CHoRUS Flow Chart

Consolidate and submit data to the central cloud environment

Create & Submit Extract

D5

Remove sensitive information as per site-specific DUA's, perform QC

DEIDENTIFY & QC DATA

D4

Connect patient and encounter information between modalities

LINK DATA

D3

Harmonize data to standard formats to enable downstream integration

STANDARDIZE DATA

D2

Capture and characterize data across various modalities

GET DATA

D1

Iteratively update D1-D5 to improve quality and completeness

Improve data

D6

Evaluate quality and completeness of the extract

Assess Data & Provide Feedback

C2

Process and load data to facilitate standard assessment

INGEST Data

C1

Once data fulfills CHoRUS requirements, merge with other approved extracts

Approve & MERGE

C3

If you ARE A DATA GENERATING SITE

If you ARE WORKING WITH DATA INFRASTRUCTURE IN THE CLOUD

TO ANALYTICS ENCLAVE

data sources

Structured EHR

Flowsheet

Free TeXT

imaging

WAVEFORM

Discussions

office hours

progress

Standards

Data acq.

Tooling

Standards

Data acq.

Tooling

Standards

Data acq.

How To FIND An SOP on This page

This task refers to two steps. The frist is a standard process of evaluating data extracts for their quality and fitness for use in the broader data enclave. The second is providing the data generating sites with feedback about the extracts that they delivered.

Motivation

Assess data & Provide Feedback

X

Resources

S.O.P.

• TO BE ADDED

OFFICE HOURS

Codebase

• TO BE ADDED

• ICU Module: DQD

• CHoRUS Reports

This task refers to the process of verifying the identify-ability, plausibility, completeness, and conformance of the dataset. Here, we will use established open-source tools (e.g. Achilles, DQD, Ares) to execute a series of validated checks and then produce an extract (i.e. AresIndex) that can be visualized and compared with other OMOP instances with regard to its richness, quality, and diversity. It is this extract that data contributing sites will be required to submit to the central MGH cloud instance for evaluation and feedback.

Motivation

Deidentify and perform quality control

X

Resources

• Deidentification

S.O.P.

• Achilles Output

OFFICE HOURS

• OHDSI Achilles

Codebase

• DQD Output

• OHDSI DQD

• Quality Control

• DQD Overview

• Ares Overview

• Contributing to Ares

• OHDSI AresIndexer

• OHDSI Ares

• Local QC

• Central QC Reports

[TYPES OF IMAGING DATA]

DESCRIPTION

Imaging DATA

X

Resources

S.O.P.

• To be added

OFFICE HOURS

Codebase

• Data Collection

• To be added

• Data Standardization

• Data Linkage

• Data Deidentification

• Quality Control

• Data Extraction

• Data Improvement

• Central QC Reports

• Local QC

[TYPES OF WAVEFORM DATA]

DESCRIPTION

WAVEFORM DATA

X

Resources

S.O.P.

• To be added

OFFICE HOURS

Codebase

• Data Collection

• To be added

• Data Standardization

• Data Linkage

• Data Deidentification

• Quality Control

• Data Extraction

• Central QC Reports

• Local QC

• Data Improvement

This task refers to connecting data from diverse modes together in a way that enables the selection and characterization of patient cohorts using a data mode(s) of choice. For example, a cohort could be selected based upon (1) diagnoses registered in a patient's EHR, (2) measurement values recorded in flowsheet data, (3) complications outlined in a discharge report, (4) artifacts identified in a CT image, or (5) artifacts extracted from a waveform signal. Once created, this dataset would contain all data modes available for the associated cohort, any of which could be used in downstream analyses.

Motivation

Linking Data modalities

X

Resources

• Data Linkage - EHR

S.O.P.

• Imaging Modalities

OFFICE HOURS

• Image Parsing

Codebase

• Private Tags

• Waveform Parsing

• Data Linkage - Flowsheet

• Data Linkage - Free text

• Data Linkage - Imaging

• Data Linkage - Waveform

This task refers to using open-source tooling like WhiteRabbit and other internal data analysis methods to investigate and understand the data available to each data contributing site. For relational EHR data, this typically requires running a database scan or producing metadata about the contents of relevant tables. For non-relational data, characterizations will likely focus on identifying quantity (storage space, number of files, etc) and diversity (unique codes, ontology structures, etc.) of data and an overview of the metadata available that will require mapping in subsequent stages.

Motivation

Collecting and characterizing data

X

Resources

• Data Collection - EHR

S.O.P.

• White Rabbit

OFFICE HOURS

• White Rabbit

Codebase

• Data Collection - Flowsheet

• Data Colletion - Free Text

• Data Colletion - Imaging

• Data Colletion - Waveform

This task refers to two steps. First, placing data in the organizational structure defined by the CHoRUS DataAcquisition team. Thus far, the convention is to create per-person directories, each with three sub-directories (OMOP, Image, Waveform). This structure is subject to change depending on results of preliminary ingestion processes in the central cloud instance. Second, the process of sharing the organized data extract with the central Azure instance hosted by MGH. The first download will use:

Motivation

create and submit Data extract to Central Cloud

X

Resources

• Data Extraction - EHR

S.O.P.

