical+Interactions+with+Services#Caching-on-Searching on caching provided by the infrastructure.
#4 Retrieve clinical data on-demand (avoid pre-fetching)
Generally, first, retrieve clinical data when needed to avoid the risk of having stale clinical data
If you are lucky, you may know enough about what your users will do to next, and thereby be able to prefetch the data they need before it's needed.
Applications (or BFFs) can prefetch the results of a query and placed into the cache
Consider But really consider if prefetching is really needed, is . Is the BFF response time better than eHealth services?
Prefetching data may result in the prefetch data is being stale, and prefetching too many items increases the load on the eHealth Infrastructure.
Design for concurrency
Design for and recognize other clients may have updated the resources
Automatic updates of the user interface can be used to avoid users looking at and updating old data.
However, automatic updates of the user interface with updated information on the eHealth Infrastructure should be limited.
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Auto updates can be done from the client, by periodically requesting same information from the eHealth Infrastructure, leading to
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.
See https://ehealth-dk.atlassian.net/wiki/spaces/EDTW/pages/1034354702/Technical+Interactions+with+Services#Caching-on-Searching on caching provided by the infrastructure.
See Telemedicine Solutions caching of information from the infrastructure for recommendations on caching in telemedicine solutions and applications.
#5 Take advantage of the eHealth FHIR Service caching
Guide:
Make use of eHealth FHIR Service Caching to achieve better response times
The caching is based on the principles described in HAPI FHIR Search Result Caching: https://hapifhir.io/hapi-fhir/docs/server_jpa/configuration.html
This cache is used when identical searches are performed (same search parameters)
Search results will be cached for a limited period (e.g. 1 minute)
Note that clients can selectively disable caching for an individual request using the Cache-Control header:
Cache-Control: no-cache
See https://ehealth-dk.atlassian.net/wiki/spaces/EDTW/pages/1034354702/Technical+Interactions+with+Services#Caching-on-Searching on caching provided by the infrastructure.
#6 Take advantage of the eHealth Infrastructure Event Model
Guide:
Telemedicine Solutions should subscribe to events, instead of polling for changes.
Telemedicine Solutions can use Infrastructure events to trigger functionality
The eHealth Infrastructure publish simple events at a CRUD resource level e.g.
patient created,
patient updated,
care plan created,
…
Applications should subscribe to events, instead of polling for changes. Using events is considered more effective than polling for changes.
The events can be used in applications to e.g. update cached information.
#7 Design the operation and content of the user interfaces to microservice architecture
Guide:
Design user interfaces in such a way that there is a minimum need to combine large amounts of data
Target user interface and workflows to only require data from one (or a few) microservices.
Target the workflows so that data is only retrieved when they are to be used.
Avoid designing a single User Interface that collects data from many of the eHealth microservices into one table or view.
A suggested approach could be to use the same microservices strategy to the user interface itself by e.g. introducing micro-apps or micro frontend patterns.
If the application needs to aggregate information from several FUT Infrastructure services, it should be considered whether the BFF beneficially could cache static or semi-static information.
#8 Design for and recognize other clients may have updated the resources
Guide:
Design for and recognize other clients may have updated the resources.
A combination of the ETag and If-Match header can prevent one client update the same resource, and the second overwrites the updates of the first
Avoid requesting (polling) for updates from the user interface, leading to
Require unnecessary processing and polling of data.
Automatic updates may put an extra Extra load on the eHealth infrastructure that may reduce response time.
Only do an auto-update of the user interface if really needed.
A ‘better’ option is to recognize other clients may have updated the resources.
A combination of the ETag and If-Match header can prevent one clients update client from updating the same resource, and the second overwrites the updates of the first
If the client wishes to request a version-aware update, it submits the request with an If-Match header that quotes the ETag from the server:
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PUT /Patient/347 HTTP/1.1 If-Match: W/"23" |
If the version id ID given in the If-Match header does not match, the server returns a 412 “412 Precondition Failed Failed” status code instead of updating the resource.
Take advantage of the opportunity for caching
Caching are both provided by the eHealth Infrastructure that performs server-side caching, but can also be done in solutions or applications.
See https://ehealth-dk.atlassian.net/wiki/spaces/EDTW/pages/1034354702/Technical+Interactions+with+Services#Caching-on-Searching on caching provided by the infrastructure.
See Client-side caching for recommendations on caching in the telemedicine solutions and applications.
Take advantage of the eHealth Infrastructure Event Model
Infrastructure events can be used in telemedicine solutions or applications to trigger functionality.
The eHealth Infrastructure publish simple events at a CRUD resource level e.g.
patient created,
patient updated,
careplan created,
…
Applications should subscribe to events, instead of polling for changes. Using events is considered more effective than polling for changes.
