Overview

   

The Gluci-Chek App is a mobile application for patients with diabetes under insulin aiming to better keep track of their carbohydrate intakes, insulin doses and blood glucose levels. The objective of the app is that the user can record information on his/her meals, insulin doses and blood levels as a self-monitoring logbook.

IPP Storage

  • AWS S3 Bucket: A native object storage server provided by AWS to storage all measurements.

  • FHIR Bundle: The app has the option of synchronizing with IPP (Roche Big Data Platform). If so, it will send data to IPP as soon as it has connection (as soon as it is online) and has new measurement entries in its internal database described above. This data will come from the meters or it will have been entered by the user manually directly in the application. Manual data will be just editable the first 15 minutes. Out of these measurements, the FHIR Bundle will be generated. The JSON file that is sent will follow a specific format and is stored in the FHIR Server hosted on IPP.

Requirements

   

Scope

  • To automatically sync BG values from Accu-Chek Guide and Mobile (via a wirless adapter)
  • To authenticate with a Smart Pix Online account (using Gigya OIDC flow) in order to send BG data to Smart Pix Online so that it can be visualized by the patient's doctor

   

Assumptions

SPOL data ingestion:

In the context of the new data ingestion flow, a process is required to ingest data into FHIR and SPOL (legacy) backend.

This ingestion flow will be used by Gluci-Chek App, but not exclusively.

  • Input for this process: 1 FHIR bundle (that later on will be mapped to N ACSPIX files)
  • Output: ingested data visible in SPOL patient profile and in FHIR
  • The Patient is the requestor of the data ingestion (so Gigya UID corresponds to the patient)

   

Use Cases

Use Case Summary Comments
1 BG measurement from meter BG observation sent consists of:
- Concentration: number
- The BG level measured eg. 128
- Concentration Unit: string
- The BG level measurement unit (always mg/dL)
- Sample Time: DateTime
- The BG measurement timestamp (in milliseconds)
- Meal timing flag: with four possible values before meal/ after meal/ bedtime/ fasting
2 BG measurement manually eneterd BG observation sent consists of:
- Concentration: number
- The BG level measured eg. 128
- Concentration Unit: string
- The BG level measurement unit (always mg/dL)
- Sample Time: DateTime
- The BG measurement timestamp (in milliseconds)
- Meal timing flag: with four possible values before meal/ after meal/ bedtime/ fasting
3 Control measurement In case of a Control measurement, the data sent consists of:
- Sample Time
- Flag indicating it is a control measurement
- Control Solution Level.
These values will be discarded, ie. not stored nor sent to SPOL.
4 Meter sensitivity out of range In case the measurement is out of the sensitivity range of the device, the data sent consists of:
- Sample Time
- Flag indicating HI or LO.
These values will be displayed and sent to SPOL.

   

Data Points

Data Point Description FHIR Resource & Element Remarks FHIR Sample
Origin of value Whether the glucose value is entered manually or from a device deviceComponent.type --> Glucometer (Device)
deviceComponent.type --> Smart Phone (Manual)
observation.code --> Manual method (qualifier value) (Manual)
observation.code --> Glucose [Mass/volume] in Capillary blood by Glucometer		 Gluci-Chek App will be compatible with Accu-Chek Guide and Accu-Chek Mobile (via the wireless adapter) only sample
Type of metric Unit of Measure for the Metric - 'Glucose [Mass/volume] in Blood', deviceMetric.unit --> mg/dL sample
Blood glucose measurement value Actual measurement value result observation.valueQuantity.value sample
Event Timing Event timing observation.extension.valueCodeableConcept (observation-event-timing) Values like:
- Before Meal
- After Meal
- Snack
- Before Exercise
- Bedtime
- Fasting
- After Exercise
- Illness
- Oral medication
- Premenstrual
- Exercise		 sample
BG measurement date and time Date and time of the BG measurement observation.effectiveDateTime sample
Control measurement In case of a control solution measurement observation.category --> Control solution observation Control observation is out of scope at this moment; it will not be sent to IPP platform, so there is no need to model it on FHIR; but Maria C. agrees with leaving the example as is. sample
Meter sensitivity out of range In case the measurement is out of the sensitivity range of the device observation.dataAbsentReason.coding --> positive infinity; observation.dataAbsentReason.coding --> negative infinity sample
Carbs Estimated carbs observation.category.coding.code --> carb-observation sample
Insulin Insulin administered by patient MedicationAdministration.dosage.dose.value there are 3 types
- Long acting
- Short acting
- Mixed		 sample

   

Solution Architecture

 

Description Link Comments
Gluci-Chek - Solution Architecture for MVP https://confluence.rochedc.accentureanalytics.com/display/ARCGOV/Gluci-Chek+-+Solution+Architecture

   

High-Level Requirements

 

Description Link Comments
Gluci-Chek App functional requirements MVP https://confluence.rochedc.accentureanalytics.com/display/RD/2.7.10.1.2+Gluci-Chek+App+functional+requirements
Gluci-Chek App functional requirements P0 https://confluence.rochedc.accentureanalytics.com/display/RD/2.7.10.2.1+High-level+functional+requirements
Gluci-Chek App functional requirements P1 https://confluence.rochedc.accentureanalytics.com/display/RD/2.7.10.3.1+High-level+functional+requirements
SPOL Data Ingestion requirements https://confluence.rochedc.accentureanalytics.com/display/RD/2.7.10.1.3+SPOL+data+Ingestion+-+Requirements
FHIR Technical specifcations https://confluence.rochedc.accentureanalytics.com/display/RD/2.7.10.1.4.1+Technical+Specifications
Infrastructure Details https://confluence.rochedc.accentureanalytics.com/display/RD/2.7.10.1.5+Solution+Architecture
FHIR to ACSPIX Mappings https://confluence.rochedc.accentureanalytics.com/display/RI/1.11.2+FHIR+to+ACSPIX+mapper

   

Non Functional Requirements

 

Description Link Comments
Non-Functional Requirements https://confluence.rochedc.accentureanalytics.com/display/RD/2.7.10.1.6+Non-Functional+Requirements

Data Protection

Gluci-Chek App shall comply to the following Security guidelines and Data Protection regulation.

 

Doc-ID Title Applicability for
Secure JS Coding Guidelines v1.0 Secure JS Coding Guidelines Secure development guides provide developers a series of recommendations to follow that allows them to build applications with security techniques.
(EU) 2016/679 Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation) (Text with EEA relevance) Data Protection regulation for protecting personal data and processing of such data.

 

In addition, in order to comply with security requirements

  • LHS will be required to provide inputs for a Risk Assessment that will be performed by RDC
  • LHS will be required to implement the findings of the remediation plan after the Application Security Assessment that will be run by RDC on the Babylon version
  • LHS will be required to fix issues from static code analysis performed by RDC    

Quality Management System

In order to comply with RDC St Cugat Quality Management System, LHS will provide the required functional and technical documentation for the software according to these procedures.

*LHS - La Haute Société

Profiles

List of profiles that are relevant to this application