• To be added

OFFICE HOURS

• MIMIC Images

Codebase

• MIMIC Waveform

• Data Extraction - Flowsheet

• Data Extraction - Free text

• Data Extraction - Imaging

• Data Extraction - Waveform

• Data Upload (provisional)

• Azure Data Share Please contact Alex Ruiz (ruiz.alex@microsoft.com) for assistance.

The second and all future downloads will use:

• Data Upload tool

• AZ CLI Please contact Heidi Schmidt (hschmidt@mgb.org) for assistance.

[TYPES OF FLOWSHEET DATA]

DESCRIPTION

FLOWSHEET Data

X

Resources

S.O.P.

• To be added

OFFICE HOURS

Codebase

• Data Collection

• To be added

• Data Standardization

• Data Linkage

• Data Deidentification

• Quality Control

• Data Extraction

• Data Improvement

• Central QC Reports

• Local QC

• Capture and Sharing of Unmapped Terms

This task refers refers to making connections between source representations of medical events or concepts (e.g. EPIC procedural code referring to an appendectomy) and standard representations of those elements (e.g. ICDPCS Procedure for appendectomy). Through the DelPhi process, we have generated a prioritized list of medical concepts that are relevant for the downstream analyses proposed in Bridge2AI.

Motivation

Standardizing Data Elements

X

Resources

• Standardization - EHR

S.O.P.

• Delphi MIMIC

OFFICE HOURS

• OHDSI USAGI

Codebase

• Mapping 101

• Map Validation pt 1

• Map Validation pt 2

• Vocab Gaps

• Flowsheets pt 1

• Flowsheets pt 2

• Flowsheets pt 3

• Usagi & STCM

• OMOP Vocab pt 1

• OMOP Vocab pt 2

OTHER

• Delphi Mappings

• Workload Disc.

• Sharing Disc.

• Delphi Disc.

• Athena Search

• Standardization - Free text

• Capture and Sharing of Unmapped Terms

• Standardization - Imaging

• Standardization - Waveform

• Standardization - Flowsheet

If you are a data generating site, there are two ways to access SOPs using this graphic (same information organized differently):

1. Click on the plus sign (+) attached to any of the steps labeled D1 thru D6. Each option has more details about the motivation and resources available (SOPs, Office Hour session, and Codebase)
2. Click on the plus sign (+) attached to any of the Data Sources (bottom left corner of graphic). Each option share same information described above (option 1).

SOPs that have been completed appear as a link and will take you to the final (or provisional) approved version on GitHub when selected.

HOW TO FIND THE Sop you need

X

This task refers to evaluating the feedback provided by the central cloud team and revising any elements that need attention.

Motivation

Review feedback and improve quality

X

Resources

S.O.P.

• To be added

OFFICE HOURS

Codebase

• Data Improvement - EHR

• To be added

• Data Improvement - Flowsheet

• Data Improvement - Free text

• Data Improvement - Imaging

• Data Improvement - Waveform

[TYPES OF FREE-TEXT DATA]

DESCRIPTION

FREE-TEXT NOTES

X

Resources

S.O.P.

• To be added

OFFICE HOURS

Codebase

• Data Collection

• To be added

• Data Standardization

• Data Linkage

• Data Deidentification

• Quality Control

• Data Extraction

• Data Improvement

• Central QC Reports

• Local QC

This task refers to ingesting csv files into a staging database and executing processing steps like date shifting and quality checks.

Motivation

Ingest data extract at central cloud

X

Resources

S.O.P.

• TO BE ADDED

OFFICE HOURS

Codebase

• Data Upload (provisional)

• Ingestion ETL

• Azure Data Share Please contact Alex Ruiz (ruiz.alex@microsoft.com) for assistance.

• AZ CLI Please contact Heidi Schmidt (hschmidt@mgb.org) for assistance.

The second and all future downloads will use:

• Data Upload tool

Thie first download will use:

[TYPES OF STRUCTURED EHR DATA]

DESCRIPTION

Structured EHR Data

X

Resources

S.O.P.

• To be added

OFFICE HOURS

Codebase

• Data Collection

• To be added

• Data Standardization

• Data Linkage

• Data Deidentification

• Data Extraction

• Data Improvement

• Quality Control

• Local QC

• Central QC Reports

This task refers to defining and evaluating quality thresholds necessary for approval, and once an extract meets those extracts, to execute a merge process to link those data with other approved extracts while retaining relationality.

Motivation

Approve Extract and merge with others

X

Resources

S.O.P.

• TO BE ADDED

OFFICE HOURS

Codebase

• TO BE ADDED

• MERGE ETL