The events can be used in applications to e.g. update cached information
#9 Make effective use of the user-selected contexts
Make effective use of the end user-selected context and thereby the results returned by the eHealth services
Use the information in context (patient, episode-of-care, careteam care team..) as a parameter in querying the FHIR services to limit the results.
If e.g., the user has set the context (patient, episode-of-care, careteam care team ..) the context can be used to:
Provide as parameter in querying the FHIR services to limit the results, the eHealth services will then filter and limit the results returned to the client.
E.g., only episode episodes of care relevant to the selected care - team
E.g., only tasks relevant to the selected care - team
Reduce response times from eHealth services
Minimize data and thereby work in telemedicine solutions or applications.
Reduce the risk of UTH (adverse events, Danish: utilsigtet hændelse)
The context can be considered as three levels of context for Attribute Based Access Control:
Use the care team for searching across resources (avoid Patient and Episode-Of-Care)
Use the patient context for more specific results
The episode-of-care limits the results further. The EOC is often required for updates.
Best practices
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NOTICE, example URLs in the following are just examples. Please look at the capability statement in the Implementation Guide for the actual capabilities. Furthermore, the infrastructure develops and capabilities may change. |
#1 Optimize call pattern (call in parallel and do not retrieve data one row at a time)
The eHealth infrastructure effectively support supports parallel requests. If an Application or BFF needs to request data from different services, prefer parallel calls instead of sequential calls if possible.
Practice
Make use of the eHealth services scaling that allows the infrastructure can handle parallel requests.
If an Application (or BFF) needs to request data from different services, prefer parallel calls instead of sequential calls if possible.
Avoid:
Do not call one microservice at a time if the call to the “next” service is not dependent on the previous call.
However, when calling with many concurrent threads from BFFs, it is may be problematic for the infrastructure (similar to DDoS attacks).
Retrieve data on-demand where possible
Best Practice is to generally retrieve data on-demand where possible
That is, first request data when needed.
Avoid prefetch of data for e.g. details view in a Master-Detail pattern
Avoid caching data with the risk of stale data, cache invalidation issues
#2 Limit the number of context changes to what is necessary
In regards to the Design Guides “Make effective use of the selected context” do this with care.
Changing context comes with a penalty. Selecting or changing context results in the user idID, access token etc. is being refreshed for the specific security context.
Therefore try to limit the number of context changes.
#2 Use the search APIs' counting options to limit the results to the client
The eHealth infrastructure services supports support count, to keep the load on clients, servers and the network minimized.
Count Counts are used to limit the number of resources fetched from the database or server.
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See also: http://www.hl7.org/implement/standards/fhir/search.html#count
#3 Take advantage of the opportunity for paging in the Infrastructure
Some of the eHealth services provides provide support for paging of results.
That is, eHealth API users only need to request to amount of data that is needed, and the limiting of the results can be done at the server or database level.
API users can define a _offset parameter in the request which means that when combined with _count the paging is done on the database level.
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The eHealth infrastructure has a default page size (i.e., default _count if not given) and maximum page size (i.e., maximum value for the _count parameter).
#5 Apply filtering to searches to get a smaller and more accurate result
Searching for resources is fundamental to the mechanics of FHIR.
Generally, FHIR use uses “AND” between the parameters in searching.Some searches allows for search on
Best practice
Retrieve multiple ids in one call, instead of multiple gets on each id.
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See also:
Use time constraints in searches to get a smaller and more accurate result
A common scenario in searches is to allow searching for resources with values (i.e. timestamps) within a range of dates.
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Some searches allow for search on multiple IDs, instead of multiple gets on each ID.
Use time constraints in searches to get a smaller and more accurate result. Example,
A range of
&date=gt2022-01-01&date=lt2022-02-01
...
is any date within January 2022.
Example URL to invoke this method:
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GET [base]/Appointment?subject.identifier=7000135&start=gt2022-01-01&start=lt2022-02-01 |
The search parameter _lastUpdated can be used to select resources based on the last time they were changed:
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GET [base]/Appointment?_lastUpdated=gt2022-02-01 |
This search finds any Appointments changed since 1- February 2022.
See also:
#6 Limited support for chained resource references
FHIR allows reference parameters may be "chained"
The eHealth services has limited support for chained resource referencesPractice:
Use chained searches to avoid subsequent calls to the same FHIR Services and save a client from performing a series of search operations.
To save a client from performing a series of search operations, FHIR allows reference parameters may be "chained" by appending them with a period (.). Example:
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GET [base]/CarePlan?subject.name=peter |
Return all the careplans care plans that have a subject whose name includes "peter“Peter “.
However, due to the eHealth microservice architecture and resources are being handled by individual microservices, the chained parameters is are only possible with the same service. That is, limited to resources handled by the same service.