Open mHealth Inside for... · Open mHealth is a non-profit startup that promotes greater access to...
Transcript of Open mHealth Inside for... · Open mHealth is a non-profit startup that promotes greater access to...
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Open mHealth Inside
Ida Sim, Emerson Farrugia, Simona Carini
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Open mHealth is a non-profit startup that promotes greater access to mobile health
data through an open standard and meaningful tools.
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what is mHealth ● data from mobile apps and sensors
○ for understanding health and health states ○ for informing health care actions ○ for driving changes in health behavior
● health interventions delivered using mobile technologies
○ behavior change (e.g., medication adherence, increasing physical activity) ○ clinical treatment (e.g., virtual consultation, cognitive behavioral therapy)
● does not include apps for navigating the healthcare
system ○ e.g., finding doctors, clinic opening hours, insurance coverage, etc.
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Open mHealth approach to data sharing
● first create a common language o schemas to structure data o an API to exchange it
● then provide free and open-source tools to
o validate data o pull in data from large and popular device manufacturers o store data and share it with securely with others o move data in and out of EHRs o process and visualize data
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Open mHealth and FHIR, co-evolving ● Open mHealth
o atomic data o in JSON Schema o RESTful API o common schemas covering
80/20 mHealth needs o schemas can be extended
(no "profiles")
● FHIR o atomic data o in XML and JSON o RESTful API o resources covering 80/20
EHR needs o profiles to extend
resources
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common schemas
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Open mHealth Schemas (n = 68)
● A schema structures data and follows design principles
● Each data point, includes o header (data point ID, body schema ID, creation date-time, source, ...)
o body (typically a measure, i.e. instance of a measure schema) o annotation to SNOMED, LOINC, RxNORM, or UCUM
"references": [ { "description": "The SNOMED code represents Blood glucose level (finding)", "url": "http://purl.bioontology.org/.../SNOMEDCT/365812005" }]
CUI
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Example Header Instance { "id": "123e4567-e89b-12d3-a456-426655440000", "creation_date_time": "2013-02-05T07:25:00Z", "schema_id": { "namespace": "omh", "name": "physical-activity", "version": "1.1.RC1" }, "acquisition_provenance": { "source_name": "RunKeeper", "source_creation_date_time": "2013-02-05T07:25:00Z", "modality": "sensed" } }
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Example Measure Instance
{ "blood_glucose": { "unit": "mg/dL", "value": 128 }, "effective_time_frame": { "time_interval": { "start_date_time": "2015-02-05T07:25:00Z", "end_date_time": "2015-06-05T07:25:00Z" } }, "temporal_relationship_to_meal": "fasting", "temporal_relationship_to_sleep": "on waking", "descriptive_statistic": "average" }
average fasting blood glucose over a 4 month period
required
optional
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Schemas Physiologic, e.g., ● BMI, height, weight ● body temp, BP, BG, HR, RR
interval, O2 sat ● sleep duration
Physical activity, e.g., ● physical activity, activity
name ● step count ● minutes of moderate activity
Utilities, e.g., ● time, units ● descriptive statistic
Environmental, e.g., ● ambient temp
Medication, e.g., ● med prescription,
adherence percent ● patient med schedule
Breathing, e.g., ● inspiratory time, expiratory
time ● breath carbon monoxide
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API and tooling
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API ● the Data Point API exchanges JSON schema instances using
REST o models data points as RESTful resources, e.g. POST /dataPoints o secured with OAuth 2.0
● when a new data provider implements the API o a consumer can get those data points without new development o the Open mHealth ecosystem grows
● to offer the API, data providers can o either implement their own system to support the API o or run the open-source storage component as an appliance
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STORE DATA
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tooling > storage component
● an application that implements the Data Point API ● supports credential management and authorization
● written in Java ● keeps data in MongoDB
o other data stores can be added, Spark is likely next
● can run in Docker as an appliance, to isolate it
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INTEGRATE DATA
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tooling > integration with existing APIs
● provide libraries called shims that o call existing APIs o translate response data to Open mHealth format
● run within an appliance called Shimmer
● currently have support for
o Fitbit, RunKeeper, Withings, Jawbone, Misfit o iHealth o Google Fit
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tooling > HL7 v2 mapping
● interoperability with EHRs requires the HL7 v2 mapping ● Catalyze have open-sourced their HL7 mappers based
on Mirth Connect o and they’re bi-directional
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tooling > integrating with HealthKit
HealthKit Sample HealthKit
Sample HealthKit Samples
app
● Apple doesn’t offer a web API for HealthKit data o so there’s no API to shim to
● Granola is an iOS library that serializes HealthKit data into the Open mHealth format o can be dropped into existing iOS apps
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tooling > integrating with HealthKit
HealthKit Sample HealthKit
Sample HealthKit Samples
app
Granola
OmH data
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tooling > processing
● most data will need to be processed ● but why rewrite common processing?
● we’re extracting processing logic into components
o minutes of moderate activity o medication adherence
● and a processing API is being designed to make your
own processing components reusable and pluggable
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VISUALIZE DATA
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tooling > visualization
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tooling > tech
● open-source o and that really does matter here o GitHub for source control o contributions are the way forward
● written using mainstream languages and tools
o Java for backend stuff o HTML/CSS/JS for frontend stuff o RESTful APIs to support polyglot integration o Docker to provide isolation
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mHealth and the EHR
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Workflow Tool
When do mHealth data need to be stored in the EHR database? Or do they just need to be accessible to the clinician workflow?
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relationship to FHIR
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Use Case Differences ● mHealth data
o for use by people, patients, and clinicians
o personal perspective o life-based o 24/7 anywhere o often poorly validated o held by many different
commercial companies from the consumer space
o atomic data exchange for real-time analytics
● EHR data o is for use by healthcare
providers o enterprise perspective o encounter-based o episodic o reflects administrative
and other biases o held (tightly) by dominant
EHR companies and healthcare organizations
o batch data exchange for care coordination
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Open mHealth Schemas FHIR Resources
n = 68 n = 93
Current Overlap n = 6 DataElement Value Set Naming System Body site Observation Medication
Future Overlap n = 4 Goal Patient Person Condition
Pending Overlap n = 4 Location Provenance Questionnaire Questionnaire Response
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Example: medication modeling ● Open mHealth
o medication o medication prescription o pharmacy dispensing o patient med schedule o single dose taken o reason dose not taken o med adherence %
● prescription → patient schedule (with acceptable window) + doses taken → adherence
● FHIR o medication o medication order o medication dispense
o medication administration
(actual record) o medication statement
(recalled)
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Summary ● Open mHealth has co-evolved a very similar technical
approach to data interoperation as FHIR ● Open mHealth provides platform components for mHealth
use cases o open schemas, open APIs o data integration, storage, processing and visualization tools o growing community of developers and users
● Complements FHIR, for use outside health care system
o exploring mapping between OmH and FHIR
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Questions