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Data Integrity
&
Data Sleuth - Our Data
Validation Modules
Delivering an
accurate electronic report to CMS for an Eligible Professional
Background requires
constant vigilance; Our CMS Report
Generation employs an automated DATA SLEUTH includes an automated multistage review process.
- Our review process is targeted to meet
the stringent multi-tiered HL7, ONC, CMS report
requirements, reducing rejected submissions.
- Our data import checks for errors early in the report
generation process.
Our method includes strongly typed data
validation for each field, including parameters such as missing
data, datatype, syntax, character set(s), correct sign and within
range boundaries.
- We review the precise syntax required by CMS
BEFORE submission. Implementing the data structure validation
with via QPP and QRDA schemas greatly reduces the chance for
disqualification due to an incomplete review process.
- Reports and input data that
fail validation are separated into individual 'buckets', depending
on severity and routing options.
- Our processes are designed to
route requests for followup for validation correction to appropriate
administrative personnel in order to minimize the
impact on the workflow of providers while generating CMS reports
- We dynamically support
multiple contexts, such as different submissions, medical record
data structures, reporting periods, etc. We do this by totally
integrating the use of electronic standards (such as NIST
encoded JSON standard files) to be accurately execute submission
testing context changes.
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Step #1 - Error detection
Data Sleuth validates data, routes files w/error messages |
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Provider supplies EHR data
QCDR-HISP Data Sleuth tests incoming using default rules for data
validation.
Data Sleuth separates individual rejections into buckets with embedded
or separate error messages. |
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Data Sleuth setup process for EHR / PM
/ IE / HIE |
Contact us |
Step #2 - Error processing setup
Errors reviewed & error route processing protocol is designed |
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Provider and QCDR-HISP staff
reviews
Data error metrics:
Frequency, types and severity.
Decide error routing:
Correct data at source EHR,
QCDR-HISP:
Scrubbing, XLAT, default, error bucket routing, manual process,
quantitative
rejection weighting. |
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Determine error processing protocol |
Contact us |
Step #3 - Error processing running
Errors processing & routing batch run and review |
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Patient data is batch processed
with error rules invoked.
Error scrubber routes data to chosen
paths.
Outputs are reviewed.
Comgined staff reviews error
process & routing.
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Data Sleuth system process
verification |
Contact us |
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QCDR-HISP Hybrid Cloud Support for
QPP submissions
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